in ARIZONA RESOURCES and the SOUTHWEST

in ARIZONA RESOURCES and the SOUTHWEST

At.,

War

VOLUME 12

HYDROLOGY and WATER

RESOURCES in ARIZONA and the

SOUTHWEST

PROCEEDINGS OF THE 1982 MEETINGS

OF THE

ARIZONA SECTION -

AMERICAN WATER RESOURCES ASSN.

AND THE

HYDROLOGY SECTION -

ARIZONA - NEVADA ACADEMY OF SCIENCE

APRIL 24, 1982, TEMPE, ARIZONA

VOLUME 12

HYDROLOGY and WATER

RESOURCES in ARIZONA and the

SOUTHWEST

PROCEEDINGS OF THE 1982 MEETINGS

OF THE

ARIZONA SECTION -

AMERICAN WATER RESOURCES ASSN.

AND THE

HYDROLOGY SECTION -

ARIZONA ACADEMY OF SCIENCE

APRIL 24, 1982, TEMPE, ARIZONA

TABLE OF CONTENTS

Publications of the Arizona Section (AWRA)

Preface

Instructions to Authors

Page iv v vi

Comparison of Methods to Estimate Runoff From Small Rangeland Watersheds

H.B. Osborne, C.L. Unkrich and D. J. Busar

ET Measurements over Riparian Saltcedar on the Colorado River

L W

Gay and R.K. Hartman

A RPN Program for the Generalized Penman Equation

L.W. Gay and Robert J. Greenberg

Changes in Streamflow in an Herbicide- Treated Juniper Watershed in Arizona

Malchus B. Baker, Jr.

Determining Watershed Conditions and Treatment Priorities

Rhey M. Solomon, James R. Maxwell and Larry J. Schmidt

Seasonal Change in Infiltration and Erosion from USLE Plots in Southeastern Arizona

J R Simanton and K.G. Renard

Distribution of Loss Rates Implicit in the SCS Runoff Equation

Richard H. Hawkins

Quasi Three -Dimensional Finite Element Model of the Madrid Basin in Spain

Jesus Carrera and Shlomo P. Neuman

Geostatistical Analysis of Aquifer Test And Water Level Data from the Madrid Basin, Spain

Patricia J. Fennessy and Shlomo P. Neuman

Energy and Water Resources Interactions in Arizona,

Nathan Buras

Potential Energy Resources of the Gulf of California, Northwestern Mexico

Barney P. Popkin

Nonstructural Flood Control Evaluation for Tucson, Arizona (Abstract)

Kebba Buckley

Impacts of the Arizona Groundwater Act on Tucson Water

Stephen E. Davis

Water Resources - The Primary Factor in Tucson's Future Growth

Thomas M. McLean

A Survey and Evaluation of Urban Water Conservation Programs in Arizona (Abstract)

Marc Bennett

An Application of the Almon Polynomial Lag to Residential Water Price Analysis

Donald E. Agthe

SEDCON:

A Model of Nutrient and Heavy Metal Losses in Suspended Sediment

William A. Gabbert, Peter F. Ffolliott and William 0. Rasmussen

Techniques for Studying Nonpoint Water Quality

Donovan C. Wilkin and Susan J. Hebel

A Revised Phytoplankton Growth Equation for Water Quality Modelling in Lakes and Ponds

James Kempf, John Casti and Lucien Duckstein

Mutagenic Activity of Selected Organic Compounds Treated with Ozone

Leslie Irwin and Cornelius Steelink

1

9

17

19

27

37

47

53

61

69

75

87

89

99

101

103

111

117

123

139

Key Word Index of Arizona Section (AWRA) Proceedings 147

TO ORDER COPIES OF:

HYDROLOGY AND WATER RESOURCES IN ARIZONA AND THE SOUTHWEST

Volume 1, Proceedings of the 1971 Meetings, Tempe, Arizona

Edited by Daniel D. Evans, Ph.D. (29 papers)

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Volume 3, Proceedings of the 1973 Meetings, Tucson, Arizona

Edited by Ron S. Boster, Ph.D. (25 papers)

Volume 4, Proceedings of the 1974 Meetings, Flagstaff, Arizona

Edited by Ron S. Boster, Ph.D. (30 papers)

Volume 5, Proceedings of the 1975 Meetings, Tempe, Arizona

Edited by D. L. Chery, Jr. (27 papers)

Volume 6, Proceedings of the 1976 Meetings, Tucson, Arizona

Edited by D. L. Chery, Jr. (44 papers)

Volume 7, Proceedings of the 1977 Meetings, Las Vegas, Nevada

Edited by Linda M. White (32 papers)

Volume 8, Proceedings of the 1978 Meetings, Flagstaff, Arizona

Edited by T.

R. Verma, Ph.D. (29 papers)

Volume 9, Proceedings of the 1979 Meetings, Tempe, Arizona

Edited by G. Harwood, Ph.D. & K. J. DeCook, Ph.D. (24 papers)

Volume 10, Proceedings of the 1980 Meetings, Las Vegas, Nevada

Edited by Gerald Harwood, Ph.D. (36 papers)

Volume 11, Proceedings of the 1981 Meetings, Tucson, Arizona

Edited by Gerald Harwood, Ph.D. (35 papers)

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Edited by Todd C. Rasmussen & Mary L. Tidwell (20 papers)

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ARIZONA SECTION SYMPOSIUMS

Water Conservation Alternatives (April 12, 1979)

Edited by Daniel D. Evans, Ph.D. & K. James DeCook, Ph.D.

Flood Monitoring and Management (October 26, 1979)

Edited by K. James DeCook, Ph.D. & Kennith E. Foster, Ph.D.

Water Quality Monitoring and Management (October 24, 1980)

Edited by K. James DeCook, Ph.D., Kennith E. Foster, Ph.D.

& Mary L. Tidwell

57 per copy

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Arizona Section, the curren proceedings may be purchased for a 52.00 discount.

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students

Dues for membership in the AWRA Arizona Section are 53.00

per are eligible for joint membership in the AWRA Student Chapter and year.

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iv

PREFACE

Increased desires to meet the future agricultural, industrial and municipal water needs of people living in arid parts of the world has resulted in research which is focusing on how to best obtain water of the highest quality and quantity.

As it becomes increasingly apparent that the problems of the southwestern United States are commonly fealt by other portions of the world, research instigated in this country can be used to solve global problems; shown in two articles on the development of water resources in Spain (Carrera and Neuman; Fennessy and Neuman).

Because the development of the Central Arizona Project was conceived at a time of abundant energy resources, the project is confronted with the dilemma of providing the power needed to deliver the water to its final users.

The question of where the energy will be obtained is raised by one of the authors in this proceeding (Buras), and is partially answered by a companion article by another author

(Popkin).

The option of user conservation (Davis), perhaps motivated by water pricing (see the article by Agthe), appears to be an important alternative to importing high -cost water from outside the basin.

The importance of a high quality water source motivates the articles in the remainder of the proceedings.

Such questions as sources of heavy metals (Gabbert et al.), nonpoint source water quality impacts (Wilkin and Hebel), and the production of mutagenic activity by treating water with ozone

(Irwin and Steelink) demonstrate the concern that is developing in this country for preserving the purity of our waters.

A highlight in this years proceedings is a Key Word Index for all of the articles published under the auspices of the Arizona Section (AWRA).

The index can be found at the end of this volume and should provide a bibliographic source for topics of particular interest to researchers concerned with arid land problems.

Todd C. Rasmussen

Tucson, AZ.

July, 1982

Instructions to Authors

Beginning with Volume 11, instructions have been modified to accommodate the use of word processors.

While the use of a word processor is preferred, a typewriter is acceptable.

Each submitted manuscript must be camera -ready.

Use papers in Volume 11 or later volumes as typing models.

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Please attempt to fill the page as completely as possible, keeping the right hand margin as straight as possible.

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vi

Abstract

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They should be consecutively numbered throughout the paper and appear at the end of the paper, following references cited, within the margin requirements.

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See the enclosed sample of reference citations for proper citation format.

Smith, Robert and Arthur Green.

1982.

Conflicting theories on the reproduction rate of Felis domesticus during the Great Flood.

In: Proceedings of the Society of Arcane Studies.

R.

oT nés

(Ed.).

San Francisco: Obscure Publications,

Inc.

5(14):127 -136.

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In past years, deadline extensions have been liberally granted for a variety of reasons, sometimes delaying publication for several months.

Frequently, long delays result from the government agency peer review process and improperly prepared manuscripts.

Therefore, the editors request that all authors take special care in following the instructions for manuscript preparation and do everything in their power to meet the meeting date deadline.

vii

COMPARISON OF METHODS TO ESTIMATE RUNOFF

FROM SMALL RANGELAND WATERSHEDS

H. B. Osborn, C. L. Unkrich, and D.

J. Busar

Research Hydraulic Engineer and Hydrologic Aides

USDA, ARS Southwest Rangeland Watershed Research Center, 442 East Seventh Street Tucson, Arizona

85705

Introduction

Many methods have been used to estimate peak discharge and /or storm runoff volumes from small drainages in the United States (Chow 1962; Haan 1982).

Most of these methods were developed for urban drainages, or were based on hydrologic data from the eastern and midwestern United States.

Several methods have been suggested for possible use on small rangeland watersheds in the southwestern United States.

Some, such as the Rational Formula, are easy to use but require subjective estimation of parameters and predict only peak discharge.

Others predict both peak and volume, but may require more effort to use.

In many cases, model use will determine the needed accuracy and required sophistication.

In this paper, several models (methods) are compared and evaluated for use on rangeland watersheds using data from a very small gaged rangeland watershed.

Design of Experiment

The United States Department of Agriculture (USDA), Agricultural Research Service (ARS), Walnut

Gulch Experimental Rangeland Watershed is located in southeastern Arizona, near Tombstone (Fig. 1).

The

57-mi2 watershed is divided into gaged subdrainages ranging from 0.4 acres to the entire watershed.

The study described in this paper was carried out on a 0.45 -acre subwatershed (63.105) located in the Lucky

Hills research complex near Tombstone (Fig.

1).

The small watershed is fenced and shrub -covered, and erosion pavement dominates the watershed surface.

There is a well- defined, but shallow, channel draining the watershed, but channel abstractions were considered insignificant compared to watershed infiltration.

The average watershed slope is

9 percent, and the channel slope is about 3 percent.

There is a 6 -hr weighing -type recording raingage on one edge of the watershed, and runoff is estimated from a FW -1 continuous water -level recorder mounted in a 3 -ft H- flume.

CITY OF

TOMBSTONE f -

LUCKY HILLS WATERSHEDS

N

J

1

0

I

Y

S

4

SCALE IN MILES

.. WATERSHED BOUNDARIES

MAIN CHANNELS

5

LOCATION OF

-_

WALNUT GULCH

WATERSHED

Figure 1.

Location of the Walnut Gulch Watershed and the

Lucky Hills experimental area on Walnut Gulch.

1

Six major runoff -producing events on 63.105 were chosen to compare the five methods.

The events were selected to represent a range of temporal rainfall input and antecedent conditions.

The models are compared on the basis of their relative accuracy in estimating peak discharge rates and runoff volumes of these storms.

Methods

The five methods discussed in this paper are linear regression, the Rational Method, Illinois Urban

Drainage Area Simulator (ILLUDAS), two versions of the Santa Barbara Urban Hydrograph (SBUH), and the

Kinematic Cascade Model (KINGEN).

The Rational Formula (method) can be used only to predict peak discharge.

Linear regression can be used to predict peak discharge and runoff volume separately.

The other three methods include a hydrograph output, and can be used to estimate peak discharge, time to peak, flow duration, and storm runoff volume.

ILLUDAS and SBUH were both designed for urban drainages, and we expected to make some adjustments in the program subroutines and parameters.

KINGEN had been used on both urban and natural watersheds, and considerable information pertaining to rangeland use was already available.

In some cases, we estimated the parameters a priori; in other cases, parameters were adjusted by trial and error based on comparisons of observed and computed runoff.

In each case, we have adopted the author's notation; so several symbols are not unique in definition.

Linear Regression

Osborn and Lane (1969) developed linear regression equations to predict runoff volume and peak discharge from 63.105 and other Lucky Hills subwatersheds.

With additional data, these equations have been modified for 63.105 (Osborn and Simanton, 1981) to the form:

Qp = P15 - 0.68

(r2

= 0.80)

(1)

Q

= 0.7PTOT - 0.24

(r2 = 0.78) where

Qp

Q

= peak discharge (in /hr),

= total storm runoff (in),

PTOT = total storm rainfall (in).

The equations were used to estimate peak and volume of discharge from the 6 selected events.

(2)

Rational Method

The Rational Method is still one of the most popular and simple methods for predicting peak discharge from an ungaged watershed.

The equation is:

(3)

Qp = CiA where i

Qp = peak discharge (cfs),

C

A

= a constant based on watershed characteristics,

= watershed area (acres), and

= maximum rainfall (in /hr) for the time of concentration.

A TI -59* hand calculator program for using the Rational Method has been developed by B.

C. Yen

(1981).

In the Yen adaptation of the Rational Method, there are two methods for determining the time of concentration.

We determined the maximum average intensity based on the first method, Kerby's (1959) equation, in which:

Tck = To + Tf

(4) where

Tck = time of concentration by Kerby formula,

To

= time of maximum overland flow from boundary to channel, and

Tf

= time of flow through the channel.

The factors To and If are based on Kerby's coefficient, slopes, channel velocity, differences in elevation, and the lengths of overland and channel flows.

These parameters must be entered into the program.

The second method for determining time of concentration, the Kirpich formula, did not give reasonable values for this watershed, and therefore cannot be recommended for use on such rangeland watersheds.

The program TI -59 can be divided into three parts.

the Kerby formula.

First, the time of concentration is estimated using

Second, precipitation intensity is determined by either assuming Td (rainfall duration)

=

Tc for a statistical event (such as the 30-min, 100 -yr storm), or by entering rainfall depth from an actual storm.

Finally, peak discharges are obtained for each event.

*Reference to a specific calculator program does not constitute endorsement of the brand.

2

ILLUDAS

The ILLUDAS model, developed by Terstriep and Stall (1969), is an objective method for the hydrologic design of storm drainage systems in urban areas.

The model improves on a method described by Watkins

(1962) for the urban drainage, and adds a grassed -area component.

The intent of our study was to investigate the "grassed- area" component of the model for possible application to rangeland drainages.

In

ILLUDAS, an observed time -varying rainfall pattern is uniformly distributed over the basin.

The basin can be divided into subbasins which produce hydrographs that are combined and routed downstream from one design point to the next until the outlet is reached.

Detention storage can be included as part of the design in any subbasin.

Time versus area curve for each subbasin is represented as a straight line from the origin to a point where the entire subbasin is contributing.

The time coordinate of this point is the time of concentration, which can be either entered directly or determined within the program with the following equations by Izzard (1946): ge = 0.0000231IL,

(5) where qe = equilibrium overland flow (cfs per ft of width),

I

= supply rate (in /hr), and

L = length of overland flow (ft), and te = 0.033KLqe- 067,

(6) where to = time of equilibrium flow (min), and

K = (0.0007I + C)S-0,33, where

S = surface slope (ft), and

C = cover coefficient = 0.046 (for bluegrass).

Standard infiltration curves were devised for soils by hydrologic group A, B, C, and D.

were calculated from the Horton equation as given by Chow (1964); f = fc + (fo - fc)e -kt where f

= infiltration at time t, fc = final constant rate, fo = initial infiltration rate (in /hr), k t

= shape factor (given as 2 in this program), and

= time from start of rainfall.

(7)

These curves

(8)

The program also requires selection of antecedent moisture conditions based on total rainfall during the five days preceeding the storm.

We found that, by changing a few data statements within the program, Izzard and Horton's equations could be easily changed to accommodate conditions other than bluegrass.

For the very small watershed,

63.105, the travel times in the channel were so short that the routed hydrograph was the same as the watershed hydrograph.

SBUH Method

The current method for generating a complete hydrograph for retention /detention basin design for storm water management in Santa Barbara County (California) is the Howard Needles version of the Santa

Barbara Urban Hydrograph Method (HNV- SBUH), originally developed by J.

County Flood Control and Water Conservation District (Golding 1980).

M. Studchaer of the Santa Barbara

The final design hydrograph is obtained by routing the rainfall excess for each time period through an imaginary linear reservoir with a routing constant equivalent to the time of concentration of the basin.

The model can be described in three parts:

(1) calculation of runoff depths,

(2) computation of rainfall excess, and

(3) routing the rainfall excess through an imaginary linear reservoir.

depths for each time period R(t), are calculated using the following equations:

Runoff

(9) R(0) -

I x P(t)

R(1) = P(t)(1 -I) - f(1 -It)

R(t) = R(0) + R(I)

(10)

(11)

3

where

P(t) f

It

I

At

= rainfall depth during time increment at (in),

= infiltration during time increment At (in),

= total impervious portion of drainage basin (decimal),

= directly connected impervious drainage (decimal), and

= incremental time period (hr).

The rainfall excess, I(t)(cfs), is computed in the second step by multiplying the total runoff depth,

R(t), for each time period, t, by the drainage basin area, A (acres), and dividing by the time increment

At:

I(t) = R(t) x

A

.

(12)

In the third part, the design hydrograph is obtained by routing the rainfall excess with a time delay equal to the time of concentration of the drainage basin: where

Q(t)

= Q(t-1) + K [I(t) + I(t -1) - 2Q(t -1)]

TC - 2Tc°+

At

(13)

(14)

As was the case with ILLUDAS, the infiltration, f, is computed by the Horton equation (Eq. 8).

The program is also similar to ILLUDAS in that the standard infiltration curves established by

Terstriep and Stall (1969) which adjust fo in equation (8) are used to compute infiltration.

Again, the infiltration parameters can be changed to accommodate specific soil types.

The original program was written for an HP -67* programmable calculator and used a numerical integration scheme in the infiltration routine.

With the help of Dr. Donald Ross Davis, Department of Hydrology, University of Arizona, the program was rewritten for a TI -59* calculator (DRD- SBUH), and the infiltration curve solved in closed form.

Both methods were used in the study.

KIN6EN

Program KINGEN is a modified version of the Kibler -Woolhiser (1970) kinematic cascade model for routing overland flow over a cascade of planes and through trapezoidal channels (Lane and Woolhiser

1977).

Input to the program is rainfall excess based on the Phillip (1969) equation: f = 1/2 St-112 + A

(15) where s

= sorptivity of the soil, and

A = steady state infiltration rate.

The program can be operated in either a simulation or optimization mode.

Given slopes and channel characteristics, the program computes flow area, hydraulic radius, velocity, and shear stress for the channel segments.

Output is a complete storm hydrograph from which peak time, discharge rate, and volume of runoff are obtained.

Comparison of Methods

Hydrographs were simulated for 6 selected runoff -producing events on subwatershed 63.105, and compared to actual data (Fig.

2 -6).

Peaks and volumes of simulated and actual events were also compared

(Tables 1 and 2).

Both peaks and volumes tended to be overpredicted with ILLUDAS, and peaks underpredicted with either version of SBUH (Fig.

2 -4).

Both ILLUDAS and SBUH badly underpredicted runoff from the high- intensity, short -duration rainfall of 5 July, 1975.

KINGEN generally gave a better "fit" of the data, including the 5 July, 1975 event (Fig.

5 -6).

We could have improved the "fit" of the actual and simulated peaks from the Rational Method by simply changing the "C" value.

Since we had followed the instructions for estimating peak discharge for an ungaged watershed, we felt the strong tendency to over predict should be noted.

The ILLUDAS and SBUH methods were adjusted based on early fittings, and the hydrographs in Fig.

2 -4 are based on parameter adjustments.

The hydrographs developed with KINGEN are without adjustment.

At this point, we clearly have more confidence in KINGEN than in the other methods.

However, KINGEN is, by far, the most complex of the methods.

Discussion

Regression equations are easy to develop when rainfall and runoff data are available, and they can be used on similar ungaged watersheds.

However, there are several assumptions which limit the value of such equations.

First, watershed characteristics such as size, slope, and drainage density must not differ significantly between "similar" gaged and ungaged watersheds.

Second, rainfall is assumed uniform over the watershed, both in time and space.

Third, rainfall intensity within the assumed constant

*Reference to a specific calculator program does not constitute endorsement of the brand.

4

19JUL74

1.4

1.4

1.2

Ñ

1.0

(

I

/

-

-

65E274

- 40TU4L

_ IL1.5045

- MN

%1

)

N

+

)

\

)\ `\1

20 30

TIME (MINUTES)

40

50

Figure 2.

Comparison of three methods for estimating runoff for storms of 24 Sep 67 and 19 July

74.

20

60

TIME (MINUTES%

40

60

60

Figure 3.

Comparison of three methods for estimating runoff for storms of 24 Sep 74 and 8 Sep 70.

245E267

1.2

1.0

/.

IMUL4TE0 6uN01F 160M

6E4% TEINT 641N14LL

- lIYYL4TE6 4uN011 ITEY

Y4%16 YIM 641MI4LL

19JUL74

.6

5.011.75

242E274

0 20 30

TIME [MINUTES)

Figure 4.

Comparison of three methods for estimating runoff for storms of 6 Sep 72 and 5 July 75.

0

O 20 30

TIME (MINUTES)

40 50

6

Figure 5.

Comparison of estimated runoff using breakpoint and maximum 15- min rainfall in a kinematic cascade model (KINGEN) with actual rainfall and runoff data for three storms (from

Osborn and Simanton, 1981).

5

regression rainfall duration must not significantly affect the estimate of peak and volume of runoff.

Because of the extreme variability in rainfall, both in time and space, and the non -homogeneity of rangeland watersheds, linear regression is generally limited to very small rangeland watersheds of no more than a few tens of acres.

Regression equations can be used to predict time to peak and flow duration also, but generally with considerably less accuracy than peak discharge and runoff volume.

Table 1.

Comparison of estimated peak discharges for 5 methods and 6 selected events on subwatershed 63.105.

Storm date

6 Sep 72

19 Jul 74

24 Sep 74

5 Jul 75

Rainfall

Maximum

Total intensity

(2 min)

Actual Regression

Peak Discharge (cfs)

Rational ILLUDAS

DDV

SBUH

HNV

(in)

(in /hr)

24 Sep 67

0.39

8 Sep 70 1.14

.79

.94

.47

.59

4.50

4.20

3.90

3.00

2.70

5.12

0.64

1.04

.78

.55

.64

.98

0.40

1.08

.77

.63

.55

.40

0.59

2.24

1.38

1.36

.91

.62

KINGEN

0.70

0.53

0.40

0.45

1.45

1.20

1.13

.99

1.90

1.14

1.12

.89

.68

.62

.90

.64

.60

.49

.48

.44

.30

.67

.45

1.26

Table 2.

Storm date

Comparison of predicted storm runoff for 5 methods and 6 selected events on subwatershed 63.105.

Rainfall

Maximum

Total intensity

(2 min)

Storm runoff (in)

Actual Regression Rational ILLUDAS

(in)

(in/hr)

SBUH

DDV

HNV

KINGEN

24 Sep 67

8 Sep 70

6 Sep 72

19 Jul 74

24 Sep 74

5 Jul 75

Average

0.39

1.14

.79

.94

.47

.59

.72

4.50

4.20

3.90

3.00

2.70

5.12

--

0.12

.61

.37

.31

.20

.21

.30

0.04

.56

.31

.42

.09

.18

.27

0.11

0.15

0.11

0.14

.85

.88

.74

.59

.46

.30

.14

.10

.33

.66

.45

.31

.14

.43

.63

.32

.23

.09

.36

.38

.28

.17

.25

.30

In this study, the regression coefficients were determined from runoff events for a 15 -yr period and used to predict the 6 selected events, so the fit of actual and estimated volumes was as good as those based on KINGEN, and the fit of actual and predicted peaks as good as all but those based on KINGEN.

It is

The Rational Method is limited to predicting peak discharge independently of peak time and volume.

a simple method to use, and it is indeed rational in that the units are proper, and the peak discharge depends upon rainfall intensity for the time of concentration.

However, like linear regression, rainfall is assumed uniform, both in time and space, and the watershed is considered homogeneous.

The

"C" value must be representative of the runoff -producing features of the watershed, and is determined, to a large degree, subjectively.

Time of concentration must be accurately estimated, and if the rainfall is too variable within the time of concentration, the predicted peaks may be in considerable error.

The

Rational Method is also limited to very small areas (in terms of acres).

As stated earlier, adjustments were made on the ILLUDAS and SBUH programs, both initially and as the study progressed.

It became apparent early in the study that peak discharge and time to peak were extremely sensitive to the infiltration subroutine.

Both ILLUDAS and SBUH were developed for urban drainages, with routines for both pervious and impervious areas within the same drainage.

We found that the infiltration parameters, which were based on grassed urban areas, did not represent rangeland soils.

We had to adjust the parameters considerably to reduce the infiltration for more and faster runoff.

most cases, we predicted no runoff with the original grassed -area infiltration parameters.

In

The ILLUDAS and SBUH methods are somewhat similar, using the same infiltration equations as well as similar routine techniques.

Both are designed for use on larger watersheds, at least up to several square miles.

Unlike the Rational Method and linear regression, rainfall can be varied in time, which improves the accuracy of estimation.

However, neither program can handle spatial variability, which limits their usefulness for larger watersheds.

ILLUDAS does include infiltration from subbasins within the drainage, which allows for non -homogeneous watersheds.

We have not, as yet, investigated the sensitivity of shape factor, K, in the Horton equation.

6

Both ILLUDAS and SBUH were fitted to the 6 selected events.

Each had infiltration parameters derived from infiltrometer data rather than the standard curves provided.

Initial runs of both SBUH and

ILLUDAS produced almost no runoff, because Izzard's equation gave a time of concentration four times longer than was reasonable.

On subsequent runs, the time of concentration was entered directly.

The output for the 6 events from KINGEN are as shown. We used both breakpoint data and the maximum

15-min rainfall to better illustrate the need for breakpoint input.

based on previous knowledge from other watershed studies.

The program parameters were entered

The parameters were not adjusted to improve the fit of actual and predicted peaks.

In this test, KINGEN, with breakpoint data, clearly outperformed

ILLUDAS and SBUH, but KINGEN had been used on other rangeland watersheds; whereas, we were starting from scratch with ILLUDAS and SBUH.

Summary

Several suggested methods for estimating runoff from rangeland watersheds were compared using six selected events from a very small gaged watershed on the USDA experimental watershed.

These methods included linear regression, the Rational Formula, ILLUDAS (Illinois Urban Drainage Area Simulator), two versions of the SBUH (Santa Barbara Urban Hydrograph) method, and KINGEN (a kinematic cascade model).

KINGEN was the most complex of the models, the Rational Formula the simplest.

Estimates of both runoff peaks and volumes, based on KINGEN, were significantly more accurate than those from the other methods.

Although the linear regression estimates were as accurate as those from ILLUDAS and SBUH, regression equations are not easily transferred to ungaged watersheds.

ILLUDAS and SBUH were both designed for urban drainages, but were developed for use on ungaged watersheds.

Neither method gave particularly good estimates in this test, but they may be applicable to other watersheds with revisions to accommodate spatial rainfall variability and /or time of concentration.

The Rational Method can only be used to make quick peak estimates on very small watersheds.

At this point, we have more confidence in KINGEN than in the other methods tested.

6JUtTS

0 I0 20

30

TIME I MINUTES)

40

50 60

Figure 6.

Comparison of estimated runoff using breakpoint and maximum 15 -min rainfall in a kinematic cascade model (KINGEN) with actual rainfall and runoff for three storms (from Osborn and Simanton, 1981)

7

References

Chow,

V.

T.

1962.

Hydrologic determination of waterway areas for designs of drainage structures in small drainage basins.

Univ. of Illinois Engr. Exp.

Sta. Bul. 462.

Chow, V. T.

1964.

Handbook of Applied Hydrology.

McGraw -Hill Book Co., Inc., New York, p. 14 -17.

Golding, B. L.

1980.

Hydrograph synthesis by the HNV -SBUH method utilizing a programable calculator.

Proc. SWMM Users Group, Toronto, Ontario.

Haan, C. T.

1982.

Hydrologic Modeling of small watersheds.

ASAE Monograph.

Izzard,

C.

F.

1946.

Hydraulics of runoff from developed surfaces.

Research Board 26:129 -146.

Kerby, W. S.

1959.

Proc. 26th annual meeting, Hwy.

Time of concentration for overland flow.

Civil Engineering, Vol. 74.

Kibler, D.

F., and Woolhiser, D.

A.

1970.

Univ. Hydrology Paper No. 39, 27 pp.

The kinematic cascade as a hydrologic model.

Colorado State

Lane, L.

J., and Woolhiser, D.

A.

1977.

surface runoff.

J. Hydrol. 35:173 -190.

Simplification of watershed geometry affecting simulation of

Osborn, H. B., and Lane, L.

J.

1969.

Precipitation- runoff relationships for very small semiarid rangeland watersheds.

Water Resources Res., AGU 5(2):

419 -425.

Osborn, H.

B., and Simanton,

J.

R.

1981.

Maximum rainfall intensities of southwestern thunderstorms.

Proc. Fourth Conference on Hydrometeorology, Am.

Meteorological Soc., 166 -173.

Phillip, J.

B.

1957.

The theory of infiltration.

Soil Sci. 84:257 -264.

Terstriep, M. L., and Stall, J.

B.

Hydr. Div. 95(HY6):1809 -1834.

1969.

4. Sorptivity and algebraic infiltration equations.

Urban runoff by the road research laboratory method.

ASCE J.

Watkins, L. H.

1962.

The design of urban sewer systems.

Majesty's Stationery Office, Road Research Tech.

Dept. of Sci. and Industrial Res., London, Her

Paper No. 55.

Yen, B. C.

1981.

TI -59 calculator program for storm sewer design using Rational Method.

(Unpublished method used with permission of author.

For further information, contact Professor B. C. Yen, Dept.

of Civil Engr., Univ. of Illinois, 208 N. Romine St., Urbana, Ill.

61801.)

8

ET MEASUREMENTS OVER RIPARIAN SALTCEDAR O1 TEE COLORADO RIVER

L. W. Gay and R. K. Hartman

School of Renewable Natural Resources

University of Arizona

Tucson, AZ 85721

Abstract

Evapotranspiration (ET) from an extensive stand of saltcedar on the Colorado

River floodplain was defined throughout the growing season by a series of Bowen ratio energy budget measurements in 1980 and 1981.

The water table depth at the

site near Blythe, California, was about 3 m during the two summers of measurement.

Daily ET totals ranged from 2.9 mm /day in early April up to 11.0 mm /day in late

June, and dropped down to 1.8 mm /day in late October.

These values are means from two separate measurement systems, averaged over measurement periods of two to four days in length.

The highest single day total measured by an individual system was

12.7 mm on June 28,

1981.

The mid -summer ET rates from the saltcedar at this

experimental site are substantial, and rank among the highest rates that have been reported elsewhere for irrigated cropland.

The seasonal saltcedar water use of 1727

mm (including 90 mm of annual precipitation) is somewhat lower, however, than

earlier, more speculative estimates for saltcedar that ranged up as high as 2100 mm per year.

Introduction

The lower Colorado River flows through one of the warmest, driest regions in

the United States.

For example, the average annual rainfall at Blythe, California airport is only 78.7 mm (3.1 inches), and the maximum temperature of record is 50 °C

(122 °F).

Maximum temperatures frequently exceed 46 °C in each month from May through

September.

The Colorado River serves as a large source of irrigation water for this

arid region, however, and this supports a prosperous, flourishing agricultural

industry.

The Colorado River also supports extensive riparian plant communities on its

floodplain.

The composition of these communities has changed through the years, as

native species such as mesquite (Proeopis sp.) have been generally replaced by

saltcedar ( Tamarix chinensie).

Saltcedar is widely perceived as a heavy user of water that might otherwise be available for more beneficial use by man, and so it

has been studied extensively for many years in the southwest.

The studies have evaluated both the consumptive use of saltcedar, and means for

eradicating the plant in order to "salvage" water and thus augment existing water

supplies.

The earlier work on water use was summarized by Horton and Campbell

(1974) who concluded (1) that a dense, mature stand of saltcedar would use 1.8 to

2.1 m (6 to 7 ft) annually on the Gila River near Phoenix, (2) the somewhat higher elevation sites at Safford, Arizona, and Carlsbad, New Mexico, would lose about 1.5

to 1.8 m (5 to 6 ft), and (3) use at the still higher elevation Bernardo site near

Albuquerque would be about 1.2 to 1.4 m (4 to 4.5 ft) per year.

The climatic conditions along the lower Colorado River are even more extreme than on the Gila

River, and this should increase riparian water use, especially since the stable

flows of the now -controlled Colorado provide for relatively high ground water tables beneath the extensive, heavily vegetated floodplains.

It is surprising to conclude that definitive estimates of water use by riparian species are lacking in the southwest, despite the wide interest in this topic.

is partly due to the complexities of the problem.

This

Water use depends not only upon the climatic regime, but also upon type and density of vegetation and the supply and salinity of water.

The lack of water use measurements is also partly due to limita-

tions of the various experimental approaches.

For example, Van Hylckama's (1974) lysimeter water budget studies are the basis for the Gila River water use figures

9

cited above.

Van Hylckama pointed out that lysimetric measurements are not only

time consuming, but the results can be extrapolated only to areas of similar characteristics.

The same restriction applies to water budget studies such as the comprehensive measurements described by Hansen, et ál. (1972) along a 15 -mile reach of the

Gila River in eastern Arizona.

The energy budget approach offers possibilities for

generalization, but the energy budget studies in saltcedar have extended over

periods of only a few days (Gay and Fritschen, 1979a).

It is apparent that improved estimates of water use by riparian communities

would contribute to better management of our limited water resources.

ET should be

estimated from measurements that take into account environmental and vegetative differences between sites.

The energy budget is such a method that has proven

useful for field estimates of ET in agriculture and in natural communities as well.

Consequently, we began several years ago to evaluate ET with the energy budget

method in a large stand of saltcedar along the lower Colorado River.

Objectives

The objectives of this study were threefold:

(1) to develop an estimate of

seasonal ET; (2) to evaluate short term ET rates as an aid for process studies and

for later modeling; and (3) to refine and develop measurement techniques for the

energy budget method.

Methods

The energy budget method was chosen for this study because its fundamental basis allows generalizations to areas other than where the experiments were con-

ducted.

The method requires a moderate level of technical sophistication in order to operate in the field and away from the laboratory.

The theory is well -known and has been thoroughly described (see, for example, Monteith, 1973).

The Bowen Ratio Energy Budget Model

The energy balance equation is a statement of the conservation of energy, i.e., the sum of all energy fluxes for a given system must equal zero.

The major thermal fluxes in the soil- plant -atmosphere system at the surface of the earth are expressed as:

Q* + G + H + LE = O.

(1)

The symbols are:

Q *, net radiation; G, soil heat flux or change in thermal storage;

H, convection or sensible heat; and LE, latent heat of vaporization.

Photosynthetically fixed energy is small and is disregarded.

The units are either energy flux

densities (i.e., W /m2) or energy totals for a specified time period (i.e., J /m2).

All fluxes directed to the earth's surface, whether from above or below, are positive and all fluxes away from the surface are negative.

Bowen (1926) introduced the ratio of convection to latent energy

( a- H /LE) as

a means of estimating some of the fluxes in Equation

(1).

The Bowen ratio reduces to: a= H /LE = A

30/ 3e

(2) where

X is a coefficient equal to 0.66 mb / °C at sea level, and 10/1e is the ratio of potential air temperature gradient (30 /3z,

°C /m) to vapor pressure gradient (3e /3z, mb /m).

The model assumes that the eddy diffusivities for heat and for vapor are equal

to unity over the distance across which the temperature and vapor gradients are

measured.

In practice,

30 /3z and 3e /3z

are approximated by measurements of differences 4T and 4e across a vertical distance 4z.

The distance 4z is usually

of the about

1

m, and the bottom level of measurement is a little above the top

canopy.

The Bowen ratio method has been widely used for measuring ET, and the basic accuracy of the model is well documented (see, for example, Fritschen, 1965).

The

measurements do require careful work and high precision, however, in order to

achieve the desired accuracy.

10

The Measurement System

The system used for the Bowen ratio measurements is similar to that described

earlier by Gay (1979).

The key features are:

a

data acquisition system of

excellent precision; a microprocessor computer; precisely calibrated, ceramic wick

psychrometers (Gay, 1973; Hartman and Gay, 1981); and an exchange mechanism to interchange the psychrometers between observations.

Net radiation and soil heat flux are also measured, and supplementary measurements are made of solar radiation, wind speed and direction.

The data acquisition and processing equipment is housed in a small van; power is provided by a portable generator.

Two sets of sensors are mounted on separate masts so that two independent ET estimates are obtained.

The psychrometer mechanisms were placed so that the lower psychrometer was just

above the tips of the canopy, and the two sampling levels were separated by a vertical distance of 92 cm.

The pair of psychrometers was interchanged every 6 minutes so that mean temperature and humidity gradients could be obtained each 12

minutes,

free of instrument bias (Sergeant and Tanner,

1967).

The exchange

mechanism is described in detail by Gay and Fritechen (1979b).

The mean 12- minute

gradients were based on 40 samples at the tvo levels, after the psychrometers had

comme into equilibrium following the interchange.

Data Acquisition and Processing

The data logger houses a 40 channel scanner, an integrating digital voltmeter, a real -time clock, and a strip printer, all in a compact case.

The maximum resolution of the voltmeter is better than 0.001% (1 uV in 120 mV full scale), at a scan

rate of 2.4 readings per second.

The data logger has an averaging option that compresses many sequential samples into a single average for transmission to the

microprocessor computer for analysis.

The Tektronix 4051 computer is a microprocessor -based system with graphics

capability on a CRT screen.

Computing and graphics functions are specified in BASIC language.

The unit has 32K bytes of internal memory, and has an internal magnetic tape cassette with capacity of 450K bytes.

Raw and processed data are stored on the magnetic tape for subsequent retrieval and further analysis when desired.

Site Description

The saltcedar study area was a vast saltcedar thicket of some 10 km2 in area, located on the floodplain of the Colorado River some 50 km south of Blythe, California.

The elevation was about 90 km.

The fetch at the measurement site was about

1 km to the west, and from 2 to 3 km in the other cardinal directions.

The height of the vegetation was about

7 m.

The sandy soils were spotted with coarse pockets laid down by the meandering river channel in the past.

The water table remained constant at about 3.3 m throughout the two summers of measurement.

Sampling

The effects of spatial variability were minimized by selection of a site in a dense, relatively homogenous portion of the stand.

The two masts were separated by about 10 m, and they are considered to sample the same area.

Temporal variability

was minimized by frequent sampling within a given day and by sampling for several

consecutive days within each month.

The energy budget (and latent energy) each day was summed from the 12- minute means, each of which was based on 40 measurements.

Results and Discussion

The data collected in this study represent an unusually precise evaluation of

ET rates from saltcedar throughout the growing season.

We shall first examine some of the daily measurements, and then look at the implications for seasonal water use.

Daily Measurements

The energy transfer rates throughout the day are illustrated in Figure 1 for

July 28, 1980, for the daylight period when Q *>0.

This day was the warmest of all those sampled.

The midafternoon air temperature reached 45.1 °C, with a relative

humidity of 15.6%.

The Figure shows the single value of G, mean values (averaged

11

JULY 28, 1988

ENERGY BUDGET / COLORADO RIVER SALTCEDAR

-400

-600

-808

200

0

-200

808

680

400 w

---- -1 "

////

/N e ti

I

1

A n It

L.'`

AI

p

I

'tr..' %, r

`r 'w

A

LE1 -

LE2

-1088

600

1 1 1

1

808

1 r 1 1

1090

1

1 11

1

1280

1 .

1

1

1489

.

1 1

1

1600

1 1 1

1

1888

1 .

I

2800

TINE (HRS)

Figure 1. -- Daytime energy budget over saltcedar on the Colorado River floodplain.

Net radiation (Q) and convection (H) are means from two sets of sensors; latent energy (LEI and LE2) is shown separately for each set of sensors.

Soil heat flux

(G) was measured with a single disc.

between masts) of

and

k,

and the separate mast estimates of LEI and LE2.

Table 1. -- Energy budget totals (in MJ /m2 and equivalent mm depth of evaporated water) for

0624 -1836 July 28, 1980.

Flux

Q*

G

Ti.

ER

(LE1/LE2)

MJ /m2

18.3

- 0.2

5.4

-23.5

(-23.8/-23.2) mm

7.32

-0.08

2.16

-9.40

(9.52/9.28)

The smooth trace of Q* confirms the rather clear sky conditions that day, marred only briefly by clouds in midmorn-

ing.

The value of G is quite small, confirming that very little soil heat flux takes place beneath the closed canopy in

this stand.

The amount of energy stored in the foliage was considered negligible, and no correction for this quantity was applied to G.

The positive value of H confirms that advection took place all day long as

warm air moved from the surrounding desert,

across the relatively cool, evaporating

canopy.

IT is essentially the sum of Q*

and H since G a 0.

The close correspondence of LEI and

LE2 is indicative of the precision with which the two sets of sensors are estimating i!.

It is apparent from the Figure that the two sets of sensors are in exceedingly

close agreement, but serial correlation prevents us from establishing confidence

limits on the precision.

The closeness of the daily totals also serves as an index of precision.

Flux totals are summarized for July 28, 1980, in Table 1

for the daylight period of positive net radiation.

The range in estimates of LE by LEI and

LE2 is only ?1.3%.

This is

a very close comparison, especially since the commonly

accepted accuracy estimates for Bowen ratio evaluations of LE are ±10% or 15%.

12

COLORADO RIVER SALTCEDAR

14

12

_

I0

_

8

_

6

_

4

_

ir

+ t

+

+*

+

DAYTIME ET

+

NIGHTTIME ET

o

0

2

_

41.

0 o m

0

8

11I11I111g1I1.11111111111111,tj41I111

90

30 60 120 ISO 180 210

240

270 300 330 360

DAY OF YEAR

Figure 2. -- Daytime and nightime evapotranspiration totals from saltcedar on the

Colorado River floodplain.

Estimates were obtained for the daylight period of positive net radiation on 21

days throughout the growing season.

The number of successive days in each run ranged from 2

to 4.

Night time data were obtained from 11 nights during this

period.

The totals obtained from each date (averaged between masts) are plotted in

Figure 2, for day and for night.

The daylight water consumption ranged from around

2 mm /day in spring and fall up to 12 mm in midsummer.

The nighttime water use was small, and ranged from 0.08 mm in spring and fall up to 0.6 mm in midsummer.

Since there are "missing" nights, we shall examine measured daylight totals as an indication of accuracy, and then extrapolate nightime observations as needed to obtain 24 -hour totals for estimating seasonal water use.

The daytime water use measured at site

1

(ET1)

is regressed against that measured at site 2 (ET?) in Figure 3.

The linear equation ET1

-0.03 + 0.945 E2 has r 0.991.

The scatter is very small; 95% confidence limits at ET?

6.45mm

are only +0.03%.

The offset ( -0.03 mm) and the failure of the slope coefficient to

equal unity (0.945) suggest a difference in evaporation rates at the two sites.

This was confirmed by exchanging sensors between masts during several successive

runs.

The small difference remained, thus eliminating instrumentation as the cause

of the observed difference.

The precision of these measurements derives from improvements described by Hartman and Gay (1981).

These include the care used in

sensor calibration, the experimental design (exchanging psychrometers, frequent samples, timing of analysis), and the high quality of the data acquisition and

processing system.

13

Seasonal Water Use

COMPARISON BETWEEN MASTS

I

AND 2

COLORADO RIVER SALTCEDAR ET

Apr 6,7

Apr 28,29

May 28,29,30

Jun 26,27,28

Jul 28,29

Aug 15,16,17

Sep 12,13

Oct 30 -Nov 2

ET1 e -0.03 + 0.94 * ET2

Table 2. --Mean daily totals (in mm) based upon two separate masts and dates as shown.

day

- 2.8

- 6.8

- 8.2

-10.5

- 9.0

- 8.4

- 6.9

- 1.8

night*

-0.1

-0.3

-0.4

-0.5

-0.6

-0.6

-0.5

-0.1

*includes interpolated values.

24 -hour

- 2.9

- 7.1

- 8.6

-11.0

- 9.6

- 9.0

- 7.4

- 1.9

The seasonal water use estimate is derived from averages for each of the two to four day runs.

The values in Figure 2 are averaged

and tabulated in Table 2,

thus

providing data

for

evaluating

evapotranspiration losses throughout the growing season.

For this purpose,

it is assumed that evapotranspiration is

negligible throughout the dormant

season.

This is likely, since the

saltcedar loses its leaves.

Further, winter rainfall is low, and a layer of dry sand at least a meter

thick overlies the water table which is

3.3

m deep.

The spring greenup and fall dormancy date is arbitrarily set at March 23

and

November 11, based upon inspection of the data in Table 2.

0

0 2 4

6

8 10

MAST $2 DAILY WATER USE,

1

12

MM.

14

A simple trapezoidal integra-

tion of the evapotranspiration for

the 233 day growing season yields the following totals:

day, -1548 mm; night, -89 mm; total, -1637 mm.

Figure 3. -- Comparison of daytime ET from mast 1 versus mast 2.

The 1637 mm of evapotranspira-

tion were developed from measurements of water transpired by the

saltcedar.

This total should be increased by some percentage of the annual rainfall to yield a better estimate of annual evapotranspiration.

The annual precipitation

at Ehrenberg, Arizona, 4 miles east of Blythe and about 25 miles north of the

saltcedar site, averaged 89.7 mm (3.53

in) for the 1931 -72 period (Sellers and Rill,

1974).

Of this meager amount, 47% or 42.3 mm fell during the April through October

growing season, and the remainder during the dormant season.

The storms are generally light and infrequent, and it is probable that essentially all of the

precipitation falling on the floodplain in this region evaporates, i.e., there is no

effective runnoff.

Our measurements did not coincide with rain, and there was

little evidence of any antecedent soil moisture in the dry blanket of sand at this site.

In our judgment, the evapotranspiration estimate should then be increased 42

mm during the growing season and 48 mm during the dormant season to account for direct evaporation of rainfall, and thus yield a "best" estimate of 1727 mm of

evapotranspiration over the year.

Other estimates from this

region are quite generalized.

For example, the U.S. Bureau of Reclamation (1964) estimated that there were 4,593 ha of saltcedar on reach number 4, which extends south from

Blythe- Ehrenberg some 30 miles to a

point just below the measurement

site.

The annual wester use was

given as 62,401,704 m', or a depth

equivalent of

1359 mm excluding precipitation.

The Bureau estimates were based on the Blaney -

Criddle method, adjusted for density of vegetation throughout the reach.

The agreement is quite

good,

considering that the saltcedar at our measurement site was quite dense, and should be using

water at a near maximum rate.

More speculative estimates

from other regions range up to 2100

14

mm for the Gila River near Phoenix (Horton and Campbell, 1974).

The climatic

conditions are warmer and drier on the lower Colorado River than on the Gila, and it

seems unlikely that even more favorable vegetation density and water availability combinations could exist to generate the high water use estimates of Horton and

Campbell.

References Cited

Bowen,

I.

S.

1926.

The ratio of heat losses by conduction and evaporation from any

water surface.

Phys. Rev. 27:779 -787.

Fritschen,

L.

J.

1965.

Accuracy of evapotranspiration determinations by the Bowen ratio method.

Intl Assoc. Hydrol. Bull. 10:38 -48.

Gay, L. W.

1973.

On the construction and use of ceramic wick psychrometers.

In:

Brown, R.

W., and B. P. Van Haveren (Eds.).

Psychrometry in Water Relations

Research.

Pp. 251 -258.

Utah Agric. Experiment. Sta., Logan.

Gay,

L.

W.

1979.

A simple system for real -time processing of energy budget data.

Proc., Symposium on Forest Meteorology, Ottawa.

WMO No. 527, pp. 224 -226.

WMO, Geneva.

Gay, L.

W. and L.

J. Fritschen.

1979b.

An exchange system for precise measurements

of temperature and humidity gradients in the air near the ground.

Proc.,

Hydrol. Water Resour. Ariz. and SW 9:37 -42.

Hansen, R. L., F. P. Klipple and R. C. Culler.

1972.

Changing the consumptive use on the Gila River floodplain, southeastern Arizona.

In:

Age of Changing

Priorities for Land and Water.

Proc., ASCE Irr. Drain. Div. Spec. Conf.

Spokane.

Amer. Soc. Civil Engrs.

Hartman, R. R. and L. W. Gay.

1981.

Improvements in the design and calibration of

temperature measurement systems.

Proc., 15th Conf. Agric. Forest Meteor., pp.

150 -151.

Amer. Meteor. Soc., Boston.

Horton, J. S. and C. J. Campbell.

1974.

Management of phreatophyte and riparian vegetation for maximum multiple use values.

Res. Pap. RM -117.

USDA Forest

Service, Rocky Mtn. Forest and Range Exp. Sta., Fort Collins.

Monteith, J. M.

1973.

pp.

Principles of Environmental Physics.

Arnold, London.

241

Sargeant, D. H. and C.

B. Tanner.

1967.

A simple psychrometric apparatus for Bowen ratio determinations.

J. Appl. Meteor. 6:414 -418.

Sellers, W. D. and R. H. Hill.

1974.

Arizona Climate 1931 -1972.

Press, Tucson.

616 pp.

Univ. Arizona

U. S. Bureau of Reclamation.

1964.

Pacific Southwest Water Plan.

Supplemental

Information Report on Water Salvage Projects - Lower Colorado River.

USER,

Boulder City, Nevada.

Van Hylckama, T.

E.

A.

1974.

Water use by saltcedar as measured by the water

budget method.

U.

S. Geol. Survey Prof. Pap. 491 -E.

GPO, Washington.

Acknowledgements

The work upon which this publication is based was supported in part by funds

provided by the Office of Water Research and Technology (Project B- 084 -ARIZ),

U.

S.

Department of the Interior, Washington, D.C., as authorized by the Water Research and Development Act of 1978, and in part by the Arizona Agricultural Experiment

Station, Hatch Project 04.

Approved for publication as Journal Paper No.417

,

Arizona Agricultural Experiment Station.

15

A RPM PROGRAM FOR THE GENUALITXD PENMAN EQUATION

L. W. Gay and R. J. Greenberg

School of Renewable Natural Resources

University of Arizona

Tucson, AZ 85721

Abstract of

The Penman potential evapotranspiration model has been expanded and generalized for a vide range

climatic

conditions by

J.

Doorenbos and W. 0. Pruitt (1975, FAO Irrig. á Drain. Pap. 24).

Their comprehensive model relies heavily on tabulations and graphs to facilitate its application in remote areas where computer facilities are lacking.

Future applications of this model have been substantially enhanced by our development of a program that runs on a HP- 41C /CV calculator.

The RPN program occupies 1778 bytes of memory, and will run on a 41CV, or a 41C with a quad memory module.

A printer is also needed. The required climatic data can be input in a variety of forms, and program execution was planned with particular attention to the non- technical user.

The entire calculator system (41CV, printer, card reader) cost less than $750, and provides for very portable use with a high degree of computing power.

Introduction

As agricultural water resources become increasingly depleted the need for efficient utilization of irrigation water increases.

Potential evapotranspiration predictions have become a vital aid for optimizing irrigation programming.

Although extensive research has been achieved on all levels of predicting potential evapotranspiration (PET), a gap exists in relaying this technology between the scientific and agricultural communities.

In recent years large agricultural interests have begun to employ computers to access irrigation requirements.

Their use has proven cost- effective in optimizing water input

- crop yield relationships.

Unfortunately, this computer -based technology has not yet become reasonably accessiblble to the small -scale agriculturist.

Small calculators provide an alternative, however.

Hand -held programmable calculators have existed for nearly 10 years.

Early models were not capable of supporting software proficient in predicting PET.

As with computers, programmable calculator design technology has improved a thousand -fold in the past decade.

High -level scientific calculations and impressive data storage capabilities are now available in shirt- pocket size units, and presently only a slim distinction exists between programmable calculators and computers.

The one indisputable difference is the portability of hand -held programmable calculators.

in

With the introduction of the HP -41C calculator (Hewlett- Packard Calculator Div.,

Corvallis,

OR)

1979, extensive PET prediction capabilities have become accessible to the small -scale agricultural community.

The 41C is expandable through a wide range of peripheral devices to suit many calculation and data storage needs.

Additionally, the 41C is now capable of interfacing with "real- world" analog signals through a new digital multimeter.

The 41C is the controller of an interactive array of peripheral devices collectively referred to as HP -IL (Hewlett- Packard Interface Loop).

These peripheral devices include mass storage tape drives, printer -plotters, digital multimeters and relays.

As with computers, the calculator communicates with the user in words as well as numbers.

Like all Hewlett -Packard calculators, the 41C utilizes a

Reverse Polish Notation (RPN) logic system that is extremely "byte" efficient and user friendly.

A RPN program has been developed for the 41C that utilizes the Penman method for determining PET predictions, based upon Doorenbos and Pruitt's (1975) comprehensive version of the Penman method, which they generalized for a wide range of climatic conditions.

The model occupies 1778 bytes of program memory, with an additional data storage requirement totalling 140 bytes.

The program requires a HP -41CV calculator, or a HP -41C calculator with a quad memory module.

A peripheral printer is also required, and a magnetic card reader or digital cassette drive is helpful.

The program was designed with particular attention towards the non -technical user.

It reduces the complicated calculation procedures that were previously required, down to a simple data input procedure.

The needed climatic data can be input in a variety of forms.

Furthermore, the program is flexible in the type of units of the input data.

17a

The Generalized Penman Hodel

The Penman combination model for evaporation (Penman,

1948) has been widely used for evapotranspiration estimates.

The model is a simplification of the energy exchange processes at the evaporating surface, yet its fundamental basis has contributed to a general acceptance of results obtained over a wide range of conditions. Doorenbos and Pruitt (1975) have generalized the Penman equation to extend its application to an even wider range of environments. In doing so they have compiled a useful assortment of graphical and tabular functions that make the application simpler and less laborious.

The RPN program in this paper includes algorithms for these functions, and provides a further reduction in the effort required for application.

The basic model, taken from Doorenbos and Pruitt (1975, page 29), is:

(1) ETo* = W Rn + (1- W)f(u)(ea -ed) (not adjusted) radiation term aerodynamic term where: ETo* is the reference crop evapotranspiration in mm/day (not adjusted);

W is a temperature- related weighting factor;

Rn is net radiation in equivalent evaporation in mm/day; f(u) is a wind- related function; and

(ea -ed) is the difference between the saturation vapor pressure at mean air temperature and the mean actual vapor pressure of the air, both in mbar.

To find ETo, the reference crop evapotranspiration, ETo* needs to be adjusted for day and night -time weather conditions.

Components of the RPM Program

The computations with this model are often rather tedious, because the wide range of acceptable data may be in many different forms and limits.

The programmable calculator reduces this effort significantly.

The components of the Penman model will be described separately and the algorithms identified.

Vapor Pressure

The moisture content of the air appears in various forms, and may be expressed in many different sets of units.

The model uses millibars for units in calculating the vapor pressure deficit of the air (ea -ed), but relative humidity, dewpoint, or dry- and wetbulb temperatures can also be input into the program.

The model calculations are for daylong averages of ea -ed.

In practice, this can be obtained from an average of the maximum and minimum values.

Even a single measurement of actual vapor content (ed) can give a reasonable estimate of the mean daily ed for use in the program.

The saturation vapor pressure (ea, mb) at mean air temperature ( tmean = (tmax - tmin) /2) is calculated in the program from Murray's (1967) approximation: ea = A exp [B tmean /(c + [mean)] (2) for tmean > 0 °C, and where A = 6.1078 mb, B = 17.2691°C and c = 237.3 °C.

Observed vapor pressure (ed) data may be available, in which case subtraction yields the desired

(ea -ed).

Relative Humidity Input.

The ed is estimated from mean relative humidity (RHmean = (RHmax

RHmin) /2) from the relation ed = RH ea /100, where ea is calculated from Murray's formula (Equation at tmean.

Example: given tmax = 35 °C, tmin = 22 °C, RHmax = 80 %, RHmin = 30%.

The program calculates ea

= 38.91 mb at tmean = 28.5 °C, ed = 21.40 mb at RHmean = 55% and ea -ed = 17.51 mb.

Dewpoint Input.

In this case, the ed is estimated directly from mean dewpoint temperature (tdew,

°C) with Murray's approximation

(Equation 2), and ea is again calculated with Murray's approximation using tmean.

lib

Example: given tmax = 35 °C, twin = 22 °C, tdew = 17.5 °C.

The program calculates ea = 38.91 mb at tmean = 28.50 °C, ed = 20.00 mb at tdew = 17.5 °C, and ea -ed = 18.91 mb.

Psychrometric Inputs.

The program uses the general form of the aspirated (ventilated) psychrometric equation (see, for example, Fritschen and Gay, 1979) to calculate ed = es -Y (tdry - twet)

(3) where es(mb) is saturation vapor pressure at twet ( °C) from Equation (2),Y is the psychrometric constant (Tr= 0.66 P /Po, mb / °C, and P /Po is the ratio of actual atmospheric pressure to that at sea level where Po = 1013.25 mb), and tdry - twet ( °C) is the wetbulb depression.

Actual atmospheric pressure is not normally available, so the program estimates the ratio P /Po from the International

Standard Atmosphere (List, 1949):

P /Po = ((288 - 0.00652)/288)5.256

(4) where Z is elevation above sea level, in meters.

Example: given tmax = 35 °C, twin = 22 °C, and a midmorning observation of tdry

25 °C and twet =

20 °C, at an elevationZ = 0 m (sea level).

The program calculates ed = 20.08 mb, ea = 38.91 mb at tmean = 28.5 °C, and ea -ed = 18.83 mb.

Wind Function

The wind function f(u) in Equation 1 expresses the mixing power of the atmosphere, as a function of daily wind travel measured at a height of 2m (U2, km /day).

The program uses the formula of

Doorenbos and Pruitt (1975): f(u) = 0.27 (1 + 02 /100).

(5)

The program corrects wind measured at other than 2 m height with an empirical approximation: where UZ

U2 = U2/(0.1877 Ln(Z) + 0.87025)

(6) is the wind run (km /day) measured at height Z (m) above the surface.

Example: given that wind run at 3 m height is 250 km /day.

While Equation (6) calculates U2 =

232.24 km /day, the program rounds to 2 decimal places to match Doorenbos and Pruitt's (1975) table, and yields U2 = 232.50 km /day and f(u) = 0.90.

Weighting Factor

The weighting factor is Doorenbos and Pruitt's (1975) simplification of variables in Penman's original derivation (i.e., V = A /( A+ Y), where

A is slope of saturation vapor curve, dea /dt (mb / °C) at tmean, and Y is the psychrometric constant which was defined earlier). The weighting factor W depends upon temperature and pressure.

A is calculated in the program by differentiating Murray's approximation for ea and tmean, and incorporating the pressure correction for Y

The pressure ratio

(P /Po) is estimated in the program by the International Standard Atmosphere given earlier in Equation

(4)

The program calculations are:

W = [ea(Bc) /(c + t)2] /[(ea(Bc) /(c + t)2) + 0.66(288 - 0.00652)/288)5'256]

(7) where ea is calculated at t = tmean with Equation 2, the constante B,c are defined in Equation 2, and

Z is elevation above sea level in meters.

Example: given tmax = 35 °C, twin= 22 °C, elevation = 95 m.

The program calculates W = 0.78,

1 - W = 0.22.

Doorenbos and Pruitt (1975) show W = 0.77 for these data; the difference is probably due to rounding.

Net Radiation

The radiation term may lead to some tedious calculations, because the necessary data are often lacking and one must resort to various estimation approaches.

If net radiation (Rn) data is available, then the Penman model can be applied quite easily.

If not, then estimation procedures usually begin with an evaluation of net solar radiation (Rns), based upon extraterrestrial solar radiation (Ra), estimates of cloud cover from climatological observations, and an estimate of crop albedo.

The net longwave exchange (Rol) is then estimated from meteorological characteristics, and the two estimates are combined to yield net radiation:

17c

Rn = Rna - Rnl

(8)

Note that Rn is shown as the difference between Rns and Rol in Equation (8), since daily Rnl is usually a negative quantity in the crop enviroment.

Solar Declination.

If solar radiation (Rs) data is not available, it can be estimated from extraterrestrial solar radiation (Ra), as a function of latitude and time of year.

This requires solar declination (DEC).

The program calculates DEC( °) as follows (adapted from Ball, 1978, p. 253):

X _ [0.9856(DOY + 0.5)] - [0.2458333((YR Mod 4) -1) - 15.785 + .0095 YR]

(9)

Y = (0.02 sin 2X + 1.916 sin X + X) - [(- 47/2750)YR + 111.24]

DEC = arcsin (sin Y sin 23.42)

(10)

(11) where DOY is day of year (1 to 366) and YR is calendar year (e.g., 1982).

The modulo function returns the remainder of YR divided by 4 (i.e., 1, 2, 3, or 0).

of 0 in Equation (9).

When YR Mod 4 = 0, the program uses 4 instead

The program uses an algorithm from Ball (1978, p. 241) to calculate day of year from calendar date.

Example: given the date of July 20, 1972 (DOY = 202).

The program calculates DEC = 20.58° at solar noon.

Extraterrestrial Solar Radiation.

Given declination (DEC) and latitude (LAT), extraterrestrial solar radiation (Ra, in mm of evaporation) is calculated from known solar geometry as follows:

S = sin LAT sin DEC

C = cos LAT cos DEC

N =

(arcos (- S /C))/7.5

V =

Ra =

N/24

(48/)[VS + C sin(57.29578V)]

(12)

(13)

(14)

(15)

(16)

Example: at 30 °N, on July 20, 1972, Ra = 16.9 mm /day.

Solar Radiation.

Solar radiation (Rs) is estimated from the relation

Ra = (0.25 + 0.50 n /N) Ra

(17) where n is observed number of hours of actual bright sunshine and N is maximum possible number of bright sunshine hours.

The value of N for a given date and latitude is given in Equation (14).

Net solar radiation (Rns) is then obtained by the simple relation

Rna = (1 - a)Rs (18) where a is the albedo of the evaporating surface.

a is about 0.25 for green crops.

Example: given observed n = 11.5 hrs on July 20, 1972, over a crop with albedo of 0.25.

The program calculates Rs = 8.5 mm /day, N = 13.67 hrs, and Rns = 8.5 mm /day.

Longwave Radiation.

The next longwave radiation (gal, in mm of evaporation) is obtained in the program as a function of air temperature, vapor pressure and sunshine, using the simple formulation from Doorenbos and Pruitt (1975):

Rnl = oTk4(0.1 + 0.9 n /N) f(ed)

(19) where a is 2 X 10

-9 mm /day °R4, Tk is mean daily air temperature in °R (Tk = t( °C) + 273.16), n/N is ratio of observed hours to possible hours of bright sunshine, and f(ed) is 0.56 - 0.0794a in humid climates, and 034 - 0.044/ in dry climates.

Example: given tmean = 28.5 °C, ed = 21.4 mb, n/N = 11.5/13.67, and a dry climate.

Rnl = 1.94

mm /day.

Net Radiation.

Finally, the desired net radiation is obtained from Equation (8).

For this example, Rns = 8.5 mm /day, and Rnl = 1.94 mm /day, so Rn = 6.6 mm /day.

Application of the Model

The program output must be adjusted to account for failure of the aerodynamic portion of the

Penman model to fully describe the energy exchange processes.

17d

Unadjusted Reference Crop Evapotranspiration

The initial application of the model yields unadjusted reference crop evapotranspiration (ETo *).

This is illustrated with the following example from Doorenbos and Pruitt (1975), portions of which have already been used in this paper.

Location is Cairo, at latitude 30 °N and elevation 95 m.

Data is for July 1972.

Solar radiation on the date July 20 is taken to represent the mean for the entire month.

Other data for July are: tmean = 28.5 °C, RRmean = 55%, sunshine n = 11.5 hr., U2 = 232 km /day, and

a

= 0.25.

The program calculates (1 - W)f(u)(ea - ed) = 3.74 mm /day, and W Rn = 5.14 mm /day, so ETo* - 8.88

mm /day.

Adjusting for Climatic Characteristics

Doorenbos and Pruitt (1975) surveyed many data and concluded that the unadjusted values need little correction when daytime wind speeds are about twice those during night -time, and RR maximums are > 60%.

They identified six other climatic regimes, however, when ETo* may differ substantially from ETo ('03 ETo* < ETo <-1.2 ETo *).

Their classification follows:

Case #1: ETo - 1.2 ETo *.

Important in areas with moderate to high radiation (>8 mm /day) during summer months, which consistently have low- humidity winds during much of the day ( >4 m /sec) and calm night -time conditions with high night humidity values approaching 100%.

Case #2: ETo -1.05 to 1.10 ETo *.

Applies in areas where daytime winds are <4 m /sec and nights are very calm and humid, i.e. REmax > 75 %.

The daily wind distribution should give a day -night ratio of 3 or more.

Case #3:

ETo = ETo *.

Daytime wind speeds of about twice those during the night -time are generally found and maximum relative humidity > 60 %.

No adjustment of Penman ETo* is required.

Case #4: ETo -0.75 to 0.95 ETo *.

ETo will be slightly over predicted in areas with moderate tc high radiation and with wind speeds < 4 m /sec but about equal during the day and night.

Relative humidity during night -time is > 60 %.

Case #5: ETo -0.65 to 0.80 ETo* 1/.

Relatively rare but applies for spring, summer and autum conditions with moderate to high radiation and when wind speeds during the day and night are between and 8 m /sec with maximum relative humidity < 40%.

Case #6: ETo - 0.55 to 0.65 ETo* 1/.

Also rare, but applies during spring, summer and autur with moderate to high radiation and when wind speeds during day and night are > 8 m /sec and wi relative humidity day and night < 40 %.

Case #7: ETo - 0.30 to 0.35 ETo* 1/.

Very rare, but will apply under very strong winds of > I m /sec during both day and night, while relative humidity, day and night, is low and < 40 %.

Case 7 applies only when radiation is low, i.e. during late autumn and winter (Rns < 4 mm /day).

Doorenbos and Pruitt (1975) used graphical adjustments to correct ETo *.

The program uses the linear relationship.

ETo = ETo* (1.629 - 0.21046 C)1 /2

(20) where ETo is adjusted reference crop ET (mm /day), ETo* is unadjusted ET (mm /day) and C is case number

(1 to 7) as identified above.

Example: Doorenbos and Pruitt (1975) conclude that Case #4 characterizes the Cairo climate.

Adjustment of ETo* by Equation (20) yields ETo = 7.55 mm /day.

Conclusions

Doorenbos and Pruitt's (1975) generalized version of the Penman equation should reduce the number of anomalous results that occur when the equation is applied in environmental conditions quite different from those of the original site in the English countryside.

The generalizations, bower, introduce some additional considerations which Doorenbos and Pruitt handle neatly with supplementary graphs and tables.

The compression of this supplementary material into appropriate algorithms, and organization into the convenient program described in this paper, will further help bring the Penman equation to bear on practical problems of ET estimation.

1/.

These drastic corrections occur when relative humidity is low and conditions are very windy.

Such conditions are rare and persist only a few days in most climates (Doorenbos and Pruitt,

1975) .

17e

The program fits easily into the HP -41CV handheld calculator.

portable and relatively easy to operate.

This calculator is powerful,

While the program works well for our purpose, it could undoubtedly be changed and improved.

The identification and inclusion of the basic algorithms in this paper will make it easy for other users to adapt the Penman model to their special needs.

the

The current version of Robert Greenberg's Penman program with user's guide can be obtained authors for the cost of materials ($10 includes 11 magnetic cards in "write from all" format; make checks to the

University of Arizona).

It can also be supplied on a micro -casette cassette drive.

The authors would appreciate comments and suggestions.

for the HP -IL

References Cited

Ball, John A.

1978.

Algorithms for RPM Calculators.

John Wiley.

330 pp.

Doorenbos J., and W.

D. Pruitt.

1975.

Drainage Pap. 24, FAO, Rome. 179 pp.

Guidelines for Predicting Crop Water Requirements.

Irrig. 6

Fritachen, L. J., and L. W. Gay.

1979.

Environmental Instrumentation.

Springer.

216 pp.

List, R.

J.

1949.

Smithsonian Meteorological Tablee.

Smithsonian Misc. Coll. Vol. 114.

Ed., fifth reprint issued 1971.

Smithsonian Institute Press. Washington.

6th. Rev.

Murray, F. W.

1967.

On the computation of saturation vapor pressure.

J. Appl. Meteorol.

6:203 -204.

Penman, H. L.

1948.

Natural evaporation from open water, soil and grass.

Ser. A.

193:120 -145.

Proc. Royal Soc. (London)

Acknowledgements

The work in this publication was supported by the Arizona Agricultural Experiment Station.

Project 04.

Hatch

Approved for publication as Journal Paper 420, Arizona Agricultural Experiment Station.

a.

Appendix

The program outputs are listed below for the example problem given in the text.

Executing program

PN generates a header and a listing of the inputs required to run the program, and the output to be obtained: b.

The program prompts for max, tmin, RHmax, and RHmin, and then calculates tmean,

RHmean, ed and ea -ed:

* * * * * * * * * * **

* * * * * * * * * * **

* MODIFIED *

*

PENMAN

*

* ET MODEL *

* * * * * * * * * * ** ssssssasss+asssssasssss t INPUTS *

'NOR PRESSURE:

T'sax'=

35.88

T'sin'=

22.88

T'sean'= ea= 38.91

28.58

RH'sax'=

80.881

RH'sin'=

RH'icean'=

38.881

55.881

ed= 21.48

ea-ed= 17.51

degrees

C.

gauge ht.

s.

wind run ks/day altitude s.

radiation se./day esssts**sss**asssssset** t OUTPUTS t c.

The program next prompts for wind travel and height of measurement, and calculates wind speed at 2 m and value of f(u): sssssstasstssasttsssss

800 FUNCTION:

E. T.

an./day

************

u3.88= 258.88

u2=

1(u)=

232.58

8.98

17f

d.

The program prompts for altitude, and calculates weighting factors W and 1 - W using tmean from before: ssssssssssssssssssssssss

KICKING FACTOR: altitude=

N=

I -N=

0.78

8.22

95.88

e.

The radiation calculations begin with a prompt for observed n, followed by N.

Since N is not known in this example, the program will prompt for year, month and day of month.

year,

The program outputs day of and prompte for latitude.

It then calculates N and n /N.

It prompts for ka which if unknown (as in this example) is then calculated and used to estimate solar radiation.

The program requests albedo and calculates net shortwave radiation.

The longwave calculations begin with a prompt for dry or wet climate designation, followed by calculation of the longwave components, net radiation, and evaluation of Penman ETo* (unadjusted).

assasssssssasassssssss

NET RADIATION: n= 11.58

DATE= 7./ 28.' 72.

DAY 282.

26= 28.58

latitude= 38.88

N= n /N=

13.67

8.84

Ra=

Rs=

16.98

11.33

Albedo=

Rns=

8.25

8.58

DRY Climate f(ed)= f(n /H)= f(t)=

Rn1=

Rn=

8.14

8.86

16.31

1.91

6.59

ssssssssssssss»sssssses

ETos = 8.64 nit./day sees

17g

CHANGES IN STREAMFLOW IN AN HERBICIDE- TREATED

JUNIPER WATERSHED IN ARIZONA

Malchus B. Baker, Jr.

Rocky Mountain Forest and Range Experiment Station

Flagstaff, Arizona

Abstract kill

A 147 -ha juniper watershed in north -central Arizona was sprayed with an herbicide mixture to all overstory vegetation.

After the area was sprayed, annual water yield increased significantly

when flow was greater than 12 mm.

The ratio of mean annual quick flow to event flow prior to treatment was 0.86 and remained essentially the same after treatment.

The herbicide treatment reduced evapotranspiration losses and increased water yield by killing the overstory trees and leaving them in place.

These dead trees provided some shade and wind resistance and created a microclimate that reduced evaporation and enabled the soil below 30 cm to remain above its soil moisture wilting point.

Although mean annual water yield increased by 27% (6 mm, 8 -year mean), this increase may not be practical from a management view point.

Therefore,

it is unlikely that extensive juniper acreage will be treated.

The amount of treated acreage will depend on the demand for water and on the value

of water in the market place.

The area treated will also be constrained by consideration of other resource values and desires of the public.

Introduction

The pinyon -juniper woodland type is between 1,220 and 1,980 m above sea level and occupies extensive areas in the Southwest [Spencer, 1966; Arnold et al., 1964; U.S. Department of Agriculture, Forest Service, 1958].

Pinyon -juniper covers about 21 million ha in Arizona, New Mexico, Colorado, and Utah [Clary et al.

1974].

The distribution and number of trees in this woodland type has increased since the early 1900's because of increased livestock grazing and because of the reduced number of forest fires [Arnold and Schroeder, 1955; Barr, 1956].

cities,

Arnold and Schroeder [1955] reported that encroachment of pinyon -juniper reduces grazing capaincreases erosion, increases livestock handling cost, and possibly decreases water yield.

Barr

[1956] estimated a probable increase in annual water yield of 13 to 25 mm from the removal of pinyon juniper in

Arizona if the land were reseeded with grasses.

However, in

a study of pinyon -juniper removal,

1964b]

Collings and Myrick [1966] found no significant change in water yield.

Skau [1964a and

reported that any change in water yield from pinyon -juniper removal would probably result

from reduced interception and evapotranspiration losses.

Clary et al. [1974], after reviewing all documented hydrologic results from the southwestern pinyon- juniper type, stated that the possibility of increasing water yield through overstory removal was only marginal.

The Beaver Creek research watersheds in north -central Arizona were established by the USDA

Forest Service

in the mid- 1950's to quantify treatment effects on water yield from pinyon -juniper

woodland and ponderosa pine forests.

ulation in

pinyon -juniper woodlands:

The Forest Service has studied two types of vegetation manip-

clearing of the overstory and killing of the overstory with herbicides [Clary, et al.,

1974].

Preliminary results of the herbicide treatment have previously been

reported by Clary et

al.

[1974].

This paper documents results of the 8 -year period following the

herbicide application on a 147 -ha watershed.

Study Area

The two watersheds used in

this study are about 80 km south of Flagstaff,

Arizona,

in the pinyon -juniper woodland type of the Beaver Creek drainage (Figure 1).

Watershed 3, which had the

herbicide applied to it, is 147 ha in area; watershed 2, an untreated control, is directly adjacent and

51 ha in size (Table 1).

The soils in the area are developed from volcanic basalt parent material.

The predominate soil

is a Springerville very stony clay that is about 112 cm deep and has a clay texture throughout [Williams and Anderson, 1967]. Most of the clay fraction is montmorillonìte, which produces pronounced swelling

19

BEAVER CREEK

WATERSHED

Miles

2 3

Watershed Boundaries

Vegetation Type Lines

Improved Roadways

--: Unimproved Roadways

TO FLAGSTAF

'..

Stoneman

Comp tarde

Semi - Desert

Utah Juniper

Alligator

Juniper

I

Pond

Figure 1. -- Location of watershed 2 and 3 in the Beaver Creek drainage area.

Pine

Table 1.

Physical Characteristics for Two

Experimental Watersheds on Beaver Creek

Characteristic

Size (ha)

Aspect

Mid -Area Elevation (m)

Basal Area (m2 /ha)

Annual Precipitation

Before (mm)

After (mm)

Annual Streamflow

Before (mm)

After (mm)

Herbicide

Watershed

147

W

1573

13

453

426

22

28

Control

Watershed

51

NW

1591

12

466

425

25

20 and shrinking.

After each wet and dry cycle, cracks form, opening as much as 5 cm wide and 1 m deep.

Mean elevation of watershed 3 is

1,573 m above sea level, ranging from 1,516 to 1,676 m

(Table 1).

The general aspect of the watershed is west with 92 percent of its area in slopes of

10 percent or less.

Prior to application of the herbicide, watersheds 2 and

3 were stocked with

Utah juniper

(Juniperus osteosperma (Torr. ) Little) and pinyon pine (Pinus edulis (Engelm. )).

Total basal area on watersheds 2 and 3 averaged 12 and 13 m /ha, respectively, with an average of 33 trees per ha

(trees 13 cm d.b.h. and greater).

Mean annu$1 temperature is

13.3° C, and average monthly temperature varies from 3.3° C in

January to 25.0

C in

July.

Mean annual presítpitation on watershed 3 is 442 mm, with a high of

20

691 mm in water year 1973 followed by a low of 210 mm in 1974 (Figure 2).

Mean precipitation

during the seven winter months, October through April, is 270 mm, or 61 percent of the annual total.

Two major precipitation seasons characterize this area.

The most important period from a water yield standpoint is the winter season from October through April.

Most of the remaining precipitation

falls during July, August, and September.

Winter precipitation is associated with widespread, protracted, frontal storms.

Snowfall commonly

begins in November and increases into December.

Snowfall usually declines in January and February, followed by an increase to a peak in March.

Typically, the snowpack is intermittent throughout the season at this elevation [Baker, 1981].

Nearly all summer precipitation falls during thunderstorms.

Although they are frequent, individual storms usually cover relatively small areas.

Mean summer rainfall averages 172 mm.

Continuous streamflow records on both watersheds are obtained from precalibrated, concrete, trapezoidal flumes [Clary et al., 1974].

Mean annual streamflow from the herbicide treated and control watersheds is presented in Table 1.

Annual streamflow on watershed 3 has varied from zero in

1959, 1963, and 1974 to 149 mm in 1973 (Figure 3).

Mean annual streamflow from watershed 3 prior to the herbicide treatment (1958 -1968) was 22 mm, with 82% occurring from October through April as a result of snowmelt or winter rains.

Most of the water yield from the Beaver Creek experimental watershed is produced in the winter.

During the period of this study on watershed 3, in 11 of the 19 years, 96% or more of the annual discharge was during the winter season.

The soil mantle begins to recharge during the winters,

when water from rain or snowmelt is available and evapotranspiration demands are low.

Most streamflow is

in March and April.

The stream channels in these headwater basins become dry before the onset of summer rains.

Summer rains are preceded by the two driest months of the year, May and June, during which precipitation amounts average 13 and 10 mm, respectively.

Because of the high evapotranspiration demands and the distribution and amount of precipitation during the summer on watershed 3, only 4 summer seasons out of 19 years have had 6 mm or more of streamflow.

Although, summmr streamflow

is infrequent, maximum peak discharges from watershed 3 of 7.7 and 5.1 m s km occurred in

August, 1964 and Septemlr, _11970 respectively.

Peak discharges from the same storms on watershed 2 were 9.3 and 4.1 m s

km

.

Much of the streamflow from these upland or headwater basins is the product of quick flow

[Hewlett and Hibbert, 1967].

The shallow A- horizon (about 8 cm deep, with infiltration rates ranging from 20 to 64 mm /hr) on these watersheds, covers a relatively impermeable soil layer (hydraulic conductivities of less than 1 mm /hr).

Rainfall and snowmelt intensities greater than these infiltration and permeability rates are not uncommon on Beaver Creek [U.S. Department of Commerce, 1967; Ffolliott and Hansen, 1968].

Water storage capacity of the Springerville soil series is over 46 cm.

1,00

900

800

700

Summer

Winter

Winter

Average

Average 600

500

400

100

300

200

58 59 60 bl hi fi2

63 64 65 66 fil

Water Year

68

69 70 71 72 73 74 i

75 76

Figure 2. -- Average winter (October -April) and summer precipitation on watershed 3.

21

Treatment and Analysis

Watershed 3 was treated with a foliage spray application of 2.8 kg acid equivalent of picloram and

5.6 kg acid equivalent of 2, 4 -D [(2, 4- dichlorophenoxy) acetic acid] as triisopropolamine

salts in 94 1 of water per ha.

The watershed was treated in August 1968, and the overstory inventory of October

1969 showed that 86 percent of the trees were killed.

The paired watershed method [Wilm, 1943; Kovner and Evans, 1954; Hewlett, Lull, and

Reinhart,

19691 was used to evaluate changes in annual water yield brought about by the herbicide treatment.

A covariance analysis was used to test significance of the pretreatment and posttreatment

annual water

yield regressions.

Confidence limits (95% level) were placed on the pretreatment regression, and posttreatment data were located with reference to these limits to determine significance of treatment in the individual years [Harr, Frederiksen, and Rothacher, 1979].

Effects of Herbicide Application

Streamflow for 19 years on watershed 3 has been divided into two periods (Figure 2).

The first

11 years are the pretreatment or calibration years (1958- 1968), and the last 8 years

(1969 -1976) are

the treatment period following application of the herbicide.

Annual and Seasonal Flow

The

11 years

of pretreatment data (1958 -1968) define the regression (correlation

coefficient

(r) = 0.99) used in determining posttreatment effects on annual water yield.

A covariance analysis

of

the pre-

and posttreatment regressions (1969 -1976,

r = .98),

(0.05 level) in annual water yield following the herbicide application.

indicates

a significant increase

The analysis shows that the treatment response is multiplicative and is significant only when flow is greater than 12 mm

(6 mm on

the control watershed).

In drier years there is a predicted 8 mm increase in water yield when the

control watershed yields 13 mm.

In wet years, when the control yields 102 mm, the herbicide treated watershed is predicted to yield an increase of 28 mm or 121 mm.

Killing the overstory vegetation caused annual water yield to equal or exceed the 5%

prediction

limit 3 out of the 8 posttreatment years (years 1969, 1970, and 1973).

Of the other 5 years, 3 years

(1971,

1972, and 1974) received below average winter precipitation, and all but 1976 received below average annual precipitation (Figure 2).

The fact that 1975 received normal winter precipitation and

160

140 i 120

100

80

60

â

40

20

58 59

60

61

62

63

64

65 66

67

68

Water Year

69 70 71

72 73 74

75 76

Figure 3. -- Annual water yield from watershed 3.

from pretreatment regression.

Increase in water yield due to treatment determined

22

1976 received normal winter and annual precipitation without showing a significant increase may indicate that the effect has ended.

Prior to the herbicide application, the ratio of mean annual quick flow to event flow was 0.86 on watershed 3 and 0.88 on watershed 2 (Table 2).

There was little change in this relationship after the application of the herbicide on either the treated or control watershed.

Discussion

The hydrologic regimes of the forested areas on volcanic- derived soils on Beaver Creek are different from many other forested areas. Because of the relatively shallow soil depth, the impermeable clay soil, and the predominately short spring streamflow period, manipulation of the forest vegetation has a limited affect upon the streamflow regimes from these upland watersheds.

In the hydrograph analyses used, the term quick and delayed flow are used to define the hydrograph components because of the difficulty in defining and quantifying direct runoff and baseflow [Hewlett and Hibbert,

1967] .

Most forested areas have a higher portion of their streamflow produced by the delayed flow

component.

On Beaver Creek the higher percent of streamflow results from quick flow because of their characteristic soil and climatic conditions.

The herbicide treatment applied on watershed 3 reduced evapotranspiration losses, as shown by the increase in annual water yield and the decrease in soil moisture loss.

The soil mantle (with an available soil water storage of 46 to 56 cm) begins to recharge annually during the fall and winter period on both treated and untreated areas, as observable in the saturated surface soil and overland flow conditions during most spring runoff periods and as apparent in the high ratio of quick flow to

event flow.

The increase in water yield was achieved by killing the overstory trees and leaving them in place.

These dead trees provided shade and wind resistance and created a microclimate which reduced evaporation and enabled the soil below 30 cm to remain above its soil moisture wilting point [Johnsen,

1980].

With reduced soil water loss, less precipitation was needed to recharge the soil mantle and

consequently more precipitation became available for streamflow.

tion.

Analysis of the annual water yield response showed a sharp increase after the herbicide applica-

The increase is

believed to be largely the result of reduced evapotranspiration loss.

An additional contributing factor would be the increased exposure of soil following the defoliation of the overstory trees.

The soil surface would be particularly susceptible to raindrop impact and subsequent soil surface "puddling" and reduced infiltration rates.

The initial increase, 65% as reported by

Clary et al.

(1974), was reduced after 1972 and remained consistent through 1976.

By 1973 the watershed would have had the opportunity to stabilize.

Herbage production increased following the treatment and the additional ground cover would provide protection for the soil surface and contribute to an increase in soil permeability.

Table 2.

Effects of Killing Pinyon -Juniper Trees on

Mean Quick Flow and Delayed Flow

Period

Water Year (Oct -Sept)

Before Treatment

After Treatment

Summer

Before Treatment

After Treatment

Winter

Before Treatment

After Treatment

22

18

5

2

17

16

Mean

Quick flow

Control

Watershed

Herbicide

Watershed

Mean

Delayed flow

Control

Watershed

Herbicide

Watershed

MM

19

23

4

3

15

20

3

2

0

0.4

3

2

0

0

3

5

3

5

23

Although the increase in annual streamflow is statistically significant on the treated watershed for flow events of greater than 12 mm, the 27% (6 mm) increase in mean annual streamflow (8 -year mean) may not be a practical or a significant increase from a management view point.

To make this treatment economically feasible,

a land manager might need additional increases in other resources such as additional grazing caused by increased herbage production and increased benefits for wildlife.

The results also indicate, but were not experimentally verified, that the treatment effect may only last

5 -8 years and that the watershed will then have to be retreated to maintain the increased flow.

tation.

The reservoir system in Arizona depends on water yields derived primarily from winter precipi-

Although a significant increase in annual streamflow can be realized by killing overstory vege-

tation on an upland basin,

it cannot be assumed that such a treatment will produce an increase in water yield in the valley below.

Because of the limited spring streamflow period, most water yield increases resulting from vegetation manipulation will be added to flowing stream channels.

Therefore, the water yield increase or a significant portion of the increase is less likely to be lost in transmission from the headwater basins

to the reservoir system.

However, as Hibbert [1979] observes, an increase in water yield from treatments on small upland watersheds is no assurance that the increases can be measured at the

downstream reservoir even if transmission losses are negligible, because the increased flows may not be detectable after combining with flows from other sources.

There is also little likelihood that extensive acreage will ever be treated as in this study.

As

Hibbert [1979] states, the actual water yield increases from vegetation manipulation will likely be less than the maximum potential because only a portion of each vegetation type can be treated economically for water yield increases.

The amount of acreage that can be treated will depend on the demands for

water and on the value of water in the market place.

The amount of acreage treated will also be constrained by considerations of other resource values and desires of the public.

These results show that water yields can be increased on basins with volcanic soil by chemically

killing the juniper overstory and leaving the dead trees standing.

Therefore a management system could be devised where dispersed upland juniper basins are chemically treated to provide some additional water yield.

However, these treated areas may not be esthetically pleasing and the use of

chemicals in the environment might be undesirable.

References Cited

Arnold, J.

F., D. A. Jameson, and E. H. Reid.

The pinyon -juniper type in Arizona: grazing, fire, and tree control.

USDA Prod. Res. Rep. 84, 28 p, 1964.

Effects of

Arnold, J. F., and W. L. Schroeder, Juniper control increases forage production on the Fort Apache

Reservation.

Stn. Pap.

18,

Sta., Fort Collins, Colo., 1955.

35 pp., USDA Forest Serv., Rocky Mt.

Forest and Range Exp.

Baker, M. B., Jr., Hydrologic regimes of forested areas in the Beaver Creek watershed.

Gen. Tech.

Rep. RM -88, 8 pp., USDA Forest Serv., Rocky Mt. Forest and Range Exp. Sta., Fort Collins,

Colo., 1981.

Barr, G. W., Recovering rainfall, part 1, 33 pp., Arizona Watershed Program, Arizona State Land

Department, Water Division,

Arizona, 1956.

Salt River Valley Water Users' Association and the University of

Clary, W.

P., et al.,

Effects of pinyon -juniper removal on natural resource products and uses in

Arizona, Res. Pap. RM -128,

Sta., Fort Collins, Colo., 1974.

28 pp., USDA Forest Serv., Rocky Mt.

Forest and Range Exp.

Collings, M. R., and R. M. Myrich, Effects of juniper and pinyon eradication on Pap. 491 -B, 12 pp.,

U.S. Geol. Surv., 1966.

Ffolliott, P.

F., and E. A. Hansen, Observations of snowpack accumulation, melt, and runoff on a small Arizona watershed, Res. Note RM -124, 7 pp., USDA Forest Serv., Rocky Mt. Forest and

Range Exp. Sta., Fort Collins, Colo., 1968.

Harr, R. D., R. L. Fredriksen, and J. Rothacher, Changes in streamflow following timber harvest in southwestern Oregon, Res. Pap. PNW -249, 22 pp., USDA Forest Serv., Pac. Northwest Forest and Range Exp. Sta., Portland, Oreg., 1979.

Hewlett, J. D., and A. R. Hibbert, Factors affecting the response of small watersheds to precipitation in humid areas,

Press, New York, 1967.

in

International Symposium on Forest Hydrology, pp.

275 -290, Pergamon

Hewlett, J. D., H. W. Lull, and K. G. Reinhart, In defense of experimental watersheds, Water

Resour. Res., 5(1), 306 -316, 1969.

24

Hibbert, A. R., Managing vegetation to increase flow in the Colorado River Basin. Gen. Tech. Rep.

RM -66, 27 p.

1979.

USDA Forest Serv., Rocky Mt. For. and Range Exp. Stn., Fort Collins, Colo.,

Johnsen, Jr., T. N., Picloram in water and soil from a semiarid pinyon -juniper watershed, J.

Environ. Qual. 9(4), 601 -605, 1980.

Kovner, J. L., and T. C. Evans, A method for determining the minimum duration of watershed

ex-

periments, Trans. Amer. Geophys. Union, 35(4), 608 -612, 1954.

Skau, C. M., Interception, throughfall, and stemflow in Utah and alligator juniper cover types of

northern Arizona, For. Sci. 10, 283 -287, 1964a.

Skau, C. M.,

Soil water storage under natural and cleared stands of alligator and Utah juniper in northern Arizona Res. Note RM -24,

Exp. Sta., Fort Collins, Colo., 1964b.

3 pp., USDA Forest Serv., Rocky Mt. Forest and Range

Spencer, Jr., J.

S., Arizona's forests.

Resour. Bull. INT -6, 56 pp., USDA Forest Serv., Intermt.

Forest and Range Exp. Sta., Ogden, Utah, 1966.

U. S. Department of Agriculture.

Forest Service, Timber resources for America's future, For.

Resour. Rep. 14, 1958.

U. S. Department of Commerce, Rainfall frequency atlas of Arizona for durations of 6 -24 hours and return periods from 2 to 100 years, 1967.

Williams,

J. A., and T. C. Anderson, Jr., Soil Survey of Beaver Creek area, Arizona.

USDA Forest

Serv., and Soil Conserv. Serv., and Ariz. Agric. Exp. Sta., 75 pp., Washington, D. C., 1967.

Wilm, H.

G.,

Statistical control of hydrological data from experimental watersheds, Trans. Amer.

Geophys. Union, 2, 618 -622, 1943.

25

DETERMINING WATERSHED CONDITIONS AND TREATMENT PRIORITIES by

Rhey M. Solomon

James R. Maxwell

Larry J. Schmidt

USDA Forest Service

Albuquerque, New Mexico

Abstract

A method is presented for evaluating watershed conditions and alternative watershed treatments.

A computer model simulates runoff responses from design storms.

The model also simulates runoff changes due to management prescriptions that affect ground cover and structural treatments.

Techniques are identified for setting watershed tolerance values for acceptable ground cover and establishing treatment priorities based on the inherent potentials of the watershed.

Introduction

Watershed conditions have historically been an important issue in the Southwest and Intermountain

West.

Early in this century, forest reserves were set aside primarily to sustain favorable conditions of flow for downstream users.

During the period 1910 -1960, considerable research was devoted to investigating relationships between vegetation, soil, ground cover, and runoff.

Classic studies revealed a strong relationship between ground cover of plants and litter and surface runoff (Croft and Bailey, 1964;

Meeuwig, 1960).

As ground cover decreases, surface runoff increases especially from intense summer storms (Coleman, 1953). Primed with this knowledge, Federal land management agencies began adjusting livestock numbers to conform with land capability, aggressively suppressing wildfires, and installing runoff controls such as contour trenches.

Many of these controls were installed by the CCC in the

1930's to improve or protect vegetation cover.

By the 1960's, many communities that had experienced flood damages associated with poor watershed condition now enjoyed the benefits of managed watersheds with revitalized cover.

Many who experienced the consequences of poor watershed condition have passed on.

The new generation, and the influx of people unaware of local history, generally take the absence of severe floods in managed areas for granted.

In some cases, people have developed lands that were once active floodplains.

In the Southwest, the emphasis of the 1960's was on increasing water yield through vegetation changes.

The 1970's spawned a degree of environmental awareness with an emphasis on water quality.

Most universities shifted attention to these areas.

These two items had scientific and media appeal, and overshadowed the traditional watershed condition concerns.

The 1980's have given us stronger emphasis on commodity production, and population shifts to the Southwest.

awakening a concern for watershed conditions among land managers.

These pressures are re-

Periodic summer floods have renewed interest in the role of watershed condition in regulating flood peaks.

This has encouraged a reevaluation of past research to find means of assessing watershed condition.

Some of the most relevant research was completed before the age of computer libraries and was difficult to discover.

However, a strong body of knowledge exists which relates vegetation cover and soil conditions to runoff.

A technique for linking plant and litter cover to peak flow is fabricated from this knowledge base and builds upon the approach outlined by Lull (1949).

We have developed a process model that ties ground cover to peak runoff for a specified design storm typical of the summer season in the Southwest.

The model can determine the potential for reducing peak flows by increasing ground cover and installing structural treatments.

The procedure also proposes a rationale for determining a minimum tolerance cover necessary to protect the site and downstream values.

This paper outlines and documents an approach for quantifying watershed condition.

discuss the computer model used to simulate runoff.

We first

Using this computer tool, we show examples of how changes in watershed conditions alter peak flows, and discuss the ability to improve runoff responses through changes in vegetative cover and structural treatments.

To adequately translate

2 7

this modeling tool to an easily understood concept, we introduce the concept of "tolerance" and a

"watershed condition index ".

Modeling Approach

A principal indicator of watershed condition is the fluvial system's ability to transport water through a watershed without damaging channel stability, floodplain improvements, or riparian values.

Because flow energies, area of inundation, and unstable conditions are greatest during peak flows, we need to assess the effects of land management on the magnitude and frequency of damaging peak flows.

Our approach is to model the hydrologic processes affecting runoff and then look at effects management could have on these processes.

The two principal hydrologic processes which management can influence are infiltration and surface detention storage.

We can, therefore, propose land treatments that affect these two components.

Optimum infiltration and storage are best accomplished by assuring an adequate ground cover of plants and litter (Rosa, 1954; Croft and Bailey, 1964).

We can also increase them by such activities as soil ripping, plowing, or other techniques that break up compacted or sealed surfaces (Croft and Bailey, 1964).

These techniques are short lived unless vegetative cover is increased in conjunction with initial treatment.

Horton (1933) concluded that streamflow consists of two components: and (2) ground water flow.

(1) direct overland runoff

He proposed that storm flows occur when rainfall exceeds infiltration rates and that base flows are fed by ground water aquifers.

This exceedance of infiltration is apparent to anyone who has been caught in an intense Southwestern rainstorm.

However, this is not the sole source of runoff in forests or where rainfall intensities are moderate (Hibbert, 1975).

We focused on overland flow because of our ability to affect this component and its importance in generating peak flows in the Southwest.

We also incorporated the variable source area concept (Hewlett and Nutter,

1970) into the modeling approach, because it is important, and perhaps the dominant process, in forests that are in good watershed condition.

Our goal was to model runoff processes and express them in simple terms that have meaning to the manager as well as the scientist.

met the following objectives:

To meet this goal, we searched for a model that best

1.

Sensitive to hydrologic processes that management can affect.

2.

Theoretically defensible.

3.

Requires minimal data input (i.e., data that is readily available or easily estimated).

4.

Applies to the full range of conditions in the Southwest.

5.

Applies to small (1 -10 sq. mi.) watersheds where management practices can affect hydrologic responses.

6.

Applies to individual rainfall events.

All major hydrologic processes which occur during rainstorms can be simulated in detail with the current state -of- the -art.

data.

The problem is to mirror these complex processes using only readily available

Therefore, our efforts focused on models that consider only the most significant factors in simulating the processes controlling runoff.

Numerous models were reviewed.

The "event" oriented models we investigated were: the SCS model

(USDA, 1972) and various modifications (Ward et al., 1981; Knisel, 1980); the "Rational" Formula;

HYMO (USDA, 1973); the Stanford Model (Crawford and Linsley, 1956); and USDAHL -70 (Holton and Lopez,

1971).

Each of these models has merit but none meets all the listed objectives.

The principal failing was an inability to model short, intense rainstorms and be sensitive to changes in infiltration and storage.

Accordingly, we were required to piece together parts from various models to best meet the objectives.

The result was a simple computer model that is sensitive to land management treatments, requires a moderate amount of data, and appears theoretically sound.

The model was developed in the belief that watershed conditions are best reflected by flood flows resulting from intense rainstorms.

If satisfactory watershed conditions are a principal objective of management, then we need to demonstrate our ability to affect peak flow and timing of runoff.

The Model

The model SHOWER was developed by incorporating theoretical as well as empirical relationships that describe the processes outlined previously.

tions were made to fill these voids.

Where data or theory were vague or absent, assump-

A complete discussion of the model is given by Solomon (1982).

28

Precipitation is the driving input.

This input is infiltrated for a designated time increment.

Precipitation that does not infiltrate is cumulated in detention storage until the next time increment.

Quantities in excess of infiltration and detention storage become surface overland flow.

The model places this excess water into the channel system and routes it to the downstream point of interest.

Water that infiltrates the soil is added to the soil water and cumulates until the soil is filled to gravitational free water.

At this point water is fed to the channel at a rate dependent on the amount of water in excess of free water holding capacity and the drainage density.

This soil excess is added to the surface excess and routed to the downstream point of interest.

Watershed Condition Examples

Two examples portray the concept of watershed condition and our ability to affect storm hydro

graphs.

Agricultural Research Service Watershed 47.003, near Albuquerque, New Mexico (Hickok et al.,

1959), and Halfway Creek, near Farmington, Utah (Doty, 1971), were chosen because of available data describing treatment responses.

These watersheds contrast sharply as shown in Table 1.

Table 1. Watershed Characteristics for Example Watersheds.

Characteristic

Albuquerque 47.003

Halfway Creek

Area:

176 Acres

464 Acres

Average Slope:

10%

50%

Channel Slope:

3%

38%

Soils:

Clay loam and silt loam; 2 -3 feet deep shallow loam, sandy loam

Vegetation: sagebrush, grasses, snakeweed, saltbrush oakbrush, sagebrush, aspen

Ground Cover:

25%

60 -80%

Mean Annual Precipitation:

8"

30"

These two watersheds illustrate runoff sensitivity to vegetative cover and structural treatments for actual storm events.

We found that it is not the total volume of rainfall that dictates the hydrograph, but rather the distribution and intensity of rainfall.

Many models fail to mimic hydrograph peaks because they fail to model rainfall input on a short enough time base.

Ground Cover Changes

Ground cover can have marked effects on surface runoff (Croft and Bailey, 1964; Woodward,

1943; Meeuwig, 1960).

Watershed 47.003 shows how the computer model responds to cover changes and how dominant cover can be in determing peak flow responses.

(1) August 3, 1964, (2) September 2, 1965, and (3) June 10, 1966.

Three rainstorms are used:

These storms were of moderate volume and intensity as shown in Table 2.

They were simulated for different cover conditions.

Figure 1 shows the considerable influence management can exercise on peak flow.

Increasing ground cover from 25 to 35 percent would cause about a 50 percent reduction in peak flow for all the storms modeled.

Conversely, allowing ground cover to deteriorate from 25 to 15 percent would increase peak flows about 50 percent.

Comparing different storms, the storm of September 2, 1965 would have produced the same peak flow as the June 10, 1966 storm if ground cover were 5 percent rather than 25 percent.

This would translate to a 2 year storm producing a peak flow more characteristic of a 10 year storm.

Total storm runoff volumes are plotted in Figure 2 as a function of cover.

the same pattern as Figure 1.

These changes show

Reduced runoff volumes have implications to reservoir management and translate to greater soil water for increased plant growth and base flows.

29

Time

(Minutes)

0

5

August 3, 1964

Accumulated

Volume

(Inches)

.04

10

15

20

25

30

35

40

45

.71

.73

.74

.37

.56

.67

.08

.12

.18

Intensity

(In /hr)

.48

.48

.48

.24

2.28

2.28

1.32

.48

.24

.12

30

35

40

45

50

55

Time

(Minutes)

0

September 2, 1965

Accumulated

Volume

(Inches)

5

10

15

.03

.04

Intensity

(In /hr)

.36

.12

.12

20

25

.05

.06

.07

.08

.11

.12

.12

.12

.36

.17

.26

.45

.56

.72

1.08

2.28

1.32

.06

60

65

.61

.63

,24

10

12

8

6

2

4

Time

(Minutes)

0

June 10, 1966

Accumulated

Volume

(Inches)

14

16

18

.2

.37

.49

.66

.81

.90

.98

1.03

1.04

Intensity

(In /hrl

4.5

2.7

2.4

1.5

6

5.1

3.6

5.1

.3

Table 2. Precipitation Data for Three Storms on the Albuquerque Watershed 47.003.

200

100

80

m

":.60

o

40

OJ

30

LL

< 20

W

o.

\

\

qu\ep

Ó°

\\

.

0

P

;

N \

¡

ó

°

Ó

'O

°-

2

1

10

8

6

4

10

20 30 40 50

GROUND COVER

60

70

80

(percent)

90 100

100

80

60

%

?, o°

\Q4,

ú.

4.

11)

\

\

\ \

'?

s\

4

,

°e;

\%

\

á

1

\

)

1

10 20 30

40

50 60 70

80

GROUND COVER (percent)

90

100

Figure 1. Peak Flow Responses to Ground Cover

Changes for Three Summer Storms.

Figure 2. Runoff Responses to Ground Cover

Changes for Three Summer Storms.

30

The next step in model verification and refinement will be to simulate hydrographs on watersheds where significant cover changes have actually taken place and hydrologic data are available.

The classic Watersheds A and B of the Great Basin Station in Utah (Meeuwig, 1960) offer this opportunity and hopefully will confirm the preliminary results.

Structural Treatments

When cover decreases on a watershed due to overuse, rehabilitation can be difficult.

ment of vegetative cover and favorable soil structure may require decades.

Reestablish-

In today's economy, managers must be concerned about the resource entropy associated with harvesting resources in excess of the land capability (Rifkin and Howard, 1980).

through erosion.

The state of entropy comes from dissipating the soil productivity

This makes any stabilizing treatment far more costly than proper management would have been.

Green (1971) captures this concept in his statement:

The most difficult job is to guard against negating the benefits of spending by accomodating public pressures for certain types of land use that can either act counter to the goals of watershed management or increase the management cost of rehabilitation activity.

The public land manager is no less responsible for fiscal integrity than he is for biological, ecological and physical concern for the resource.

In many cases, recovery may have to be aided with structural treatments.

These treatments serve two purposes: (1) they reduce erosion and runoff immediately; and (2) they help reestablish cover by reducing water losses and increasing available water.

Such structural treatments were applied to Halfway Creek (Doty, 1971).

Before -and -after situations were modeled with SHOWER.

Peak flows agree well with actual hydrographs for those storms.

Additionally, SHOWER was used to simulate what the hydrograph from the storm in 1945 would have looked like with trenching and what the hydro graph from the storm in 1965 would have looked like without trenching (Figure 3).

20-

18

16 d14 d12

510

J 8

LL

6

4

2

HALFWAY CREEK

Storm of Aug. 19,1945 Storm of July 18,1985

WITHOUT TREATMENT(edtud)

1 2 3

TIME(hrs.)

4

5

I

'

I

I,`WITHOUT TREATMENT(modeled)

`

\

WITH TREATMENT(actual)

1 2 3

TIME(hrs.)

Figure 3. Pre -and Post -Treatment Hydrographs for Halfway Creek.

This type of comparison visually demonstrates the direct effects of structural treatments for an event rather than by traditional means such as paired watersheds.

This method does not lend itself to statistical interpretation as other methods might, but the decision maker can readily identify the tradeoffs being made.

31

Cover Versus Structures

Through modeling, it is possible to compare hydrograph changes from increasing cover versus installing structural treatments.

August 3, 1965.

Numerous simulation runs were made on Watershed 47.003 for the storm of

Figure 4 shows the increase in cover and corresponding amount of contour trenching or furrowing necessary to reduce peak flow by equal amounts.

This diagram clearly demonstrates that both structural measures and cover can effectively control surface runoff.

However, prudent planning should consider only the improvement in cover for evaluating long term benefits.

Structural treatments, while effective, are relatively short lived and provide only temporary site control pending establishment of

This vegetation.

The structural measures may temporarily be more effective than the long term cover.

is because the design of the structures must consider the risk of failure over the period required to attain satisfactory cover.

This is a function of downstream consequences of structural failure, a level of risk, and the costs of retreatment if the measures are damaged.

It certainly is not prudent or justified to expect more than temporary control of runoff from structural measures.

EQUIVALENT TREATMENT MEASURES

100 wáBÓ xo,

N e

<

60

ó

«40

G e

I- mi

Z" w

20

c)

¢

w

G.

Storm of Sept 2,1965

watershed 47.003

5

10 15 20

25 30

GROUND COVER INCREASE(percent)

35

Figure 4. Comparison of Treatment Effectiveness.

SHOWER offers a technique for evaluating peak flow alterations due to changes in cover and structural treatments.

Additionally, roads can be incorporated into the model by considering the road network as one or more hydrologic units and applying the appropriate infiltration characteristics and runoff routing factors.

Roads are also considered an extension of the channel network for soil water flow (Megahan, 1972).

The Concept of Tolerance

The previous section showed how reducing ground cover increases runoff.

become unacceptable?

When do such increases

We must answer this question to distinguish between satisfactory and unsatisfactory watershed conditions.

Watersheds and land units have a maximum potential ground cover that can be achieved naturally.

This condition prevailed over most of the Southwest before 1880.

Persistent land disturbance progressively reduces ground cover from the potential.

Eventually, runoff may increase to a point where it causes economic or environmental impacts which the land manager deems unacceptable.

Ultimately, runoff may increase to a point where water flows and land productivity are permanently impaired.

The following discussion presents techniques to derive tolerance levels of ground cover for runoff.

Two levels of tolerance are discussed:

(1) a variable "management" tolerance responsive to social concerns for selected areas; and (2) an absolute "resource" tolerance responsive to permanent physical damage for all areas.

32

Management Tolerance

SHOWER calculates flood peaks for varying levels of ground cover.

For each watershed, the land manager must decide how big an increase in flood peaks (how big a risk of increased flood damages) he is willing to accept (Schmidt, 1978).

Watershed priority (Shaw et al., 1981) should be used to determine this marginal level of risk.

Many low priority watersheds may not warrant a management tolerance because risks of flood damages are very low.

If the flood peak calculated for existing ground cover exceeds the management tolerance set for a watershed, the watershed condition is unsatisfactory.

Resource Tolerance

Channel networks form as a function of the erosive force of runoff and the erodibility of the watershed. A channel forms where runoff becomes sufficient to incise the surface.

In any area, there is some minimum drainage area or slope distance required for a channel to form (Schumm, 1977).

As ground cover is progressively reduced from the potential, the erosive force of runoff increases and the resistance of the surface to erosion decreases.

Thus, the drainage area or slope distance required for a channel to form is reduced.

Eventually, the channel network will expand headward in response to these changes.

If unchecked, this process ultimately will severely degrade the watershed and permanently impair the discharge- sediment function of the fluvial system.

One approach for deriving a resource tolerance for runoff computes a critical slope distance, represented by complete expansion of the channel network up all slope depressions to the ridge.

The resource tolerance is exceeded when ground cover is reduced enough to permit such a drastic response, which would occur over several decades.

Horton (1945) introduced the concept of the "belt of no erosion." it as the mean horizontal distance from a channel to the nearest ridge.

two equations:

B

5280

For channel erosion, he defined

It can be computed using

(Equation 1)

2d

B=

65 f(sinl'17a)(cos'501a) s1.67

r

(Equation 2) where: B = belt of no erosion (feet), d = drainage density (miles per square mile), f = surface friction factor, a = slope angle (degrees), s

= soil shear resistance factor (pounds per square foot), and r = maximum runoff intensity (inches per hour).

A "tolerance" B is computed by extending the channel network to the ridge and using equation 1.

Equation 2 can be solved for any level of cover.

Eventually, reducing ground cover will increase r and lower s to the point where the existing B (equation 2) declines to the tolerance B (equation 1).

At that leveT of cover, watershed condition is unsatisfactory.

If ground cover is not increased, radical channel expansion will ultimately occur.

Measure of Watershed Condition

A measure of cover can provide an index of watershed condition that is straightforward, responsive, and meaningful to management.

Watershed conditions can be evaluated using ratings that represent the general hydrologic conditions of the land.

These condition ratings are determined by comparing measured existing cover against estimated potential and tolerance cover.

Lands with different natural capabilities are thus equalized; desert watersheds are not compared with forested watersheds for condition ratings.

The watershed condition index is defined by:

W

Where:

W = watershed condition index,

E

= existing area -weighted cover,

P

T

= the natural maximum weighted cover, and

= the cover conditions necessary to prevent excessive risk of flood damage or channel expansion.

33

If existing cover is below tolerance levels the watershed condition is unsatisfactory (W< 0.0).

Satisfactory conditions are defined as having W between 0.0 and 0.5.

Optimum conditions are W values greater than 0.5.

The distinction between satisfactory and optimum watershed conditions is arbitrary and serves only to alert management to the conditions relative to potential and tolerance.

A watershed in satisfactory condition meets minimum land stewardship requirements but is closer to tolerance than to potential cover.

An optimum condition watershed is closer to potential.

A further expansion of the classification system is needed if the system is to have more meaning to management.

In addition to knowing how well a watershed performs hydrologically, the manager needs to know where he can invest the fewest dollars for the greatest returns.

This is done by putting watersheds into "opportunity classes."

These opportunity classes are a measure of the difference between potential and tolerance cover (P -T).

The larger this difference is, the greater are the opportunities for affecting favorable conditions of flow.

The smaller this difference is, the more limited are the opportunities.

We can therefore display watershed conditions as shown in Figure 5.

The numerical ratings in Figure 5 give the treatment priority.

An UNSATISFACTORY /FULL opportunity watershed would receive first priority for planning treatment measures.

Note that all unsatisfactory watersheds regardless of opportunity class, should be planned for restoration before satisfactory watersheds.

100

C

41

280

WATERSHED CONDITION /OPPORTUNITY CLASS

1.7 Decreasing planning and treatment priority

POTENTIAL COVER

W 60

O

U

0

Z

4 0 wit-

\MTE d

UNSAT/LIMITED I

3

I

5AT

Ift°-

4

5

UNSATfMODERATE

2

I

I

UNSAT/FULL

1

TOLERANCE COVER

INCREASING ELEVATION AND PRECIPITATION

Figure 5. Watershed Conditions and Opportunity Classes.

This classification system is purposely made simple by relating watershed performance to a single index, ground cover.

It serves to convey the concept of favorable watershed conditions to management.

Our feeling is that the concepts for improving hydrologic response have often been needlessly complicated by technical specialists.

Over the years, appreciation of our ability to affect runoff and erosion has been given to specialists, and therefore, a commitment to maintaining favorable conditions of flow has been partially lost by management.

It is again time that all levels of managers, technical specialists, and decision makers realize their responsibilities for maintaining satisfactory watershed conditions.

This can only come about by instilling an understanding of the processes of watershed management in a straightforward way.

Future Research, Equipment, and Data Needs

The process of developing the model and technique identified several needs as follows:

1.

Rainfall and runoff data for short time increments (1 to 5 minutes) on small basins

(5 to 10 sq. mi.).

34

2.

Gaging equipment which is event oriented, solid state (to enhance accuracy), and directly computer -processible to facilitate data handling.

3.

An assessment of current ground cover conditions for public lands.

4.

Techniques for estimating potential ground cover for various ecosystems in the West.

5.

Effects on baseflows and interflow resulting from alterations of infiltration and reduced overland flow.

6.

Relationship between cover and activities on infiltration and runoff.

Conclusion

Good watershed conditions benefit everyone. Rain and snow are absorbed into the soil reservoir on slopes and released over a longer period of the year.

capacity of downstream reservoirs.

This increases the effective regulating

Reservoirs and irrigation works require less maintenance because of reduced sediment.

Productive soil is maintained on -site providing for sustained production of lumber, fuelwood, livestock, wildlife, recreation and water.

There is ample evidence in the literature of the efficacy of improving watershed condition and the relationships between ground cover and runoff.

There are examples of successful treatments in New Mexico in pinyon -juniper and juniper -grasslands (USDA, 1960;

Columbus, 1980).

To achieve and maintain satisfactory watershed conditions, land uses must be designed to match the inherent capability of the land and be compatible with the needs of downstream communities.

Floods, muddy water, and streams that dry up quickly are symptoms of unsatisfactory watershed conditions.

Many of these consequences have been inherited by the present generation and are accepted as the natural situation.

However, we can in many cases make positive changes in watershed condition and hydrologic responses.

References Cited

Colman, E.A. 1953.

Vegetation and watershed management.

The Ronald Press Co., New York. 412 p.

Columbus, J.T. 1980.

Watershed abuse -the effect on a town.

Rangeland 2(4):148 -150.

Crawford, N.H. and R.K. Linsley. 1962.

digital computer.

The synthesis of continuous streamflow hydrographs on a

Dept. of Civil Engineering, Stanford Univ. Technial Report No. 12. 121 p.

Croft, A.R. and R.W. Bailey. 1964.

Mountain water.

Ogden, Utah. 64 p.

USDA Forest Service, Intermountain Region,

Doty, R.D. 1971.

Contour trenching effects on streamflow from a Utah watershed.

Research Paper INT -95. 19 p.

USDA Forest Service

Green, A.W. 1971.

Sone economic considerations of watershed stabilization on National Forests.

USDA Forest Service Research Paper INT -92. 10 p.

Hewlett, J.D. and W.L. Nutter. 1970.

The varying source area of streamflow from upland basins.

In: Proc. of the Symp. on Interdisciplinary Aspects of Watershed Management. p. 65 -83. Amer.

Soc. of Civil Engr. New York.

Hibbert, A.R. 1975.

Percolation and streamflow in range and forest lands.

In: Proceedings of

Fifth Workshop of the United States /Australia Rangelands Panel, Boise, Idaho. pp. 61 -72.

Hickok, R.B., R.V. Keppel and B.R. Rafferty. 1959.

Hydrograph synthesis for small aridland watersheds.

Jour. of Agric. Engineering. 40(10):608 -611, 615.

Holton, H.N. and N.C. Lopez. 1971.

USDAHL -70 model of watershed hydrology.

Research Service.

Technical Bulletin No. 1435. 84p.

USDA Agricultural

Horton, R.E. 1933.

The role of infiltration in the hydrologic cycle.

14:446 -460.

Amer. Geophy. Union. Trans.

Horton, R.E. 1945.

Erosional development of streams and their drainage basins; hydrophysical approa( to quantitative morphology.

Bull. of the Geological Soc. of Amer. 56:275 -370.

35

Knisel, W.G. (ed). 1980.

management systems.

CREAMS -a field scale model for chemical, runoff, and erosion from agricultural

USDA Conservation Research Report No. 26. 643 p.

Meeuwig, R.O. 1960.

Watersheds A and B -a study of surface runoff and erosion in the subalpine zone of central Utah.

Jour. of Forestry. 58(7):556 -560.

Megahan, W.F. 1972.

Subsurface flow interception by a logging road in mountains of central Idaho.

In: Proc. Natl. Symp. of Watersheds in Transition.

Fort Collins, Co.

Am. Water Resour. Assoc.

p. 350 -356.

Rifkin, J. and T. Howard. 1980.

Entropy.

The Viking Press, New York. 305 p.

Rosa, J.M. 1954.

Guides for program development flood prevention on small watersheds of the Rocky

Mountain area.

USDA Forest Service, Intermountain Region, Ogden, Utah. 152 p.

Schmidt, L.J. 1978.

The use of risk in specifying job quality.

Region.

Hydrology Note No. 8. 8 p.

USDA Forest Service, Southwestern

Schumm, S.A. 1977.

The fluvial system.

John Wiley and Sons, New York. 338 p.

Shaw, D., R. Solomon, J. Maxwell, and L. Schmidt. 1981.

program in the Southwestern Region for the 1980's.

Hydrology Note No. 11. 17 p.

A system for focusing the watershed management

USDA Forest Service, Southwestern Region.

Solomon, R.M. 1982.

SHOWER -storm hydrograph output for watershed evaluation and restoration.

USDA Forest Service, Southwestern Region. 30 p.

Ward, A., T. Bridges and B. Wilson. 1981.

A simple procedure for developing a design storm hydrograph.

Water Res. Bull. 17(2):209 -214.

Woodward, L. 1943.

Infiltration -capacity of some plant -soil complexes on Utah range watershed -lands.

Trans. Am. Geophy. Union. 24:468:475.

USDA. 1960.

Tour guide to Bernalillo watershed protection project.

Region, Cibola National Forest. 7 p.

USDA Forest Service, Southwestern

USDA. 1972.

Hydrology.

Section 4, National Engineering Handbook.

USDA Soil Cons. Service,

Washington, DC.

USDA. 1973.

HYMO: problem- oriented computer language for hydrology modeling.

Research Service.

ARS -5 -9. 75 p.

USDA Agricultural

36

SEASONAL CHANGE IN INFILTRATION AND EROSION FROM USLE PLOTS IN SOUTHEASTERN ARIZONA

J. R. Simanton and K. G. Renard

The authors are Hydrologist and Hydraulic Engineer, respectively, U.S. Department of Agriculture, Agricultural Research Service, Western Region, Southwest Rangeland Watershed Research Center, 442 East Seventh Street, Tucson, Arizona

85705.

ABSTRACT

A rotating boom rainfall simulator was used on

3 x

10.7 m plots to determine Universal

Soil Loss

Equation (USLE) parameter values.

Simulator runs were made in the spring and fall of 1981 on two replications of four treatments on three soil types in southeastern Arizona.

The treatments were: natural, vegetation removed, erosion pavement and vegetation removed, and tilled (moldboard plowed and disked).

Runoff, infiltration, and soil loss varied significantly between treatments and, most interestingly, between the spring and fall runs.

Plot surface characteristics of rock, gravel, soil, litter, and vegetation cover could not explain this seasonal variation in hydrologic response.

ARIZONA

OCHI SE COUNTY

WALMUT 6L1LCM ERPERIAIEMTAL WATEREMEM

PERIPMERAL AREA

WATERSHED AREA META.0

Figure 1.

Watershed location map.

INTRODUCTION

Rangeland areas, like many other areas, exhibit extreme variability in the hydrologic processes affecting erosion and sediment yield.

As part of a nation -wide effort to improve application utility of the USLE (Wischmeier and Smith 1978) to various regions of the United

States, the Southwest Rangeland Watershed Research Center, USDA -Agricultural Research Service, in Tucson, Arizona has been using a rainfall simulator and runoff -erosion plots to determine values for the various USLE factors which might be applicable for rangelands.

This work is being conducted on the 150 km2 Walnut Gulch experimental watershed near Tombstone, in southeastern Arizona

(Fig.

1).

This watershed is representative of millions of hectares of brush and grass rangeland found throughout the semiarid Southwest.

Major vegetation of the watershed includes creosote bush (Larrea divaricata), white thorn (Acacia constricta), tarbush (Flourensia cernua), black grama

Bouteloua eriopoda), blue grama (Bouteloua gracillas) tobosagrass (Hilaria mutica), and bush muhly

(Muhlenbergia Porteri).

Soils are generally well drained, calcareous, gravelly loans with large percentages of rock and gravel on the soil surface.

Average annual precipitation on the watershed is about 300 mm, and is bimodally distributed, with approximately 70 percent occurring during the summer thunderstorm season of July to mid

September.

Differences between summer and winter precipitation can be tremendous on Walnut Gulch.

Summer precipitation is dominated by convective thunderstorms which are limited in areal extent, and characteristically have maximum

5-min rainfall rates greater than 100 mm /hr (Osborn and

Simanton 1981).

Winter precipitation, though covering larger areas, has maximum 5-min rainfall rates which are usually less than 10 mm /hr (Osborn et al.

1979).

This ten -fold difference between summer and winter precipitation rates has a significant effect on runoff and erosion.

For example, over 99 percent of the annual Walnut

Gulch runoff for the past 25 yr has occurred during the summer thunderstorm season.

Rainfall- runoff studies on Walnut Gulch indicate

37

that variables, such as vegetation and soil moisture, are not as significant as precipitation characteristics when used in rainfall- runoff regression models (Schreiber and Kincaid 1967; Osborn and Lane 1969).

However, in other areas where precipitation characteristics are not moisture are important factors (SCS 1972).

as dominant, vegetation and soil

Dixon (1975) has suggested that easily measured surface characteristics are indirectly related to infiltration and erosion, and has shown that the two surface parameters (microroughness and macroporosity) that do directly influence infiltration are not easily measured.

The possible effects of soil surface compaction, such as would be expected from cattle grazing, have not been determined for soils on Walnut Gulch.

However, studies elsewhere, that have related grazing to increased soil bulk density and decreased infiltration and increased erosion, seem mixed in their conclusions (Gifford and Hawkins 1976).

This paper describes and discusses one year's spring and fall variations in runoff and erosion from

USLE study plots, and discusses these findings in relation to plot surface, soil, and vegetative characteristics.

EXPERIMENTAL BACKGROUND

Method

The research plan of this study on application of the USLE to rangelands followed procedures used in rainfall simulation studies to develop values for the USLE soil erodibility factor (Wischmeier and

Mannering 1969).

This plan includes the use of relatively large plots (3 x 10.7 m long plots are known to show the effects from overland flow erosion), a standard surface treatment (continuous fallow produced by up- and down -slope plowing and disking), standard 9 percent slope, and standard sequences of rainfall inputs. These standard procedures were used so that our results could be compared with results from other

USLE research.

The study includes seasonal application of simulated rainfall on three treatments and a control that are replicated twice on three soil series, and is expected to continue for at least 3 years.

Soils

The three soil series selected were Bernardino (a thermic Ustollic Haplargid), Cave (thermic, shallow Typic Paleorthid), and Hathaway (thermic Aridic Calciustoll).

These are all gravelly loams, and are

USDA -Soil Conservation Service bench mark soils for Arizona.

They comprise nearly 45 percent of the Walnut Gulch watershed area, and are described in detail by Gelderman (1970).

The Bernardino series is a deep, well- drained, fine -textured soil formed in old calcareous alluvium.

This soil can have up to 50 percent, by volume, of gravel and cobbles in the surface 10 cm, and usually less than 35 percent gravel in the remainder of the profile.

The Cave series is a shallow, well- drained, medium textured soil with indurated lime hardpans that have developed at less than 45 cm in old, gravelly and cobbly calcareous alluvium.

This soil can have up to 60 percent, by volume, of gravel and cobbles in the surface 10 cm, and usually less than 40 percent gravel in the remainder of the profile.

The Hathaway series is a deep, well- drained, gravelly medium and moderately coarse -textured soil over very gravelly, coarse -textured materials of moderate depths.

This soil was formed from gravelly or very gravelly calcareous old alluvium, and can have up to 70 percent, by volume, of gravel and occasional cobbles in the surface 10 cm, and usually less than 50 percent in the remainder of the profile.

Plots

Criteria for plot selection were largely based on requirements set forth during the original development of the LISLE, and on constraints of the rainfall simulator.

The criteria included: (1) plots had to be in pairs separated by no less than 3 m but no more than 4 m; (2) each pair had to be at least 7 m apart; (3) paired plots had to be parallel; (4) plot slope had to be near 9 percent; (5) plot slope had to be uniform; (6) rills or other obvious drainages must not be present, and (6) plot pairs on each soil series had to be relatively close to one another.

The 24 experimental plots were each 3.1 m x

10.7 m in size, with the long axis parallel to the slope.

Each plot was delineated on three sides by 15 cm metal borders that were installed so that 3 cm were inserted into the soil and 12 cm extended above the surface.

The downslope end of the plot was delineated by a 20 -cm deep metal sheet with a sill plate on one edge.

soil so that the sill plate was flush with the soil surface.

This sheet was inserted into the

The soil -metal interface was sealed with a silicone rubber -paint thinner solution which, upon drying, formed an impervious connecting joint.

Runoff from the plots were collected in troughs that divert the water into a runoff -measuring flume equipped with a FW-1 water -level recorder that measures instantaneous discharge.

After the plots on each soil

38

series were selected and plot borders installed, plot pairs were randomly treatment.

assigned their particular

Treatments

The three treatments imposed included the standard moldboard plowed and disked up and down slope treatment (tilled), a vegetation removed treatment where the ground surface and then controlled with a systemic herbicide vegetation initially was clipped at the

(clipped), and a vegetation and erosion pavement (rock and gravel > 2 mm) removed treatment where the vegetation was clipped at the ground surface, as previously detailed, and the erosion pavement was hand picked from the plot to minimize soil surface disturbance (fallow).

Two natural cover plots were also selected for each of the soil of both vegetation cover and erosion pavement on soil loss.

series.

These were used as control plots.

soil erodibility factor (K).

The tilled treatment is standard for determining values for the USLE

The other two treatments and the control were selected to show the effect

Prior to treatment, the plots were fenced to exclude cattle grazing.

After treatment, each plot pair was subjected to an initial 60-min rainfall simulation (dry), followed 24 hr later by a 30-min run (wet), which was then followed 30 min later by another 30 -min run (very wet).

The simulated rainfall rate for each of these runs was about 60 mm /hr.

By combining results from the runs, each series of runs provides runoff and erosion data for 30 mm and 60 mm continuous rains, a 90 mm rain with one 24 -hr interruption, and a 120 -mm rain within approximately a 24 -hr period.

This simulation sequence was applied to the 24 plots, or 12 -plot pairs in the late spring (April -May) and early fall

(Oct -Nov) within the same year.

The test periods, which are periods of just before and after the summer rainy season (July- Sept).

low rainfall probability, were

Rainfall Simulator

The rainfall simulator used was a trailer -mounted rotating -boom simulator capable of applying either

60 or 120 mm /hr rainfall rates (Fig. 2) (Swanson 1965).

There are 10 arms radiating from a central stem.

The arms support 30 nozzles that are positioned at radii of 1.5, 3.0, 4.6, 6.1, and 7.6 m, with 2,

4, 6,

8, 10 nozzles on each respective radius.

The two rainfall intensities obtained by using either 15 or 30 nozzles.

(60 mm /hr or 120 mm /hr) are

The nozzles spray downward from an average height of 2.4 m, apply about 15 liters /min, and produce drop -size distributions

(Swanson 1979).

similar to those of natural rainfall

Preliminary results of a study of rainfall energies associated with the simulator indicate that the energies are about 80 percent of those of natural rainfall.

Because of the simple design and portability of the simulator, many plots can be evaluated in a relatively short time

(a complete series of runs can be made on 8 plots in one week).

Figure 2.

Trailer mounted rotating -boom rainfall simulator.

Field Measurements

Plot surface characteristics and vegetation cover were measured before the initial treatment, and then before the 60-min simulation.

Characteristics measured were bare soil (particles <

2 mm in diameter), gravel (particles 2 to 20 mm in diameter), rock (particles > 20 mm in diameter), litter, vegetative basal cover, and vegetative crown cover.

A 3.05 m long pin -point meter with holes spaced at 6 cm intervals was used.

The meter is placed perpendicular to the plot slope, and rests on the metal plot border at 10 positions along the plot.

At each position, 49 pinpoint surface and vegetation measurements are made by dropping a pin through each pin hole.

Thus, there is a total of 490 point measurements per plot to describe the surface characteristics.

Rainfall amount and application rate were measured with a modified recording raingage that was placed between each plot pair.

The raingage was modified to increase its sensitivity to rain fall rate by doubling the rainfall -collecting area and enlarging the recorded time scale.

Rainfall distribution over each plot was measured with four small plastic gages that recorded only rainfall amount.

One gage was placed near each of the four corners of each plot.

three

On some early testing of the simulator, narrow slotted tubes were placed across

39

each plot to check the appliclation amount.

This scheme was abandoned when (1) the amounts were found to agree very closely with those obtained from the four small plastic gages, and

(2) a small ridge was observed to form on the plot surface beneath each slotted tube because of the interception of the simulated rainfall.

The flumes used to measure runoff have a capacity of about 4 liters /sec, minimize sediment deposition.

and have sloped floors to

The water -level recorders were sensitized so that small changes in runoff are noticeable on the runoff hydrograph.

Figure 3 illustrates a complete plot pair field arrangement.

Sediment samples, manually collected in quart sample bottles, were taken at the flume exit periodically during the runoff period.

Sampling intervals were dependent on changes in the runoff rate, with frequent sampling when discharge was changing rapidly.

The shortest sampling interval was 1 min, usually during the first 10 min of the runoff, and the longest was no more than 15 min, usually toward the end of the run, when runoff rate was relatively constant.

The time when the sample was collected was recorded for later correlation to the runoff hydrograph and calculation of sediment discharge rate and amount.

Data Analysis

\

ROTATING BOOM RAINFALL SIMULATOR

Plot vegetative cover and surface characteristics were tabulated and converted to percent cover for subse-

/

\

\

/

/

\

/

// sm

/ i a:

'':\

N

\

\

\\

\ \

quent correlation effect.

to runoff, erosion, and treatment

Rainfall records were digitized and tabulated to give rainfall hyetographs for use in infiltration studies.

Analog records from the water -level recorder on each flume were digitized, converted to discharge rates, and tabula ted to give a hydrograph and runoff volume.

\

/

ono*

-

N

\

Sediment samples were analyzed for total concentra-

/

//

/

N

\I

\

\

I

\ i

\ j 1 tion and particle -size distribution was determined (Haverland and Cooper 1981).

Sediment discharge rates and total soil loss were calculated using sediment concentration values and the runoff hydrograph.

Sediment trapped in the flume was measured and distributed in proportion to the flow rate.

-

-

I `,

/ /

-

/

/

RESULTS AND DISCUSSION i

_ s'^ro

R«,ROINA

`

...WT.

-

/ i

D l/

Average surface characteristics for the spring and fall rainfall simulations for the different soil- treatment

/ ;;*IN combinations are shown in table 1.

Vegetation data for the natural control plots are listed in table 2.

Spring and fall runoff and sediment treatment averages for the dry, wet, and very wet surface simulations are listed in

Figure 3.

Typical plot layout with schema- tables 3,

4, and 5, respectively.

Spring and fall hydro tic of simulator nozzle path.

graphs and sedigraphs for a natural plot on two soil types are shown in fig. 4 through 6.

Only data from the natural plots are presented because they show only seasonal change and not changes caused by treatment.

Since data from the plots on the Cave and Hathaway soils exhibited the same pronounced seasonal shift in runoff, infiltration, and soil loss, only the Hathaway plot data are shown.

Final infiltration rates in the spring decreased 20 percent between the dry and wet surface runs on the Hathaway soil, and a decrease of only 8 percent on the Bernardino soil.

In the fall, the final infiltration rate decreased approximately 20 percent between the dry and wet surface areas on the Hathaway soil and approximately 15 percent on the Bernardino soil.

Seasonal differences in final infiltration rates were measured only during the dry surface simulations.

There was about a 60 percent decrease in final infiltration rates from spring to fall on the Hathaway soil, and an approximate increase of 60 percent in the spring to fall simulations on the Bernardino soil

(fig. 4 - 6).

Soil loss from the Bernardino natural plots was significantly less in the fall, and there also was a significant decrease in runoff volume.

The soil loss from the natural plots on the other two soils increased, though not significantly, even though there was a significant increase in runoff (table 3).

One of the main objectives of this USLE plot study was to identify and quantify those soil surface characteristics that have a significant influence on runoff and erosion from rangelands.

To eliminate treatment effects, only natural plots were used in collected.

a multiple linear regression analysis of the data

In effect, correlation coefficients were determined between plot runoff and soil loss and surface characteristics for the spring, fall, and combined season data.

Spring runoff volume was positively correlated with erosion pavement (combined percentage of rock

40

and gravel) (r = 0.90) and grass crown cover (r = 0.93), but negatively correlated with litter cover (r =

-0.93) and shrub crown cover (r = -0.90).

The correlation coefficient needs to be greater than 0.87 to be significant at the 5- percent level.

Soil loss was positively correlated to erosion pavement (0.94).

Table 1.

Plot surface characteristics

( %)

Soil (< 2mm)

Gravel 2mm -2cm

Treatment

(Avg)

Spring

Fall

Spring

Fall

Rock > 2cm

Spring

Fall

Litter

Spring

Fall

Rock and Gravel

Spring Fall

Natural

Tilled

Clipped

Fallow

Natural

Tilled

Clipped

Fallow

Natural

Tilled

Clipped

Fallow

Natural

Tilled

Clipped

Fallow

28.06

62.45

32.65

63.78

19.80

20.00

66.50

25.00

42.00

24.50

68.68

68.50

17.34

37.50

55.51

57.50

29.18

52.34

29.28

63.78

25.70

61.20

26.40

61.00

21.50

31.50

34.50

59.00

22.00

55.50

32.30

52.80

37.55

21.84

28.37

15.72

33.06

12.34

36.22

6.74

21.12

10.52

24.28

7.24

30.60

14.90

29.60

9.90

Bernardino Soil

53.00

8.70

26.33

21.50

43.00

46.50

9.28

20.00

18.68

23.00

1.63

4.00

Hathaway

33.00

12.00

15.00

12.76

24.00

18.00

30.00

25.00

13.26

26.00

4.18

6.50

39.50

12.50

36.50

29.50

Cave

11.22

17.00

28.47

9.49

3.68

50.50

14.50

6.50

All Soils

41.80

11.10

17.50

16.80

20.80

29.50

36.50

33.70

13.80

21.20

3.20

5.70

6.32

6.43

20.30

18.88

30.00

6.22

32.86

4.00

4.80

9.00

7.50

33.57

11.00

35.30

8.68

36.94

14.50

24.90

23.90

7.10

16.00

1.50

6.50

21.00

5.50

6.00

13.70

3.90

30.00

10.00

25.80

8.2

63.88

17.34

49.49

10.92

48.10

75.00

31.12

28.50

43.05

66.00

50.50

48.06

57.00

25.10

30.00

56.00

31.50

32.35

47.00

38.98

63.00

33.78

10.92

51.00

33.50

59.70

31.70

40.50

43.40

57.70

13.10

38.50

Soil

Crown

Base

Crown

Base

Crown

Base

Table 2.

Vegetative cover ( %) natural plots

Grass

Spring Fall

Forb

Spring Fall

Shrub

Spring Fall

Total

Spring Fall

11.2

1.6

7.9

1.68

4.1

1.7

46.3

1.0

36.6

2.2

14.7

.8

0.6

Bernardino

18.4

---

- --

8.1

0.1

3.1

0.2

Hathaway

10.2

- --

10.0

0.3

0.5

Cave

0.8

19.5

1.3

3.0

- --

5.8

- --

15.9

0.1

19.9

1.7

21.0

2.1

24.1

3.0

68.2

1.0

52.6

2.2

31.4

.9

Fall runoff volume and soil loss were poorly correlated to plot surface characteristic.

The combined season correlation matrix also did not indicate sufficient correlation between runoff or soil loss and plot surface characteristics.

The erratic nature of the sedigraphs (fig.

4 -6) for all the spring runs may be the result of an observed buildup and breakdown of debris dams on the plots.

Under constant rainfall rates, these dams become more a function of surface characteristics than would be expected with varying rainfall intensities of natural storms.

The frequency of these debris dam formation and dissipation, and the magnitude of their effects may be dependent on the plot slope, roughness, and amount of litter.

41

Treatment

(Avg)

Table 3.

Runoff

(mm)

Spring

Fall

Dry surface runoff and soil loss

Runoff coefficient

Soil loss

(Q/p)

Spring

Fall

(gms)

Spring Fall

Sediment concentration

(gms /liter)

Spring Fall

Soil Loss

(T /ha)

Spring Fall

Natural

Tilled

Clipped

Fallow*

Natural

Tilled

Clipped

Fallow

Natural

Tilled

Clipped

Fallow

Natural

Tilled

Clipped

Fallow

34.1

0.2

27.9

37.8

18.0

5.5

20.4

28.2

6.6

0.8

11.7

17.8

19.6

2.2

20.0

27.9

16.1

0.3

32.1

34.4

32.4

11.2

34.3

39.6

19.7

1.7

38.0

34.0

22.7

4.4

34.8

36.0

0.59

0.004

0.49

0.67

0.33

0.10

0.37

0.52

0.12

0.01

0.20

0.30

0.35

0.04

0.35

0.50

Bernardino Soil

0.28

1483

0.005

0.56

84

1229

0.60

6946

Hathaway

0.56

0.20

992

614

0.60

0.69

1310

6486

0.36

0.03

Cave

462

172

356

139

2522

8005

1134

1878

3524

13076

810

186

0.68

0.59

808

1309

All Soils

0.40

979

0.08

290

0.61

0.63

1116

4914

3549

13877

767

734

3198

11653

1.9

4.3

1.7

5.9

1.4

6.1

1.4

5.6

1.7

3.4

2.0

7.3

2.6

3.4

1.7

4.8

0.7

5.5

2.5

7.1

1.1

5.4

2.5

10.1

1.3

4.8

2.8

12.6

1.0

5.2

2.6

9.9

0.46

0.03

0.38

2.14

0.30

0.19

0.40

1.99

0.14

0.05

0.25

0.40

0.30

0.09

0.34

1.51

0.11

0.04

0.78

2.46

0.35

0.58

1.08

4.02

0.25

0.06

1.09

4.27

0.24

0.23

0.98

3.58

Runoff

Treatment

(Avg)

(mm)

Spring

Fall

Table 4.

Wet surface runoff and soil loss

Runoff coefficient

Soil loss

(Q /p)/

Spring

(gms)

Fall Spring Fall

Sediment concentration

(gms /liter)

Spring Fall

Soil loss

(T /ha)

Spring Fall

Natural

Tilled

Clipped

Fallow*

Natural

Tilled

Clipped

Fallow

Natural

Tilled

Clipped

Fallow

Natural

Tilled

Clipped

Fallow

15.6

2.2

15.8

15.6

8.2

12.8

10.1

12.4

4.8

3.6

9.3

14.3

9.5

6.2

11.7

14.1

12.8

10.4

17.1

17.6

13.3

17.9

19.8

18.3

13.1

4.4

18.5

18.2

13.1

10.8

18.5

18.0

0.54

0.09

0.59

0.56

0.29

0.48

0.37

0.43

0.16

0.12

0.30

0.46

0.33

0.23

0.42

0.48

Bernardino Soil

0.44

650

0.36

194

0.58

534

0.61

2970

Hathaway

0.46

0.61

0.67

0.62

430

1882

452

3323

Cave

302

1526

1192

5842

521

3153

1750

6678

462

383

1220

0.45

0.16

314

436

530 0.64

0.64

2788

All Soils

0.45

0.38

0.63

0.62

465

837

505

3027

5436

428

1687

1387

5985

1.3

3.2

1.1

5.9

1.6

4.8

1.4

8.2

2.2

3.9

1.6

5.9

1.7

4.0

1.4

6.7

0.8

4.0

3.1

10.1

1.2

5.7

2.7

11.4

1.1

2.9

2.0

9.2

1.0

4.2

2.6

10.2

0.20

0.06

0.16

0.91

0.13

0.58

0.14

1.02

0.10

0.13

0.16

0.86

0.14

0.26

0.15

0.93

0.09

0.47

0.37

1.80

0.16

0.97

0.54

2.05

0.14

0.12

0.38

1.67

0.13

0.52

0.43

1.84

*Fallow plots had the vegetation clipped, and the erosion pavement was removed from the plot surface.

TQ is the surface runoff in mm; P is the applied rainfall in mm.

42

Runoff

Treatment

(Avg)

(mm)

Spring Fall

Table 5.

Very wet runoff and soil loss

Runoff coefficient

(Q /p)/

Spring Fall

Soil loss

(gms)

Spring Fall

Sediment concentration

(gms /liter)

Spring

Fall

Soil loss

(T /ha)

Spring

Fall

Natural

Tilled

Clipped

Fallow*

Natural

Tilled

Clipped

Fallow

Natural

Tilled

No veg

Natural

Tilled

Clipped

Fallow

18.4

5.8

17.6

17.6

10.7

15.7

15.4

15.9

7.5

10.8

13.1

17.5

12.2

10.8

15.4

13.0

13.2

13.4

18.9

19.3

15.8

18.2

20.0

23.9

14.3

9.5

17.3

19.4

14.4

13.7

18.7

20.9

0.64

0.20

0.62

0.62

0.40

0.57

0.56

0.58

0.25

0.36

0.44

0.58

0.43

0.38

0.54

0.59

Bernardino Soil

0.46

746

0.46

0.64

435

758

0.67

0.62

0.68

3871

Hathaway

0.54

514

2616

0.72

648

4316

0.50

0.32

Cave

363

952

0.62

598

342

1488

1654

6328

507

3508

1697

6340

442

596

1290

6146

0.66

3384

All Soils

0.50

541

0.47

0.65

0.68

1334

668

3857

430

1864

1547

6271

1.6

2.5

1.3

5.8

1.5

3.6

1.3

6.9

1.3

2.8

1.3

6.7

1.5

5.6

1.3

8.2

0.8

3.2

3.3

10.0

1.0

1.9

2.2

9.7

1.0

6.0

2.7

9.4

0.9

3.7

2.7

19.7

0.23

0.13

0.23

1.19

0.16

0.80

0.20

1.33

0.11

0.29

0.18

1.04

0.17

0.41

0.21

1.19

0.11

0.46

0.51

1.95

0.16

1.08

0.53

1.95

0.14

0.18

0.40

1.89

0.13

0.57

0.48

1.93

*Fallow plots had the vegetation clipped, and the erosion pavement was removed from the plot surface.

TQ is the surface runoff in mm; P is the applied rainfall in mm.

Analysis of variance (ANOVA) (Ouncan's multiple range) among treatments and seasons showed that runoff volumes of the dry surface runs were significantly less (1 percent level) from the tilled plots than any other treatment in both seasons.

Other significant differences in dry surface runoff volumes were:

(1) fall natural treatments < fall clipped and fallow, (2) average spring runoff (all treatments) age fall runoff (all treatments).

< aver-

Soil loss from the dry surface runs were: (1) significantly greater (1 percent level) from the fallow treatment than any other treatment in both the spring and fall, and (2) significantly less (1 percent level) from the spring fallow treatment than from the fall fallow treatment.

Although the statistical difference between the runoff volume for the wet or very wet replications was not significant between treatments within a season or between seasons, the SCS Curve Number concept for estimating runoff did indicate a consistent pattern of increasing curve numbers with increasing cedent moisture (SCS 1972).

ante-

The runoff and soil loss differences measured between the spring and fall simulations on the natural plots could not be statistically attributed to any measured surface or soil parameter.

However, these seasonal differences might possibly be explained by changes in soil surface compaction (Schumm and

Lusby

1963; Rauzi and Smith 1973).

The spring runs were made on a soil surface loosened throughout the fall and winter by the combined effects of diurnal soil temperature fluctuations and the wetting and drying the upper soil layer.

of

This loose soil surface in the spring affected the Hathaway and Cave sites more because of the lower amounts of erosion pavement.

This pavement would act as an insulating cover on the

Bernardino soil, tend to moderate soil surface temperatures, and reduce soil water evaporation.

In the spring, the soils would tend to have a greater initial infiltration rate than the more compacted and crusted soil surface in the fall produced by the high energy associated with the previous summer's thunderstorm rainfall.

To exemplify this, analysis of the natural plot's runoff hydrographs indicates that the time between start of simulated rainfall and runoff is significantly less in the fall than in the spring for the Hathaway and Cave soils, but is not much different for the Bernardino soil (table 6).

also had a dramatic effect on soil loss.

The loose soil surface

Sediment concentration in the runoff in the spring for the natural plots was twice that in the fall (table 3).

Another possibility for these seasonal runoff and soil loss changes could be associated with ery from grazing exclusion.

a recov-

The three soil sites chosen had been grazed until the sites were fenced just prior to plot treatments.

The recovery from grazing is a combined effect of changes in soil compaction,

43

vegetation density, and litter accumulation.

This response may be an important time -related parameter, especially on plot -size areas.

Table 6.

Conditions

Dry

Wet

Very wet

Time to beginning of runoff after start of simulated rainfall (min)

Bernardino

Spring

3.50

3.00

2.25

Fall

4.00

2.75

2.00

Natural

Hathaway

Spring

Fall

5.00

5.25

2.50

3.75

3.75

1.90

Cave

Spring

11.50

5.00

3.60

Fall

4.65

3.00

2.00

60

F

Q

C

2

10

APNICATIQN

NATURAL PLOT 7

BERNARDINO SOIL

DRY SURFACE

FA LI_

SPRING

SPRING

FALL

RUNOFF

- - INFILTRATION

40-

30-

2

\ r

NATURAL PLOT IS

HATHAWAY SOIL

DRY SURFACE

RING

FALL

FALL

SPRING

RUNOFF

INFILTRATION

É

3000

Q ,

Z

Ó

1000

10

20 30

40

TIME (MINUTES)

50

NATURAL PLOT 7

BERNARDINO SOIL

DRY SURFACE

SOIL LOSS

SPRING 16910ms

FALL 4014464

60 70

0 20

30

40

TIME (MINUTES)

4000

1: 3000f o

NATURAL PLOT IS

HATHAWAY SOIL

DRY SURFACE

SOIL LOSS

SPRING 6B99ms

FALL

7794m,

60 g moo-

.

W

t0

. 100o-

SPRING

FALL

70

20 30 40

TIME (MINUTES)

50 60 70

10

Figure 4.

Dry surface infiltration, runoff, and sedigraph.

20

30

40

TIME (MINUTES)

50

60

70

CONCLUDING COMMENTS

A significant feature of this initial interpretation of the runoff, erosion, and surface character ics relationships is that one season's or year's data are, even under carefully controlled conditions, y difficult to define in terms of easily measured physical parameters when the data are analyzed using mole ANOVA procedures such as were used here.

At this point in the experimental work, it appears that a great deal of additional work will be needed to understand the cause- effect relationships on these plots.

Certainly, the differences in runoff and soil loss between spring and fall for the different soils considered would indicate that either the freeze -thaw mechanism or the exclusion of grazing may be changing the bulk density which, in turn, may markedly change the infiltration and erodibility of these rangeland soils.

44

60

50-

"\

\\

\\

\\

\\

4

APPLICATION

NATURAL PLOT T

BERNARDINO SOIL

WET SURFACE

SPRING

SPRING

ALL

O

- RUNOFF

-- INFILTRATION

0

4000

I 3000-

NATURAL PLOT 7

BERNARDINO SOIL

WET SURFACE

É

20

TIME IMINUTES)

30

SOIL LOSS

SPRING

7004ms

FALL

3199ms

á

2000z

2

C

W 1000 -

30-

20-

IP}ICATION

I.

\\

\ \\

\

\

\

\

\

\

NATURAL PLOT IS

HATHAWAY SOIL

WET SURFACE

SPRINS

FALL

FALL

SPRING

- RUNOFF

-- INFILTRATION

40

W

2000

P z

W i

Ó

W

W 1000

10

4000

NATURAL PLOT IS

HATHAWAY SOIL

WET SURFACE

3000

20

TIME (MINUTES)

SOIL LOSS

30

SPRING428am4

FALL 3344ms

40

20

TIME (MINUTES)

30

40

00

Figure 5.

Wet surface infiltration, runoff, and sedigraph.

10

20

TIME IMINUTES)

30 40

ACKNOWLEDGMENTS

The authors would like to thank Howard Larsen and Jim Smith for their assistance, dedication, and enthusiasm in the collection of the field data.

Also, the efforts of Loel Cooper in the lab analysis of the sediment data and the assistance of Dr. E. D. Shirley in the computer analysis are greatly appreciated.

REFERENCES CITED

Dixon, R. M.

1975.

Infiltration control through soil surface management.

Management, ASCE, Logan, Utah.

p. 543 -567.

Geldérman, F. W.

SCS, 55 p.

1970.

Proc. Symposium on Watershed

Soil Survey, Walnut Gulch Experimental Watershed, Arizona.

Special Report USDA -

A look at the

Gifford,

G.

F., and R.

H. Hawkins.

record.

J.

1976.

Grazing systems and watershed management:

Soil Water Cons. 31(6):281 -283.

Haverland, R. L., and L. R. Cooper.

soils.

1981.

Microtrac:

A rapid particle -size analyzer of sediments and

Proc. Ariz. Sec., AWRA -Hydrology Sec., Ariz. Acad. Sci. 11:207 -211.

Osborn, H. B., and L.

J. Lane.

1969.

Precipitation- runoff relationships for very small semiarid rangeland watersheds.

Water Resources Research 5(2):419 -425.

45

50-

40 -

If

II

II

II

1\

1

\\

\

\

O

20

APPLICATION

NATURAL PLOT 7

BERNARDINO SOIL

VERY WET SURFACE

SPRING

FAIL

FALL

SPRING

RUNOFF

- - INFILTRATION

10

20

TIME (MINUTES)

4000

2

3000 -

F

NATURAL PLOT 7

BERNARDINO SOIL

VERY WET SURFACE

30

SOIL LOSS

SPRING 6784ms

FALL

33OOWR

H

2000

V

2

W

O w m 1000t'

50-

\)

\\ ao -

\\

APPLICATION

NATURAL PLOT

IS

HATHAWAY SOIL

VERY WET SURFACE

FALL

30-

20 -

- RUNOFF

- INFILTRATION

40

É

H

2000-

F

2

7 a w m

.00.

O

4000

3000-

NATURAL PLOT IS

HATHAWAY SOIL

VERY WET SURFACE

20

TIME (MINUTES)

SOIL LOSS

30

SPRING 542Im,

FALL 3S6Gz.

10

20

TIME (MINUTES)

30

40

20

TIME (MINUTES)

Figure 6.

Very wet surface infiltration, runoff, and sedigraph.

Osborn,

H.

B., and

J.

R.

Simanton.

1981.

Maximum rainfall intensity of southwestern thunderstorms.

Fourth Conference on Hydrometeorology, Reno, Nevada American Meteorological Society.

Osborn, H. B., R. B. Koehler, and J.

R. Simanton.

1979.

Winter precipitation on a southeastern Arizona rangeland watershed.

Proc. Ariz. Sec., AWRS -Hydrology Sec., Ariz. Acad. Sci. 9:15 -20.

Rauzi, F., and F. M. Smith.

eastern Colorado.

1973.

Infiltration rates: Three soils with three grazing levels in north-

J. of Range Management 26(2):126 -129.

Schreiber, H. A., and D.

R. Kincaid.

duration convective storms.

1967.

Regression models for predicting on -site runoff from short -

Water Resources Research 3(2):389 -395.

Schumm, S. A., and G.

C. Lusby.

slopes in western Colorado.

1963.

Seasonal variation of infiltration capacity and runoff on hill -

J. Geophys. Res. 68(12):3655 -3666.

Soil Conservation Service.

1972.

National Engineering Handbook, Sec. 4, Hydrology.

Swanson, H.

P.

1965.

Rotating -boom rainfall simulator.

Trans. Amer. Soc. Agr. Engr. 8:71 -72.

Swanson, N. P.

ska.

1979.

Field plot rainfall simulation (rotating -boom rainfall simulator), Lincoln, Nebra-

Proc. Rainfall Simulator Workshop, Tucson, Arizona March 7 -9, p. 166 -169.

Wischmeier, W.

H., and J.

V. Mannering.

Sci. Soc. Amer., Proc. 33(1):131 -137.

1969.

Relation of soil properties to its erodibility.

Soil

Wischmeier, W. H., and D.

D.

Smith.

1978.

Predicting rainfall erosion losses - -A guide to conservation planning.

USDA, Agriculture Handbook No. 537.

46

Distribution of Loss Rates

Implicit in the SCS Runoff Equation

Richard H. Hawkins

Utah State University

Logan, Utah

84322

Introduction

General:

It is a practice in applied hydrology, approaching a hallowed tradition, to assume that runoff processes on small watersheds are spatially uniform.

modeling fraternity calls this "lumping ", and it is associated with

The small watersheds almost by definition.

Both practitioners and researchers make the uniformity assump-

tion for reasons of ignorance and simplicity.

Not much is known of spatial vari-

ability of soil, vegetative, and hydrologic properties of landscapes, and that which is known promises confusing complexity if and when realistically applied.

Nonethe-

less, it is also acknowledged that even small watersheds are indeed not uniform,

though the consequences of the uniformity assumption are not clearly understood.

As a simple example, consider a small 100 acre watershed producing 1.00 inch of runoff (or 100 acre -inches) from a rainstorm of 2.00 inches.

This rainfall excess could have arisen from a variety of conditions:

1) Half the watershed (50 acres)

producing 2 inches of excess; 2) The entire watershed yielding 1.00 inch of excess;

or 3) Any number of intermediate combinations, such as 80 acres at 1.25 inches, or mixtures such as 20 acres at 2 inches plus 60 acres at

1 inch.

Mass accounting

requires that the sum of the area -excess products be equal to the basin runoff, or:

Q =E Qiai/A

(Qi S P)

[1]

Where Q represents the rainfall excess depth from contributing area ai, A is

the total watershed area, and Q is the net watershed runoff depth.

This paper will offer an organized though untested approach to dealing with this phenomenon in analysis and synthesis of runoff, with accent on its interpretation in the case of the SCS runoff equation.

Background: In a previous paper (3), the writer has developed the notion of

distributed effective loss rates, f, on small watersheds, and established the following equivalences.

Given that effective loss rates are distributed as g(f), then the rainfall excess rate q for a period of intensity i is shown to be: q

=

Jr i

(i-f)g(f)df

0

[2]

The foundation for this is illustrated in Figure

1.

By expanding [2], and

making distribution and conservation -of -mass interpretation, it can also be shown that

G(i) r dq /di

[31

Where G(i) is the value of the cumulative distribution of g(f) at i =f, or (as a

net watershed process), the fraction of the watershed yielding rainfall excess at

intensity i.

The derivative expression in [3] indicates that this is the slope of the rainfall- runoff rate curve at intensity i.

Thus, the slope of the rainfall

47

Figure

1.

>-

1-

O

>-

I-

This portion has i >f .

Generates rainfall excess.

w

I-

CCa fn o era m p,

O

CC g (f

)

This portion has i<f.

Generates no rainfall excess.

0 f

LOSS RATE ( f) AND RAINFALL INTENSITY( i )- 7T

Diagrammatic illustration of probability density for distribution of effective loss rates on a model watershed.

While the minimum loss rate is known here as zero, situations in which Emin >

0 are also

possible, as are polymodal distributions, mixtures, and upper un-

bounded distributions.

function is the fractional contributing area.

Equation [3] is differentiated to

produce the density function g(), so that: g(i)

= d2q /di2

[4]

This is the underlying kernel distribution of loss rates.

Note that it can be

determined through differentiation of the rainfall excess function. This will be

explored here for the case of the SCS runoff equation.

When the above reasoning is applied to situations of variable rainfall intensities, net watershed loss rates appear to vary positively with rainfall intensity up to the limit of i =fm

Examples of such performances are surprisingly prominent in available data sets from plots and watersheds, thus offering at least indirect support for the general contention of spatially variable loss rates.

SCS Runoff Eauation

Background: method.

The SCS equation is the heart of the widely used Curve Number

The runoff depth function is:

Q

=

(P- .2S)2 /(P +.8S) P > 0.2S

[5]

Q

= 0

P < 0.2S

Where Q is the direct storm runoff depth (inches), P is the storm rainfall depth

(inches), and S is an index of basin retention, equal to the maximum possible dif-

ference between effective rainfall (P -0.28) and runoff Q.

curve number (CN) is a transformation of S, or:

The land condition index,

CN =

1000/(10+S)

[6]

48

Equation [5] can be standardized on the parameter S, leading to:

QIS = (PIS- .2)21(P /S +.8) which is a much more convenient form and useful for what is to follow.

in Figure 2.

[7]

It is shown

Documentation of the method's development is given in its foundation publication

(6) and general subsequent papers (4,7).

A critical appraisal of it is given by Chen

(1). Despite visible shortcomings, it is the most popular technique of its type in

use today, and is applied to a wide variety of situations on an international basis.

Its ability to incorporate land use, condition, and site moisture into runoff calcu-

lations, its documentation and agency origin, and the lack of suitable alternate

techniques have promoted its use.

Assumptions:

The distributed loss rate theory requires rainfall and excess

rates, not depths (volumes).

However, in its original and most robust application,

the SCS runoff equation was applied only to daily data, or a time interval of

one day.

It was used to transform daily rainfall frequency descriptions to a parallel

description of daily runoffs.

Thus, it is consistent to assume rainfalls and runoffs

as one day intensities, or, to be more general, as average intensities for storm durations used.

In what is to follow it is necessary to stretch rates to cover

assumed or understood storm durations

T, such as 24 hours, so that: i and q

= P/T

= Q/T f = i-q

[8]

[9]

[10]

As odious as this compromise seems at first glance, it is at least partially

justifiable. Equations 8 -10 inflict the presumption of a uniform intensity storm, for

which there is some literature support, to achieve the SCS runoff equation (5).

Additionally, common use of the SCS runoff equation as an infiltration method

achieves the same effect by applying it to individual intervals throughout the gress of design storms.

pro-

In addition to the above, all the assumptions required of the foundation equa-

tions [2] through [4] are necessary.

A major item is that the watershed is composed of an undefined large number of independent loss rate cells or contributing smaller runoff units, each operating with a characteristic time constant loss rate, distributed as g(f).

The "runoff -runon" process is ignored within these cells.

Curve Number Loss Rate Distribution

Development:

The intellectual strategy in linking the SCS equation and the

distributed loss rate concept assumes that the former is empirically correct but that the runoff occurs via the distributed processes imagined in the latter, and not as a

lumped uniform phenomenon as historically assumed.

The equivalence is drawn by

simply equating equations [2] and [5].

Therefore, being careful with limits,

Q

= J

2S

The task is now to solve for g(

).

Rather than deal with equation [11] direct-

ly, the principles previously discussed and given as equations [2] and [3] may be

used.

That is, differentiating the right hand of equation [11] (which is equation

[5]) with respect to P and simplifying yields:

G(P) = dQ /dP =

1- (P /S +.8) -2 P > 0.2S

[12] gives:

Of concern is the situation when P = f in the above.

Thus substituting f for P

G(f)

=

1-(f/S+.8)-2 f > 0.2S

[13]

49

1.0

.8

.6

4

.2

0

0 0.2

2/S

1

G(f) :1 -'f/5+0.8)2

2

3 4

g

)

=

S

f/S

4'

0.8

3

0

0 0.2

4

5 f

S

5

> f/S

Figure

2.

Above: Dimensionless expression of the SCS rainfall- runoff equati standardized on the storage index S.

Center: Cumulative distribut of effective loss rates implied by the SCS equation.

Bottom: Dens function of loss rates.

Note the strong positive skew, and the lo limit of 0.2S.

The mean is 1.2S, and the median is 0.61425.

50

The density function is obtained by differentiating the above with respect to f, and simplifying, giving: g(f) _

(2 /S)(f /S +.8) -3 f 2 0.2S

[14]

Equation

[14] above is the distribution of storm loss rates f, which when

inserted into equation [2] will give equation [5].

It reconciles the two ideas.

Characteristics:

Figure 2 shows the original SCS equation, standardized on S,

and the simultaneous display of G(f) and g(f), also standardized on the watershed

index S.

The expected value or mean of the distribution is found by the method of

moments as:

E(f)

= f* f =

1.2S

and the median or f50 is found to be:

[15]

f50 = (171.8)S = 0.6142S

[16]

The higher moments, i.e. the variance, skewness, kurtosis, etc. are undefined

(they approach infinity). Nonetheless, it exhibits a distinct positive skew.

It should be noted that the distribution is valid only for f 2. 0.2S, which asserts that the watershed has no loss rates less than 0.2S.

This uncomfortable item springs from the original SCS equation's demand for an initial abstraction of 0.2S.

Undoubtedly,

a more flexible expression relying on a general value of initial abstraction could

also be derived.

Application

Contributing Fraction:

Given a storm depth and curve number, the inferred

contributing fraction or partial area can be calculated.

For example a storm of P

=

2.00 inches falling on a watershed of CN =80, yields a calculated runoff of 0.56+

inches.

0.61.

Applying equation [13] for f r 2.00 inches calculates G(f) =

1- (1.6)-

_

This may be interpreted as 61% contributing area, or 39% of the watershed with f

>

2 inches, and thus non -contributing.

This information would give guidance towards possible land treatment strategies to reduce runoff,

pickup.

erosion, or pollutant

Loss Rate Equivalences:

The relationship in equation [15] can be exploited to

provide a translation between mean watershed loss rate and the widely used and

handbook -backed Curve Number.

Substituting S from equation [6] into equation [15]

yields: or

AL f' 1.2S r 1.2(1000/CN-10)

CN =

1200/(12+ AO

[17]

[18]

It should be kept in mind that / f is the mean watershed loss rate when distri-

buted as given in equation [13].

An identical result using a 0 -index has been

previously demonstrated (2).

Summary

The SCS rainfall -runoff equation may be united with a spatially varied loss rate via the distribution g(f) _ (2 /S)(f /S + 0.8) -3, which has a mean of 1.2S, a median of 0.6142 S, and undefined higher moments.

Use of this notion reconciles the popular concept of partial area contribution with the curve number equation.

Interpretations of fractional contributing area may be made for specific conditions.

51

References

1.

Chen, C.L.

1981.

Assessment of Soil Conservation Service Model with Runoff

Curve Numbers.

Presented at International Symposium on Rainfall- Runoff

Modeling, Mississippi State University, May 18 -21,

1981.

(Proceedings in Press)

2.

3.

Hawkins,

R.H.

1978.

Effects of Rainfall Intensity on Runoff Curve Number.

In

Hydrology and Water Resources of Arizona and the Southwest, Vol. 8, pp. 53 -64.

(AWRA and AAAS Arizona Meeting, Flagstaff, April 14 -15,

1978).

Hawkins, R. H.

1981.

Runoff Relationships.

Interpretation of Source Area Variability in Rainfall -

Presented at International Symposium on Rainfall Runoff

Modeling, Mississippi State University, May 18 -21,

1981.

(Proceedings in

press).

4.

5.

6.

7.

Kent, K. M.

1968.

A Method for Estimating Volume and Rate of Runoff in Small

Watersheds.

U.S.D.A., Soil Conservation Service, CSC -TP -149, 58 pp.

Morel -Seytoux,

H.

J.

1981.

Extension of the Soil Conservation Service

Rainfall- Runoff Methodology for Ungaged

Watersheds Report FHWA /RD- 81/060,

Federal Highway Administration.

79 pp.

(Available from NTIS).

U.S. Department of Agriculture, Soil Conservation Service.

1956 (et seq.).

National Engineering Handbook, Section 4, Hydrology.

USGPO, Washington, D.C.

U.S. Department of Agriculture.

1975.

Tech. Release No. 55.

Urban Hydrology for Small Watersheds.

52

QUASI THREE -DIMENSIONAL FINITE ELEMENT MODEL OF THE MADRID BASIN IN SPAIN

Jesus Carrera and Shlomo P. Neuman

Department of Hydrology and Water Resources

University of Arizona, Tucson, AZ 85721

Abstract

Groundwater flow in the Tajo River basin surrounding the city of Madrid is studied with the aid of a quasi three -dimensional model.

element method recently described

The model is based on an efficient by Neuman et al. (1982).

adaptive explicit -implicit finite

The top layer is unconfined and interacts with the Tajo River and its tributaries.

Reproduction of the existing conditions in the aquifer demonstrates the existence of local and intermediate flow patterns which flow pattern.

are superimposed on the regional

Such flow patterns could not be identified with a conventional two -dimensional model.

The manner in which these patterns are affected by topography and stream configuration is clearly illustrated with the aid of three -dimensional plots constructed from a certain viewing angle.

Similar plots are used to illustrate the evolution of drawdown zones due to pumpage at predetermined locations in the aquifer.

Introduction

The Madrid aquifer is a thick, detritic unit extending over the central part of Spain (Fig. 1).

It exhibits a marked vertical anisotropy due to layering.

As a result of structural and topographic control, the flow pattern in the aquifer forms a complex three -dimensional picture.

ious aspects of this flow pattern have been reported by López Garcfa

Attempts to model var-

(1979) and

Sahuquillo et al.

(1975).

A full -scale three -dimensional model is currently being developed by the Geological Service of

Spain, based on a modified version of the Prickett and Lonquist (1971) finite difference computer program.

The purpose of this paper is to investigate the feasibility of modeling three -dimensional flow in the Madrid aquifer with the adaptive explicit -implicit quasi three -dimensional finite

FLUMPS, recently developed by Neuman et al. (1982).

element model,

The results of this model compared favorably with those obtained from the Prickett- Lonquist model by the Spanish Geological Service.

Hydrogeology sists

The detritus of the Madrid basin has been formed from alluvial fans (López Vera, 1979).

of lenses rich in sand which appear to be randomly distributed

It conwithin a clay -rich matrix.

The granulometric properties of the aquifer material vary according to their source:

The three main facies,

Madrid, Toledo, and

Guadalajara, derive from the west- central

Mountains, respectively.

range, east -central range, and Toledo

As a result of the large spatial variability of the granulometric properties, the hydraulic parameters of the aquifer are also highly variable.

The largest transmissivities (30 -100 m2 /day) are encountered facies which extends over the central part of the aquifer.

in the

Madrid unit of the Madrid

The Tosco unit of th

Madrid and Toledo facies, in the western part of the aquifer, has transmissivities between 20 and 50 m4/day.

In the east, transmissivities of 10 -30 m /day characterize the

Alcala and Guadalajara units of the Guadalajara facies.

Least permeable is the evaporite unit extending over the southern and south -eastern part of the aquifer (Fig. 1), with transmissivities around 5 -10 m2 /day.

On the basis of two -dimensional computer modeling studies in the vertical plane conducted by Llamas

(1976) and others, vertical hydraulic conductivities appear to be smaller than horizontal ones by a factor of 100.

Recharge appears to be around 200 m3 /km2 /day, or 73 mm /year.

The surface drainage system consists of the Tajo river in the south, and its northern tributaries which are perennial except in very dry years.

53

N.

Detrltle facies

Transition facies

L-=

Rei

Chemical facies

MOCI

Bedrock

0.44.. Inverse fault

Watershed limit

Figure 1.

Location and geology of Madrid basin.

Modeling Approach

Flow in the aquifer is modeled element program, FLUMPS, with the adaptive explicit -implicit quasi three -dimensional finite of Neuman et al. (1982).

The quasi three -dimensional aspect of the model requires that the aquifer be subdivided into horizontal layers in which the flow is strictly horizontal.

The Madrid aquifer is subdivided into three such layers, as illustrated by the horizontal finite element grids in Fig. 2.

Each square in these grids has an area of 25 km2, and the computer program into two triangles.

is automatically subdivided by

Flow between the layers is strictly vertical.

It is handled by vertical strings of linear finite elements connecting the nodes of the horizontal grids.

Ten such strings, each consisting in our case of a single linear element, are shown in Fig. 2.

The entire finite element grid for the Madrid aquifer includes 621 nodes, 285 in layer

1 at the top, and 168 in layers 2 and 3 in the middle and at the bottom, respectively.

The grid consists of 981 triangular elements, of which 483 lie in layer 1, and 251 in each of layers 2 and 3.

In addition, there are 336 line elements connecting the horizontal grids in the vertical direction.

Layers 2 and 3 have impermeable boundaries on all sides.

boundary condition of the following type:

Layer

1 at the top has an impervious boundary on the north side; the remainder of its boundary follows the outline of streams.

run within the interior of layer 1.

All grid points along streams are assigned

Streams also a mixed (Fourier)

Constant rate of aquifer recharge when the water table lies below the stream bottom, and an aquifer discharge rate proportional to the difference between the computed water table and the water level in the stream when the former lies above the stream bottom.

similar type boundary condition is assigned along ephemeral streams, at spring locations, and over swamp

A zones or other areas where discharge by evapotranspiration can take place.

The adaptive explicit -implicit aspect of the model consists of solving the finite element equations explicitly at nodes having stability limits in excess of the decomposition or iteratively at all other nodes

(in time step, At, and implicitly this work iterations were used).

by LU-

For details

54

Figure 2.

Horizontal finite element grids for layers 1, 2, 3 with a few vertical line elements.

concerning this method of solution, the reader is referred to Neuman et al. (1982).

Since explicit solution is much faster than implicit solution, the adaptive scheme leads to considerable savings of computer time.

It also leads to improved accuracy because one can use small time steps when hydraulic heads vary most rapidly at relatively little extra computer cost.

In FLUMPS, the size of At is varied automatically by the program.

At the beginning when derivatives of heads with respect to time are largest, At is very small, and most nodes treated by the program as explicit.

are automatically

As time progresses, the large time derivatives imposed by pumpage dissipate, and At increases until at some nodes, At may come very close to (or exceed) the stability limits of these nodes.

Such nodes are then automatically reclassified as implicit.

The stability limit of each node is a function of the mesh geometry and the hydraulic parameters in the immediate vicinity of the node.

Since in our case the mesh is uniform but the parameters vary in space, the stability limit varies from node to node.

Fig. 3 is a typical graph showing how the number of implicit nodes in our model varies with the number of time steps when At is allowed to increase without limit.

limited increase in At is allowed in all the steady state simulations reported below.

An un-

In all transient simulations, the maximum At is restricted to one year, which is less than the smallest stability limit of any node in the grid.

Thus, all the nodes during a transient simulation run remain explicit at all times.

Fig. 4 shows the amount of CPU time on the Cyber 175 computer of the University of Arizona versus the total number of time steps required for each of the 9 steady state and transient runs performed in our study.

Despite the respectable size of our quasi three -dimensional grid, the CPU time is small, being less than one minute in 8 out of the 9 runs.

When all nodes remain explicit (steady state run 1, transient runs 6 -9) CPU time increases linearly with the number of time steps.

Points departing from this straight line represent steady state runs in which some, or all of the nodes, become implicit at various stages of the solution process.

Departures from the straight line are always in a direction of increased CPU time for a given number of time steps.

Steady State Results

Until the late 1960's, the Madrid aquifer is assumed to be at steady state.

steady state simulations was to calibrate the model against recorded data.

The purpose of our

The final result of the five calibration runs performed gave excellent agreement with the data and with the results obtained by the

Spanish Geological Service with the Prickett -Lonquist model

(1971).

A three -dimensional plot of our results is shown in Fig. 5a.

55

600-

100-

10-

100

TIME STEPS

Figure 3.

Number of implicit nodes versus time steps for three steady -state runs.

the same runs as those of Figure 4.

Numerals refer to

The steady state configuration of the water table in layer

1 at the top is a close reflection of ground surface topography.

Since there is no pumpage, convex areas represent recharge, and concave areas represent discharge.

All streams are gaining water from the aquifer.

Of the total recharge, 60 percent leave the aquifer via river nodes, and 40 percent via discharge nodes.

charge nodes are close to the streams, much of the corresponding

Since many of these disdischarge water must reach these streams via small creeks and superficial alluvium.

The water table configuration in layer 1 reflects the existence of local groundwater of the kind originally postulated by Toth (1963).

flow patterns

The piezometric surface in layer 2 is smoother, exhibiting fluctuations of a smaller frequency and amplitude than the water table in layer 1.

These fluctuations can be taken to represent intermediate flow patterns.

The piezometric surface of layer 3 is very smooth, sloping gently from east to west, and indicates the presence of regional flow in that same direction.

Transient Results

Transient pumping regimes.

simulations were performed over periods of 50 years for three

The initial condition in each case is taken to be the steady pumping occurs primarily in layer

1 different hypothetical state.

In each case,

(to some extent in layer 2) and is heaviest to the northeast, northwest, and southwest of Madrid.

A more or less recharge is imposed on the area east of Madrid.

uniform pumping rate similar to the local rate of

The three pumping regimes differ from each other primarily in the total rate of extraction from the aquifer.

56

180

W

40w 30z

ac .)

20-

9

4

2

10

0

0

2

X TRANSIENT

STEADY-STATE

4

6

KCYC (x100)

8

5

IO

Figure 4.

CPU time versus number of time steps (KCYC) for each of nine runs.

Fig. 5b shows the results in all three layers, after fifty years of pumping, at a total to about 60 percent of total recharge.

Maximum drawdown in layer

1 rate equal is 130 -140 m (clearly, the drawdown near individual wells may be larger).

The local flow regime, as reflected by the water table in layer

1, is now substantially different from what it was at steady state.

points along the water table coincided with streams

Whereas at steady state the low which effectively divided layer 1 into sub -basins, the lows after 50 years of pumpage are different, and there is some transfer of groundwater from one such sub -basin to another.

layer 1.

Layers 2 and 3 again show a gradually smoothed replica of the

However, the amplitude and frequency of the fluctuations in these layers are situation in larger than at steady state, reflecting the effect of pumpage.

As a consequence of pumping, most of the original discharge zones near centers of pumpage are no longer discharging, and some of the stream reaches lose water to the aquifer.

After 50 years of pumpage, the total surface discharge is reduced from 100 to 60 percent of total recharge, a rate approximately equal to that of total extraction.

This means that about 35 percent of total extraction (equivalent to about 20 percent of total recharge) is derived from storage.

If the same rate of pumping continues into the future, the discharge rate will diminish until its sum with the rate of extraction will be equal to the rate of recharge; the system will then be at a new steady state.

Due to the relatively low transmissivity and high near pumping centers but the areal extent of storativity of the aquifer, drawdowns the drawdown zones is small.

are large

To prevent excessive draw downs in localized areas, wells and well- fields should be spaced at sufficient distances from each other.

Conclusions

The adaptive explicit- implicit quasi three -dimensional finite element model FLUMPS is well suited for the simulation of steady state and transient three -dimensional flow patterns in the Madrid aquifer.

Time steps of one year are treated explicitly with this model, a fact which results in considerable savings of computer time.

The model provides a three -dimensional picture of flow in the Madrid basin which clearly illustrates the presence of local and intermediate flow patterns superimposed on the regional pattern.

The effect of pumping is shown to be significant but restricted to small areas.

57

Figure 5.

Perspective of piezometric surfaces in layers 1, 2,

3 a.

at steady -state b.

after 50 years of pumpage

Acknowledgments

The authors wish to thank

Dr.

S.

N. Davis for his help and useful comments.

This work was supported by Cooperative Research Grant No. T3770171 of the U.S.- Spanish Joint Committee for Scientific and

Technological Cooperation.

The authors wish to acknowledge M. Busse for drafting.

References

Llamas, M.

R., 1976.

La Utilización de Aguas Subterráneas en Madrid.

Modelos Digitales.

Estudios geologicos.

Madrid.

32:121 -139.

De los Mayrat Musulmanes a los

López García, J., 1979.

Historia de la Modelacion del Acuifero de la Cuenca del Tajo.

progress report of cooperative research between S.G.O.P.U. and University of Arizona.

Unpublished

López Vera, F.,

1977.

Tecniterrae.

Madrid.

Modelo de

No. 18.

Sedimentación de los Medios Detríticos de la

Fosa de Madrid.

58

Neuman, S.

P.,

C.

Preller and

T.

N.

Narasimhan, 1982.

Adaptive Explicit -Implicit

Quasi three- dimensional Finite Element Model of Flow and Subsidence in Multiaquifer Systems.

In Press.

Prickett, T.

A.

and C.

G. Lonnquist,

1971.

Selected Digital

Computer Techniques for Groundwater

Resource Evaluation, Illinois State Water Survey Bull. 55, 62 pp.

Sahuquillo, A., B. Martí, B. López- Camacho, A.

Balenilla, L. López García, 1975.

Modelo Bidimensional para el Estudio de la Componente Vertical del Flujo en un Acuífero de Gran Espesor.

II Congreso

Iberoamericano de Geologia Economica.

Buenos Aires.

Toth, J., 1963.

A

Theoretical

Geophysics Research.

Analysis of

68(16):4796 -4812.

Groundwater Flow in Small

Drainage Basins.

Journal

59

GEOSTATISTICAL ANALYSIS OF AQUIFER TEST AND WATER LEVEL DATA FROM THE MADRID BASIN, SPAIN

Patricia J. Fennessy and Shlomo P. Neuman

Department of Hydrology and Water Resources

University of Arizona, Tucson, AZ 85721

Abstract

Log -transmissivity, specific capacity, and water -level data from the Tajo River basin surrounding

Madrid, Spain, are analyzed by geostatistical methods.

The existing log- transmissivity data base is augmented with the aid of regression on log- specific capacities.

The augmented set of data is used to obtain estimates of mean log- transmissivities over finite sub -regions of the aquifer by kriging.

Kriging of water -level data at selected points in the aquifer is accomplished by removing the drift through an iterative generalized least squares procedure.

The covariance matrices of the log- transmissivity and water -level estimation errors are used to investigate the structure of these errors.

Introduction

Ground -water models are becoming increasingly more sophisticated.

tematic interpretation of the input data has been largely ignored.

However, development of a sys-

Kriging may be one way to fill this gap.

In the past, transmissivity and head data were estimated subjectively by hand -contouring, thereby including the modeler's biases.

The degree of interpretation varied widely.

To minimize this subjectivity, automatic contouring and interpolation techniques have been developed.

However, most of these methods disregard knowledge of the physical variability of the data (Delhomme, 1978).

A measure of the reliability of such contours is lacking.

Kriging provides such a measure.

Kriging is an interpolation technique based on the geostatistical theory of Matheron (1963).

This technique has the ability to yield unbiased estimates with minimum estimation error variance as well as a total covariance matrix of the estimation errors.

The theory assumes that spatial fluctuation of the data (i.e., log- transmissivity or hydraulic head) about their mean values can be considered a realization of an intrinsic stochastic process.

The process can be characterized by an ensemble mean and a semi -variogram function which are considered uniform over large segments of the aquifer.

While log transmissivity can be assumed to fluctuate about a constant mean value, the fluctuations of head occur about a regional trend, or drift, in the general direction of the gradient.

This drift must be removed before the head fluctuations can be treated as an intrinsic process.

Prior to kriging, the semi -variogram is determined based on field observations of data.

semi -variogram, kriging computes estimates at selected points, or average values over

Using the discrete subregions of the aquifer.

The method also computes the variance of the estimation error (kriging variance) at each point, or subregion, and the covariance matrix associated with these errors.

error is dependent on the natural fluctuation of the observed data as described by the

The kriging variogram function, on measurement errors, and on the relative locations of the measurement points.

One may therefore expect the kriging errors to be smallest in the vicinity of observation points, and largest far from these points.

This paper describes the application of kriging to log- transmissivity and water -level data from the

Madrid basin, Spain.

Similar applications to ground -water basins in Arizona were reported earlier by

Binsariti (1980) and Clifton and Neuman (1982).

Setting of Study Area

1).

The study area is an elongate northeast -trending alluvial basin surrounding Madrid,

The basin is approximately 160 kilometers long and between 30 and

60 kilometers wide.

Spain (Figure

The study area is bounded to the north and northwest by the Central Range and to

Jarana, and Henares Rivers.

the south and east by the Tajo,

61

0 kilometers

25

AQUIFER PARAMETER

MEASUREMENT SITE

Figure 1.

Location of Madrid basin, Spain, with aquifer parameter measurement sites.

The climate is continental with a mean annual temperature of 13 °C and a yearly precipitation of 400 to 600 millimeters.

The sediments are typical of a continental basin.

the mountains and grade into chemical

Fans of coarser detritic deposits spread from evaporitic deposits in the southeast.

The sediments are heterogeneous with interfingering of detrital and chemical deposits.

Their thickness is believed to reach

2,000 to 3,000 meters (Llamas and Cruces de Abia, 1976).

The aquifer of interest includes the Toledo, Madrid, and Guadalajara groups of the detrital facies

1

(Llamas and López Vera, 1975).

m /day, and

Average horizontal hydraulic conductivity is low, on the order of 0.5 to vertical conductivities are about 100 times smaller

(López Vera, Lerman, and Muller,

1981).

the interfluvial zones and snowmelt in the

Recharge occurs by infiltration of precipitation in mountains.

The aquifer discharges to the rivers.

Kriging Theory

Kriging is a best (minimum variance) linear unbiased estimator (BLUE).

precludes any detailed discussion of kriging theory, only a brief

As the length of this paper outline will be given here.

Interested readers are directed to David (1977), Delhomme (1978), or Journel and

Huijbregts (1978).

which under the intrinsic hypothesis has a

Let Z(x) be a random function constant mean, defined in a region, R,

E[Z(x)] = mz

and a semi -variogram,

Y(X,x+s) = E{[Z(X*s) - Z(x)]2} where E represents expectation.

The semi -variogram depends only on the displacement vector, s.

arity implies that the kriging estimator, Zk(x), of the function

Z(x), is of the form

Line

Zk(x

)

=

N

E

1 =1 aiZ *(xi) where Z *(xi) is the conditions i -th of N observations, and the "kriging weights," ai, are obtained by of minimum variance and unbiasness.

imposing the

These conditions lead to the following N +1

"kriging equations ",

62

E

N j=1 as(

(xi

-

aft i2+u =y

(xi ,So)

i=1,2

N

N

E j =1 aj =1 where N is Lagrange multiplier, ai2 is variance of measurement error at i -th observation point, y(xi,xa) is semi -variogram between two experimental points xi and x, and y(xi,So) is mean semi -variogram between point xi and subregion So.

When kriging at a point, the last term reduces to y(xi,xo), the semi variogram between experimental point xi and kriging point xo.

The method was applied to log -transmissivity and

Spain.

residual water -level data from the Madrid basin,

Kriging of Log -Tranmissivity

Regression Analysis

Specific capacity data are available from 299 sites in the Madrid basin (Figure 1).

ties calculated from aquifer tests are available only at 44 out of these 299 sites.

Transmissivi-

To increase their number, estimates of log -transmissivities were generated from the more numerous data by linear regression.

The resulting regression equation is log- specific capacity log10T = 0.24685 + 0.70721 log10SC where T is Aransmissivity and SC is specific capacity, both given in m2 /day.

mination, R4, for the regression is

0.49.

The 95% confidence interval transmissivity is

The coefficient of deterfor the predicted log -

1o910T t 2.02 oT(SC) where aT2 is variance of the error of prediction.

These formulae were used to predict log transmissivities, and to compute the associated error variance at the remaining 255 sites.

Semi -Variogram Calculation and Modelling

The log -transmissivity field is assumed isotropic for the purpose of sample semi -variogram determination.

(1981).

The sample semi -variogram was calculated using the computer code SEMIVGM written by

Clifton

The resulting sample semi -variogram was fitted with a spherical mode by trial and error (Figure

2).

The equation of this spherical model is y(s) =

.10 + .08[1.5(s/40) - 0.5(s/40)3]

.18

s<40 s >40 where s is the distance in kilometers between two points.

The fitted semi -variogram model was calibrated by systematically deleting each data point one at a a time and using the remaining data to estimate the deleted point by kriging.

The true errors were unbiased and consistent with the computed kriging errors as outlined by Deihomme (1978).

Kriging of Log -transmissivities

The log -transmissivities were kriged and averaged over 54 finite zones of about 100 square kilometers each.

The kriging was done using computer code KRIGE developed by Clifton (1981).

Each zone was kriged using a maximum of 30 log -transmissivity data points selected from a circular neighborhood of radius 35 kilometers centered on the zone.

Data points nearest to the zone centroid were preferentially selected.

Log -transmissivities derived by regression from log- specific capacities have known prediction which are accounted for in the kriging system.

Measurement errors errors associated with of log transmissivities derived from aquifer tests are accounted for indirectly through a jump of the semi variogram at the origin (nugget effect).

semi -variogram within the zones.

Numerical integration was used to calculate mean values of the

63

2

ample Semi -variogram

?o rn

I

G/

Model

0

0

10

s

20

( Kilometers)

30

Figure 2.

Log -transmissivity sample semi -variogram and fitted model.

40

50

After the average log- transmissivities were kriged over each zgne, the corresponding transmissivity estimates, T; xi), and variance of associated estimation errors, aT (xi), were computed from the kriged estimates,

Zkzi), and the kriging errors, ak(xi).

plotted on Figure 3.

Contours of These transmissivity

The coefficient of variation, CV, defined as estimates are

CV

°T(il)

*

T (xi) is contoured in Figure 4.

This figure shows that zones with the most reliable transmissivity estimates

(lowest CV values)) occur in areas where data points are densely spaced.

Where data are scarce, as happens close to the basin margins (particularly on the right and in the lower central areas), the coefficients of variation are relatively large indicating that the transmissivity estimates are highly uncertain.

0 kilometers

25

TRANSMISSIVITY IN m2/DAY

Figure 3.

Contour map of transmissivity (T *(xi)) derived from kriged log- transmissivity.

64

9 kilometers

25

Figure 4.

Contour map of coefficient of variation (CV) of transmissivities derived transmissivities.

from kriged log -

It is important to recognize that our kriged transmissivity estimates are spatial averages over the zones and may thus differ from point transmissivities as determined by pumping tests or regression from specific capacities.

Without a careful study of kriging errors, results may be misleading.

For example, or indirectly, coefficients of variation, the kriging kriged transmissivities in the southeastern portion of the basin are higher than one might expect on the basis evaporites and other chemical deposits which of geological considerations; the area consists of should have relatively low transmissivities.

lously high kriging estimates in this area are an artifact, caused partly by lack of

This lack of data is reflected in the relatively large coefficients

The anomasufficient data.

of variation obtained in this area.

Kriging of Heads

Whereas log -transmissivities may be treated as an intrinsic stochastic process, the same is usually not true for hydraulic heads.

drift.

Generally, head data are associated with a

In order to use the simple kriging equations given above, the drift non -constant mean, m(x), or must first be removed from the data.

Steady -state water -level measurements are available for 279 shows the location of the measurement wells and points in the Madrid basin.

water -level contours drawn by the

Figure 5

Spanish Geological

Service.

This contour map was drawn on the basis of more data than those shown in

Figure 5.

Unfortunately, these additional data were not available to us.

An experimental semi -variogram based on the original water -level

We did this by assuming that drift is a data demonstrated the need for filtering the drift.

determined by generalized least squares.

The least taking the correlation into account, was repeated iteratively until polynomial whose coefficients squares fitting was done iteratively.

can be

We started with a polynomial of first order and assumed, as a first nomial are uncorrelated.

of the residual head with polynomials similar of fluctuations by second, third, and fourth order.

step, that head fluctuations about this poly-

After fitting the polynomial to the data, we studied the correlation constructing their semi -variogram.

This procedure was repeated

The third and fourth semi -variograms, and we chose the latter to represent the drift.

The least structure order polynomials gave squares fitting, there was no significant change from one iteration to the next.

The resulting experimental semi -variogram of the model (Figure 6).

computed residuals was fitted with a spherical y(s) = r1850[1.5(s/18) - 0.5(s/18)3]

L1850 s<18 s>l8

The theoretical model was validated, as in the case of log -transmissivities, by systematic each data point in turn and kriging that value using all remaining points.

deletion of

65

-

2kilometers

25

WATER LEVELS IN METERS

ABOVE MEAN SEA LEVEL

LOCATIONS OF WATER LEVEL

MEASUREMENT SITES

Figure 5.

Contour map of water -level contours (from Spanish Geological Service) with location of available water -level measurement sites.

3-

\Model

í

Sample Semi -variogram

.

.

-

.

N

\ ._.

/`

10

20 s

( Kilometers)

30 40

50

Figure 6.

Hydraulic head residual sample semi -variogram and fitted model.

Head residuals were kriged at 294 nodal points of a finite element grid to be used later for aquifer modeling.

1981).

Kriging was accomplished using a modified version of the computer code KRIGE

Each nodal point was kriged using a

(Clifton, maximum of 25 data points in a circular neighborhood of radius 30 kilometers centered on the point.

drift estimates to produce total head values.

The kriged residuals were then added to the polynomial

66

Figure 7 is a contour map of the kriged steady -state head estimate.

smoother than those in Figure 5.

The contours are seen to be

One reason for the smoothing is the relatively large spacing of kriging points (on the order of 5 kilometers) which precludes the mapping of small scale features.

Another reason may be the fact that we used fewer data than those used by the Spanish Geological Service to construct their map.

0 kilometers

25

WATER LEVELS IN METERS

ABOVE MEAN SEA LEVEL

Figure 7.

Contour map of kriged hydraulic heads.

Kriging estimation errors, oH(xi) are plotted on Figure 8.

the errors are seen to be largest in the southeast and

As in the case of log -transmissivities, northern portions of the basin.

The reason, as before, is the relatively small amount of data in these areas.

0 25 kilometers

I

Figure

8.

Contour map of hydraulic head kriging errors (aH(xi)).

Conclusions

The following conclusions can be drawn from this study:

1.

Kriging is a useful tool for the interpolation taking into account measurement errors.

and spatial averaging of log -transmissivities

It provides not only estimates of these values, but also information

Madrid basin.

about the errors of estimation.

The method appears to work well for the

67

2.

An iterative method to simultaneously determine the drift and residual variogram of hydraulic heads, using generalized least squares, has been applied with apparent success to the Madrid basin.

Acknowledgments

The authors wish to thank Dr. S.

N.

Davis for his support, and their helpful comments.

J. Carrera and E.

A.

Jacobson for

This work was supported by Cooperative Research Grant No. T3770171 of the U.S. -

Spanish Joint Committee for Scientific and Technological Cooperation.

The authors also wish to acknowledge S. Adams for typing and M. Busse for drafting.

References

Binsariti, A. A. 1980.

Arizona.

Statistical Analysis and Stochastic Modeling of the Cortaro aquifer in Southern

Ph.D. dissertation, Universtiy of Arizona, Tucson. 242 p.

Clifton, P. M. 1981.

fer.

Statistical inverse modeling and geostatistical analysis of the Avra Valley aqui-

M.S. thesis, University of Arizona, Tucson. 190 p.

Clifton, P. M. and S.

P. Neuman. 1982.

Effect of kriging and inverse modeling on conditional simulation of the Avra Valley aquifer in Southern Arizona. Water Resour. Res.

In Press.

Developments in Geomathematics 2.

Elsevier

David, M.

1977.

Geostatistical Ore Reserve Estimation:

Scientific Publishing Co.,

New York.

384 p.

Delhomme, J.

P. 1978.

Kriging in the hydrosciences.

Advances in Water Resources.

5:251 -266.

Journel, A.

G. and Ch. J. Huijbregts.

1978.

Mining Geostatistics.

Academic Press, New York.

600 p.

Llamas, M.

R.

and

J. Cruces de Abia.

1976.

the Tertiary basin of the Tagus River.

of Budapest.

p. 186 -202.

Conceptual and digital models of the groundwater flow in

Spain.

Mem. of the Inter. Assoc. of Hydrogeo.

13.

Sym.

Llamas, M.

R. and C.

F. López -Vera.

metropolitana de Madrid.

1975.

Estudio de los recursos hidráulicos subterráneos del area

Avance de las características hidrogeol6gicas del Terciario Detritico de la Cuenca del Jarama -Aqua.

Barcelona.

88:36 -55.

López Vera, F., J. C. Lerman and A.

reconnaissance.

B. Muller.

Jour. of Hydr.

54:151 -166.

1981.

The Madrid basin aquifer:

Preliminary isotopic

Matheron, G.

1963.

Principles of geostatistics.

Econ. Geol.

58:1246-1266.

68

ENERGY AND WATER RESOURCES INTERACTIONS IN ARIZONA

Nathan Buras, Ph.D.

Department of Hydrology and Water Resources

University of Arizona, Tucson, AZ 85721

Abstract

Water and energy interact strongly in Arizona.

The Arizona State Water Plan mentions that under

1970 normalized conditions 60% which may have increased in of total use in the the last decade.

State was from groundwater aquifers, a proportion

The utilization of groundwater resources requires substantial amounts of power.

In addition, the Central Arizona Project is an energy- intensive pr9ject: its Granite Reef aqueduct will require a pumping lift of 1,084 ft (352 year.

m) using about 1.665 x

10 kwh/

The Tucson aqueduct component will have an additional lift of 997 ft

(304 m).

The hydropower installations planned within the CAP will have only limited generating capacities: Agua Fria

3 Mw,

Granite Reef 3.5 Mw, and Maxwell 11 Mw.

The remainder of the load will have to be picked up by thermal power plants and by pumped storage schemes which, by the year 2000, may need over 100,000 acre -feet per year to make up evaporative losses.

Thus, energy is required to make water available to users, and water is a necessary ingredient in energy -related activities.

These and other water -energy interactions in the Lower Colorado Basin are discussed.

Introduction

By and large, the United States has substantial quantities amounts of surface and groundwater.

However, in the Southwest of energy resources and especially in and considerable

Arizona, water is scarce and most of it is already allocated to various sectors of the economy, the most notable being agriculture and mining.

The availability of water resources in reliable quantities and of adequate quality ranks as an important criterion for the siting of thermoelectric power plants.

Water and energy interact in two ways (Buras, 1982).

On the one hand, energy is an input to many water resources systems, from pumping of groundwater to treatment of liquid wastes.

On the other hand, almost all energy -related activities use water, either as process water in the production of synthetic fuels or as a transport medium for the removal of waste heat and /or waste matter.

Water- energy interactions are shown diagramatically in Figure 1.

Almosobere

L

Inter basin transfers

Energy

Nmpetl w ge

Shea , am outflow

1 r

Water demand

MuniclpalenE i

Ene

Surface

Luoplv Agricultura water treatment

tL

Ene.

1

Tra lee

%Warlt

Ile

Ocean

Figure 1.

Water- energy interactions.

69

Water Requirements for Energy -Related Activities

The use of water in energy -related activities is consumptive and it consists of three major components:

1.

Process water, such as in the case of synthetic fuels where water contributes to the making of the product.

2.

Evaporation, which removes excess (waste) heat from energy -related processes.

3.

Waste water, which removes waste matter.

The use of water by energy -related activities is shown in Table 1.

Table 1.

Estimated Water Use in Energy -Related Activities

(Acre- feet /1015BTU).

Activity

Process

Water Evaporation

Waste

Water Total References

Light -Water Reactors

Fossil Fuel Thermal Power

Stations (No scrubbing)

Coal Gasification, HRTU

Oil Shale Conversion

Coal Gasification, LBTU

Coal Liquefaction

Nuclear Fuel Processing

Coal Slurry Pipeline

Oil Refining

Coal Mining, Underground

Coal Mining, Strip,

Revegetation

Coal Mining, Strip,

No Revegetation

32,500

21,700

1,000

2,800

537,200

358,100

68,100

32,000

56,000

36,700

37,400

16,000

7,700

3,380

1,800

55,600

37,100

2,800

8,000

700

17,500

3,900

6,200

592,800a

395,200b

103,400

61,700

57,700

57,000

41,300

34,000

22,200

7,700

3,380

1,800

Davis and Wood, 1974

Gold et al, 1977

Gold et al, 1977

Gold et al, 1977

Chandra et al, 1978

McNamee et al, 1978

Davis and Wood, 1974

Davis and Wood, 1974

James and Steele, 1977

Gold et al, 1977

Gold et al, 1977 a.

b.

0.66 gal /kwh

0.44 gal /kwh

Development of Groundwater

Much of the water currently used in Arizona in energy -related activities is pumped from aquifers, and it is quite possible that this situation will ceivable that as the demands continue in the foreseeable future.

It is also confor water will continue to rise, the different economic sectors in the

State will increase their competition for the limited water resources to the point of conflict.

It is important, therefore, to develop strategies for the management of the groundwater basins so as to meet the competition and avoid the conflict.

Figure 2 (Domenico, 1972).

The groundwater management issue is shown schematically in

The crucial question is whether to exploit the aquifer within safe -yield limits or to mine the groundwater.

An optimal management policy seems to be found between two extreme positions: mining of groundwater will definitely lead toward the exhaustion of the aquifer within a unregulated finite time period, while infinite preservation based on a safe -yield policy may waste groundwater due to the

70

Precipitation

1

Evapotranspiration i

Figure 2.

Schematic representation of a groundwater basin.

natural aquifer outflow (Mandel and Shiftan, 1981).

Thus the safe -yield concept, based on the natural recharge, should be substituted by the principle of sustained yield. Sustained yield is defined as the maximum rate of groundwater abstraction that can be maintained over a long period of time

(e.g., more than a century) without causing consequences point of view.

unacceptable from an economic, political

Examples of undesirable effects are lower water levels and or environmental reduced well discharges, deterioration of water quality due to intrusion of saline waters, and land subsidence.

The "undesirable effects" may be expressed quantitatively by ranges of values, so that their limits can be used as constraining conditions in mathematical programming models of groundwater systems.

The development of regional groundwater resources should be planned in conjunction with the surface waters.

In Arizona in particular, aquifers need to be integrated within the State Water Plan.

The Arizona State Water Plan

The major components of an Arizona Water System could be the following: surface water: the Salt River Valley Project the Central Arizona Project other surface water projects groundwater:

Tucson Active Management Area

Phoenix Active Management Area

Prescott Active Management Area

Pinal Active Management Area other groundwater basins

The integration of the major (and other) components into a comprehensive system, including its legal framework required for the development, utilization, and management of state's water resources, is a time -consuming process.

So far, an inventory of water resources was completed (Arizona Water Commission, 1975), some alternative futures were explored (Arizona

Water Commission, 1977), and a number of important water uses were analyzed (Arizona Water Commission, 1978).

Currently, the state water planning efforts are concentrated on the groundwater components of the state water resources system (Arizona

Water Commission 1980).

These efforts should continue so that an integrative plan should emerge in the near future, according to which groundwater aquifers and surface subsystems would be operated conjunctively.

The Arizona State Water Plan should include provisions for establishing water quality standards and guidelines for water quality management.

Water quantity and water quality are inseparable issues: influence each other and are integral parts of the natural hydrological processes.

they

Even if it may seem economically attractive and politically acceptable in the immediate particularly obvious when considering that the or short range to deal reclamation of marginal waters (e.g., with water quality separately from water quantity, the irreversibility of most policy decisions separation may generate considerable social costs in the medium and long time horizon.

based on this

This becomes brackish groundwater, effluent from wastewater treatment plants) is an energy -intensive activity.

71

The Central Arizona Project

The Central Arizona Project will divert from the Colorado river about 1.2 Maf /year on the average

(U.S. Bureau of Reclamation, 1962).

Roughly two -thirds of this amount is allocated to irrigated agriculture and the remainder to the municipal and industrial sectors including electric power generation.

The contribution of the CAP to the Arizona state water system will be considerable less than the current groundwater overdraft which is in excess of 2.2 Maf /year.

Energy considerations overshadowed the CAP in the last decade.

related development in the Upper Colorado Basin (such

It was suspected that energy as coal -based synthetic fuels, or oil shale exploitation) will deplete all remaining water supplies so that none will be left for CAP.

studies (Steiner, 1975) refuted these suspicions.

Nevertheless, the CAP is

Subsequent an energy -intensive component of the Arizona water resources system.

long) involves a pumping lift of 1,084 ft.

Its Granite Reef aqueduct (capacity, 3,000 cfs; 219 miles

The Tucson aqueduct, which will deliver about 100,000 af/ year (capacity, 150 cfs; 56 miles long), will need a pumping lift of 97 ft.

The annual pumping power requirements for the Granite Reef aqueduct are estimated at 1.665 x 10 kwh.

The projected power plants included in the CAP --Agua Fria,

3 Mw; Granite Reef, 3.5

ginally to satisfy these requirements.

Mw; Maxwell, 11 Mw- -will contribute only mar-

Hence, most of the load needed by the CAP will have to be picked up by power plants outside the project.

Water- Energy Interactions

The Central Arizona Project, one of the most energy -intensive components of the State Water System, is located in a region where electric power requirements are projected to increase more than four -fold during the last two decades of this century: from 6,617 Mw of peak demand in 1980 to 28,532 Mw in year

2000 (Arizona Water Commission, 1971).

By the year 2000, it is estimated that the annual consumptive use of water for pumped- storage and thermal power plants in the CAP service area may exceed

100,000 af/ year.

A second component where water and energy interact strongly is

Colorado River International Salinity Control Project.

the desalination plant for the

This desalination plant, with a projected output of

101,000 of /year, will require all the power generated by a plant of about 35 Mw capacity (Jacoby,

1975).

Finally, the groundwater basins which supply the bulk of the water currently used in the state use considerable amounts of power for pumping.

lowers the water table, so that the

The increased demand for water increases pumping rate, which amount of energy required to lift one unit of water is steadily increasing.

It is estimated that each foot of increased pumping head in the southern half of Arizona requires the equivalent of about 6 million kWh of electric energy (U.S. Water Resources Council, 1978).

Summary

The water -energy interaction highlights a very important question: to what extent are water problems in Arizona a barrier to development within the State?

Apparently, an answer to this question must take into account four unresolved water issues (Brown and Kneese, 1978): the equity issue, the efficiency issue, the environmental quality issue, and the water development issue.

In many cases solutions exist, some of which were already tested, accepted, and are being implemented; others are still in the theortical- conceptual stage.

Water is an essential ingredient in almost all energy -related activities, primarily for the removal of excess heat.

Energy is a major component of the Arizona State Water Plan, especially when considering that about 60% of the water is pumped from the aquifers and that the major surface water system (the

CAP) is energy- intensive.

The necessity of studying, planning, designing, and energy sectors of the State cannot be overemphasized.

operating the water and

Arizona Water Commission.

1971.

Electric Power.

Phoenix, AZ.

Lower Colorado Region Comprehensive Framework Study,

Arizona Water Commission.

Phoenix, AZ.

1975.

References

Arizona State Water Plan, Phase I.

Appendix XIV:

Inventory of Resources and Uses.

Arizona Water Commission.

AZ.

1977.

Arizona State Water Plan, Phase II.

Alternative Futures.

Phoenix,

Arizona Water Commission.

Phoenix, AZ.

1978.

Arizona State

Water Plan, Phase III - Part 1.

Water Conservation.

72

Arizona Water Commission.

1980.

Tenth Annual Report, 1979 -1980.

Phoenix, AZ.

Brown, Lee and Allen V. Kneese.

Review.

68(2):105 -109.

1978.

The Southwest: a region under stress.

Buras, Nathan.

1982.

report EA -2259.

Modeling water supply for the energy sector.

EPRI.

Palo Alto, CA.

The American Economic

Electric Power Research Institute

Chandra,

K., B. McElmurry, E.

W.

Neben and G.

E. Pack.

1978.

combined cycle systems for electric power generation.

Economic studies of coal Gasification

Electric Power

Research Institute report

AF -642.

EPRI.

Palo Alto, CA.

Davis, G.

H. and L.

A. Wood.

Survey circular 703.

1974.

Reston, VA.

Water demands for expanding energy development.

U.S. Geological

Domencio, Patrick A.

1972.

Concepts and Models in Groundwater Hydrology.

New York:

McGraw -Hill.

Gold, H., D. J.

Goldstein, R.

F. Probstein, J.

S.

Shen and D. Yung.

steam -electric power generation and synethic fuel plants mental Protection Agency report no. 600/7 -77 -037.

EPA.

1977.

Washington, D.C.

Water requirements for in the Western United States.

Environ-

Jacoby, Jr., G. C.

1975.

ings of the Conference on Water Requirements for Lower Colorado Basin Energy Needs.

of Arizona.

Overview of water requirements for electric power generation.

Tucson, AZ.

In:

Proceed-

The University

James,

I.

C.,

II and T. D. Steele.

1977.

Application of residuals management for assessing the impacts of coal- development plans on regional water resources.

Third Internation Symposium in Hydrology.

Colorado State University.

Ft. Collins, CO.

Mandel, Samuel and Z.

L. Shiftan.

1981.

Groundwater Resources.

New York: Academic Press.

McNamee, G. P.,

N.

K. Patel, T.

R. Roszkowski and G. A. White.

of alternative coal liquefaction concepts.

Electric Power

1978.

Process engineering evaluations

Research Institute report AF -741. vol.

1.

EPRI.

Palo Alto, CA.

Steiner, W.

E.

1975.

Water for energy as related to water rights in the Colorado River

Basin.

Proceedings of the Conference on Water Requirements for Lower Colorado Basin Energy Needs.

University of Arizona. Tucson, AZ.

U.S. Bureau of Reclamation.

1962.

Appraisal Report.

Central Arizona Project.

Boulder City, NV.

In:

The

U.S. Water Resources Council.

1978.

Government Printing Office.

The Nation's Water Resources 1975 -2000.

Washington, D.C.: U.S.

73

POTENTIAL ENERGY RESOURCES

OF THE GULF OF CALIFORNIA, NORTHWESTERN MEXICO by

Barney P. Popkin

Water Resources Consultant

5502 Briarwood Forest Drive

Houston, Texas 77088

Abstract

The Gulf of California in northwestern Mexico is a tropical sea of the northeastern Pacific

Ocean.

Earthquake activity is common in the region, especially towards the northwest where transform faults are associated with volcanic and geothermal activity, and features such as the San Andreas fault zone.

The Gulf contains 132,000 cu km of seawater, with a surface area of 162,000 sq km, and a mean depth of 815 m.

Its surface salinity is about 35 ppt.

The Gulf is subject to the second highest tides (>10 m in range) in North America.

The region is currently undergoing extensive human development and energy exploration.

After reviewing the climatic, geologic, soil and vegetation, and oceanographic settings, the potential energy resources of the Gulf are evaluated.

These resources include those controlled by climate (solar, wind), geology (hydrocarbon, geothermal), biology (biomass) and oceanography (tidal, wave, hydrothermal).

Climatic energy sources (unproven technology) have fair potential for modest -scale, onshore and near -use development.

Geologic sources are online, and have high potential for large -scale commercial development with export value.

Biological sources

(unproven technology) have low potential for small- scale, near -use development.

Oceanographic sources have high potential for moderate -scale near -use potentially exportable development.

Introduction

The Gulf of California (Sea of Cortes) in northwestern Mexico is a tropical latitude sea of the northeastern Pacific Ocean adjoined by Baja California Norte and Baja California Sur to the west, and

Sonora, Sinaloa and Nayarit to the east (Figure 1).

The trough- shaped Gulf contains a very irregular base with several basins and has free communication with the Pacific at its entrance above depths of 3,000 m.

The Gulf was formed from the plate tectonic spreading center on the East Pacific Rise during Tertiary time and exhibits northwesterly transform faults.

Earthquake activity is common, especially towards the northwest where the faults are associated with volcanic and geothermal activity and features such as the San Andreas fault zone of California.

The Gulf contains 132,000 cu km of seawater, with a surface area of 162,000 sq km and a mean depth of 815 m.

It receives some recharge from rivers to the southeast, although it is excessive winter cooling and summer evaporation which tend to raise the Gulf's surface salinity.

The Gulf is subject to the second highest tides in North America, which is partly why novelist John Steinbeck and his marine biologist friend, Ed Ricketts, called the Gulf "a highly dangerous body of water (39)." sive

Though the region is among the last to be settled in Mexico, it is currently undergoing extenurban development

(based on fishing, tourism, ranching and farming, and mining) and energy exploration.

Small scale solar energy research and geothermal energy exploration, and biomass conversion research began in the 1960's and 1970's, respectively.

Petroleum exploration began in earnest in the early 1980's.

The purpose of this report is to review the potential energy resources of the Gulf of

California.

Cultural Setting

By

In

1900, the population of the Gulf states was 716,100, or 5.3 percent of the national total.

1940 and

1980, the population grew from 1,204,100 to 6,292,000 or 6.1 to 8.8 percent of the national total, respectively.

75

This growth represented a 43.2, 51.6, 49.5 and 61.0 percent increase in the Gulf states population in 10 -year intervals, while the national population increased by only 31.2, 35.4, 41.0 and

49.1 percent for the same time intervals.

The Gulf's population doubled in the past 15 years, while the national population has doubled in the urban centers.

in the past 20 years.

Most of this enormous growth occurred

The Gulf states have grown, from fastest to slowest, in this order:

Baja

California Norte, Baja California Sur, Sinaloa, Sonora and Nayarit.

densely populated part of Mexico.

The Baja peninsula is the least

Agricultural products from the region include maize, vegetables, cotton and alfalfa (predominantly in the Colorado Delta), wheat, beans, sugarcane and rice (Sinaloa and Nayarit) and coffee

(Nayarit).

Irrigation is commonly practiced.

mules, donkeys, sheep, goats, hogs and poultry.

There are also fruit trees, beehives, cattle, horses,

Fishery production, especially shrimp, is a major activity, with high tonnage from the Bajas and high value from the Rajas,

Limited coal and lignite deposits occur southeast of Hermosillo (Sonora).

Sonora and Sinaloa.

Copper, salt, sand, gravel and lime are important mineral products.

Recent tourism and American recreational and retirement communities have contributed significantly to the Gulf's economy.

The Mexican economy is rapidly expanding and diversifying, while also suffering from the current world -wide recession.

Mexico now has an annual five percent growth (1982) in real gross domestic product, though 10 percent was forecast.

There is increasing demand for professional and skilled workers.

While the annual

U.

S.

inflation rate is falling to less than 10 percent, the Mexican inflation is rising to over 30 percent, and the peso was significantly devalued in early 1982.

Inflation in February 1982 reached 53 percent on an annual basis.

Mexico, which began exporting energy in the early 1970's, is now the world's fourth -largest producer of oil and gas and the fifth largest exporter.

The effects of increasing population, agriculture, tourism and supporting industries and activities, coupled with the social expectations of a rapidly evolving economy, has astronomically increased the demand for energy in the Gulf.

Mexico's cultural and economic expectations demand that exportable energy be developed to support growth and security.

Physical Setting

The climate, geology, soil and vegetation, and oceanography of the Gulf of California are the relevant physical components to examine when evaluating the Gulf's potential energy resources.

Climate

The climate of the Gulf region varies from the arid Rajas and Sonora, the semi -arid Sinaloa, and the semi -humid Nayarit (20).

The Bajas, most of Sonora and north -coastal Sinaloa have a hot, desert climate; central -coastal Sinaloa and south - coastal

Sonora have a hot, steppe climate; and

Nayarit and south -coastal Sinaloa both have a dry winter, tropical rainy climate (2).

25 °C

25 °C.

The mean annual air temperature varies from about 15 °C in the mountains of northern Baja to in coastal Nayarit.

Most of the Gulf has an average annual air temperature between 20 to

The mean annual rainfall varies from less than 250 mm in the northwest, to about 900 mm in the southeast.

The area -weighted annual interannual variability.

rainfall averages 250 mm, with 25 to 60 percent relative

The average annual evaporation rate is on the order of 100 to 200 mm.

Winds are generally less than 10 km /hr, but may exceed 100 km /hr during severe storms.

Geology

The geology of the Gulf is structurally controlled by the San Andreas fracture zone which formed the Gulf (17, 28).

The thin, western landmass rises abruptly as a coastal plain to the Baja mountain ranges.

The broad, eastern landmass rises gently as a coastal plain of buried mountains.

The Gulf drains about 668,800 and 432,000 sq km of land from the U.

S.

and Mexico, respectively.

Nearly all the surface water runoff from the U.

S., and most of that from Mexico, does not contribute directly to the Gulf, but contributes to numerous, small internal basins.

like playas, especially on the northeast coast of the Gulf.

Many of these form sahkeh-

The Gulf separates the mountainous peninsula of Raja California to the west (a westward -tilted plateau with a steep eastern side) and the broad coastal Sonora plain to the east (a northern late -

Cenozoic desert plains and minor ranges, with central and southern modern deltas, lagoons and twisted and elongated plains).

Landward from the eastern coastal plain rises basin and range topography to the high range of the Sierra Madre Occidental.

The Colorado River has built a large delta with extensive flanking tidal flats at the northwestern end of the Gulf.

The terrain sloping toward the Salton Sea from the Colorado Delta is the Valle de Mexicali

(Mexicali Valley), and becomes the

Imperial

Valley in the U.

S.

The Gulf occupies a structural depression which embraces the Salton

Sea in the U.

S.

76

The eastern coast is straight, low and sandy, with deep water bays at Topolobampo (Sinaloa) and

Guaymas

(Sonora), and natural lagoons enclosed by sand bars or sandy spits.

The western coast has the bay of La Paz (Baja California Sur).

Guaymas and Mazatlán (Sinaloa) are principal ports.

The southern Gulf has a relatively thin crust, where the Moho is 10 to 11 km below sea level.

The Moho is about 23 to 25 km beneath the Baja peninsula and the mainland.

The Gulf is structurally part of the

Pacific Ocean.

The Gulf floor's topography suggests that it was formed by lateral movements along northwest- southeast trending fractures associated with the San Andreas fault system.

Shallow earthquakes are common.

The Gulf was formed from the plate tectonic spreading center on the

East Pacific Rise during late Tertiary time.

The recent rate of motion between the Pacific and North

American plates is about 5.5 cm /yr (28).

Soil and Vegetation

The soils of the Gulf region are generally poorly developed, well- drained, calcareous sandy alluvial and aeolian soils, with poorly drained flood plain and estuarine silts and lesser, saline and gypsiferous inland -basin silts and clays.

Soils tend to be low in organic matter, alkaline and calcium rich.

Soil erosion is slight to moderate.

There is a yearly soil moisture deficiency, where potential evapotranspiration exceeds precipitation, except along south -coastal Sinaloa and

Nayarit where there is significant soil moisture recharge during summer.

The native vegetation is mostly temperate desert types, except for temperate mesquite grasslands in south -coastal

Sonora.

coastal

There are also tropical decidous and thorn forests along south -

Sonora, Sinaloa and

Nayarit, and some tropical savannas along south -central

Sinaloa and north -coastal Nayarit.

Flat coastal marshes support halophytic and estuarine vegetation, especially near the northern Gulf.

Oceanography

The Gulf of California is an arid, tropical latitude sea of the northeastern Pacific Ocean.

This elongated, northwest -southeast trough has a very irregular base with ten basins.

communication with the Pacific at its entrance above depths of 3,000 m.

It has free

A central constriction and a group of islands separate the shallow northern section from the deep southern region.

northern section is less than 200 m, while the southern basins are 1,000 to 3,600 m deep.

The

The Gulf contains 132,000 cu km of seawater with a surface area of 162,000 sq km and a mean depth of 815 m.

It is 1,500 km long and 100 to 200 km wide.

The Gulf receives some limited flow from the Colorado River and perhaps as much as 18.3 x 109 cu m /yr of recharge and 162 x 106 metric tons /yr of sediment from six eastern rivers.

Excessive winter cooling and summer evaporation tend to raise the Gulf's surface salinity.

Its surface salinity is about 34 to 36 ppt.

No permanent streams exist on the western, or northeastern banks, but there are permanent streams in the southeast.

Surface water in the northern Gulf ranges from 16 to

19 °C in winter and from 29 to 30 °C in summer.

In winter, the northern Gulf's waters are almost isothermal from surface to bottom because of convective mixing.

In summer, evaporation produces marked stratification with a warm, slightly more saline surface layer.

In the deeper northern basins, strong tidal mixing produces a homogeneous water mass.

In the southern Gulf, the water is the Equatorial Pacific.

In the central and southern Gulf, water below the thermocline is identical in salinity and temperature to equatorial

Pacific water, with a pronounced oxygen minimum between 400 and 800 m.

Above the thermocline, water is modified slightly by evaporation.

In the south, water above the thermocline is modified by surface inflow of equatorial Pacific water and water from the California current flowing around Baja.

Surface water circulation is controlled by seasonal wind regimes.

Water is driven out of the

Gulf by a low- pressure system east of the Gulf and replenished by deeper flow from the Pacific in winter.

Water is blown into the Gulf from the Pacific surface by a low- pressure system over the northern peninsula and leaves the Gulf by deeper flow in summer.

Upwelling occurs along the eastern bank in winter and along the western bank in summer, resulting in high plankton production.

The mean tidal range in the Gulf increases from about 1 m in the south to 8 m near the mouth of the Colorado, where it exceeds 10 m at spring tides.

The northern Gulf is subject to the second highest tides in North America.

The tidal wave is a progressive, northward -traveling wave, where tidal current, velocities are high in the northern Gulf and between the large islands of Tiburón

(Sonora) and Angel de la Guarda (Baja California Sur).

Energy Resources

The energy resources of the Gulf of California are controlled by climate, geology, biology and oceanography.

domestic.

These will be either renewable or nonrenewable, and exportable or exclusively

The Appendix presents energy or work, and power unit conversions.

77

Climatologically Controlled Energy

Solar and wind energy are controlled by climate.

These energy sources are renewable, currently exclusively domestic, with fair potential for development in the Gulf.

Currently, they are merely research topics.

These energy sources are available onshore and near ultimate use.

Solar resources.

Solar resources are currently used for desalination, heating and cooling, irrigation pumps, corrosion control of pipelines, and to activate photovoltaic cells which directly convert sunlight into electricity.

The estimated total annual energy flux from the sun's radiation is about 1041 ergs (26).

Photovoltaic power supplies about a million watts world wide for use in remote places such as weather stations, cathodic protection and ocean buoys (6).

There are solar villages, solar schools, solar ponds and solar shields (1).

ties

Leading research centers and universiin the Middle East and U.

S.

Southwest, including the University of Arizona, have extensive on -going solar research projects.

The Gulf, because of its abundant sunlight, has a fair to good potential for solar energy development.

Wind resources.

Wind energy requires a minimum wind speed of 10 to 40 km /hr to be practical

(16).

The estimated total annual energy flux from near -surface wind is about 1029 ergs (26).

The

Gulf, because of its low to moderate winds, has a poor to fair potential for wind energy development.

Geologically Controlled Energy

Hydrocarbon and geothermal energy are controlled by geology.

energy which are exportable.

They are nonrenewable forms of

There is high potential for geologically controlled energy sources in the Gulf on a commercial scale.

Hydrocarbon resources.

Hydrocarbon resources are particularly attractive because their conversion to energy is an established technology, refining produces numerous useful by- products, and such resources have an immediate exportable value.

A 42- gallon (159 -1) barrel of crude petroleum produces 5 800 x 103 BTU (1016 ergs) and a dry cu ft (0.0283 cu m) of natural gas produces 1.021 x

103 BTU (103 ergs).

The geological evidence favorably suggests hydrocarbon accumulation and entrapment in the

Sebastian Vizcaino Embayment, the

Eugenia Abrejos Province and the

Iray Puríima Region of the

Pacific side of Baja California Sur, peripheral to the Gulf (4, 32).

The Sebastian Vizcaino covers about 13, 000 sq km and contains 3.0 km or 29,200 cu km of sediments.

The Eugenia Abrejos covers about 5,200 sq km and contains 9.1 km or 25,000 cu km of marine and offshore sediments adjoining the

Pacific Ocean.

The Iray Purisima covers about 12,000 sq km and contains 3.0 km or 45,900 cu km of sediments adjoining the Pacific opposite La Paz (Baja California Sur).

Gas strikes in Baja were announced by Pemex in 1978 (24).

Hydrocarbon shows were reported in the Huichol wildcat drilled by Pemex in the Pacific waters off Nayarit and east of Islas Marias in 1979 (25).

Pemex studies found sedimentary basins covering

77, 700 sq km in waters off Sinaloa, Nayarit and Jalisco in 1979.

In 1979, Pemex completed Jalisco #1 as an oil discovery on the Pacific Coast (9).

The Oanwood Ice drillship was used to drill Totoaba #1

(dry and abandoned) off the Pacific coast.

The Zapata Trader drillship (renamed Cora) drilled

Huichol

#2, which reported gas shows.

In 1980,

Pemex explored the Gulf and found no shows (9), though researches have found petroleum in offshore geysers (40).

Pemex began a seven -well advanced exploration program both on and offshore from the Gulf and past the tip of Baja to Manzanillo.

A wildcat 21 km offshore from Nayarit found gas in producible amounts (42).

Guzman

(21) reviewed the petroleum possibilities in the Altar Desert of northwestern Sonora, northeast of the Gulf.

Gravity, magnetic and seismic surveys indicate that the Altar Basin has good prospects for petroleum production.

The basin covers about 15,500 sq km and contains 4.0 km or

46,500 cu km of continental and marine sediments.

The Basin, which extends south to Tiburón Island

(Sonora), has a about very close relationship to the San Andreas fault system to the southwest.

Since

90 percent of

California's basin petroleum production is from similar Miocene to

Pliocene sediments, Altar's marine sediments are likely to be productive.

Drag folds due to movement of the

San Andreas fault produced structural traps.

Displacement along the fault system is about 350 km.

Should the rocks be returned to their original position, the Altar Basin would be opposite the productive Los Angeles Basin.

Drilling near Hermosillo (Sonora) indicated oil shows in Eocene Rocks.

In early May 1981, Pemex announced that it plans a stepout from its indicated commercial gas strike in the Gulf off the mouth of the Colorado River (35).

It reported that its Extremeño #1 flowed 5.7 MMcfd (0.16 MMcmd) of gas plus some condensate through a 1 /4 -in.

(0.64 mm) choke from an interval

(4,799 m).

of 13,510 to 13,543 ft (4,118 to 4,128 m).

The total depth of the well was 15 746 ft

The strike was drilled by the Reforma drillship in 130 feet

(40 m) of water, 80 km south of Mexicali (Baja California Norte) and north of Montage Island.

The Extremeño #1 strike was from a Pleistocene sand at 16 km offshore from the mouth of the

Colorado River, from a structure thought to cover 60 sq km (42).

The strike was the first to establish commercial gas production in Mexico's western offshore area.

According to World Oil (42),

78

Pemex has been looking for production in this horizon since 1948 and has drilled about 40 wells in the past seven years.

Fourteen of these had shows.

In 1975, Pemex found subcommercial gas at Catrina

I and II onshore near Guerro Negro.

Exploration picked up in 1978 when Pemex brought three floating rigs to the Sea of Cortes, in the Pacific, and west and south of the Baja peninsula.

The Extremeño #1 strike sparked land leasing for petroleum rights in the Imperial Valley of

California (36).

The Oil & Gas Journal

(36) noted that "geothermal hot waters probably have been flushing the hydrocarbons up dip along the flanks" of the Valley, where a number of noncommercial gas shows have been found at 600 to 1 200 m.

Hydrocarbon discoveries are expected in Baja California, Chihuahua, the Gulf of California and offshore Mazatlan in the medium term in northwestern Mexico (42).

However, World Oil (43) projects a 13.6 percent decline in the number of wells to be drilled in 1982 over 1981, which may delay new discoveries and encourage cautious production in proven fields in and near the Gulf of Mexico where

Mexico's production is secured.

Two factors contribute to the projected decline:

1)

Mexico's

"cardinal sin of borrowing heavily against resources in the ground" at the same time that there is a world -wide decline in political climate, demand or unexpected- softness of the world crude market; and

2)

Mexico's in which drilling traditionally declines in an election year.

Mexico lost at least five billion dollars in anticipated revenues as a result of the 1981 - 1982 world oil glut.

However, world -wide market or supply changes, such as a new Middle East war or a world -wide economic recovery, would increase the value of Mexican oil.

Mexico became an oil exporting country in the early 1970's.

From 1976 to 1981, Mexico annually produced about 1.5,

1.6,

2.0,

2.3, 3.3 and perhaps 4.5 to 5.0 percent of the world's crude oil.

Its anticipated that this percentage will increase in the mid term, with increasing production from existing and new fields, including those yet to be developed in the Gulf.

Mexico's proven reserves are estimated to be about twenty percent of those of the U. S.

Mexico's prospective areas of major hydrocarbon fields include 60, 000 sq km offshore from

Sinaloa and Nayarit, 68,000 sq km in western Baja California Sur, 84,000 sq km offshore at the mouth of the Gulf, and 245,000 sq km in northwestern Sonora (3).

Geothermal resources.

Geothermal energy is extracted from superheated underground steam or water with temperatures often greater than 300 °C.

The estimated total annual energy flux from the thermal gradient is about 1028 ergs (26).

At least 22 countries are developing geothermal resources to produce electricity.

The Oil thermal

& Gas Journal (34) reported the beginning of a five -year study of the hot -brine georesources of the Cerro Prieto area, 32 km southeast of Mexicali and the California- Mexico border in Baja California Norte.

At that time, the area was the site of a geothermal plant with an electric generating capacity of 75 MW and an ultimately planned annual production capacity of 440 MW.

The Cerro Prieto Geothermal Field in Mexico's Mexicali Valley had its first wells drilled in 1959 and

1961 as a

8 result of hot springs, geysers, mud pots and fumaroles observed near Laguna Volcano about km southeast of the volcanic Cerro Prieto.

The Cerro Prieto Geothermal

Field is a hot -water dominated system.

Underground hot brines contain pressured water that "flashes" into steam at the earth's surface.

Water and steam from the Cerro Prieto system is reported to be as hot as 330 °C.

The Geological Society of America led a

November 1979 field trip to the Salton Trough, and reported that the Cerro Prieto Field completed its 75 -MW power plant in 1973, and increased production to 150 MW in April 1979

(12).

By November 1979, 65 deep geothermal wells were completed in the field.

Several geothermal anomalies which lack surface expression have been discovered in the Imperial

Valley and the Mexicali Valley.

By 1979, 63 geothermal production wells were drilled in the Imperial

Valley for a 10 -MW plant, and several additional power plants are planned.

These include Republic

Geothermal's 50 -MW dual -flash power plant at East Mesa, Southern California Edison's 10 -MW plant near

Brawley, Southern California Edison /Union Oil's 10 -MW plant and Southern California Edison's 55 -MW plant near Red Hill

Volcano at the Salton Sea Geothermal

Field, and Southern California Edison/

Chevron Resources' 50 -MW unit at the Heber Geothermal Field near El Centro.

According to the U.

S.

Geological

Survey, six identified geothermal fields in the Imperial

Valley with reservoir temperatures greater than 150 °C could produce a total of 6,800 MW for 30 years, or 225 MW /yr (5).

Imperial

Additionally, there are numerous smaller experimental geothermal plants in the and Mexicali Valleys.

Western Services,

Inc. estimates that the Imperial Valley could provide up to 10,000 MW of power over the next 30 years (16).

There are

350 °C -hot springs on the 2,650 -m deep sea floor on a mid -ocean ridge in a small region along the crest of the East Pacific Rise near the entrance to the Gulf of California (29).

79

Additionally, 315 °C -hot geysers have been found in petroleum -seeping mounds at 2 000 -m depths along transform faults offshore Baja California Sur in the Gulf (40).

Numerous indications of hydrothermal activity suggest that productive geothermal fields may be present beneath the Gulf.

Biologically Controlled Energy

Biomass energy is controlled by biology in the Gulf.

This is a renewable resource which is currently exclusively domestic.

1028 ergs (26).

The estimated total annual energy flux from marine biomass is about

Currently, the biomass energy source is merely a research topic, where conversion of fiber to energy is a promise.

Though forest and wood products are scarce, there is an abundance of natural salt -tolerant or halophytic plants which may be irrigated with sea water to produce a locally available, biomass energy source.

Cooperative research studies in this regard have been conducted by the Univegity of Arizona's Environmental

(Sonora) since 1978.

Research Laboratory and the Universidad de Sonora near Puerto Penasco

More recently, the University of Arizona's College of Agriculture and the

Office of Arid Lands Studies have entered this research area (33).

Mature Atriplex (salt bush) and Salicornia (pickleweed) contain about 35 and 20 percent of crude fiber, and about 35 and 40 percent ash, respectively (22).

Soaking the ground product in 10 volumes of fresh water for 16 hours can reduce the ash content in saltbush and pickleweed to about 15 and 7 percent, respectively, to make a more energy -rich product.

These leached plant products could provide a limited, near -site energy supplement.

There are arid -land plants, such as Simmondsia (jojoba) and Euphorbia (gopher plant), which have naturally high hydrocarbon contents (27).

Jojoba data are sparse, but gopher plant data from

California indicate production of

10 to 25 barrels of crude oil /ha /yr

(104 /ergs ha /yr).

Additionally, Salsola (common Russian thistle, or tumbleweed) have a high energy content and could yield about

3, 500 cal /g land (19).

or about 32 billion cal /ha /yr

(1015 ergs /ha /yr) from fertilized and irrigated

Unfortunately, jojoba, gopher and tumbleweed plants require fresh water.

Combined agricultural production and biomass energy conversion may be feasible in the Gulf if an agronomic crop, with high energy conversion, could be cultivated.

On the big island of Hawaii, for example, over 40 percent of all energy needs are met from biomass energy conversion of sugarcane wastes.

Additionally, marine biomass power could be developed in shallow water through eelgrasses and kelps which are efficient producers of organic material and are easily harvested (26).

Oceanographically Controlled Energy

Tidal, wave and hydrothermal energy are controlled by oceanography in the Gulf.

These energy sources are renewable and potentially exportable.

systems.

Isaacs and Schmitt (26)

These energy forms generally require no storage discussed the nature and distribution of non -petroleum power sources of the sea, including waves, tides, currents, salinity and temperature gradients, as well as submarine geothermal sources, salt domes, ice and other marine -associated concentrations.

Tidal resources.

Tidal energy uses the oscillatory flow of water in the filling and emptying of partially enclosed coastal energy may be basins during the semidiurnal partially converted into renewable tidal rise and fall of the tides (11).

This electric power by damming such basins to create a difference in water level between the ocean and the basin, and then using the water flow while the basin is filling or emptying to drive hydraulic turbines to propel electric generators.

The hydraulic head for power generation can generally be available for 6 to 12 hrs daily.

The estimated total annual

1025 ergs each (26).

energy flux from major ocean currents and feasible tidal power is

Globally, near -shore areas with a great tidal range and potential for tidal power development are widely distributed; they include the coasts of Alaska and

British Columbia, the

Gulf of California, the Bay of Biscay, the White Sea, the central

Indian Ocean, and the coasts of

Maine and eastern Canada.

Existing installations are in the French Rance River estuary (producing

240 MW) and at Kislaya Bay in the Soviet Union (producing 440 kW).

The energy, E, produced between high water and low water (10) amounts to:

E

= mgh

=

8 gpAs2 / T where m is the mass of water, q is the gravitational acceleration, h is the tidal range, p is the water density,

A is the cross -sectional area, s is the wave amplitude, and T is the tidal period.

The mean tidal range is 2s, and the water volume flowing through a hay during half a tidal period is

2sA.

Theoretical power output, TPO (kW), from a hydromechanical device can be calculated from the following equation (30):

Q (lps) x H (m)

Q (cfm) x H (ft)

O (cfs) x H (ft) _

TPO =

708

11.8

102

80

where Q is the flow of water through the perfect power generating system, and H is the hydraulic head.

If variable head drives the device, the energy produced is about 90 percent of what is calculated.

In practice, head losses from pipe flow and fittings must be subtracted from the hydraulic head, and the overall efficiency must be multiplied by the TPO to derive the operating power output.

Actual power output,

APO (kW), can be calculated from APO

=

OE x TPO, where OE is the overall efficiency of the system (usually 0.50 to 0.80).

The electrical output, EPO (kW), from a turbine can be calculated from the following equation (30):

EPO

D (ft) x C (cf) x N x R x F

708

D (m) x C (1) x N x R x F

102 where D is the diameter of the turbine, C is the working volumetric capacity of each cell, N is the number of cells in the turbine, R is the rotational speed in rpm, and F is the turbine efficiency

(usually 0.60 to 0.80).

Based on a review of published figures for one existing and six planned power stations (7, 11,

13 -15, 38), it appears that the tidal power plant with 1 -m tidal range and 15 000 -m barrage length produces about

1

000 -MW power output, or power output (MW) equals 15 times tidal range (m) times dam or barrage length (m).

The Gulf has good to high potential for tidal energy development.

Wave resources.

Wave energy uses the up and down motion of the waves to drive air turbines to propel electric alternators (38).

stages.

The estimated total

This renewable energy source is still in early experimental annual energy flux from waves is about 1027 ergs

(26).

Waves could produce about 50 kW per meter of wave, assuming 50 percent efficiency for generation and 50 percent efficiency for transmission losses (37).

About 1,000 km of devices could produce 12 kW in sites off the coast of the United Kingdom.

The Gulf has fair to good potential for wave energy development.

Hydrothermal resources.

the cycle.

Hydrothermal energy uses warm currents from tropical waters to heat a fluid, such as ammonia, and turn it into vapor which drives a turbine to produce electricity.

seawater from depths of about 900

Cooler m cools the vapor and condenses it to form water needed to repeat

Hydrothermal energy could theoretically be harvested by ocean thermal energy conversion

(OTEC) plants (6), where a 64 ° -F (36 ° -C) range of water temperature is available.

The Gulf has a high potential for hydrothermal energy development.

Technical Feasibility

The technical feasibility of an energy resource may improve with time due advances and economic demand.

to of technical

Climatic energy sources are currently an unproven technology with storage, transmission efficiency, electronic and structural problems.

Solar energy generally requires an energy storage system, and wind energy demands fatigueless metals or ceramics.

These sources are currently research areas with fair potential for modest -scale development in the Gulf.

proven technology with technical limits.

Geologic energy sources have a

Hydrocarbon energy has safety and air quality problems, and geothermal energy has turbine efficiency, structural and fatigue, and corrosion problems.

Offshore development has unique structural and corrosion problems.

These sources are currently on -line with high potential for large -scale commercial development in the Gulf.

Biological energy sources are an unproven technology riddled with biological uncertainties, corrosion and air quality problems.

sources are currently research topics with low potential

These for small -scale development in the Gulf.

Oceanographic energy sources have turbine and transmission efficiency, and corrosion problems.

Tidal energy has a proven technology, though most plants are research plants.

production are currently research projects.

Wave and hydrothermal energy

These sources have a high potential for moderate -scale development in the Gulf.

Environmental Impacts

The environmental impacts of energy exploration, development and transmission can be considered in terms of air, water, soil and biota.

Climatic energy has a low impact on air, water, soil and biota.

There is no air pollution.

Development would require consideration of drainage and erosion impacts.

Geologic energy has moderate, high, moderate and fair impact on air, water, soil and biota, respectively.

Development of geologic energy would require consideration of brine disposal, spills and water demand.

FERTIMEX is currently building a potassium chloride recovery unit for geothermal plants in Cerro Prieto, indicating that waste recovery is feasible.

on air, water, soil and biota, respectively.

Development would require consideration of saltwater agriculture, drainage, soil salinity and water demand.

Oceanographic energy has a low impact on air, water, soil and biota.

Biological energy has a fair, moderate, fair and small impact

There is no air pollution.

Development would benefit by water storage, which would reduce operating costs and prolong operating hours.

81

Any offshore and nearshore energy development to the Gulf must consider the impact of seismic activity.

The eastern Pacific Shelf off southern California near Baja has had 24 earthquakes in the past 60 years of a local magnitude 6 (Richter scale) or larger (23).

The Pacific and the Gulf coasts are subject to earthquakes, tsunamis seismic sea waves), and slumps and slides.

Mid- 1980's Production Costs

Assuming a 15 percent annual inflation, it will cost about $350 /kW and $2,000 /kW in capital for a natural gas /oil -fired steam plant and a nuclear power plant, respectively (38).

Currently designed and nearly completed coal -fired steam plants are costing about $800 /kW and $1,600 /kW, respectively in the Texas gulf coast.

The following costs are projected in the Gulf for comparative purposes only.

Climatic energy would cost about $40,000 to $50,000 /kW for solar (6) and wind forms, while geologic energy would cost about $350 to $3,500 /kW for hydrocarbon (38) and geothermal (6, 16) forms in the mid- 1980's.

Biological energy would cost more than $50,000 /kW.

Oceanographic energy would cost about $7,600, $35,000 and

$1,200 /kW for tidal

(8, 13 -15,

38), wave

(38) and hydrothermal

(6, 38).

These cost estimates could be reduced with technical solutions to engineering problems.

For example, turbine and metal fatigue problems caused by brine in geothermal power units has recently forced redesign for a second 10 -MW plant operated by Southern California Edison.

capital costs in the Imperial Valley to $3,000 /kW (16).

in future plants.

This has doubled

Technical solutions could reduce this cost

Energy Investment Strategies

41).

There are four general methods used for selecting alternative energy investment projects (31,

These include accounting (average rate of return, payback) and discounted cash flow (internal rate of return, net present value) methods.

Data are unavailable to allow comparison of investment strategies between climatic, geologic, biological and oceanographic energy.

In Mexico, the federal government determines and implements the country's energy policy through

Pemex (Petróleos Mexicanos) for hydrocarbons and the Comisi6n Federal del

Electricidad (CFE) for electric power at the operating level.

On March 18, 1938, Mexican President Lazaro Cárdenas nationalized the oil industry, and established Mexican control.

More recently, however, Brown & Root, a division of Halliburton, Inc., has become the prime contractor for Pemex, responsible for organizing the engineering, purchasing, building and managing of Mexico's major fields (18).

Mexico's energy program for the 1980's, announced in November 1981, is that export sales will be guided by the need to finance intrastructural improvements and to achieve national security goals

(3).

Mexico in the early 1980's plans to conduct exploratory drilling activities in only about 10 percent of the areas which are likely to contain hydrocarbons.

Acknowledgements

I thank the research libraries at Gulf Publishing (World Oil), PennWell Publishing (Oil

& Gas

Journal), the

Fondren Library at Rice University and the Science Library at the University of

Arizona, the Houston Public Library, the University of Houston Bookstore, and the Brown Book Shop,

Inc.

I also thank Georgia A. Henderson for editorial review, and Ella Cook and Sandy Jackson for manuscript preparation.

Dames & Moore supported the preparation of this work.

1.

Aramco World Magazine.

Sept. -Oct.

References Cited

1981.

Aramco World Magazine 32(5): 18 -29.

Saudi Arabia and solar energy a special section.

2.

Arbingast,

S.

A.

and others, eds.

1975.

Austin, Bureau of Business Research.

Atlas of Mexico, 2nd ed.

University of Texas at

3.

Baker, G. Mar.

1981.

Mexico's energy plan puts exports at

(3):109 -110, 114, 116, 118.

1.5 MMbopd in 80s.

World Oil

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Beal,

C.

H.

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C.

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and others.

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90 °C.

In:

Hydrothermal convection systems with reservoir temperatures

Assessment of the Geothermal Resources of the United States.

L. J. P. Muffler, ed.

U.

S. Geological Survey, Circular 790.

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Changing Times. Sept. 1979.

Eight ideas that promise more energy.

7.

Clark, W. 1987.

Energy for Survival.

Anchor, Garden City, N.

Y.

CT 33 (9):25 -28.

8.

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The Cousteau Almanac - An Inventory of Life on Our Water Planet.

day /Dolphin, Garden City, N.

Y.

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South America, Central America, the Caribbean, and Mexico.

American Association of Petroleum Geologists, Bulletin 65(10): 1940 -1995.

10.

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3rd ed.

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Y.

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The Energy Fact Book.

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Elders, W.

A., ed. 1979.

Guidebook: Geology and Geothermics of the Salton Trough, Field Trip

No. 7. Geological Society of America, 92nd Annual Meeting, San Diego.

13.

Electric World. May 1981.

Interest in small hydro is rising.

EW 195 (5): 23 -24.

14.

Engineering News Record. Oct. 29, 1981.

Tidal power test taps Fundy flow: Nova Scotia energy dreams come true.

ENR, p. 39 -40.

15.

16.

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Nov. 12, 1981.

Alaskan tidal power costly.

ENR, p. 40.

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Dec. 24, 1981.

Geothermal power boom awaits developer push.

ENR, p. 11.

17.

Encyclopedia Britannica. 1977.

Macropadia, 15th ed., Vol. 8.

18.

Forbes. Aug. 15, 1977.

Pemex to Brown A Root: Yankee, Come In.

Forbes 120(4):28.

19.

Foster, K.

E.

Dec.

1979.

Arid lands biomass production in Arizona.

Arizona Water Resources Project Information, Project Bulletin 22.

University of Arizona,

20.

21.

Goodrich Euzkadi. 1964.

Guzman, A.

B.

Aug. 24, 1981.

79(34):110 -126.

Atlas, Caminos de Mexico.

Galas de Mexico, S. A., Mexico.

Petroleum prospects in Mexico's Altar Desert.

Oil & Gas Journal

22.

Hodges,

C.

N.

and others. Dec. 1980.

against climate variability.

Seawater -based agriculture as a food production defense

University of Arizona, Environmental Research Laboratory.

23.

Howell, D. G., D.

S. McCulloch and J. G. Vedder. 1968.

General geology, petroleum appraisal, and nature of environmental hazards, eastern Pacific Shelf,

U. S. Geological Survey, Circular 786.

Latitude 28° to

38° North.

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25.

26.

International Petroleum Encyclopedia. 1979.

Petroleum Publishing, Tulsa, Okla.

.

1980.

PennWell Publishing, Tulsa, Okla.

Isaacs,

J.

D. and W.

207:265 -273.

R.

Schmitt. Jan.

18, 1980.

Ocean energy: forms and prospects.

Science

27.

28.

Johnson, J. D. and C. W. Hinman. May 1980.

Oils and rubber from arid land plants.

Science 208:

460 -464.

Kennett, J. P. 1982.

Marine Geology.

Prentice -Hall, Englewood Cliffs, N. J.

29.

Macdonald,

K.

and B.

P.

Luyendyk. May 1981.

American 244(5):100 -116.

The crest of the East Pacific Rise.

Scientific

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McGuigan, D. 1978.

Harnessing Water Power from Home Energy.

Garden Way, Charlotte, Vt.

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32.

Megateli, A. 1980.

Investment Policies of National Oil Companies.

Praeger, N.

Y.

Mina, F.

1951.

America

-

Mexico

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A Symposium.

Lower California.

In: Possible Future Petroleum Provinces of North

M.

W.

Ball

Geologists, Tulsa, Okla., p. 242 -244.

and others, eds.

American Association of Petroleum

83

33.

Neary, J. June 1981.

Pickleweed, Palmer's Grass and Saftwort.

Science 81 2(5):38 -43.

34.

Oil

& Gas Journal. Nov. 21, 1977.

Geologists studying hot -brine Cerro Prieto area in Mexico.

OGJ 75(48):61.

35.

36.

.

.

May 11, 1981.

June 8, 1981.

Newsletter.

OGJ 79(19).

Pemex offshore strike sparks California leasing.

OGJ 79(23):

62.

37.

Ross, D. June 9, 1978.

Will Britain miss out on wave power?

New Statesman 95:762 -763.

38.

Savage, J. A.,

E.

Power Sources.

E. Weynard and W. G. Wyatt. Jan. 1975.

Potential of Tidal and Gulf Stream

The State of Texas, Governor's Energy Advisory Council, Project

N /T -9.

39.

Steinbeck,

J.

and

E.

F.

Ricketts.

1941.

Research.

APPEL, Mamoboneck, N.

Y.

Sea of Cortez:

A Leisurely Journal of Travel and

40.

Sullivan, W. Jan. 29, 1982.

41.

Van Horne,

J.

C.

1971.

Cliffs, N. J.

Divers find natural

"oil refineries ".

The New York Times, p. Al2.

Financial Management and Policy, 2nd ed.

Prentice -Hall, Englewood

42.

43.

World Oil. Aug.

15,

1981.

North America: U.

S.

activity is unprecedented.

WO 193(3):57 -.

.

Feb. 15, 1982.

World drilling moves into new countries.

WO 194(3):213.

Appendix

Energy or Work

One British thermal unit (BTU1 equals 1.0548 x 1010 ergs or dyne -centimeters (dyne -cm), 777.97

foot -pounds (ft -lb), 3.9292

x

10-4 horse power -hour

(hp -hr),

1054.8 joules

(J) or newton -meters

(N -m), 0.25198 kilogram -calorie (kg -cal) or 2.930 x 10-4 kilowatt -hour (kW -hr).

Power

One horse power (hp) equals 42.418 British thermal units per minute (Btu /min), 7.4560 x 100 ergs per second (erg /sec) or dyne -centimeters per second (dyne -cm /sec), 550 foot -pounds per second (ft -lb/ sec), 10.688 kilogram -calories per minute (kg -cal /min), 0.74570 kilowatt (kW), or 745.70 watts (W) or joules per second (J /sec).

84

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85

Nonstructural Flood Control Evaluation for Tucson, Arizona

Kebba Buckley

Contractor to U.S. Army Corps of Engineers, Tucson, AZ

Abstract

Nonstructural and nontraditional flood control measures are required to be included in any Corps of

Engineers Urban Study.

However, Corps policy and practice are not specific as to evaluative techniques.

In Tucson, a preliminary study of nonstructural and nontraditional measures was conducted for several dozen sites along eight watercourses.

The evaluation showed that such measures appear feasible for about one -third of the sites, and further study of these sites is warranted.

When a more complete data base is available for these watercourses, more detailed evaluations may be undertaken.

87

IMPACTS OF THE ARIZONA GROUNDWATER ACT ON TUCSON WATER

Stephen E. Davis

Tucson Water

P.O. Box 27210

Tucson, Arizona 85726

Abstract

The 1980 Arizona Groundwater Management Act is the product of decades of court decisions and years of work and negotiation by representatives of the

State's major water users, members of the State

Legislature, and the Governor.

through the establishment

The Act intends to conserve and manage the State's groundwater resources of the Arizona Department of Water Resources (DWR).

The Tucson Active

Management Area (TAMA) is one of four geographical areas specifically designated within the legislation.

There is established a Tucson office, locally staffed and administered by the DWR.

The legislated goal for the TAMA is to balance groundwater withdrawal with dependable supplies by the year 2025.

A series of time -specific management plans will incorporate conservation, supply augmentation, and farmland retirement to fulfill the 2025 goal.

This paper discusses the existing and projected TAMA water supply /demand imbalance assuming no groundwater management and potential impacts of the Act on management and customers of the Tucson Water

Utility.

Specific positive impacts include increased public awareness, regional metered water use information, and reduction in groundwater overdraft.

Specific negative impacts include more regulation, higher customer water rates, reduced water quality, and potential growth limitations.

Introduction

An appreciation of the history of Arizona's groundwater law is pertinent to impacts of the 1980 Groundwater Management Act on the Tucson Water

Utility.

the discussion of the

Increasing withdrawals of groundwater by agricultural users in the past resulted in a marked increase in groundwater overdraft in specific areas of support for the State.

During the 1940's the Central Arizona the Department of the Interior

Project unless something was done threatened to withhold locally to limit the unrestricted pumping of groundwater.

The State Legislature responded with the

1948 Groundwater Code prohibiting expansion of agricultural acreage irrigated with groundwater in designated "critical groundwater areas."

Three critical groundwater areas were established in the Tucson area, namely the Avra -Marana, Sahuarita-

Continental, and Tucson critical groundwater areas.

The 1948

Act was only a starting point for controlling groundwater overdraft, and a multitude of water -related court decisions confirmed the Code's inadequacy.

In 1953, the Arizona Supreme Court reversed its

Court ruled that the doctrine of reasonable beneficial earlier decision in Bristor vs.

Cheatham.

The use applied with the constraint that groundwater could not be transported off the Land from which it was pumped if adjacent transportation.

During the

1950's and

1960's the City of pumpers were damaged by the

Tucson experienced remarkable growth in population and corresponding demand for groundwater.

Foreseeing the potential problems associated with water table declines in the Tucson metropolitan area, the

City applied for and received a federal grant for $1.4

million in 1967 from the Department of Housing and Urban Development to construct a new wellfield and importation pipeline to bring in water from the Avra Valley west of Tucson.

In 1969, the

Arizona Supreme Court ruled in Jarvis I that the City was illegally transporting groundwater from one critical groundwater area to another, and the wellfield was shut down.

The City appealed, and in 1970 the Supreme Court decided in Jarvis II that if the City purchased and retired irrigated farmland in the

Avra -Marana Critical Groundwater Area it could transport into the City that amount of water historically used for irrigation.

In 1971 the City purchased the first

Valley.

The Hill

Farm, adjacent to Ryan of over 20 parcels it

Field, was purchased for has retired from farming

$500 an acre.

To in the Avra date, Tucson has purchased approximately 12,000 acres of Land previously irrigated in Avra Valley at an average price of

$800 per acre.

In Jarvis III, the Arizona Supreme transport the amount of water consumptively used on

Court ruled in 1976 that the City could only retired farmland.

This amount was determined to be slightly more than half of the water previously pumped for agricultural use.

In the FICO suit (1976) the Farmers Investment Company asked that the mining companies and the City of Tucson be restrained from pumping and transporting water out of the

Sahuarita- Continental Critical Groundwater Area.

The Supreme

Court enjoined the transportation of groundwater by the mines to points outside the critical groundwater

89

area, but did not enjoin the City.

The threat of injunction against the City and the economic impacts upon the prompted the mines south of Tucson

Legislature in 1977 to enact Senate Bill 1391.

This Bill was an interim package which provided the following:

1.

2.

3.

4.

A mechanism for transferring groundwater between critical groundwater areas.

The right of an injured party to collect damages.

The prohibition of injunctions against groundwater pumping by the City and mines.

The establishment of a

Groundwater

Management Study Commission reformation of the State's groundwater law.

and a timetable for the

After many drafts of a proposed new code by the Commission, review and approval by the Secretary of

Interior as a condition of

Central Arizona Project completion and finalized allocations, and participation by the Governor in writing the final version, the Legislature adopted the 1980 Groundwater

Management Act.

Major Elements of the 1980 Groundwater Management Act

The legislative intent of the 1980

Groundwater Management Act

Policy, Section

45 -401.

A portion of that statement is stated is worth quoting herein.

in the Declaration of

"It is, therefore, declared to be the public policy of this state that in the interest of protecting and stabilizing the general economy and welfare of this state and its citizens it allocate the use of groundwater resources of the state is necessary to conserve, protect, and and to provide a framework for the comprehensive management and regulation of the withdrawal, transportation, use, conservation, and conveyance of rights to use the groundwater in this state."

Primary elements of the Act affecting municipalities in general are discussed in this paper.

More comprehensive summaries have been recently written by Pontius (1980) and Johnson (1981).

A key element of the Act was the establishment of a strong state agency called the Department of

Water Resources with jurisdiction over the management of groundwater, surface water rights, dam safety, flood control, interstate streams, the Central Arizona Project, and, to a limited extent, water quality.

The Director is given flexibility and broad powers to organize the Department and administer all laws relating to groundwater in the State.

Four Active Management Areas

(AMA's) were created by statute including the Tucson AMA, Phoenix AMA, Prescott AMA, and

Pinal AMA.

These initial AMA's account for 69 percent of the groundwater overdraft in Arizona and contain over 80 percent of the State's population.

Local AMA Directors have been selected, and each is advised by a five- member Groundwater Users' Advisory

Council appointed by the Governor representing major water -using groups within the AMA.

The goal of the Tucson AMA is to attain safe yield (the long -term balance of groundwater withdrawals and natural and artificial recharge) by January 1, 2025.

Mandatory conservation, supply augmentation, and purchase and retirement of agricultural Land are the three principal tools through which the Director must attain safe yield.

These tools will be applied in varying degrees over the 45 year timeframe for achieving safe yield in five successive management periods.

An initial management plan for the Tucson AMA is required under the Act by January 1, 1983, but staffing and data limitations will most likely that "reductions delay preparation by one year.

in per capita use and such

During each of the management periods other conservation measures as the Act states may be appropriate for individual users" will be required of all municipal water users.

During the second management period supply augmentation including artificial recharge is to be implemented by the Director.

If these management tools are not successful by 2010, the end of the third management period, the Director must begin a program of purchase and retirement of irrigated land within the AMA.

Within an Active Management Area all existing legal uses of groundwater are "grandfathered" and may continue subject to conservation requirements imposed by successive management plans.

The right to continue pumping groundwater is called an Irrigation Grandfathered

Right, a Type 1 Non -Irrigation

Grandfathered Right, or a Type 2 Non -Irrigation Grandfathered Right.

Rights will be issued by the

DWR indicating the annual amount of

Certificates of Grandfathered water to be withdrawn, location of withdrawal, and location of use.

Groundwater uses specifically recognized as legal uses under the Act.

authorized under Certificates

A municipality is permitted of Exemption to increase are its pumping and freely transport water within its service area defined as that area actually being served water for non -irrigation purposes.

A city may not drill new wells nor increase its groundwater pumping outside its service area unless Grandfathered Rights are acquired.

A city may extend its service area to serve new development, thereby extending the area from which groundwater may be pumped.

Other groundwater management tools available to the Department of Water Resources include the issuance of Certificates of Assured Water Supply, well construction and spacing regulations, metering of pumpage, groundwater transportation regulation, groundwater provisions.

withdrawal fees, and specific enforcement

Inside an AMA a Certificate of Assured Water

Supply is required from the Director prior to sale of subdivided or unsubdivided land.

An assured water supply means that "sufficient groundwater or surface water of adequate quality will be continuously available to satisfy the water needs of the proposed use for at least one hundred years, the projected water use is consistent with the management plan and achievement of the management goal for the active management area, and the financial capability

90

has been demonstrated to construct the delivery system and any supply of water available for the proposed use." treatment works necessary to make the

The service area of the City of Tucson has been deemed to have an assured water supply on the basis of its filed letter of intent to purchase CAP water.

Tucson Active Management Area Baseline Data

Preliminary to discussion of specific impacts of the Act on Tucson Water, it understand the regional water supply- demand environment of which Tucson is a part.

is salient to

The Tucson Active

Management Area contains a wide diversity of water -using economies, each solely dependent upon groundwater for its water needs.

Major water pumpers include the City of Tucson, four mining companies south of the City, Farmers Investment Company

(FICO), Cortaro -Marana Irrigation District,

Irrigation District, private water companies, and private well owners.

Avra Valley

Staff of the Tucson Active

Management Area have recently prepared a baseline estimate and projection of existing and anticipated water uses and supplies from 1980 through 2025.

That data is indicates the basic problem of the Tucson AMA: summarized in

Table 1 which readily groundwater mining.

Much of the tabulated data was provided by individual water users.

The baseline projections for 2000 and 2025 assume no management of groundwater on the part of the Tucson AMA, but do incorporate specific assumptions with regard to population projections, irrigated acreage, incidental recharge, Central Arizona Project water availability and usage, and wastewater effluent reuse.

These assumptions cannot be realized, however, without management of groundwater inasmuch as the management provides the incentive to use Central

Arizona Project water and wastewater effluent.

The population projections used as the basis for predicting municipal water use are 1979 Arizona

Department of Economic Security figures and have recently been updated and increased by that agency for

Pima County.

Larger population projections result in larger municipal water of the potential overdraft (groundwater mining) problem.

use and an understatement

Tucson Water is assumed to serve 80 percent of the Tucson Active Management Area, and a per capita water use factor of 160 gallons derive municipal water use.

per day is used to

Industrial uses include golf courses, power plants, parks, cemeteries, hospitals, schools, sand and gravel industries, dairies,

Davis -Monthan

AFB, and

Arizona.

Water use by copper mines in 1980 was established using data provided in the University of applications for

Certificates of Exemption.

Agricultural use is the sum of non -Indian water application at 4.45 acre feet per acre and Indian application at 5.4 acre -feet per acre.

Municipal incidental recharge is assumed to be 70 percent of the wastewater effluent discharged into the Santa Cruz riverbed.

Recharge from mining is assumed to be 20 percent of pumpage except where interceptor wells are operated.

applied.

Agricultural recharge is assumed to be 20 percent of the total water

Central Arizona Project water is the total of DWR staff allocations to municipal, mining, and

Indian users based upon a statewide availability of

640,000 acre -feet per year for municipal and industrial users and

160,000 acre -feet per year for Indian users.

wastewater was used

In

1980, 3,400 acre -feet by golf courses, and 5,200 acre -feet was used by agriculture.

In of

1980, approximately 395,000 acre -feet of groundwater and wastewater effluent was used in the Upper Santa Cruz and Avra Valley subbasins of the Tucson AMA.

Analysis of Table 1 the total 1980 water use was agricultural, 23.5 percent data indicates that 53.7 percent of was municipal, 15.2 percent was mining, and 7.6

percent was industrial.

Groundwater pumpage exceeds natural recharge by

Tucson AMA.

Consumptive a factor of five to one in the use of water exceeds natural recharge by a factor of four to one.

The large imbalance between groundwater supply and demand has resulted in water table declines of over 175 feet in the Avra

Valley since 1952 and since 1947.

nearly the same amount along the

Santa Cruz riverbed south of Tucson

Four major impacts of groundwater table declines are increased cost for pumping, decreased well capacity due to higher consolidation of aquifer sands and gravels, reduced water quality, and potential

Land surface subsidence.

For these reasons it is prudent that the Tucson AMA develop a workable plan to reduce overdraft.

Under the no groundwater management scenario prepared by the Tucson AMA staff, overdraft is projected to decline from 238,000 acre -feet in

1980 to 87,000 acre -feet in 2025.

Key assumptions include full utilization of wastewater effluent agricultural land to urban uses, new irrigation of 5,000 by 1990, some gradual conversion of private acres of San Xavier and 2,000 acres of Schuk

Toak Papago Indian

Land beginning 1990, and full requesting entities in the amount allocated by DWR.

utilization of

The

Central Arizona Project water no management scenario indicated in Table 1 by is not the worst case, however, in that projected water uses may be understated, and water supplies utilized from surface sources may be overstated.

Tucson AMA staff are preparing additional no management" scenarios which will indicate the full range of overdraft possibilities given other assumptions about water uses and supplies.

Given the severity of the impacts of overdraft the Tucson

Groundwater Users Advisory Council is evaluating the possibility and impacts of moving forward the safe yield date from 2025 to 2005.

Beneficial Impacts of the Groundwater Act

Tucson Water is a municipally owned and operated water people through 126,000 active metered services.

utility providing domestic water service both inside and outside the corporate limits of Tucson.

square miles having an elevation difference of over

Water is provided to a service area of over 300

1,500 feet.

Presently, Tucson Water serves 440,000

This represents

80 percent of the Pima County

91

population and over 85 percent of the metropolitan Tucson population.

In 1980 -81, Tucson Water actively pumped 189 wells from four wellfields serving the central metropolitan system and 43 wells serving fifteen isolated systems.

Sixty percent of the 78,000 acre -feet pumped by Tucson Water in 1980 -81 was from the central, interior wellfield and seventeen percent was from the Avra Valley.

The remainder was pumped from the Southside and Santa Cruz wellfields near the riverbed south of Tucson.

Tucson Water uses population projections officially adopted by the Arizona Department of Economic

Security and the Pima Association of Governments for Pima County.

The December 1981 figures indicate a

County population of 536,100 in 1980 and a

2035 projection of 1,807,400.

The associated Tucson Water population and water use projections are shown in

Table 2.

Water use for municipal purposes is projected to more than quadruple from an average of

68.6 million gallons per day in 1980 to 231.3

million gallons per day in 2035 based upon an assumed average daily per capita use of 160 gallons, the current use by Tucson Water customers.

To meet the projected water demands of existing and future customers, Tucson Water will have three primary supplies: groundwater, Central Arizona Project water, and wastewater effluent.

Each of these sources is impacted by the passage of the 1980 Groundwater Management

Act.

Our sole potable source currently, groundwater, will be subjected to increasingly more stringent requirements for conservation, although our dependence upon it will increase until delivery of Central Arizona Project water.

Figure 1 is a graph of projected annual water need assuming 160 gallons per person per day and the expected combination of groundwater and CAP water required to meet that need.

The graph indicates that, although a reduction in municipal groundwater pumpage occurs upon acceptance of CAP water, the growth in demand and limitation of Central Arizona Project water allocation to

Tucson by the Department of Water

Resources (151,000 acre -feet in 2034) will require a gradual increase in groundwater pumping by the City to a level in 2034 equal to the pre -CAP pumping level.

Municipal water conservation discussed in the following section will impact the demand for groundwater, but previous successes of the Utility will limit its effectiveness.

The importation of Central Arizona Project water to the Tucson AMA and the use of same by Tucson

Water has both beneficial and adverse impacts.

The immediate positive effect of delivery (assumed to be about 1990) will be a one -for -one reduction in groundwater pumping, thus furthering the goal of groundwater preservation.

As Figure 1 indicates, Tucson Water expects to accept and treat 30,000 acre feet in the first year of delivery.

While this amount will provide only thirty percent of our total need in 1990, Tucson Water management will develop expertise in operating the area's first municipal water treatment plant, and customers won't be shocked with a major water quality change through increased total dissolved solids.

By 2035, sixty -two percent of Tucson Water's anticipated need will be met by Central Arizona Project water.

Since the Act's goal is conservation of groundwater reuse of its municipal wastewater effluent.

In response pumping, Tucson Water is induced to maximize to a perceived void, the Tucson Water Effluent

Reuse Plan (1982) was prepared in draft.

This document primarily addresses reuse in the long -term incorporating the Department of Water Resources assumption that

Pima County mines will ultimately use a blend of fifty percent effluent and fifty percent CAP water and that 28,200 acre -feet of effluent per year will be provided to the Papago Indian Tribe in accordance with the Southern Arizona Water Rights

Settlement Act of 1982.

Additionally, effluent delivery systems were identified and cost- estimated from both the Ina Road and Roger Road Wastewater Treatment Plants to serve existing and projected golf courses and cemeteries.

Subsequent to report preparation, proposed contracts to purchase effluent for agricultural use downstream of the Ina Road plant were submitted to the

City.

The Tucson Mayor and

Council referred the contracts and draft effluent reuse report to the Tucson

Citizens' Water Advisory

Committee for their review and policy recommendation.

The Committee initially evaluated the total spectrum of potential effluent users over time and, with Tucson Water staff, developed delivery scenarios indicated in Figure 2.

Near -term users include downstream agriculture and metropolitan Tucson golf courses.

Indian

Reservation and a

Santa Cruz River recharge system.

Mid -term users

Long -term include the users require the

San Xavier highest expenditure of funds for delivery systems and pumping costs and include Pima

County mines south of

Tucson.

The Committee has recently restricted its effluent reuse policy considerations to the near -term on the basis of

Irrigation District.

proposals by BIN farms, Incorporated in the Avra

Valley and the Cortaro -Marana

Agricultural users can blend the secondary- treated effluent with groundwater to meet quality standards adopted by the Arizona Department of Health Services.

The addition of a properly- designed filtration plant downstream of the existing secondary waste treatment process will permit the use of effluent on parks and playgrounds fence golf courses.

where children play and preclude the requirement to

Tucson Water is presently evaluating potential users of advanced waste treatment effluent for inclusion in a second draft of the Tucson Water Effluent Reuse

Plan.

In conjunction with the Pima County Wastewater Management Department, Tucson Water staff is evaluating the economics of constructing subregional waste treatment facilities closer to potential effluent users.

The passage of the Act has provided the necessary impetus for groundwater users to foresee the value of converting to wastewater effluent as a reliable water resource.

Effluent could prove to be very economical for a variety of uses in light of the projected costs of Central Arizona Project water and limits imposed on groundwater pumping.

The marketability of effluent by Tucson Water has been hindered in the past by the lack of adequate groundwater regulation and restriction.

The new law has prompted increased awareness in the need to maximize use of wastewater effluent and has encouraged the

92

City to adopt generalized policies by which proposed contracts can be evaluated.

Another positive impact of the Act on Tucson Water will be improved from water rights determinations, well registration, and metering of regional data bases resulting groundwater pumpage.

Heretofore, the Tucson Water Department has been the Leader in basinwide groundwater management and associated data collection activities.

The state has now assumed this role through the provisions of the new law.

The gradual reduction in overdraft required by forthcoming

Tucson AMA groundwater management plans will mitigate costly effects of water table declines, directly affecting the longevity and capability of

Tucson's wells.

The establishment of the local Tucson AMA office and the employment of competent staff has already provided a renewed public awareness of the groundwater management problem, the importance of water conservation, the need for Central Arizona Project water, and the necessity to use wastewater effluent.

Adverse Impacts of the Groundwater Act

Since the primary tool of the Act is mandatory conservation, Tucson is concerned about the degree to which Tucson Water customers can further reduce water usage beyond that which has already been attained (Davis, 1978).

The implementation of an increasing block cost -of- service water rate structure, a winter- summer rate differential, the

"Beat- the -Peak "summer demand management program, and public education through the news media have collectively reduced the Tucson Water per capita use from 205 gallons per day in 1973 -74 to 159 gallons per day in 1980 -81.

The lowest use was obtained in 1978 -79 when Tucson Water's daily per capita use was 147 gallons.

has assumed 140 gallons per

In planning for future water facilities staff person per day using 50 -year sizing criteria.

Since the per capita wastewater flow has stabilized at 90 gallons per day, this lower figure would appear to be the minimum obtainable assuming that all outdoor water uses were eliminated.

Potential tools to effectuate additional municipal groundwater conservation include higher water rates, plumbing code regulations,

Land use /zoning restrictions on large water uses, and mandated effluent

Forthcoming objectives in groundwater management plans will dictate the timing reuse where practical.

and extent of municipal conservation.

A potential major impact adversely affecting the Tucson Water Utility is the requirement to accept and treat more

Central Arizona Project water than is currently planned for initial years of delivery.

Restrictions placed upon municipal groundwater pumping could force the City into this resource usage mode and accelerate those impacts of Tucson's source transition discussed previously by McLean and Davis

(1981).

The most significant impacts include capital repayment and operation and maintenance costs assessed by the Central Arizona Water Conservation District (collectively estimated to be $85.00 per acre -foot for municipal water), construction and operation costs associated with plant, capital costs associated with a CAP water treatment rebuilding the Tucson Water transmission system to distribute a single, large source of water in conjunction with the well supply points, and water quality degradation associated with increased total dissolved solids, hardness, and chlorination.

Economic impacts of using

Central Arizona Project water in the municipal system are already projected to be significant in terms of increased water rates and assessment of water development fees to newly -developing areas.

Increased

CAP use will result in even higher rates and considerable water quality degradation.

Additional cost impacts of the Act include the assessment of groundwater withdrawal fees by the DWR and fees for grandfathered rights applications and well registration.

Withdrawal fees consist of three components: not more than one dollar per acre -foot pumped for administrative costs, not more than two dollars per acre -foot for water supply augmentation (beginning no sooner than 1984), and not more than two dollars per acre -foot for purchase and permanent retirement of irrigated land beginning no sooner than 2006.

The Tucson Water Department has paid $20.00 each for 248 grandfathered rights applications and $10.00 each for 489 well registration applications.

Regulatory impacts include the requirement to file annual pumpage reports, adherence to well construction standards, the requirement to obtain new well drilling permits, and licensing of well drillers.

The ultimate impact of the Groundwater Management Act on Tucson Water will be limitation of growth.

For some this result is beneficial rather than adverse.

This issue is discussed in more detail by

McLean (1982).

The total population which can be supported by the projected potable water sources depends upon the quantities ultimately available on a long -term reliable basis and the per capita water use.

If the combination of Central Arizona Project water and groundwater available to the Tucson area is ultimately

200,000 acre -feet per year, the amount of people which can be supported is 1,785,000 assuming 100 gallons per person per day average water use and 1,116,000 assuming 160 gallons per person per day.

Both of these values are lower than the recently- adopted 2035 projection of 1,807,400 for Pima

County.

The degree to which Tucson area growth will be limited by the lack of water will depend upon the effectiveness of the successive Tucson AMA groundwater management plan conservation amount of reliable Central Arizona Project water available which legally can be pumped by municipal users.

programs, the to the area, and the amount of groundwater

A growth- related issue is the determination of Tucson's assured water supply service area via regulations to be promulgated provision that Central by the DWR.

Concepts recently distributed by the DWR include the

Arizona Project allocations for 2034 would determine the extent of the assured water supply service area in which developers would not be required to obtain a Certificate of Assured

Water Supply if they received water from Tucson.

This projected boundary is shown in Figure 3 along

93

with the existing corporate limits and the area actually being served water by the Utility in 1980.

Impacts of this proposal are difficult to predetermine in that a number of questions still remain with respect to service area extensions and well drilling.

The existence of discontiguous, isolated systems both within and without the projected water supply boundary complicate any assessment at this time.

Conclusion

While the overall intent of the 1980 Groundwater Management Act is clear with respect to safe yield within the Tucson Active Management Area, more definitive impacts of the Act on Tucson Water will depend upon specific groundwater management plans to be promulgated in the future.

This paper has attempted to assess the major management and potential rate -payers.

impacts that will both benefit and adversely affect the Tucson

Water

The implementation of the Act is in its infancy stage, and only through better definition of time -specific municipal conservation goals and development of municipal service area regulations can a more thorough assessment be accomplished.

Tucson Water is highly supportive of groundwater management and will continue to coordinate with the Tucson Active Management Area and the

Department of Water Resources to assure customers of the most reliable, cost- effective water service to meet domestic needs.

References Cited

Pontius, Dale E., "Groundwater Management in Arizona:

A New Set of Rules," Arizona Bar Journal, October

1980.

Johnson, James

W., "Summary of the 1980 Arizona Groundwater Management Act,"

State Bar of Arizona,

Continuing Legal Education paper, 1981.

Tucson Water, "Tucson Water Effluent Reuse Plan (draft)," January 1982.

Davis, Stephen E., "Tucson's Tools for Demand Management,"

Hydrology and Water Resources in Arizona and the Southwest, Volume 8, pp. 9 -15, 1978.

McLean, Thomas M. and Stephen E.

Davis, "The Alternatives and

Impacts Associated With a Future Water

Source Transition for Tucson Water," Hydrology and Water Resources in Arizona and the Southwest,

Volume 11, 1981.

McLean, Thomas M., "Water Resources as a Limiting

Factor to Tucson's Growth," Hydrology and Water

Resources in Arizona and the Southwest, Volume 12, 1982.

94

POPULATION

IRRIGATED ACREAGE

TOTAL WATER USE (Acre -Feet)

Municipal

Industrial

Mining

Agricultural

TOTAL

CONSUMPTIVE USE

Municipal

Industrial

Mining

Agricultural

TOTAL

INCIDENTIAL RECHARGE

Municipal

Industrial

Mining

Agricultural

TOTAL

POTENTIAL WATER SUPPLIES

Central Arizona Project

Reused Wastewater

Natural Recharge

Incidental Recharge

TOTAL

OVERDRAFT (MINED GROUNDWATER)

1980

518,200

47,300

93,000

30,000

60,000

212,000

395,000

60,000

30,000

53,000

170,000

313,000

24,000

7,000

0

42,000

73,000

0

9,000

75,000

73,000

157,000

238,000

TABLE

1

TUCSON ACTIVE MANAGEMENT AREA

WATER USES AND POTENTIAL SUPPLIES

2000

828,500

43,000

149,000

53,000

69,000

198,000

469,000

78,000

53,000

61,000

158,000

350,000

0

0

8,000

40,000

48,000

134,000

71,000

75,000

48,000

328,000

141,000

From the Arizona Department of Water Resources Tucson Active Management Area Staff

2025

1,225,200

31,500

220,000

83,000

69,000

147,000

519,000

115,000

83,000

61,000

118,000

377,000

0

0

8,000

29,000

37,000

215,000

105,000

75,000

37,000

432,000

87,000

95

Year

1980

1985

1990

1995

2000

2005

2025

2035

TABLE 2

TUCSON WATER POPULATION AND WATER USE PROTECTIONS

Pima Countyl

Population

536,100

620,000

710,100

810,700

921,900

1,048,400

1,554,400

1,807,400

Tucson Water

Service Population2

428,880

496,000

568,080

648,560

737,520

838,720

1,243,520

1,445,920

Water Use (MGD)3

68.6

79.4

90.9

103.8

118.0

134.2

199.0

231.3

1From Arizona Department of Economic Security, December 1981.

2Pina County population times eighty percent.

3Tucson Water service population times 160 gallons per person per day.

300,000

PROJECTED TUCSON WATER NEEDS AND SUPPLIES

PER CAPITA USE= 160 GALLONS /DAY

260,000

200,000

160,000

100,000

0-

GROUNDWATER

50,000

CENTRAL ARIZONA PROJECT WATER

o

1980 1986 1990 1996 2000 2005 2010

YEAR

FIGURE 1

2015 2020 2025 2030 2035

96

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97

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CITY V TUCSON

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TUCSON WATER

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WATERMAIN SERVICE AREA

98

WATER RESOURCES - THE PRIMARY FACTOR IN TUCSON'S FUTURE GROWTH

Thomas M. McLean, P.E.

Tucson Water

P.O. Box 27210

Tucson, Arizona 85726

Abstract

The community of Tucson faces a tremendous future challenge regarding the management of its local water resources.

With the advent of the new Groundwater Code and a plan to balance the basin by the year 2025, it is impossible to discuss the growth of the metropolitan area without first questioning the availability of adequate water resources.

community expansion will be measured.

In Tucson, water will soon become the yardstick by which

The Tucson Water

Utility plays a significant role in the management of the local water resource.

Although there is currently complete reliance on groundwater, Tucson has received a tentative allocation of Colorado River water by means of the Central

Arizona Project to supplement the groundwater supply in the future.

In addition, the reuse of wastewater effluent and further conservation efforts must be planned in order to accommodate growth.

The key ingredient to regional resource management, however, involves the cooperation that must exist among the major water -using entities

Water, the mines, farmers, private water companies, and private well owners.

of the area: Tucson

This paper addresses the potential favorable and unfavorable impacts of limited water resources on future growth with respect to these concerns.

Introduction

The metropolitan community of Tucson, situated in eastern Pima

County (see Figure

1), is experiencing growing pains of a slightly different nature than one would normally expect.

These pains come from the realizations that future growth carries with it a high price tag and that the major water using entities coming years.

of the region look forward to some difficult water resource -related decisions in the

A brief overview of the current water supply situation in eastern Pima County is appropriate at this point.

The Tucson Water Utility is the major in the metropolitan area of purveyor of water for municipal and industrial users

Tucson, but it is only one of many local water -using entities all of which subsist entirely on groundwater for their source of supply.

the near vicinity;

There are four copper mining companies in several agricultural interests such as the Cortaro -Marana Irrigation District, the

Avra Valley Irrigation District and the Farmers Investment Company; a number of private water companies; and various private well owners.

Agricultural interests utilize the largest amount consumptively followed by the mines and then the City Water Utility (see Figure 2).

Pumpage of water in this area is estimated to exceed natural recharge by a factor of approximately five to one, and, as a result, there exists a large imbalance between groundwater supply and demand which has resulted in long -term declines in local groundwater levels.

Projected Growth of the Tucson Metropolitan Area

The Tucson Water Utility presently provides service to approximately 450,000 people through 130,000 service connections.

As the major metropolitan area water utility, Tucson Water's interaction with regional planning efforts can and does provide an important element in the process of formulating projected urban growth patterns.

The Water Utility is represented on an intergovernmental planning team along with other governmental agencies and utilities.

This group coordinates the expertise which contributes to the process of developing regional land use plans.

necessary technical

Additionally, local governmental agencies (including Tucson Water) play a significant role in outlining the State

Arizona's regional population projections administered by the Department of Economic Security.

of

A great deal of development pressure exists in the

Tucson vicinity.

peripheral areas of the community in search of large portions of undeveloped

It land.

is pushing to the

Urban growth, and, therefore, intensive southwest and southeast

Land use planning is currently focused on three major regions: the northwest,

(see Figure 3).

Expansion to these areas must be accompanied by a number of basic support services, and never before has the availability of water supply been such an integral

99

factor in the decision- making process as it is today.

Evidence of this situation is demonstrated by the fact that coordination with land use planning efforts has resulted in the establishment of area -specific water plans (McLean, 1980).

These water plans are aimed directly at resource management, but more essentially provide technical and financial solutions to the problem of water delivery to specific areas of the community.

The water plans address the need for short and long -term water supply concepts which provide an overview for future residential and associated water system expansion.

A financial mechanism is also established in an effort to provide funds growth in that particular area as it occurs.

for the capital improvements required to support

Recently, land use plans for new major urban areas in the southeast and metropolitan area have been under consideration for adoption by the northwest portions of the local governing body.

It is apparent that there exists political indecisiveness regarding proposed land long periods of deliberation required before the plan use densities due to the is adopted.

These delays appear to reflect the difficulty with which officials must decide regarding the location and extent of urban expansion and the capability of supporting such growth with the available and projected services.

The propensity for growth in the

Tucson area is not only displayed by the activity of Land use planning, but is also reflected in the statewide population projections produced by the Arizona

Department of Economic Security (DES).

In 1979, the DES projected that Pima County population of 818,600 people by the year 2000 and 1,269,000 people in the year 2030.

would have a

In 1982, the DES revised these projections and now estimates that Pima County will have a population of 921,938 in the year 2000 and 1,680,560 by the year 2030 (see Figure 4).

predicted the population will increase further to 1,867,400.

Five years beyond that, in 2035, it is

Future Water Resources Available to Meet Tucson's Growth Needs

Responsible land use planning together with a reasonable projection of future population distribution obviously provide the key ingredients for planning the community's water system expansion.

Major additions to

Tucson's water system are proposed pressure.

However, the in these same areas of intense development question that must logically come first can be simply stated -will there be adequate water resources to supply the projected demand?

Projected growth translates directly into additional water supply requirements, and the alternatives available to this arid region can be enumerated as we see them today.

The continued use of groundwater to meet local requirements is envisioned to some extent, but the limitations on the availability of this resource are extremely difficult to quantify due to a number of extenuating circumstances.

1)

A New

State Groundwater Law -

Groundwater

Management

In June of 1980, the State of Arizona passed into law a

Act which sets forth ambitious goals for the regulation of groundwater use within the State.

With its eye on balancing demand with groundwater supply within the Tucson Active Management Area by the year 2025, the State Department of

Water Resources proposes to formulate and administer a series of groundwater management plans designed to impose various conservation regulations for all water using- entities.

New subdivisions are required to prove an assured water supply for a period of 100 years.

2)

Potential for Land Surface Subsidence

- As previously mentioned, a serious overdraft condition exists in eastern Pima

Utility officials

County.

Historical declines over a 35 -year record in some areas of Tucson's central excess of 120 feet.

basin (where the municipality of Tucson resides) are in

Continued long -term pumping from this area represents a concern for due to the potential for land surface subsidence (particularly differential) and its associated impacts.

3)

Legal Limitations - The value of groundwater resources in the Tucson area and the intense competition for rights to its use are exemplified by the current Legal confrontation with the Papago Indian Tribe.

Due to the President's veto of the Southern Arizona Water Rights

Settlement Act of 1982, negotiations with the Tribe and the

Federal Government have been reopened.

If the lawsuit persists, injunctions could be issued by the court requiring cessation of pumping in both the City's Avra Valley and Santa Cruz wellfields.

4)

Groundwater Contamination - The community of Tucson faces another challenge to its current water supply from

Trichloroethylene (TCE) contamination.

The historical disposal of industrial waste in the southwestern parts of the city has resulted in the contamination of small portions of the aquifer.

As a result, a number of public and private wells have had to be shut down until measures can be taken to mitigate the problem.

Facing a relatively complex disposition of its future groundwater supply, Tucson Looks to the importation of a surface water supply as a potential remedy to its water source problems.

Tucson has a tentative allocation of Central Arizona Project (CAP) water which is proposed to be delivered by 1990 through the Tucson Aqueduct.

The

CAP in itself is not a panacea, however.

As part of the Central

Arizona Project Act of 1968,

Arizona is obligated to curtail pumping from the Colorado River during periods of low flow as measured by water elevations in reservoirs along the river.

The project itself

100a

is behind in its original schedule of construction and is subject to constant scrutiny of its projected economic benefits.

As can be expected, statewide competition is keen for long -term allocations of this water and will continue as such until the federal government finalizes CAP allocations and sales contracts are signed.

The final costs of CAP water are not defined.

The Tucson community anticipates that the purchase of CAP water will represent a fairly sizeable impact on the rate payers.

Planners and administrators must carefully assess these economic factors before long -term community commitments can be extended.

Lastly, the quality impacts of this new future source are yet another question mark.

Tucson, accustomed to relatively high quality, low TDS groundwater must now re- orient its supply system configuration to operate with its first water treatment facility.

While this plant will remove suspended solids and taste and odor problems associated with surface water, hardness and total dissolved solids will increase.

In an effort to maximize the availability of its potable water supplies,

Tucson plans to maximize the use of its wastewater effluent available at two secondary treatment plants in the northwest portion of the Tucson metropolitan area.

Studies are underway to ascertain the most efficient and practical future use of effluent to replace potable water use wherever possible.

Examples of this are already realized through the application of effluent on a number of local golf courses.

In this manner an extension to the life of local groundwater reserves can be accomplished.

A final option for augmenting Tucson's water resources lies with increased conservation efforts.

Since 1977, Tucson Water has successfully advocated a summer demand management program known as "Beat the Peak." A by- product of this voluntary program has, in fact, been the realization of a significant amount of water conservation.

Per capita usage was reduced from 205 gallons per person per day (gpcpd) in 1973 -74 to approximately 150 gpcpd in 1978 -79.

This resulted in not only Less pumpage overall, but also a reduction in the expenditure of capital funds due to decreased demand.

In effect, the life of some water facilities was extended.

Since "Beat the Peak" is a summertime campaign, other conservation programs have followed such as "Slow the

Flow ".

This program is designed to take advantage of the successful summertime effort and broaden the public's awareness of the need for intelligent indoor water conservation to reduce sewage volume and extend the life of wastewater treatment and conveyance facilities.

Once again it is noted that these efforts are voluntary, and increased emphasis in these areas in the future may positively impact the water resource situation locally.

As previously mentioned, the new groundwater code will bring more attention to water conservation through guidelines that are mandatory in nature which stem from an overall management plan with time -specific per capita use goals.

The Impacts of Limited Water Resources on Tucson's Growth

At this point in the discussion it is pertinent to pause and attempt to put information in perspective through the use of a rudimentary example.

the aforementioned

Estimates have been made that approximately 100,000 acre -feet (a -f) of natural recharge is available annually to the local water table.

Assume that the basin is in balance in the year 2030 and all of this recharge is available for use by the municipality of Tucson (a sizeable assumption in itself).

Further expectation of CAP delivery for that year of 100,000 a -f.

If a per assume a reasonable capita usage characteristic of 150 gpcpd is applied to this situation, the total population which can feasibly be supported by these resources is 1,200,000 people (see Figure 5).

At this point in time (year

2030) it is assumed that

Tucson Water is providing retail or wholesale service to essentially all of eastern Pima County and only a very small amount of population exists outside the service area.

As you may recall, it was previously indicated in this paper that the most recent planning efforts indicate a population projection for Pima

County of 1,680,560 people by the year 2030.

We are realizing, therefore, a potential disparity between what is projected as growth for the Tucson area and what can be reasonably accommodated.

Since the maximum supply side of the equation is relatively fixed, the demand side must be reduced to match the supply.

The issues surrounding the future of water supply for the southwestern community of Tucson paint a complicated and undefined picture, to say the Least.

The governing bodies and the citizens at large must possess a keen awareness of the water resource question at the earliest possible stage in order to adequately address these issues.

Prudent and responsible planning of the community's growth must carry a high priority with the realization that difficult tradeoffs lie ahead and choices must be made for the benefit of the majority.

Competition for local water resources will only increase in the future, and all areas of the local economy will feel the impact.

The agribusiness, being the highest consumptive user, will probably reduce.

A limitation on municipal and industrial growth can be reasonably expected.

On the other side of the coin the impacts of limited water resources can be viewed favorably.

previously stated, it will encourage intelligent and prudent Land use planning

As in order to efficiently accommodate the community's needs with the resources available.

Since scarcity encourages efficiency, the integrity of local water delivery systems will undoubtedly improve.

Similarly, the pricing of the commodity of water will be adjusted upward to a more efficient and proper level.

Last, but not least, it is anticipated that the region will cooperatively resolve the overdraft situation and eventually realize the achievement of a "Safe- Yield" condition.

100b

Conclusion area.

The availability of

It is

questioning the no longer water resources is an extremely availability of

community's growth

possible to discuss

adequate water

will be a measure of the ability of manage and conserve the local water resources.

important factor in the growth the expansion

resources.

of the metropolitan

In Tucson, the nature of the Tucson area without and extent

the local water -using entities first of the

to effectively

McLean, Thomas M.

The Northwest Area Water Plan

Arizona and the Southwest, Volume 10.

References Cited

- Tucson, Arizona ", Hydrology and

Water Resources in

100c

PIMA COUNTY

FIGURE 1

1980 WATER USE IN EASTERN PIMA COUNTY

USE CATEGORY

AGRICULTURE

MUNICIPAL

INDUSTRIAL

RECREATIONAL/OTHER

TOTAL

POMPAGE

QUANTITY

IACRE FEET I

CENT

OF TOTAL

224.953 AF

02.328

80,144

3,282

57.6

21.1

20.5

0.8

390.707 AF

100.0

CONSUMPTION

QUANTITY

PERCENT

OFD

151.857 AF

32.841

80,144

3.282

56.7

12.2

29.9

1.2

208,124 AF 100.0

FROM WRCC REPORT TO CECIL D. ANDRUS.SECRETARY OF THE INTERIOR, APRIL 14, 1980

FIGURE 2

100d

N

100e

(1)

UMMERHAVEN

PIMA COUNTY POPULATION PROJECTIONS

(DEPARTMENT OF ECONOMIC SECURITY)

YEAR

2000

818,600

2030

1,269,000

DES-1979

DES-1981

921.938

1,680,560

FIGURE 4

WATER SERVICE CAPABILITY AT VARIOUS PER CAPITA USE RATES

I WATER SUPPLY-100,000 ACRE-FEET PER YEAR I

160

150

140

130

120

110

100

90

2.0

1.9

1.8

1.7

1.6

1.5

SERVICE POPULATION

I X 1,000,0001

FIGURE 6

100f

1.4

-

1.3

1.2

1.1

100g

A Survey and Evaluation of Urban Water Conservation Programs in Arizona (Abstract)

Marc Bennett

Arizona Department of Health Services

Phoenix, AZ

Abstract

Numerous cities and towns in Arizona are in the process of developing and implementing water conservation programs aimed at reducing wasteful water use activities of its citizens.

Most of these programs have been initiated because of:

1) future water conservation mandates in the State's groundwater law and in contracts for Central Arizona Project (CAP) water; and

2) increasing economic pressures for delivering water because of rising costs and reduced future dependable supplies.

This paper will review these legal requirements and assess the economic pressures on cities and towns in Arizona for water conservation programs.

In addition, existing and future urban water conservation programs being developed in the State will be examined.

The ability of these programs to reduce water demand will be evaluated based on experiences in Arizona and other states.

101

An Application of the Almon Polynomial Lag to Residential Water Price Analysis

Donald E. Agthe

Economic Consultant

1321 East Elm Street

Tucson, Arizona 85719

A recent article by Agthe and Billings (1980) concerned itself with the application of Koyck form lagged dynamic economic models to measure the price elasticity of demand for residential water consumption.

The Koyck form lagged models have a lagged dependent variable, quantity of water consumed, and assume that the greatest adjustment of quantity to price occurs in the first period after the price change and succeeding adjustments are progressively smaller and less important.

This study will consider an alternative dynamic economic model in which the independent variable price is assigned a distributed lag.

The distributed lag model chosen is the Almon Polynomial lagged model (Almon,1965) as it is expected that the lagged response to a price change is nonlinear in nature.

The results of several potential Almon lag forms are compared to the results of the simple Koyck lagged model found in the Agthe and Billings (1980) study.

This Koyck form was by far the best result found in the earlier study.

One of the most intriguing advantages of the Almon polynomial lagged model over the Koyck model is the ability to specify the form and the length of the adjustment to the price changes.

Given the fairly long periods of stable price structures for water and similarly priced public utility type goods, the consumer has a long time period to adjust and readjust his position to given price structure in the market place.

Therefore, initial overadjustment to price changes with later readjustments is a viable hypothesis for consumer behavior.

This behavior can be accounted for in the polynomial lag model but not in the Koyck lag model.

The Almon process also reduces the possibility of autocorrelation that is frequently associated with the lagged dependent variable that appears in the Koyck model.

The Models and Variables

This study utilizes the general form of the Almon lag model (Gujarati, 1978) as follows:

Q =

bo +b1W +b2Y +b3D

+ b4 Pt + b5Pt -1 +

+ b1Pt and the Koyck model in the form:

Q = bo + b1Qt

-1

+ b2W + b3Y + b4D + b5Pt where:

Q

=

Average water consumption (100 cubic feet) per household for active single residential water connections by month (January 1974 thru November 1977) (Tucson,

1978)

D =

The difference between what the typical consumer actually pays for water and what would be paid if all of the water were purchased at the marginal rate.

(Dollars)

Personal income per household (dollars per month) (Arizona)

Y =

W

=

Evapotranspiration for Bermuda grass minus rainfall (inches) (Boul, 1963; U.S.)

103

t n

P

Marginal price facing the average household (cents per 100 cubic feet) (Tucson,

1974, 1975, 1976, 1977)

Time period in months

Length of the price lag in months

Water consumption per household (Q) is the dependent variable.

Households in this study include all single family residences, apartments, condominiums, mobile homes, duplexes, and triplexes served by individual water connections.

Multiple units served by a common water meter were excluded from the study, eliminating those households which receive water at a zero marginal price because its cost is included in their rental payments.

The inclusion of a large number of such households would result in an underestimation of the price elasticity of demand for water among households which must pay individual water bills.

A correct specification of the demand model requires the use of two price related variables when there are block rates and /or flat rate service charges in the price schedule (Billings and Agthe, 1980; Nordin, 1976; Taylor, 1975).

Since the Tucson

water rates include increasing block rates and flat rate charges, two variables must be used in the demand model.

The first, marginal price (P) or the per unit price in the marginal block, is the price the average consumer would have to pay for additional unit of water each month, based on average household water use and the City of Tucson water rate schedule.

The second price variable (D) is the difference between what the consumer actually pays for water and what would be paid if all water were purchased at the marginal price.

This variable measures the flat rate charge imposed on the consumer plus the difference between the amount paid under intra- marginal rates (i.e., block rates below the marginal rate) and what would have been paid at the consumer's marginal price.

The use of the price variable (D) provides a measure of the income effect of any changes in the rate schedule which do not alter the marginal price.

It also measures income effects arising from marginal price changes which are in addition to those which would be predicted on the basis of the change in marginal price alone.

The difference variable measures a pure income effect which might be expected to have the same impact on water use as any other change in income.

Since this study utilized monthly data, a weather variable (W) to account for variations in sprinkling demand is particularly important.

The weather variable incorporates the effects of rainfall and evapotranspiration which influence the amount of water required for lawn, shrub, and tree irrigation.

Since Bermuda grass is the primary residential lawn cover in Tucson, its evapotranspiration rate was selected because it is likely that many residents use the appearance of their lawn to judge their irrigation needs.

Personal income per household (Y) was included in the model to account for variations in the economic situation of water consumers during the study period.

This variable was found significant in a previous study of residential water demand in

Tucson (Billings and Agthe, 1980) and is normally considered an important factor in most demand analysis.

Because of the substantial inflation which occurred during the study period, the model was estimated using real values of the variables.

Real values were derived by dividing the price, difference, and income variables by the consumer price index

(Board of Governors).

Consumers were found to respond to water prices on the basis of real (Price adjusted) values for water rates and income rather than nominal prices in a previous study (Billings and Agthe, 1980).

If one wishes to model the downward overadjustment with later slight upward consumption adjustments, the Almon Lag Model in cubic form, as plotted in Diagram 1, is probably the best model.

Of course, a result with an inflection point is also possible.

A potential problem with the Almon model is that a lag of at least 4 periods is required when a cubic equation is tested.

Since Hogarty and MacKay (1975) argue that most of the adjustment to marginal price changes occurs in the first three months after the price change, there is some possibility of a cubic equation with a minimum lag of 4 months being too long.

To allow for this, a second degree equation with a 3 month lag is considered as an alternative.

Results

The similarity of the results (Table 1) for the b values of the Almon lagged variables was gratifying while the accompanying low t- values were less satisfying.

The low t values may result from the strong multicolinearity inherent in the Almon procedure.

In any event, the consistency of results between equations appears to call for

104

acceptance of the b values in spite of the low t ratios.

The majority of the downward adjustment of water consumption in response to marginal price increases appears to be completed by the end of the 3rd month, a result that agrees with Hogarty and MacKay (1975).

While there appears to be a slight upward adjustment in consumption for the fourth and fifth months after the price change, the less stable b values and poor t ratios preclude any definitive statement concerning the exact size of this upward adjustment other than it is likely to be small if it exists.

It also appears that the adjustment process is complete by the beginning of the fifth month.

These results are in agreement with the earlier result using the

Koyck model (Agthe and Billings, 1980). This model also demonstrates the greatest decreases occurring in the first period with successively smaller decreases in water and in later months.

The long run and short run price elasticity of demand coefficients are presented in Table 2.

The short run coefficients for the Almon procedure are calculated for each time period by the formula: and the long run price elasticity of demand coefficients are calculated by the formula:

4

E i=0 b

F

-

The elasticities were calculated for 5 periods in each case, period to plus 4 lagged periods.

The long run results range from .468 to .513.

Roughly interpreted, this means that a 1 percent change in price will produce a .5 percent change in water use within 5 periods of the institution of a price change.

The Koyck model yielded a long run price elasticity of demand coefficient of .5306.

This is slightly larger than the

Almon procedure results as the Koyck model does not allow for partial readjustment to a higher consumption level.

The Koyck short run price elasticity of demand is - .4164, a coefficient similar to that of the first period Almon procedure values.

The price elasticities reported for the Almon process fall well within the range reported in

Agthe and Billings (1980).

Conclusion

This study presented the Almon Polynomial Lag as an alternative to the Koyck model to measure consumer response to increased residential water prices because it has the advantage of being able to specify the length and form of the lag.

A high amount of multicolinearity inherent in the model precluded obtaining good t ratio results for the most of the lagged prices.

Most of the downward adjustment in residential consumption occurs within three months of the price change and any upward readjustment in consumption is likely to be small.

Since the upward readjustment produces uncertain statistical results and the price elasticities are about the same for both the polynomial and Koyck results, there is no reason to believe the polynomial results are superior to the Koyck results or that the hypothesized upward adjustment exists.

105

Pt-5 t

W t

Qt-1 t

D t

Y t

Constant t

Variable or Statistic

Pt t

Pt-1 t

Pt-2 t

Pt-3 t

Pt-4 t

Adjusted R2

F

Durbin -Watson h

Table 1 - Best results of the application of the

Almon Polynomial Lag to Residential Water Demand in Tucson, Arizona

ALMON POLYNOMIAL LAG FORM

X2 4 Mo.

-.0964

( -1.91)

-.0347

(-1.404)

-.0006

(-.017)

+.0230

(.00)

+.0064

(.063)

Degree and Length of LAG

X3 4 Mo.

-.0960

( -1.41)

-.0374

(.519)

-.0001

(.000)

+.0161

(.012)

+.0095

(.037)

Koyck

Lag

-.0897

(2.32)

.0053

(8.09)

.0436

(2.00)

-.0061

(-3.46)

-4.589

( -.79)

.793

26.52

2.04

.0053

(7.94)

.0436

(1.96)

-.0061

(-3.40)

-4.592

( -.775)

.787

22.06

2.04

.2154

(2.15)

-.0042

(6.22)

-.0418

(2.27)

-.0052

(-3.30)

-5.69

( -1.15)

.817

39.50

1.33

106

Time Period t0 t -1 t -2 t -3 t -41

Long Run

Table 2

- The Short Run and Long Run

Price Elasticities of Demand Associated With

The Almon Polynomial Lag Results

Model Chosen and LaR

X2 4 Mo.

-.4475

X3 4 Mo.

-.4456

-.1597

-.0027

+.1037

+.0285

-.4675

-.1719

-.0005

+.0726

+.0423

-.5131

107

References Cited

Agthe, Donald E. and Bruce R. Billings.

1980.

Dynamic models of residential water demand.

Water Resources Research.

Washington, D.C.

16(3):476 -480.

Almon, Shirley.

itures.

1965.

The distributed lag between capital appropriations and expend-

Econometrica.

33(1):178 -196.

Arizona Department of Economics Security.

1978.

Arizona Population and Income Estimates.

Monthly unpublished data Phoenix, Arizona.

Billings, R. Bruce and Donald E. Agthe.

1980.

Price elasticities for water:

A case of increasing block rates.

Land Economics.

56(3).

Board of Governors.

1977.

Federal Reserve System.

A -66 (Consumer Price Index).

Washington, D.C.

Federal Reserve Bulletin.

Table

Soul, S. W.

1963.

Calculated actual and potential evapotranspiration in Arizona.

University of Arizona, College of Agriculture, Tucson, Arizona.

Technical Bulletin 162.

Gujarati, Danodar.

1978.

Basic Econometrics.

(McGraw -Hill, New York).

Hogarty, Thomas F. and Robert J. MacKay.

1975.

The impact of large temporary rate changes on residential water use.

Water Resources Research.

11(6):791 -794.

Houthakker, Hendrick S. and Lester D. Taylor.

1970.

Consumer demand in the United

States.

2nd Ed. Harvard University Press.

Howe, Charles W. and F. P. Linaweaver, Jr.

1967.

The impact of price on residential water demand and its relation to system design and price structure.

Water Resources Research, 3(1):13 -32.

Nordin, John A.

1976.

A proposed modification of Taylor's demand analysis: Comment.

The Bell Journal of Economics.

7(2):719 -721.

Taylor, Lester D.

1975.

The demand for electricity:

Economics.

6(1):74 -110.

A survey.

The Bell Journal of

Tucson, Arizona.

January 1,

1974, June 7, 1976 and March 3, 1977.

Water Department

Rate Schedules.

City Ordinance No. 4130, City Ordinance No. 4497 and City Ordinance No. 4626.

Tucson.

1978.

class.

Arizona Department of Water Sewers.

Water use by Month and customer

Unpublished data on computer tape.

Tucson, Arizona.

U.S. Weather Bureau.

1977.

2,

Climatological Data Annual Summary, Arizona.

Tables 1,

3 and 4.

Asheville, N.C.

National Oceanic and Atmospheric Administration.

Young, Robert A.

1973.

Price elasticity of demand for municipal water:

Case study of Tucson, Arizona.

Water Resources Research.

9(4):1068 -1072.

108

Diagram 1

The Expected Consumption and Corresponding b- value Patterns for the x3 Almon Polynomial Lag.

Ouantity of

Water t-0 t-1 t-2 t-3 t-4 t-5

Time Lag

Corresponding b- value

0

Time Leg

109

SEDCON: A MODEL OF NUTRIENT AND HEAVY METAL

LOSSES IN SUSPENDED SEDIMENT by

William A. Gabbert, Peter F. Ffolliott, and William O. Rasmussen

School of Renewable Natural Resources

University of Arizona, Tucson, Arizona 85721

INTRODUCTION

A prototypical computer simulation model has been developed to aid watershed managers in estimating impacts of alternative land management practices on nutrient and heavy metal losses due to transported sediment on forested watersheds of the southwestern United States.

The model, called SEDCON, allows users at remote locations with modest computer terminal equipment and commonly available data to obtain reliable estimates of nutrient and heavy metal concentrations in suspended sediment originating on uniformly- stocked,forested watersheds in the Southwest.

SEDCON has been structured in an interactive mode to facilitate its use by persons not familiar with computer operations.

Written in FORTRAN IV computer language, the model requires approximately 5000 words of core.

at the University of Arizona.

SEDCON is operative on a DEC -10 computer

FORMULATION OF SIMULATION TECHNIQUE

A study by Gosz, White, and Ffolliótt (1979a, 1979b, 1980) found that combinations of given geologic and vegetative types (other factors of the physical environment were assumed to be reflected by the vegetative type) produce characteristic weathering regimes that influence the physical and chemical characteristics of transported sediment.

Using the source data base collected in this study and other appropriate background sources, SEDCON was formulated to estimate nutrient and heavy metal loss by suspended sediment concentrations derived from ponderosa pine and mixed conifer forested watersheds in the southwestern United States (Gabbert, 1982).

Geologies evaluated included basalt, sandstone, limestone, and granite.

Most of the study areas have been utilized as watershed research areas (Figure 1).

In formulating SEDCON, it was important to select data sets representative of sediment transported during stream flow.

Chemical compositions of transported sediments collected in settling tanks on a control watershed (Beaver Creek Watershed Number 19) were compared with sediments taken from the stream channel on one of the study areas (Beaver Creek Watershed Number 13).

This comparison was made to determine whether the data used in the computer model were representative of sediment actually transported during stream flow.

Geology and vegetation were similar on both watersheds (Gosz, White, and Folliott,

1979a, 1979b, 1980; Gabbert, 1982).

Overall, the results of the above -mentioned comparison support the hypothesis that representative values of transported sediment concentrations can be obtained by sampling channel sediments (Gosz, White, and Ffolliott, 1979a, 1979b, 1980; Gabbert, 1982).

As a result, stream channel data were used in the formulation of SEDCON (Gabbert, 1982).

Gosz, White, and Ffolliott (1979a, 1979b, 1980) found that concentrations of chemical constituents varied among soils: under the forest canopy, on stream banks, and in stream channels.

Thus, it is important to remember that errors could result when using SEDCON to simulate nutrient and metal loss by transported sediment on disturbed or geologically unstable areas (which could result in bank and surface erosion).

Likewise, the model should not be used to simulate losses caused by extreme runnoff events

(which also result in bank and surface erosion), as the data could prove to be unrepresentative (Gabbert,

1982).

Chemical constituents transported by suspended sediments in a mixed -conifer forest (Thomas Creek) and a ponderosa pine forest (Beaver Creek) were compared to determine whether the effects of vegetation on nutrient and metal content of sediment could be separated from the effects of geology.

Both watersheds were located on similar bedrock.

The results of this comparison indicated that it would be difficult to quantify the effects of vegetation. Thus, SEDCON should only be used to estimate nutrient and heavy metal loss on watersheds comprised of: ponderosa pine forests on basalt, granite, sandstone, or limestone; and mixed conifer forests on basalt (Gabbert, 1982).

ln

ARIZONA

FLAGSTAFF

O

BEAVER CREEK

HEBER*

THOMAS CREEK*

O

PHOENIX

TESUOUE*

O SANTE FE

°ALBUQUERQUE

NEW MEXICO

*

SACRAMENTO FOREST

O

TUCSON

*

STUDY AREA

0

MILES

60

Figure 1.

Location of study areas.

Predictive equations were developed for each of the above- listed vegetative types and geologies.

These equations, which were incorporated into SEDCON, compute 90 percent confidence intervals.

General forms of the equations were:

Lower Limit

Y1 =a1Xs + b1Xf where Y1 =lower limit (ppm) of constituent concentration.

al =lower limit coefficient for sand fraction.

bl =lower limit coefficient for fine fraction.

Xs= percent sand in the sediment.

Xf percent fines in the sediment.

Upper Limit

Y2 =a2Xs + b2Xf where Y2 =upper limit (ppm) of constituent concentration.

a2 =upper limit coefficient for sand fraction.

b2 =upper limit coefficient for fine fraction.

In the above equations, it is important to note that there are separate predictive coefficients for the sand (0.061 mm to 2.0 mm) and fine (less than 0.061 mm) fractions of sediment.

This separation was essential since Gosz, White, and Ffolliott (1979a, 1979b, 1980) found that constituent concentrations of sediment vary between sands and fines.

APPLICATION OF MODEL

To encourage use of SEDCON, a readily understandable framework was constructed.

An illustration of this framework, a simplified flowchart of activities executed in the model, is presented in Figure 2.

112

`VEGETATION AND

GEOLOGY i

CHEMICAL CONSTITUENTS /

AREA

/ i

SEDIMENT PRODUCTION /

i

PERCENT SAND / i

Figure 2.

Flowchart of SEDCON.

113

Application of SEDCON can best be demonstrated with a hypothetical example (Figure 3).

begins with a question as to which VEGETATIVE TYPE AND GEOLOGY is to be considered.

Operation

In this example, ponderosa pine forest on basalt was selected.

Next, a list of available TRANSPORTED CHEMICAL CONSTITUENTS is presented.

In the example, the terminal operator chose to evaluate all of the constituents.

WATERSHED AREA (ACRES), 400 acres, was input next (Figure 3).

The user must then specify whether WINTER OR SUMMER SEDIMENT is to be evaluated.

Winter sediments are those that orginate from runoff produced by snowmelt or rain -on -snow events.

Summer sediments originate from runoff produced by thunderstorms.

Winter sediments were evaluated in this example.

Next,

SEASONAL SEDIMENT PRODUCTION (POUNDS PER ACRE) was input at 40 pounds per acre (Figure 3).

SEDCON is not designed to predict sediment production.

Instead, this information must be obtained through use of on -site inventory data, appropriate predictive equations, or other simulation models.

An interactive model designed to simulate suspended sediment yields on forested watersheds in central Arizona is available on a DEC -10 computer at the University of Arizona (Rasmussen and Ffolliott,

1979).

If desired, this model, called SED, can be linked to SEDCON to provide input data on seasonal sediment production (Gabbert, 1982).

Since concentrations of constituents vary between sands and fines, PERCENTAGE OF SAND in the sediment is requested (Figure 3).

Limits have been placed on values that should be selected for PERCENTAGE

OF SAND.

Hansen (1966) reported that sands account for 35 to 65 percent of winter suspended sediments.

Additionally, he found a mean concentration of 55 percent of the sediments were sand.

As a result, 35 and

65 percent have been incorporated into SEDCON as the range for PERCENTAGE OF SANDS in winter sediment.

A default value of 55 percent sands in winter suspended sediments is available.

Acceptance of the default value allows simulation to continue when specific knowledge of the input requested is limited.

However, the user has the option of overriding the default value.

Since winter sediments were evaluated in the example, the default value of 55 percent sands was utilized (Figure 3).

Hansen (1966) found summer suspended sediment samples varying from 0 to 20 percent sand.

Thus, 0 and 20 percent sand in summer suspended sediments were used as limits.

A default value of 10 percent sand is available.

At this point, SEDCON will calculate and display estimated values of nutrient and heavy metal transport capacity of suspended sediment.

The summary display presents values as acid digestable (primary chemical composition of sediment) and extractable (absorbed to the sediment) nutrients and heavy metals (Figure 3).

At this point, the terminal operator can request another value for percent sand, input a different value for seasonal sediment production, evaluate another season, request to have other constituents evaluated, or select another vegetative type.

Anywhere in these steps, the operator can exit the model by answering with a -1.

In the example, SEDCON was exited when asked if another value for percent sand was desired (Figure 3).

Since SEDCON calculates seasonal losses of nutrients and heavy metals transported by sediments, it is necessary to execute the model twice, once for winter losses and once for summer losses, to obtain an annual loss.

This procedure must be followed for each level management alternative to obtain an estimate of the annual loss of nutrients and heavy metals associated with each alternative.

CONCLUSIONS

SEDCON was developed to aid watershed managers and land use planners estimating the loss of sediment transported nutrients and heavy metals.

The model accepts basic watershed data on bedrock geology, vegetative type, and seasonal sediment production.

By evaluating management alternatives through the seasonal sediment production function and having an understanding of the significance of a change in site productivity, SEDCON can be used by the land manager to estimate the expected consequences of particular management options.

REFERENCES CITED

Gabbert, William A.

ment.

1982.

Simulation of nutrient and heavy metal transport capacity of suspended sedi-

University of Arizona, Master's Thesis, 49 p.

Gosz, J. R., C.

S. White, and P.

F. Ffolliott.

1979a.

Nutrient and heavy metal transport capabilities of sediment in the Southwest.

Final report for Eisenhower Consortium, Project Number 255, 58 p.

114

Gosz, J. R., C.

S. White, and P. F. Ffolliott.

1979b.

Nutrient and heavy metal transport capabilities of sediment in the Southwest.

Final report for the Eisenhower Consortium, Project Number 340, 51 p.

Gosz, J.

R., C.

S. White, and P.

F. Ffolliott.

1980.

Nutrient and heavy metal transport capabilities of sediment in the southwestern United States.

Water Resources Bulletin, 16:927 -933.

Hansen, E. A.

1966.

Field test of an automatic suspended- sediment pumping sampler.

of Agricultural Engineers, Transactions 9:738 -743.

American Society

Rasmussen, W. 0., and P.

F. Ffolliott.

1979.

An interactive model of suspended sediment yield on forested watersheds in central Arizona.

Hydrology and Water Resources in Arizona and the Southwest,

9:43 -47.

Figure 3.

Hypothetical example of SEDCON.

EXECUTE SEDCON

LINK: Loading

[LNKXCT SEDCON execution]

VEGETATIVE TYPES AND GEOLOGIES ARE:

1.

2.

3.

4.

5.

PONDEROSA PINE FOREST ON BASALT

PONDEROSA PINE FOREST ON SANDSTONE

PONDEROSA PINE FOREST ON LIMESTONE

PONDEROSA PINE FOREST ON GRANITE

MIXED CONIFER FOREST ON BASALT

ENTER NUMBER OF VEGETATIVE TYPE AND GEOLOGY TO BE EVALUATED.

1

TRANSPORTED CHEMICAL CONSTITUENTS ARE:

ACID DIGESTABLE

1.

2.

3.

4.

5.

6.

CALCIUM

MAGNESIUM

SODIUM

POTASSIUM

ZINC

IRON

7.

8.

9.

10.

11.

12.

COPPER

MAGANESE

LEAD

CADIUM

TOTAL NITROGEN

TOTAL PHOSPHORUS

EXTRACTABLE

13.

14.

15.

CALCIUM

MAGNESIUM

POTASSIUM

18.

16.

17.

ALL ACID DIGESTABLE AND EXTRACTABLE CONSTITUENTS

CATION EXCHANGE CAPACITY

ORGANIC MATTER

ENTER NUMBER OF CONSTITUENT(S) YOU WISH TO EVALUATE.

18

WHAT IS WATERSHED AREA IN ACRES?

400

DO YOU WANT TO EVALUATE WINTER(1) OR SUMMER(2) SEDIMENT?

WHAT IS WINTER SEDIMENT PRODUCTION IN POUNDS PER ACRE?

40

WHAT IS PERCENT SAND IN SEDIMENT (RANGE:35- 65,<CR> GIVES:55)?

115

CONSTITUENT CONCENTRATION (PPM)

ACID DIGESTABLE

CALCIUM

MAGNESIUM

SODIUM

POTASSIUM

ZINC

IRON

COPPER

MANGANESE

LEAD

CADIUM

TOTAL NITROGEN

TOTAL PHOSPHORUS

EXTRACTABLE

CALCIUM

MAGNESIUM

POTASSIUM

ORGANIC MATTER

CEC(MEQ /100G)=

8.78-

46.45

3885.5910.

18090.29440.

381.-

658.

895.-

1342.

71.-

57300.-

87050.

58.-

90.

81.

1018.4610.

6.-

15.

0.26-

0.26

335.-

766.

542.-

1138.

1413.2260.

378.-

1016.

126.-

202.

46250.-

80200.

DO YOU WANT TO EVALUATE OTHER CONSTITUENTS?

(1 =YES, 2 =NO, -1 =EXIT)

2

DO YOU WANT TO EVALUATE ANOTHER PERCENT SAND VALUE?

(1 =YES, 2 =NO, -1 =EXIT)

-1

STOP

END OF EXECUTION

CPU TIME: 0.27

ELAPSED TIME:

2:8.28

EXIT

VOLUME (POUNDS)

62.16-

94.56

289.44471.04

6.10-

10.52

14.32-

1.14-

21.47

1.43

916.80-

1392.80

0.94-

16.30-

0.10-

1.29

73.76

0.00-

5.36-

0.24

0.00

12.25

8.66-

18.21

22.60-

36.16

6.05-

16.26

2.02-

3.23

740.00-

1283.20

116

TECHNIQUES FOR STUDYING NOMPOINT WATER QUALITY

Donovan C. Wilkin

Susan J. Hebel

School of Renewable Natural Resources

College of Agriculture

University of Arizona

Tucson, Arizona

Introduction

While the results and techniques described in this paper apply to Midwestern watersheds, there is reason they can not equally apply to western and eastern watersheds as well.

This paper might more properly be titled "Techniques for Studying Undefined Contributions to Water Quality ".

The more common no distinction between sources for water quality is, of course, between point- as opposed to nonpoint sources.

The authors, in their work to help develop a more efficient water quality control program in the State of Illinois, have found the more useful distinction to be between defined sources of water quality and undefined sources.

A defined source is one for which the amount of a water quality constituent delivered per unit time to the active stream channel and its location of delivery are known.

The active stream channel is defined as that part of the stream bed and floodplain with greater than 50% probability of being flooded in any given year, i.e. the 2 -year floodplain.

The distinction between defined and undefined sources is more important than between point- and nonpoint sources.

Effective and efficient water quality management can only be applied to defined sources.

Water quality models to deal with management options can only simulate defined sources.

Defined sources can be either point sources as, for example, waste treatment facilities, or nonpoint sources as is floodplain farming.

Undefined sources, as well, can be either point sources, as are some illegal gravel operation discharges, or nonpoint sources such as upland farming.

In our work in Illinois, we studied several hundred watersheds to distinguish defined and undefined sources of water quality.

Prospects for effective and efficient water quality control were seen to be poor given the very large proportion of water quality deriving from undefined sources (Wilkin and Flemal,

1980).

Our analyses suggested that, except in a few urban -dominated watersheds, undefined sources were accounting for nearly 100% of the total constituent load in the stream and that total control of defined, and mostly nonpoint, sources would effect little in the way of water quality improvement.

The work suggested several crucial kinds of information needed to convert undefined sources of water quality to defined sources.

These are:

1.

2.

3.

4.

5.

6.

A fixed network of monitoring locations, including both instream and all effluent locations; periodic sampling for chemical water quality analysis using both filtered and unfiltered analysis techniques; a record of effluent discharge or stream flow at the time of water quality sampling; land use information for critical locations in the watershed; watershed loading information on the amounts and locations and timing of chemical constituents introduced to the watershed; and further theoretical and empirical studies on the movement of chemical constituents in the watershed.

No state has the ideal program for gathering this information.

Nonetheless, Illinois has had an unusually good monitoring program for water quality that provides a significant amount of this required information.

This paper describes our use of these data and what we have learned therefrom about defining presently undefined sources of water quality.

The Illinois Water Quality Monitoring Network

At times, the State of Illinois has monitored over 400 stations in a fixed network around the State.

Each station was sampled monthly, and each sample was analyzed for a suite of over 50 constituents or characteristics.

These fixed stations allowed us to divide the state into as many water quality sub basins, with drainage divides determined by the station locations.

Within each subbasin, the location of any defined sources was noted including the flow distance from that source down to the water quality monitoring station.

In addition, we attempted to identify the theoretical "center" of the subbasin for ni

estimating the average flow distance for nonpoint contributions within the subbasins.

Figure 1 is a schematic representation of the upper Sangamon River in east -central Illinois showing the subbasin or subsegment breakdown, the location of point sources, monitoring stations, and subsegment centers.

Subsegment or Subbasin

Drainage Divides

Point Source

IEPA Ambient Water Quality

Monitoring Station

Hypothetical Center of Undefined

Subbasin Inputs

Figure 1. Schematic representation of the upper Sangamon River in east-central Illinois. Station E18 is the downstream delimiter.

Mass Balance Pccounting

Mass balance accounting (Wilkin and Flemal, 1979) is the primary technique used for identifying the relative importance of defined and undefined sources in the water quality subbasins.

In effect, this procedure, which was ultimately computerized, uses the monitored constituent concentration at each monitoring station, multiplied by flow or discharge and corrected to an annualized rate of metric tons per year of chemical constituent flowing past that point in the stream.

In the Illinois network, flow data were not routinely taken, so estimates of flow had to be made based on U.S. Geological Survey stream flow records and drainage area at the sampling station.

Each defined water quality contributor to the subbasin, including the next upstream water quality monitoring station or stations, was accounted for assuming first order assimilation.

The rate of assimilation had to be obtained by solving a series of simultaneous equations, one for each subbasin in the analysis of which there had to be at least two.

The computer does this by successive approximation.

When the assimilation rate is determined, it can be applied to the constituent load at the upstream station or stations and to all intervening defined sources.

These calculations result in the total defined portion of the subbasin load arriving at the downstream monitoring station.

Anything left over by simple difference between the total constituent load measured at the downstream station and the various defined contributions from upstream is presumed to be an undefined load originating in the subbasin.

is the starting point for the search for undefined sources.

This

Wilkin and Flemal have studied the fraction of load deriving from undefined sources across Illinois.

Findings from the upper Sangamon River were typical of the state as a whole, outside urban areas.

The upper Sangamon consists of 494 square miles of drainage area with mean total discharge of 1.03 cubic feet per second per square mile.

The basin consists of five subbasins and has eight point sources contributing, on the average, 0.5 percent of the toal stream flow.

Land use in the basin is 2% urban and industrial,

96% agricultural, and 2% other.

Table 1 shows the proportion of constituent loads from undefined sources in the upper Sangamon watershed.

118

Table 1.

Fraction of load from undefined sources, upper Sangamon

River, east -central Illinois.

Constituent Fraction I!ndefined

Ammonium Nitrogen

Barium

Boron

0.84

0.99

Chloride

Copper

Fecal coliform

Fluoride

Iron, total

Lead

Manganese

0.99

0.99

0.99

0.62

0.99

0.99

0.99

0.99

0.99

MBPS

Mercury

Nitrate nitrogen

Phenol

Phosphorus, total

Sulfate

0.94

0.99

0.99

0.93

0.99

Total dissolved solids

0.99

Zinc 0.99

An analysis of individual water quality constituents is instructive.

The mean basin concentration for iron is 1.09 mg /1 with 32% of the samples violating the Illinois general use standard of 1.0 mg /l.

Only 1% of the total iron load derives from defined sources.

Even if there were total removal of defined sources, there would be no significant reduction in the violation rate for iron.

Mean basin concentration for fecal coliform organisms is 3,200 MPN /100 ml.

Sixty -nine percent violate the Illinois general use standard of 200 MPN /100 ml.

Total load from defined sources amounts to

38 %, with 62% undefined.

Even with total elimination of defined sources, the minimum feasible violation rate would be in the range of 59 %.

Phosphorus, again, has a mean basin concentration of 0.29 mg /1 with 90% of the samples violating the

Illinois general use standard of 0.05 mg /1.

Only seven percent of the total load is from defined sources, so the minimum feasible violation rate, with total removal of defined sources, is still 87 %.

Other constituents show the same general story.

Clearly, until we can define a larger proportion of the total constituent load, we have no chance of controlling these sources to accomplish our water quality goals.

The following describes the various means by which we have attempted to define previously undefined water quality contributions.

Concentration /Discharge Relationships

The importance of monitoring concentration and discharge together cannot he overestimated.

For point sources, of course, it is essential to know both concentration and discharge in order to determine the amount of the constituent being introduced to the stream.

For streamflow measurements, it is the only way to estimate the total load of the constituent arriving at that point in the stream.

essential in knowing what fraction of the load is deriving from defined and undefined sources.

Both are

Further benefits, however, can be gained in the attempt to identify and define water quality sources.

Especially where the monitoring is frequent and where individual flood events can he recorded, we can begin to gain clues to the delivery mechanisms of the constituent to the stream.

For example, where the constituent is being delivered to the stream at a constant rate, as might be the case for constituents entering with ground water seepage, there should be a clear inverse relationship between concentration and discharge.

This is the result of dilution.

Where a constituent shows such a pattern, the presumption is that of relatively constant delivery.

Nitrate nitrogen seems to follow this general pattern.

Where the constituent is delivered to the stream more rapidly at higher stream discharges, while the concentration may do anything from raising to reducing on the rising limb of the hydrograph, the product of discharge and concentration will increase significantly.

Phosphorus is a constituent whose concentration tends to increase with discharge.

This could be a combination of bed load entrainment and delivery of phosphorus- bearing eroded sediments to the stream channel.

Where high concentrations tend to persist after return of the hydrograph to baseline levels, the probable cause is bed load entrainment.

A different pattern is observed for iron.

Iron concentrations in our study streams increase sharply with increased flow.

Then, at the peak of the hydrograph, they decrease sharply to levels equal to or below baseline levels.

This is thought to indicate a "first flush" phenomenon.

Temporarily higher flows entrain material that was not otherwise involved in streamflow.

This can happen either for

119

materials being deposited on banks or for materials washed in as urban storm runoff.

In the case of iron, ground water contains high concentrations of soluble ferrous iron.

Seepage of ground water along stream channels allows oxidation to insoluble ferric iron form which precipitates onto the dry banks.

Not until the early stages of the next major flood event is this material delivered downstream.

The point of relating discharge and concentration is that we can begin to infer certain characteristics of delivery of the constituent to the stream.

This can be of significant help in pinpointing the source.

Sediment- Related Pollution

Sediment has been identified as our most serious water quality problem.

costs associated with sediment is lengthy.

The list of problems and

It includes reservoir sedimentation, disruption of navigation, disturbance of fisheries and wildlife habitat, and added treatment costs for water supplies.

is also implicated in the delivery of a significant chemical fraction to water quality.

Sediment

The Illinois

Environmental Protection Agency Task Force on Nonpoint Sources of Pollution (1978) estimated that over

90% of the organic nitrogen and phosphorus from upland agriculture delivered to streams is adsorbed to eroded soil sediment.

Clearly, other pollutants can either be delivered to surface waters adsorbed to sediment or can move as unadsorbed particulate by the same pathways as soil sediments.

Our groups attempted to study sediment movement in order to gain some ideas about the sources of this kind of water quality constituent.

This work will be reported at length elsewhere, but it can be summarized here.

It was necessary to find a tracer that would allow us to study sediment movement across the watershed, to find its areas of erosion and its areas of redeposition.

Sediment delivery was defined, for our work, as the process of sediment movement to the active flood plain.

Once sediment is at the active floodplain, it can be considered delivered to surface waters since it is only a matter of months, normally, before a flood event suspends the material and moves it downstream.

Work had been done with fallout Cesium -137, a byproduct of the atmospheric testing of atomic weapons.

Fallout Cesium -137 adsorbs strongly to surface soils.

Little of significance is removed with crops.

The inference is that, in areas of strong erosion, the surface Cesium -137 concentrations are lower than the average for the watershed.

In areas of strong redeposition, they should be higher than average.

The surprising results were that, for a large part of the watershed similar to the upper Sangamon, eroded sediments appear to be trapped by such things as upland depressions, fence rows, hedge rows, roadside ditches, and other obstructions.

The fraction of upland sediment delivered to the active floodplain seems very low indeed.

No attempt was made to estimate this accurately, but figures in the range of 10% delivery seem appropriate based on our field observations.

Sediments eroded from lands very near the floodplain, particularly on the steeply sloping land immediately next to it, are redeposited by obstructions much less frequently.

Thus, these eroded soils are delivered at a much higher rate.

Floodplain soils, in areas of floodplain farming, are not only among the most severely eroded soils in the watershed, but, since this sediment is by definition already delivered when it is eroded, it has maximum effect on instream sediment levels.

Similar logic, of course, can be applied to those chemical constituents delivered to the stream adsorbed to soil particles, or to those whose physical form causes them to move in the same manner as eroded soil particles.

Phosphorus, of course, is one such chemical constituent.

It remains now to identify not only what chemicals use such a delivery pathway, but to find out where, when and how they are loaded into the watershed in the first place, since this has a strong influence on the probability of delivery to surface waters.

Land Use /Water Quality Relationships

Early statistical studies relating land use over the entire watershed and the undefined portion of the constituent loading gave largely negative results.

The only constituent for which positive results were obtained was nitrate nitrogen.

This model explained just.over 30% of the variability for nitrate nitrogen.

This can be explained logically.

Nitrate nitrogen is highly soluble and is primarily loaded into the watershed as nitrogen fertilizer, an activity occurring relatively uniformly over the watershed.

Its high solubility and its tendency to persist in ground water suggests that a relationship should be found between land use over the entire watershed and stream water quality.

As noted previously, a constituent like phosphorus, however, being relatively insoluble and strongly adsorbed to soil particles, should show a very different pattern.

Based on the foregoing sediment work and our understanding of the chemical properties of phosphorus, land use close to the stream should be more important in determining instream phosphorus levels.

LANDSAT imagery was used to obtain land use within the 100 -year floodplain of the upper Sangamon.

To this was added any urban land use found in each subbasin.

These, then, were used in a statistical analysis of the effects of land use on two water quality constituents.

Because nitrate nitrogen and total phosphorus seem to be so different in delivery pathways, the former moving with groundwater and the latter with eroded sediment, these were chosen.

The early expectation was that phosphorus levels

120

would be better predicted by land use close to the stream than would nitrate nitrogen levels.

Results, however, suggested that both instream constituents are strongly predicted by knowing land use close to the streams.

For phosphorus, of course, these findings are consistent with those from the sediment movement work mentioned previously.

For nitrate nitrogen, however, based on highly significant regression coefficients, the inference is that enough can happen to ground water constituents, between the point of watershed loading and the stream, that land use close to the stream still tends strongly to control constituent concentrations instream.

These effects can be both additive and subtractive, depending on the land use.

Conclusions

These results only scratch the surface.

undefined water quality sources.

We can not claim to have truly defined any previously

This work suggests some fruitful directions to take this kind of research.

It seems obvious, both from a theoretical standpoint, and from our empirical results, that land uses close to the streams seem to be unusually important in determining instream constituent concentrations.

This would suggest that more work should be done closer to the streams than before.

Much more can be done, however.

could be easily monitored.

Constituent loadings into the watershed, their locations and timing

More effort could be spent in monitoring water quality during the course of storm runoff events to give better definition to the relationship between discharge and concentration.

More effort could also be given to distinguishing the water quality constituents whose delivery pathway primarily involves movement as, or adsorbed to, eroded sediment, and to those moving primarily as groundwater.

water quality.

Of course, more could be done in long -term, fixed station monitoring of instream

References

Illinois Environmental Protection Agency.

1978.

Pollution.

Task Force on Agricultural Nonpoint Sources of

Summary of the Agricultural Task Force Water Quality Plan Recommendation.

31 pp.

Wilkin, D.

C. and R.

C. Flemal.

1979.

A mass balance accounting procedure for estimating contributions to water quality.

J. Environmental Systems.

9(l):1 -16.

Wilkin, D.

C. and R.

C. Flemal.

1980.

J. Water Poll. Control Fed.

Feasibility of water quality improvement in three Illinois rivers.

52(2): 293 -298.

121

A REVISED PHYTOPLANKTON GROWTH EQUATION FOR WATER QUALITY MODELLING IN LAKES AND PONDS

James Kempf, John Casti and Lucien Duckstein

Department of Systems and Industrial Engineering

University of Arizona

Tucson, Arizona

85721

Abstract

A physiological model of nutrient uptake, based on membrane transport is combined with a phytoplankton biomass growth equation, based on internal nutrient limitation, to form a system of equations modeling phytoplankton growth which are capable of considerably richer dynamics than the

Michaelis- Menton -Monod model

(1l3) or the Droop model.

In particular, since the characteristic time scale of nutrient uptake is considerably faster than that of biomass increase, a singular perturbation problem results, leading to a relaxation oscillation similar to the van der Pol oscillator.

contrast with both the Michaelis -Mentor. Monod model and the Droop model, which were developed using

In steady state chemostat data, the present model would seem to be appropriate for batch cultures and lakes with long turnover times, where the assumptions of the chemostat steady state are not fulfilled.

The qualitative behavior of the model compares favorably with data on batch growth of phytoplankton from the literature.

Introduction

Algal cells raised under the physical -chemical conditions which, in the phytoplankton nutrition and aquatic ecosystem modeling literature, are called the chemostat "steady state ", are usually quite far fron steady state in a physiological sense.

The chemostat steady state is maintained by supplying enough nutrient externally so that the internal nutrient concentration of the phytoplankton does not change and harvesting off the resultirs growth of phytoplankton, so that the population size remains constant.

If phytoplankton are removed from a chemostat at steady state and allowed to increase in numbers until their integral nutrieri supply is exhausted, a quite different type of phytoplankton population results.

The final population size is often far higher than that of the chemostat steady state, and the cellular composition of the population is quite different (Bienfang, 1975).

A population at physiological equilibrium is more similar to a batch culture Ïr stationary phase, in which the cells may undergo morphological changes when the external and internal nutrient supply is exhausted (Fogg,

1975).

This distinction between the chemostat steady state and the ihysiological steady state is often not clearly drawn in the algal nutrition and aquatic ecosystem modeling literature.

The distinction becomes crucial when modeling lakes with very high turnover times (Hutchinson,

1957) or for explaining algal species succession.

In very large lakes and marine environments with low turnover times, the input of nutrients and removal of water containing phytoplankton occurs swiftly enough so that the chemostat is probably a good approximation.

In smaller lakes, however, outflows and inflows ten,' to be restricted, so that turnover times are higher, and the environmental conditions thus seer, better approximated by a batch culture.

Similarly, the transition in an algal sperien succession from one species to another usually occurs when the first species has exhausted the external nutrient supply.

Thus the physiological condition of the species being replaced is probably better approx.inzted by that of a stationary phase batch culture than that of a culture at the chemostat steady state, in which the cells are maintained in log phase through nutrient input.

The two most widely used r.oCcls for nutrient limited phytoplankton growth, the Michaelis- Menton-

Monod model (M3) (DiToro et al., 1971, 1977) are: the Droop internal nutrient model (Rhee, 1980) were both developed using experimental data from chemostat experiments.

In both models, the specific growth rate of the phytoplankton population, u, is a rectangular hyperbolic function of a nutrient concentration, q; being approximately linear in q for q small and appro>.inately constant in q for q large.

The difference is that, for the M model, q is the external nutrient concentration, while for the Droop model, q is the internal concentration or cell quota.

In addition, the specific growth rate becomes negative in the internal nutrient model, if q falls below q

, which is taken to be the level of q necessary for maintaining the cell's metabolic machinery inOgood order.

123

The internal nutrient nodel also requires an equation for the rate of nutrient uptake by the cell, and, in most cases, this is also of a rectangular hyperbolic form in the external nutrient concentration.

When both models are exatir:ed analytically near the chemostat stea4y state, the resulting dynamical behavior is quite similar (DiToro, 1980), suggesting that the M model would be the better choice, since it is the simpler.

In this paper, a model of phytoplankton nutrient uptake and growth, based on a simplified model of nutrient uptake, is developed and examined numerically and analytically.

The potential for relaxation oscillations similar to those in the van der Pol equation (Howard, 1979) or those discovered in a model for a grazing ecosystem (May, 1977; Kempf, 1981) is demonstrated numerically and a lower bound on the total nutrient in the culture or ecosystem is derived, above which relaxation oscillations can occur.

Numerical integration of the model results in a trajectory which is qualitatively similar to the results of a batch experiment (DeMarche et al., 1979) that measured internal nitrate concentration, and also to a case from the literature in which no measure;ert of internal nutrient concentration was made (Fogg, 1975) but which displayed an oscillating population size during the stationary phase of a batch culture.

The implications for aquatic ecosysi.er mcceling, in particular, and theoretical ecology, in general, are discussed.

The Model

The transport of nutrient across the algal cell membrane is a crucial step in nutrient uptake.

Membrane transport can be separated into two types, depending on whether or not the cell expends energy to facilitate the flow df transported substances.

If the process occurs strictly as a result of the electrochemical gradient for the transported substance, then transport is passive, while if energy is expended in the transport of the substance itself or to maintain an ionic gradient for a co- transported solute, the term active transport is used.

Membrane transport is perhaps best understood for the sodium -potassium ion pump in nerve cells (Hodgkin, 1964); but for phytoplankton nutrient transport, there is very little specific data.

Various models have been developed to explain both passive and active transport.

The most widely accepted is that enzymatic type proteins within the cell membrane latch onto substances outside the cell and either migrate across the cell membrane or change shape so that the portion of the molecule carrying the bound substance protrudes into the cytoplasm, where the substance is released.

In active transport, the affinity of the membrane protein for the transported substance is assumed to be enhanced either through the hydrolysis of ATP or through the binding of a co- transported solute

(Heinz, 1978).

Mathematical models for both passive transport (Heinz, 1978) and active transport

(Verhoff and Sudaresan, 1972; Heinz, 1978) have been developed.

In contrast with the above models, an experimental system with glucose pumping activity has been demonstrated in which no movement of a membrane protein is involved.

The system consists of a membrane in which two enzymes (a hexokinase and a phosphatase) are immobilized between two layers of a material impermeable to the enzymes' common intermediate (Thomas, 1976).

When the membrane is charged with ATP, glucose is pumped from the hexokinase side to the phosphatase side without any translocation of membrane proteins.

A mathematical model of this system, based on reaction -diffusion equations, has also been developed and studied both numerically and analytically (Kernevez, 1980).

Rather than embrace any of the above formulations, general dynamical features of phytoplankton nutrient uptake and mass balance considerations will be used to develop the nutrient uptake equation.

Evidence exists that phosphate is transported actively in Nitella translucens (Kuhl, 1974) and other species and that assimilation of nitrate and ammonia also requires ATP (Morris, 1974); however, since the exact nature of the mechanism behind active transport is not too well known in general (and may, in fact, be quite different for different types of transported solutes), it seems safer to base the model on the general dynamics of the process rather than on any particular mechanism.

Considering, for the moment, that no conversion of internal nutrient into cell material is taking place, the net flow of nutrient across the cell membrane will be the difference between the gross flux and the backward leakage rate (Heinz, 1978): q = gross uptake rate - backward leakage rate where q = internal cellular nutrient concentration (wtvl- 1cell -1)

Data from short term uptake e:,.Fneiments indicates that the gross uptake rate is approximately

Michaelis -Menton in fore in the external nutrient concentration, n (Rhee, 1980).

Theoretical considerations also suggest that the gross uptake rate probably obeys Michaelis- Menton kinetics, since enzymatic

124

type proteins are probably involved in the forward transport process (Heinz, 1978).

Since phytopiarkton have been observed, both in culture and in nature, to concentrate nutrient very strongly against the electrochemical gradient (Rhee, 1973; Bienfang, 1975), a Michaelis -Menton form for the backward leakage reaction seems inappropriate.

A more likely possibility is that the backward leakage reaction is substrate inhibited, so that at very high internal nutrient concentrations, the leakage rate decreases rather than saturating to some maximum rate.

The leakage rate would thus be approximately linear in q, for q near zero, achieve a maximum, for some intermediate q, and decrease toward zero, as q approaches infinity (see Fig. 1).

Such substrate inhibited kinetics are displayed by the uricase reaction, in which uric acid is converted by the enzyme uricase into allantoin in the presence of oxygen (Kernevez, 1980).

If substrate inhibited kinetics are assumed for the leakage rate, then the equation for uptake takes the form: vnn vqq q

(Kn + n) qll + K )

(1)

where vn, vg = respective maximum uptake rates (wtv1- 1time 1)

K1 = inhibition constant (wtvl- 1ce11 -1)

Kn, Kg = respective half saturation constants (wtvl -1 -cell-1)

Removing the assumption that no conversion of internal nutrient into cell materiallis taking place, the growth of particulate or fixed nutrient, p, will take place at a rate of up wtvl- time , where u is the specific growth ratelof theytop]ankton population.

Thus the cell pool will be "thinned out" at a rate equal to uq wtvl cell '.time

.

Including this term in Eq.

1 gives the final equation for the change in the cell pool: q vn'n

(Kn + n) -

vgq

(Kg

+q+K

2 uq (2)

Before proceeding further it might be helpful to summarize the two assumptions made in developing Eq. 2:

(1)

The uptake rate is the difference between a forward transport rate and a backward leakage rate.

This is in contrast to most developments in the literature (Rhee, 1980) which assume that the uptake rate is Michaelis -Menton in external nutrient, with perhaps an inhibition term due to increasing internal nutrient concentration, but in line with more general modelins of passive and active transport processes (Heinz, 1979).

(2)

The gross uptake rate is Michaelis- Menton and the backward leakage rate is substrate inhibited.

Both assumptions seem reasonable from a physiological standpoint, and are supported by general dynamic considerations (i.e., the ability of phytoplankton to concentrate nutrient strongly), although further experiments would be the only way to confirm this.

The functional form of the specific growth rate, u, was left unspecifie(; in the above discussion.

A reasonable form, developed by Droop (Rhee, 1980), expresses the specific growth rate as a saturating function of q, which becomes negative if q falls below a cellular maintenance concentration.

equation for the increase in particulate or fixed nutrient would then be

The c10

p =um(1 -q)

P =uP

(3)

where pm = maximum growth rate (time

-1) q0 = maintenance level of cellular pool (wtv11cel1 -1) p = particulate or fixed nutrient (wt-v1-1)

In batch culture or in lakes with long turnover times, the total amount of nutrient in the system will be constant.

Thus, assuming the lake or culture volume is constant, the sum of the external concentration, the total internal pool concentration, and the particulate concentration must be constant, in order to assure mass balance:

(4) n + a'g'P + p = nT

125

where nT = total system nutrient concentration (wt-v1-1) a = volume density of the cell (v1cellwt -1); (e.g., reciprical of the fraction of cell volume which is protein)

To facilitate the analysis, it is helpful if all the variables and parameters are rendered dimensionless, so comparisons between quantities are about at the same order of magnitude (Fife, 1979).

Let g = , P = q

'n

n =

17,-1-, n and T = tum, Eqs. 2 and 3 become:

P =

(1

- g)P = pP

(5a)

ßn

= (1 +n)

Yq

k2)

- PR

(5b)

1

1 where a = q0, ß = y q n

(

K qpm

), y = y q

(

Kqum

), and k =

K

KI

.

A now means derivative with respect to T.

To convert Eq. 4 to dimensionless form, note that if the volume density of the cell, a, is assumed constant, then Eq. 4 becomes:

N T = n + wQ + P

(5c) where w = aK and NT = KT; and Q = Pg is the nondimensional total cellular pool.

n

The nondimensional external nutrient concentration, n, can be eliminated from Eq. 5b by solving

Eq. 5c for n and substituting:

3(NT - wQ - P) g =

( 1

+ NT - w 0 1

-

P)

(1 +

Yq

+

42)

úg

(6)

Eqs. 5a and 6 can be rendered entirely in terms of Q by substituting g = P and using the chain rule to calculate Q.

The resulting equation system will be

P = (1 - I) -P

=

0(8T - wQ - P)

(1

+ NT - wQ - P) (p2 + PQ + kQ2)) P

(7a)

(7b)

Bifurcation Geometry

Experimental evidence (Droop, 1973; DiToro, 1980; Rhee, 1980) indicates that nutrient uptake is often an order of magnitude or more faster than growth.

Since the characteristic time of Eqs. 7 will be that of the growth reaction, ß and y will be very large.

Dividing both sides of Eq. 7b by ß, the system becomes (Fife, 1979):

R

= (1

- Q) p

EQ =

NT - wQ - P

7 + NT - wQ -

P) (p2 aFQ

PQ +

02)

(8a)

(8b) where o =

ß

and e = ß « 1.

Eqs. 8a and 8b constitute a singular perturbation problem, since the time derivative of Q is multiplied by a small parameter.

In the next section the dynamics of the system are described, using a nonstandard approach advocated in Diener and Poston (1980) and Lutz and Goze (1982), and the existence

12fi

of a relaxation type oscillation is demonstrated.

In order for a relaxation type oscillation to be possible, however, the zero set of Eq. 8b must have the folded structure shown in Fig. 2.

The zero set of Eq. 8b will be given by: r

= {(P,Q):

NT - wQ -

P

(1 + NT - w01 - P) aPQ

(p2

+ PQ + kQ2)

0}

(9) r = {(P,Q): h(P,Q) - g(P,Q) = f(P,4) = 01

Since the characteristic time scale of Q will be considerably faster than that of P, P can be considered a parameter for purposes of examining the geometry of r.

Because of the difference in time scales, r is often called the slow manifold (Zeeman, 1977).

Kubicek's method of continuation (Kubicek, 1976; Kernevez, 1980) was used to numerically calculate r for appropriate parameter values (see Fig. 2).

The method of continuation forms a set of differential equations for P and Q using the arc length along the curve as the independent variable.

The equations are numerically' integrated from a known point using the Adams -Bashforth method with maximal order four and a variable step size.

A correction step using Newton's method follows the integration.

be found in Kernevez (1980).

Details can

The points (P *,Q *) and (P * *, Q * *) in Fig. 2 will be such that:

(P*,Q*),(p**,Q**) E r

(10)

(P*,(1*),(P**,(1**) e {(P,(1): aQ = 0}

Following Stewart (1976) and Poston and Stewart (1978), these points will be called fold points.

An analytical solution of the two conditions in Eq. 10 for the fold points is impossible; however, the bifurcation geometry of r can be studied using an approach similar to that in Kernevez (1980).

For a particular species of algae, the parameters a, 8, y, w, and k will only change slightly with temperature.

The parameter which is most likely to determine whether or not r has the folded structure necessary for relaxation oscillations is therefore NT.

Changes in N will correspond to changes in the trophic state of the lake or other experimental systém under investigation, and therefore the bifurcation geometry of r with changes in NT will give information on how the dynamics of a particular algal species can change with trophic state.

From Eq.

9, if (P,Q) e r then

(P,Q) e {(P,Q): h(P,Q) = g(P,Q)}

This means that points on r will occur when the uptake function, h, and the leakage function, g, are, equal.

Considering g, Fig.

1 shows that, for a fixed value of P, g will achieve a maximum at some Qm and will approach zero as Q approaches infinity.

On the other hand, h will be monotonically decreasing in both P and Q, as can be seen by examining its derivatives:

2h _

2P

-1

(1 + NT - wQ - P)2

8Q

(1 + NT - wQ - P)2

Thus, if P is considered to be a slowly varying parameter, h will have a maximum when P = 0 and

Q = 0 and will decrease thereafter.

To motivate the following theorem, consider Figs. 3e and 3b, which show how r could not have two fold points.

Let the points on the graph of g and h where g and h achieve their maximum be called gm

127

and h

, respectively.

Then, as shown in Fig. 3a, if g is above h for all values of P and Q, the only intersection point between the two will be on the tailmof g. Simi9ariy, if P7 is the value of P where the graph of g, at its inflection point, intersects the graph of h and if Pr is the value of P where the graph of g, at its maximum, intersects the graph of h, then if Pig < Pm9, only one intersection will occur, as shown in Fig. 3b.

From the above comments, the following two criteria must be satisfied in order for three intersections between h and g to occur:

(1) gay < hm

(2)

Pmg < phg

The sequence in Fig. 4 shows how, for increasing P, three such intersections are generated.

These conditions on g h

Phg, and 879 are translated into conditions on the bifurcation parameter NT by the following theoYem:m

Theorem 1:

In order for r to exhibit two fold points, NT must satisfy:

NT > max[N1, N2]

(12) where

N1 a

2K + (1

- a)

N2

( 1 a

(K+2nw

- 2n) w [2K +

( 1

- o )]

2n(K+w)

[K + 2n(1 - a) + 4K12]

= cos {3 cos-1 (2K)} k > 4

K

= N

Remark:

NT = 5:

For the values of the parameters used to generate Fig. 4, namely a = 4.9, k =9, w = 0.5,

N1

= 2.33

N2 = -4.594

(13) and since NT = 5, Inequality (12) is satisfied.

Proof:

With respect tR the conditions in Points (1) and (2) above, the equations for g and h can be solved for gm, hm, Pm9, and IT in the following way.

Considering P as being fixed and differentiating g once with respect to Q gives:

4 aP(P2

-

(P2 + PQ

02) k42)2

(14)

Setting Eq.

IL to zero and solving for Q as a function of P gives:

Qm

g=

P9

K

At which g will have the value:

(15)

(16)

128

Note that Qm will be monotonically increasing with P, so that Qm will move to the right as P increases.

On the other hand, gm will be fixed with respect to changes in P.

Differentiating g again with respect to Q gives: aQ2

= QP

2 k2 Q3 - 6kOP2 - 2P3)

(P2 + PQ + kQ2)3

(17)

2

Inflection points will occur where aQ is zero.

Setting Eq. 17 to zero gives the following zero set:

0 3- kQ9P9 2-

Pg k2 = 0

(18)

This cubic will have three real roots if the cubic discriminait is less than zero:

4 k3

< 0

Solving for k gives: k > which is the condition on k in the statement of the thorem.

The middle root of the cubic in (18) will be giver by:

Q9 =

2Pg cos {3 COS

-1

K

(2K)}

9

Q9221 n

Again, Q9 will be monotone increasing with P.

The va'.er of g at the inflection point will be

9i

2an

(K + 2n + 4Kn2) which is, again, constant with respect to changes in P.

At P = 0, Q = 0, h achieves its maximum: hm

1

NT

+ NT

Substituting (16) and (23) into the condition in Point (1) gives: o

2K +1 <

NT

1 +NT

Solving for NT gives N1 in (12).

Phg can be found by equating gm and hm at Q = Qm:

(19)

(20)

(21)

(22)

(23)

(24)

129

a

2K + 1

NT -

[1 +

1,11g(1

+ K)

- Pm-(1 + K)]

(25) or

(26)

K + w

(

NT [2K +1 - a)]

Pig can be found in a similar way;

2an

(K + 2n + 4Kn2)

NT - P4(1 + 2K)

[1 + NT - P1P(1 + 2K)]

(27) or

K

K+ 2nw

( N

T

2an

[K + 2n(1 - a) + 4Kn2]

The inequality in Point (2) would then be:

K

( a \ K

//

[2K +(1 -o)] /< K +2nw \NT

2an

[K +2 (1 -a) +4Kn2]

(28)

(29)

Solving for NT gives N2 in (12).

An additional condition for relaxation oscillations is that the P = 0 isocline intersect the slow manifold on the unstable section between the fold points, as shown in Fig. 5.

If the intersection point between r and the set:

A = {(P,Q): P = á } _ {(P,Q): P = 0, P # 0}

(30) is denoted by (PI,Q1), then the condition for relaxation oscillation is:

Q* < Q

< Q

**

< PI

(31)

The following theorem gives Q1 as a function of the parameters: a[NT {kw(ak -

1) + (1 - a)} - a]

Q1

[Kw(a2 + a - 1) + a(w - a) - (a - 1)]

(32)

Proof:

Since Q1E{An r }, substituting the value of P in (30) into the equation for r gives:

3

KwQl +

QI

1 1

13-[°15(1-6)+k+0 a -1 a

2

NT[k á] á }QI + {NT

2

QI QI a 2

(33)

Factoring out a QI2 and solving for Q1 gives Eq. 33.

Dynamics

As mentioned in the previous section, the singular perturbation problem posed by Eqs. 7 will evolve on two time scales: a fast scale for Q and a slow scale for P.

The initial change in Q will be rapid; so that, before P changes appreciably, the trajectory will have already approached to within an infinitesimal distance of r.

There are a number of analytical approaches which have been used to study singular perturbation problems of this type (Fife, 1979; Diener and Poston, 1981; Lutz and Goze, 1982; Nayfeh, 1981).

One of the most attractive is nonstandard analysis (Diener and Poston, 1981; Lutz and Goze, 1982).

The small parameter E in Eq. 7b is formally set to an infinitesimal number (Robinson, 1974) instead of considering limitirc, behavior for small finite E.

While, in the numerical example in Fig. 6, a is anything but infinitesimal, the use of infinitesimals makes it easier to talk about what happens when a finite e becomes small.

Lutz and Goze (1982) formally prove the existence of relaxation oscillations in systems such as (7), so comments here will be limited to a discussion of the general behavior of the flow in the

130

state space.

Define the halo of a set, SeIR n as the set of points infinitely near S.

the system in Eqs. 7, define:

Also, with reference to

A+ _ {(P,Q): f(P,Q) > 01

(34a)

A" _ {(P,Q): f(P,Q) < 0}

(34b) and: r+ = {(P,Q): P > -10;011 (35a) r

= {(P,Q): P <

-1,;01}

(35b)

Then for (P,Q)eA

+,

Q > 0; while for (P,Q)cfl ,Q < O.

Since the Q equation will equilibrate much faster than the P equation, the flow in the Q direction will be almost perpendicular to the slow manifold, until it is within the halo of the slow manifold.

There it sill level out and flow along the slow manifold, it the direction of increasing P, if the flow is in r or in the direction of decreasing

P, if the flow is in r".

When the flow on the slow manifold reaches the upper fold point gt (P**,Q * *), the fast foliation in the Q direction will push the flow down onto the lower sheet.

Here, P < 0, so the flow will be to the left, in the direction of decreasing P.

At the lower fold point, (P *,Q *), the opposite process takes place and the result is a relaxation oscillation, as shown in Fig.

5.

Such behavior is called "slaving" by Haken (1978).

lFigs. 6 area numerical integration of Eqs. 7, with NT = 5.0, o = 4.9, w = 0.5, k = 9.0, a = 0.8, and -= 29.5.

Initial conditions were P(0) = 0.1 and Q(0) = 0.1.

Gear's stiffly stable method was used in the integration, since the difference in time scales between the two equations makes the system stiff.

The oscillating nature of the solution is obvious both from the flow in the state space, in Fig. 6a, and from the time trajectories, in Figs. 6b and 6c.

Comparison with Experimental Data

DeMarche et al.

(1979) report on an experiment in which the diatom Skeletoma costatem was raised in batch culture arc both the population size, p, and the internal

nutrient poor -o Vtrate,

q, were monitored.

Samples of the culture were taken at regular time intervals, and the population size was determined by measuring particulate nitrogen concentration in the samples.

The internal nitrate pool concentration was measured by sonicating a portion of the sample and measuring the resulting increase in the medium nitrate concentration.

p.

In Fig. 7, the data of DeMarche et al.

(1979) are replotted as a state space plot, with q against

Initially, the internal nutrient concentration rose very rapidly, over a period of less than 0.2

day, without any change in the population size.

The population size then began to increase more slowly; and, as it did so, the internal nitrate concentration also decreased slowly, until about 2.8 day into the experiment.

At this point, q decreased quite suddenly to near zero, again over a period of about

0.2 day, while no large change in p occured.

The experiment was terminated at this point.

The qualitative similarity between the experimental data, plotted in Fig. 7, and the numerical integration, in Fig. 6, is striking.

The fast initial rise in the internal concentration and the drop at the start of the oscillation match in both, as does the movement along the slow manifold.

tunately, the experiment was terminated before the oscillation could really develop.

Unfor-

Fig. 8 displays the results of an experiment in which log phase Monodus subtemaneus cells were transferred into a medium containing no nitrogen (Fogg, 1975).

After the internal nitrogen pool was exhausted, the population size began to oscillate.

Since the cells initially had no external nitrogen source, the oscillation developed sooner than would have been the case if nitrogen had been available.

Discussion

In aquatic ecosystem models which use the M3 model or the Droop model, it is not possible to obtain an unforced limit cycle or relaxation oscillation without another "external" state variable.

Addition of another trophic level, for example, zooplankton predators, can lead to population cycles of a predator -prey type (Adachi and Ikeda, 1978; Arnold, 1978) which have been widely discussed in the theoretical ecological literature (May, 1978).

Such a system is ecologically quite distinct from the system presented above, in which a rapid change in the physiological state of a single species is

131

causing a population cycle.

Another ecosystem in which a physiological variable might be causing oscillations is the cycles of small mammal populations in the Arctic (Finerty, 1980).

The lynx -hare pelt data from the Hudson Bay

Company records are one of the most widely cited pieces of evidence for limit cycle oscillations in predator -prey systems (but see May (1980) for questions on the data's validity).

Statistical examination of the data for a number of small mammal populations in the Arctic (Finerty, 1980) suggests that the predator population cycles are actually being forced by a population cycle in their chief food supply, the Arctic hare, rather than causing the cycle directly.

Finerty speculates on a number of possible causes for the hare population cycle, one of which is the kind of physiologically caused periodicity discussed above.

In general, the internal physiological state of an organism would be expected to equilibrate on a more rapid time scale than the reproductive state of the entire population.

To the extent that the reproductive state is influenced by the physiological state, a separation of the dynamics might occur, in which the internal physiological state forms a slow manifold upon which the population size evolves.

Wherever the physiological state manifold has a folded structure, like that of the internal nutrient manifold in the above model, the physiological state variable will change rapidly to a new quasi -equilibrium, and the population size will adjust more slowly.

Such a phenomenon could also occur between two different species with radically different characteristic growth rates, for example, whales and krill; with the equation for the species having the higher growth rate forming the slow manifold upon which the system evolves.

Thus, coupling between an organism's physiology and the environment might be responsible for extremely complex population dynamics, which have previously been ascribed to general mass action type interactions between organisms at two trophic levels.

A three variable system, with one physiological variable forming a slow manifold, might exhibit the type of chaotic dynamics reported by Rbssler (1979).

Two possible examples might be the bloom -dieoff cycles in eutrophic ponds, reported by Barica (1974), and the annual species succession of phytoplankton in lakes (Hutchinson, 1957).

For such systems, the population trajectories would look as if they were being generated by a stochastic process, even though the underlying dynamics were deterministic.

Conclusions

A physiologically derived phytoplankton growth model has been presented in which the phytoplankton population size can exhibit relaxation oscillations for certain values of the parareters.

The model approximates conditions in batch culture or in a self -contained lake, for which the total nutrient concentration in the ecosystem is relatively constant.

The internal nutrient equation isocline forms a slow manifold, to which the flow of the dynamical system is strongly and quickly attracted, and upon which the system evolves.

If the isocline for the phytoplankton population size intersects the slow manifold on the unstable section, oscillations in the population size can occur.

Evidence supporting the model was presented from a batch experiment in which both the population size and the internal nutrient concentration were measured, and from the large body of data in the literature on batch growth of phytoplankton, where no internal nutrient concentration measurements were made.

The implications of the model for ecosystem modeling in general have been discussed.

A comparison with another system, the Arctic small mammal populations, in which population oscillations occurred was made.

The possible role of physiological variables in ecosystem models has also been mentioned.

Acknowledgements

This research was supported by NSF Grant CEE 8110778, "Modern Stability and Dynamical Concepts in

Water Resources Management."

We also wish to thank Dr. H. Haken of the Institut fur Theoretische

Physik, Universität Stuttgart, Stuttgart, West Germany, for the opportunity to visit in the summer of

1981, during which many of the seminal ideas in this paper were developed.

Dr. Tim Poston also played a large role in clarifying the authors' thoughts on the dynamics of aquatic ecosystems.

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M.

1978.

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Barica, J.

1974.

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132

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1975.

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1977.

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1980.

kinetics.

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R.

1973.

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9:264 -272.

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1979.

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1980.

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WI.

E.

1975.

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University of Wisconsin Press, Madison,

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1978.

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1978.

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1964.

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N.

1979.

Nonlinear oscillations.

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E.

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1980.

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1980.

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1976.

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1974.

Phosphorous.

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1982.

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May, R.

1977.

269:471 -477.

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May, R.

1978.

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1980.

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1974.

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1981.

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1978.

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1980.

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1974.

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1979.

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1976.

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1976.

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134

0.517

F(0) 0.414

0.310

0.207

0.103

0.828

0.724

0.621

0.000

0.000

1.600

3.200

4.800

o

6400 8.000

9.600

10.000

8.333

6.687

0 5.000

3.333

1.867

Figure 1.

Shape of the substrate inhibited leakage function

0.828

0.724

0.621

0.517

F(0) 0.414

0.310

0.207

0.103

0.000

0.000

1.600

3.200

4.800

0

6.400

8.000

9800

Figure 2.

Slow manifold, f(P,Q) = 0, determined by

Kubicek's method of continuation for NT = 5.0, a = 4.9, w = 0.5, and k = 9.0

0.697

0.610

0.523

0.435

F(0)

0.348

0.281

0.174

0087

0.000

0.000

0.333

0.667

1.000

0

1333 .1.667

2.000

Figure 3a.

Relation between g(P,Q) and h(P,Q) for gm < hm

135

Figure 3b.

Relation between g(P,Q) and h(P,Q) for

Pmg > Phg

1.033

3.011

e.011

1411 0411 e.000

0.013

o.311

1.311

3403 e.300

an

1411

Figure 4a.

Relation between g(P,Q) and h(P,Q) for

P < P*

Figure 4b.

Relation between g(P,Q) and h(P,Q) for

P* < P < P **

0400 an

1400 I.e00

3.400

0.110

3.011

Figure 4c.

Relation between g(P,Q)

P ** < P and h(P,Q) for Figure 5.

Flow in the (P,Q) state plane, showing fast flow perpendicular to slow manifold and relaxation oscillation

136

6410

1.0

1.0

100

1.0

I.a

1410

000

0.00

-1410

-140-040 0410 0410

1410 1410 1410

1410 1.00 140 Ca001

-1.00

000 0.0 0.40 040 040 1.00 1.0 1.40

1410 1410

141005' net

Figure 6a.

State plane plot of P vs. Q for numerical integration of Eqs. 8 showing relaxation oscillation with all parameters the same as in Fig.

2 and e = 2915.

Gear's stiffly stable method was used for the integration and P(0) = 0.1, Q(0) = 0.1.

Figure 6b.

Time trajectory plot of P for numerical integration of Eqs. 8

6.00

6410

1.60

1410

1.00

1m

1 1 1 1 1 1 1 1 1

I

20

40

'

6 l

'

Particulate nitrogen (p) (yg atoms) i__I

80 i

i

0410

-1410

0-00 0.0 0.40

0.0 0.00

140 140 1.0 1410

1410 0.000*

TOE

Figure 6c.

Time trajectory plot of Q for integration of Eqs. 8 numerical

Figure 7.

Replotting of data from DeMarche et al.

(1979), Fig. 3, as a state space plot of particulate nitrogen, p, vs. internal nitrate pool, q, showing fast -slow transitions prior to extensive growth in p and prior to aborted oscillation.

Fast transitions are shown as double arrows, while slow flow is shown as single arrows.

137

400

á

E

300

743 ar

>

200

100 0cc

0 o o o o o

I

2

3

4

5 6

Days of nitrogen starvation

7

40

Figure 8.

Replotting of data from Fogg (1975), Fig. 19, p. 56, showing oscillation of population size in a nitrogen limited batch cul ture during "steady state"

138

MUTAGENIC ACTIVITY OF SELECTED

ORGANIC COMPOUNDS TREATED WITH OZONE

Leslie Irwin and Cornelius Steelink

Department of Chemistry, University of Arizona

Tucson, Arizona 85721

Introduction

In the early 1970's it was discovered by several groups of investigators that trihalomethanes (THM) were present in some American drinking water supplies, and that their presence was due primarily to the process of chlorination.

Bellar and co- workers (1974) pinpointed the appearance of trihalomethanes to the addition of chlorine in the water treatment process.

Symons and co- workers, in the National Organics Reconnaissance Survey (1975), reached the conclusion that treated water contained higher levels of trihalomethanes than untreated water supplies, as surveyed in cities across the United States.

In 1978

Glatz and co- workers reported finding increased mutagenic activity in chlorine -treated water in several

U.S. cities.

In 1976 and 1977 Rook published evidence that certain natural organic substances, such as humic and fulvic acids, might be serving as precursors for trihalomethane formation.

He pointed out that aromatic compounds with meta dihydroxy groups produce a high level of chloroform subsequent to chlorination.

Other investigators have succeeded in demonstrating formation of chloroform and other chlorinated organics in treated waters (Cheh et al., 1980; Maruoka and Yamanaka, 1980).

Because of these findings, alternatives to chlorination are being considered and studied.

One of these alternatives is ozone treatment.

Ozone is a proven water disinfectant, but little is known about the products of its reaction with complex organic compounds.

This project examined one aspect of the effect of ozone on natural water; that is, the effect on the mutagenic activity of organic compounds that may be present in ozone -treated waters.

Model Compounds

To study this effect, we chose six organic compounds to serve as models for organic material in natural or industrial process water.

These compounds include (figure 1):

1.

2.

3.

4.

5.

6.

Phenol.

Resorcinol.

Rutin, chosen to represent fulvic acid because of its meta -dihydroxylated benzene ring.

Quercetin, a known mutagenic flavanol, is obtained by cleavage of the glycosidic bond of rutin.

Lignin, represented here by coniferyl alcohol which is one of its monomers.

Lignin is present in pulp mill effluent and in leachate from woody plants.

Tannic acid, a hydrolyzable tannin, which is an ester of a sugar (usually glucose).

Tannic acid is also present in leachate.

Humic acid, the last model compound, is not represented in the figure, since it is a large complex molecule containing many phenolic, quinoid and benzenecarboxylic acid groups.

For this project a commercially prepared salt of humic acid was used (Aldrich sodium salt).

Experimental

These compounds were tested for mutagenic activity in the Ames Salmonella /mammalian microsome assay.

The Ames test is a reverse mutation assay utilizing specially developed strains of Salmonella typhimum/um.

These strains require histidine for growth, but can be reverted to histidine prototrophy by certain mutagens.

The strains used in these experiments were TA98 which detects frameshift mutation, and

TA100 which detects base -pair substitution types of mutation.

A standard agar incorporation assay was done (Ames et al., 1975), with bioactivation supplied by rat liver S9 fraction (induced with phenobarbital).

Each compound was tested over a range of concentrations with no ozone treatment; this was a dose -response experiment.

Next an ozonation experiment was

139

done for each compound: a single concentration (100 ppm) of the compound was tested for mutagenic activity against varying times of ozonation.

Positive controls were N- methyl -N'- nitro -N- nitrosoguanidine, an alkylating agent that is positive in strain TA100 withand without bioactivation, and benzidine, an aromatic amine which is positive in strain TA98 with bioactivation.

The results of each experiment were expressed as the mutation index: this is the ratio of revertant colonies on the test plate to revertant colonies on the control plate.

This ratio must be greater than 2.0 in order to demonstrate an increase in mutagenicity over control.

An analysis of variance was performed on all data from dose -response experiments and from the ozonation experiments.

For the ozonation experiments ozone was generated from oxygen by means of electrical discharge.

The ozone was passed into a 200 -ml aqueous solution of the organic compound for a period of 2, 5, 10 or 15 minutes.

Ozone output was measured by a standard iodometric titration (Standard Methods for the Examination of Water and Wastewater, 14th edition).

The ozone available to react with the model compounds was determined by measuring the amount of ozone that was not utilized by a water blank in a given time period.

The amount of ozone that reacted with the model compound was determined by the difference between the excess ozone given off by the organic solution and by the water blank.

Results And Discussion

Ozone Utilization

The results of ozone utilization are shown in figure 2; ozone consumption was recorded as moles ozone utilized per mole of organic substrate.

The amount of ozone consumed by each model compound appears to fall into a natural grouping based on the structural complexities of the compunds.

Phenol and resorcinol utilized the least amount of ozone and their rate of ozone consumption had stabilized within 15 minutes.

At the other end of the spectrum humic acid utilized more ozone than and its rate was still increasing after 15 minutes of ozone treatment.

any other model compound

This is probably a conservative estimate of ozone utilization by humic acid, because a conservative value was used for the molecular weight when calculating the molar ratio of ozone consumption.

The decrease of model compound concentration during the course of ozonation was measured bytheFolin-

Ciocalteu test for phenolics (Standard Methods for the Examination of Water and Wastewater, 14th edition).

This was done for four model compounds and the results are shown in figure 3.

The decrease in concentration of phenol was nearly linear over 15 minutes and ozone had destroyed virtually all measurable phenol.

The other compounds exhibited a rapid decrease to a concentration between 10 to 30 ppm, followed by a much slower rate of decrease.

Mutagenicity Studies

In the dose -response experiments (in which compounds were tested for mutagenicity without ozone treatment) the analysis of variance detected no correlation between increasing concentration and increase in mutagenic activity.

All compounds (except rutin) exhibited levels of mutagenic activity that were similar to control levels (The analysis of variance did indicate a significant interaction between strain, bioactivating system and compound; this interaction is due to slightly increased mutagenic activity in strain TA100 (with $9) on the part of rutin (figure 4).

This mutagenic activity was not reproducible between experiments, and the increase in activity was attributed to an unidentified impurity).

The lack of a dose -response relationship indicates that, under the conditions of this study, these model compounds are not mutagenic prior to water treatment.

In the ozonation experiments the model compounds demonstrated no increase in mutagenic activity after ozone treatment, with one exception.

This exception was lignin, which did exhibit an increase in mutagenic activity after two minutes of treatment with ozone; this activity returned to control levels with longer ozone treatment.

The analysis of variance clearly indicates the increased response of lignin at two minutes (figure 5).

One interesting point about this observed increase in mutagenic activity is that the responses of the bacterial tester strains differed.

Lignin treated with ozone for two minutes exhibited increased mutagenicity in strain TA98 with and without bioactivation, but the response without the bioactivating system was somewhat greater (figure 6).

Tested against strain TA100, the treated lignin demonstrated a weak response only in the absence of the bioactivating system; there was no increase in mutagenic activity in the presence of the bioactivating system (figure 7).

It appears from this that a transient direct -acting mutagen is being formed and then rapidly destroyed by ozonation.

While these increases in mutagenic acitivity are statistically significant, they represent only a weak mutagenic response and may not have biological significance; but it will require further testing to determine this.

This project has demonstrated several things: first, the usefulness of the Ames test in assessing the potential mutagenic effects of a water treatment process, and second, the production of a transient mutagenic species upon ozonation of lignin.

The model system presented here could be used to study more completely the effect of ozone treatment on lignin in water supplies.

140

Acknowledgment

This work was supported in part by the Office of Water Research and Technology, A -094, U.S. Department of Interior, Washington, D.C., as authorized by the Water Research and Development Act of 1978, and in part by the U.S. Environmental Protection Agency, Office of Research and Development,EPAN0.CR- 807363.

References Cited

Ames, B.N., J. McCann and E. Yamasaki.

1975 .

Methods for detecting carcinogens and mutagens with the

Salmonella /mammalian microsome mutagenicity test.

Mutation Research, 31: 347 -364.

Bellar, T.A., J.J. Lichtenberg and R.C. Kroner.

1974 .

The occurrence of organohalides in chlorinated drinking waters.

J. American Water Works Association, 66: 703 -706.

Cheh, A.M., J. Skochdopole, P. Koski and L. Cole. 1980.

Nonvolatile mutagens in drinking water: production by chlorination and destruction by sulfite.

Science, 207: 90 -92.

Glatz, B.A., C.D. Chriswell, M.D. Arguello, H.J. Svec, J.S. Fritz, S.M. Grimm and M.A. Thomson.

1978.

Examination of drinking water for mutagenic activity.

J. American Water Works Association, 70:

465 -468.

Maruoka, S. and S. Yamanaka.

1980.

Production of mutagenic substances by chlorination of waters.

Mutation Research, 79: 381 -386.

Rook, J.J. 1976.

Haloforms in drinking water.

J. American Water Works Association, 68: 168 -172.

Rook, J.J. 1977.

Chlorination reactions of fulvic acids in natural waters.

Environmental Science and

Technology, 11: 478 -482.

"Standard Methods for the Examination of Water and Wastewater," 14th edition, American Public Health

Association., Washington, D.C., 1974, pp. 456 -457, 607 -608.

Symons, J.M., T.A. Bellar, J.K. Carswell, J. DeMarco, K.L. Kropp, G.G. Robeck, D.R. Seeger, C.J. Slocum,

B.L. Smith and A.A. Stevens.

1975.

National Organics Reconnaissance Survey for Halogenated Organics.

J. American Water Works Association, 67: 634 -647.

141

OH

H o

Phenol

Resorcinol

OH

HC= CHCH2OH

Rutin

GGGG

H

OH

Coniferyl Alcohol

(monomer of Lignin)

COON

HO

H

G= Gallic Acid

Tannic Acid

Figure 1.

Model compounds.

Humic acid (Aldrich sodium salt) is the only model compound not shown.

142

Figure 2.

Utilization of ozone by model organic compounds.

Ozone utilization is calculated as a molar ratio.

All conditions of ozonation were held constant except for time.

Ozone dose = 7.1 mg /L.

i0

Time of Ozonotion (mini

15

Figure 3.

Decrease in model compound concentration during ozonation.

Standard curves of model compound concentration were constructed using the

Folin -Ciocalteu (F -C) test for hydroxylated aromatics; the same compounds were then measured by the

F -C test subsequent to ozonation.

145

Time of Ozonotion (min)

.5

03

59 i.pnImaN 5.9

7.59. .59

O. ram.un 59

Figure 4.

Analysis of variance for dose response experiment.

The significant interaction (S9 x strain x compound) does not involve concentration, but indicated a weak mutagenic response in strain TA100 with bioactivation when tested against rutin.

Mutation index must exceed 2.0 to indicate a significant increase in mutagenic activity

(log 2 = 0.301).

0 ieil<

I iz151.

IFaMrcina

ixln.

II xja iz5i.

RNm h9n.adel

I usmn

S -9 e Strain x Compound Interaction (Dose Response)

II

Iz151.

qummx5

Figure 5.

Analysis of variance for ozonation experiment.

Only lignin at two minutes of ozone treatment exceeded level of significance.

Further ozonation of lignin caused mutagenic activity to return to control levels.

as

= oz s a

9

T,

0

07a6 as oe

7 r14-

r

-a2

-03

-oa

:5

2mirt

= xx

2

'4

15nnJ

óI

=

I£i5min

Compound x Time Interaction (Ozonation Experiment)

I

144

Figure 7.

Mutagenic response of strain

TA100 to ozone- treated lignin.

The mutagenic activity is increased over control only in the absence of the bioactivating system.

145

Figure 6.

Mutagenic response of strain TA98 to ozone- treated lignin.

The mutagenic activity is greater in the absence of the bioactivating system than in its presence.

Key Word Index of Arizona Section (AWRA) Proceedings

The following index is a compilation of all articles published through the auspices of the Arizona

Section of the American Water Resources Association (AWRA).

The index contains articles from the proceedings of meetings held jointly with the Hydrology Section of the Arizona Academy of Science.

In addition, proceedings of three symposia sponsored by the Arizona Section (AWRA) are also included.

The listing is arranged in alphabetical order with each key word in a title appearing as the leading entry in the index.

Each title may have as many as three keywords within the index.

Because an entry may begin midway through a title, the end of a title is identified by the symbol S.

Following the title, the author(s) is identified.

The volume or symposia number is listed after the author.

Volumes (identified by the label Y #) relate to publications of the series Hydrology and

Water Resources in Arizona and the Southwest (Volumes 1; 1971 through Volume 11;

1981).

Symposia can be identified from the following list:

P1 - Symposium on Water Conservation Alternatives

(April 12, 1979; Phoenix, Arizona)

P2 - Symposium on Flood Monitoring and Management

(October 26, 1979; Tucson, Arizona)

P3 - Symposium on Water Quality Monitoring and Management

(October 24, 1980; Tucson, Arizona)

EXAMPLE:

Collective Utility Viewpoint $ Comparison of Water Pricing Structures from a

Bill Metter and Lucien Duckstein - V1

The actual title of the article is "Comparison of Water Pricing Structures from a Collective

Utility Viewpoint "; the $ symbol indicating the title beginning (or ending).

The authors appear on the following line along with the publication source, V1 (indicating Volume 1; 1971 in Hydrology and Water

Resources in Arizona and the Southwest).

Additionally, the title could be found using the keyword

Water Pricing.

147

Acid

Agriculture (also; Irrigation)

Aquifer (also; Ground -Water)

Arid (also; Desert, Semiarid)

Attitudes (also; Water Awareness)

Bacteria

Biologic

Burning (also; Fire)

CAP

Central Arizona Project

Chaparral

Chemical

Coal

Collective Utility

Colorado River

Conservation

Contamination (also; Pollution)

Copper

Desalination (also; Osmosis)

Desalt

Desert (also; Arid, Semiarid)

Development

Earth Fissure (also; Subsidence)

Economic

Effluent (also; Waste -Water)

Environment

Ephemeral

Erosion

Error Analysis (also; Regression)

Evaporation (also; Transpiration)

Fire (also; Burning)

Flood (also; Storm)

Forage

Forest

Geomorphic

Goals

Ground -Water (also; Aquifer)

Hydrologic

Hydrology

Infiltration

Information

Irrigation (also; Agriculture)

Lysimeter

Management

Mexico

Mine

Mining

Models (also; Simulation)

Multi -

Multiple -Use

Municipal (also; Residential, Urban)

Nitrogen

Nutrient

Osmosis (also; Desalination)

Pine

Planning

Plant (also; Vegetation)

Policy

Politics

Pollutants

Pollution (also; Contamination)

Precipitation (also; Rain, Snow)

The following list contains the keywords which were used to compile the index.

Associated with some of the keywords are related keywords which may be used to locate desired material.

Price (also; Water Rates)

Probability

Public

Pumping

Quality

Rain (also; Precipitation)

Range

Recharge (also; Transmission Losses)

Reclamation (also; Rehabilitation, Revegetation)

Recreation

Regression (also; Error Analysis)

Rehabilitation (also; Reclamation, Revegetation)

Reservoir

Residential (also; Municipal, Urban)

Revegetation (also; Reclamation, Rehabilitation)

Runoff

Safe Drinking Water Act

Salinity

Salt

Saltcedar

Sediment

Seepage

Semiarid (also; Arid, Desert)

Simulation (also; Models)

Snow (also; Precipitation)

Soil

Solar

Stochastic

Stock

Storm (also; Flood)

Streamflow

Strip -mined

Subsidence (also; Earth -fissures)

Temperature

Thunderstorms

Time

Tracer

Transmission Losses (also; Recharge)

Transmissivity

Transpiration (also; Evaporation)

Tree -Ring

Uncertainty

Unit Hydrograph

Universal Soil Loss Equation (also; USLE)

Urban (also; Municipal, Residential)

USLE (also; Universal Soil Loss Equation)

Vegetation (also; Plant)

Waste -Water (also; Effluent)

Water Awareness (also; Attitudes)

Water Consumption

Water Harvesting (also; Water Impoundment, Wax)

Water Impoundment (also; Water Harvesting)

Water Quality (see Quality)

Water Rates (also; Price)

Water Resource

Water Rights

Water Supply

Wax (also; Water Harvesting)

Weather Modification

Weathering

Wetlands

Well

148

Key Word Index of Arizona Section (AWRA) Proceedings

Acid Drainage From Abandoned Mines in the Patagonia Mountains, Arizona

Acid:

$

Sheila A. Dean - P3

Acid Solutions in Selected Arizona Soils

$ Penetrability and Hydraulic Conductivity of Dilute Sulfuric

S. Miyamoto, J. Ryan and H. L. Bohn - V3

Its Potential for Improving Irrigation Water Quality $ Sulfuric

H. L. Bohn and R. L. Westerman - V1

Agricultural and Municipal Groundwater Requirements in the Tucson Area, Arizona

Edward P. Glenn, James W. O'Leary and Barney P. Popkin - V11

Agriculture, and Implications for Urban Water Supply: The Tucson Case

$ Jojoba: An Alternative to the Conflict Between ... Kennith E. Foster and N. Gene Wright - P1

Agricultural Water Budget

$ A Potential for Water -Efficient, C44 Halophytes in Arizona's

$ Rising Energy Prices, Water

Demand by Peri -Urban ... H. W. Ayer and D. W. Gapp - V8

Agriculture s The Price of Water in Western

David L. Wilson and Harry W. Ayer - V11

Aquifer Analysis

$ Application of Finite Element and Computer Graphics Techniques in

D. F. O'Donnell, L. G. Wilson and W. O. Rasmussen - V5

Aquifer Characteristics Using Drillers' Logs

Kandy G.

Kisser and Jill S. Haimson - VII

$ Estimations of

Aquifer Test Error Analysis $ Aspects of

Ahmed M. Benbarka and Donald R. Davis - V11

Aquifer Tests

$ Correcting Tidal Responses in Observed Water Well Levels During Coastal

Barney P. Popkin - V11

Aquifer

$ Geostatistical Analysis and Inverse Modeling of the Avra Valley

Peter M. Clifton and Shlomo P. Neuman - V11

Aquifer

$ Transmissivity Distribution in the Tucson Basin

D. J. Supkow - V2

Aquifers s The Application of Step -Drawdown Pumping Tests for Determining Well Losses in Consolidated

Rock ... V. W. Uhl, Jr., V. G. Joshi, A. Alpheus and G. Sharma -

V5

Arid Environment. Tucson, Arizona

$ Water Quality Problems of the Urban Area in an

G. Hansen - V8

Arid Environments $ Estimating Potential Evapotranspiration in

Z. Osmolski and L. W. Gay - V11

Arid Lands Vegetable Production

$ Mulching Techniques for

R.

W. Peebles and Norman F. Oebker - V1

Attitudes of Arizona Water Resource Leaders

$ Man -Nature

Roger A. Kanerva and David A. King - V2

Bacteria Removal and Infiltration in Soil Columns

$ The Effect of Increasing the Organic Carbon Content of Sewage on Nitrogen, Carbon, and ... J. L. Lance and F. D. Whisler - V5

Bacterial Indicators in Assessment of Water Quality of the East Verde River

$ Use of

Patrick V. Athery, Marilyn J. Urbina and Milton R. Sommerfeld 1111

Bacterial Water Quality Investigation of Canyon Lake

$ A

W. F. Horak and G. S. Lehman - V4

Biological Problems in the Grand Canyon $ Chemical and

G. C. Slawson, Jr. and L. G. Everett - V3

Burning on Surface Water Quality $ Some Effects of Controlled

Bruce D. Sims, Gordon S. Lehman and Peter F. Ffolliott - V11

CAP Intake Area

$ Water Quality Study of Lake Havasu, Arizona near the

Simon Ince, David L. Kreamer, Don W. Young and Charles L. Constant - V6

CAP on Lake Havasu's Thermal Regime

$ Future Effects of the

David Kenneth Kreamer - V6

Central Arizona Project Concept of Operation

$

Frank C. Springer, Jr. and Albert L. Graves - V9

Central Arizona Project Water Allocation Model System

$ The Arizona Water Commission's

Philip C. Briggs - V7

Central Arizona Project

$ An Economic Analysis of the

James L. Barr and David E. Pingry - V7

Central Arizona Project

$ Economic Adjustment to a New Irrigation Water Source: Pinai County, Arizona and the ... Mark A. Boster and William E. Martin - V5

Chaparral to Grass to Increase Streamflow

$ Converting

Paul

A.

Ingebo - V2

Chaparral Watershed in Central Arizona

$ Sediment Production from a

Thomas E.

Hook and Alden R. Hibbert - V9

Chaparral

$ Root System of Shrub Live Oak in Relation to Water Yield by

Edwin A. Davis - V7

Chemical and Biological Problems in the Grand Canyon $

G. C. Slawson, Jr. and L. G. Everett - Y3

Chemical Character of a Perched Water Zone, Harquahala Valley, Arizona

$ Origin, Development and

Charles G. Graf - V10

149

Chemical Hydrographs in Groundwater Quality Studies

S The Use of

Kenneth D. Schmidt - V1

Chemical Oxygen Demand of the Antitranspirant, Folicote

$

R. H. Garrett and B. E. Kynard - V7

Chemical Quality of Streamflow by an Interactive Computer Model

William O. Rasmussen and Peter F. Ffolliott - V10

S Prediction of the

Coal Mine Lands

$ Hydrologic Evaluation of Topsoiling for Rehabilitating Black Mesa

Frank G. Postillion - V10

Coal Mining Effects on Water Quality of the Tongue River, Wyoming

S Preliminary Results from a Study of

Richard D. Olsen and Edward H. Dettmann - V6

Collective Utility of Exchanging Treated Sewage Effluent for Irrigation and Mining Water S

Stephen C. Ko and Lucien Duckstein - V2

Collective Utility Viewpoint

$ Comparison of Water Pricing Structures from a

Bill Metler and Lucien Duckstein - Vi

Collective Utility: A Systems Approach for the Utilization of Water Resources

Edwin Dupnick and Lucien Duckstein - Vi

Colorado River Corridor of Grand Canyon

$ Water Quality Analyses of the

Brock Tunnicliff and Stanley K. Brickler - V10

$

Colorado River Driftwood in the Grand Canyon S Tree -Ring Dating of

C. W. Ferguson - V1

Colorado River System

$ Salinity Control Planning in the

John T. Maletic - V4

Colorado River Trips: A User Study $ An Investigation of

Mark A. Boster and Russell L. Gum - V2

Colorado River $ Politics and the

Wesley E. Steiner - Vi

Conserve Water in Arizona S Irrigation Management and Water Policy: Opportunities to

Harry W. Ayer and Paul G. Hoyt - V10

Conservation in Arizona's Future S Role of

Laurence Linser - P1

Conservation in Arizona S Future Outlooks for Water

Sol Resnick - Pi

Conservation in the President's Water Policy S Water

Gary D. Cobb - P1

Conservation in Water Supply Planning S The Role of

Augustine J. Fredrich - P1

Conservation

S Land Treatment of Primary Sewage Effluent: Water and Energy

R. C. Rice and R. G. Gilbert - V8

Conserving Water and Energy in Irrigation

$

J. A. Replogle and D. D. Fangmeier - P1

Conserving Water with Drought -Tolerant Crops

$

D. L. Johnson and W. L. Ehrler - P1

Contamination in the Cortaro Area, Pima County, Arizona $ Groundwater

Kenneth D. Schmidt - V2

Desalination

S Fresh Water for Arizona by Salt Replacement

Anthony B. Muller - V4

Desalting Plant $ The Yuma

Dana B. Hill and K. M. Trompeter - P3

Desert Cities $ A Rational Water Policy for

W.

G. Matlock - V4

Desert Farmer S Use and Abuse of Southwestern Rivers: The

J. E. Ayres - V1

Desert Stream Channel

$ Nitrogen Species Transformations of Sewage Effluent Releases in A

P. G. Sebenik, C. B. Cluff and K. J. DeCook - V2

Desert -Household Gardening

$ Salvaging Wasted Waters for

D. H. Fink and W. L. Ehrler - V8

Develop Snowmelt- Runoff Forecasts in Arizona $ Use of Satellite Data to

Peter F. Ffolliott and William O. Rasmussen - V6

Developed in Conjunction with the Water Use Inventory on BLM Administe

$ Quantification Methods

Marvin Goss - V10

Developing Forest Management Guidelines for Increasing Snowpack Water Yields

S Progress in

David B. Thorud and Peter F.

Ffolliott - V1

Development (Abstract) $ Impact on the Environment by Water Resources

Sol Resnick - V3

Development and Chemical Character of a Perched Water Zone, Harquahala Valley, Arizona S Origin,

Charles G. Graf - V10

Development and Testing of a Laser Rain Gage

$

Arnold D. Ozment - V5

Development by the Appropriation Doctrine S Constraints on Water

William L. Lorah - V4

Development of a Groundwater Quality Protection Strategy for Arizona

Marc M. Bennett and Larry K. Stephenson - V11

$ Toward

150

Development on Groundwater in the Parker Strip

S The Effect of

L. G. Everett and T. R. Schultz - V4

Development on Stream Discharge in Navajo and Apache Counties, Arizona

S The Effects of Second -Home and

Resort -Town .

.

.

T. D. Hogan and M. E. Bond - V9

Development on Stream Flows $ Impact of

Paul D. Trotta, James J. Rodgers and William B. Vandivere - V9

Development

S Legal Aspects of Urban Runoff

D. A. Chudnoff - V8

Development

S Storm Flows Management in Relation to Industrial

Robert E. Smith - P2

Development

S Watershed Indicators of Landform

Burchard H. Heede - V5

Development

$ Well -Field Design Criteria for Coastal Seawater

Barney P. Popkin - V10

Earth Fissure Movement in South -Central Arizona S Character of

M. C. Carpenter and J. K. Boling, Jr. - V10

Economic Adjustment to a New Irrigation Water Source: Pinal County, Arizona and the Central Arizona

Project

$

. Mark A. Boster and William E. Martin - V5

Economic Alternatives in Solving the U.S.- Mexico Colorado River Water Salinity Problem

S

William E. Martin - V4

Economic and Energy Opportunities for Municipal Waste -Water Utilization in Arizona

$

E. J. Weber P3

Economic Analysis of the Central Arizona Project

S An

James L.

Barr and David E.

Pingry - V7

Economic Impacts of the Safe Drinking Water Act on Arizona's Water Systems

$ Socio-

Richard S. Williamson - V10

Effluent - An Element of Total Water Resource Planning

J. D. Goff - V8

$ Wastewater

Effluent - Irrigation Water Exchange

C.

S Metropolitan Operated District for Sewage

Brent Cluff and K. James DeCook - V4

Effluent Applied to a Soil -Turf Filter S Nitrogen Removal from Secondary

E. L. Anderson, I. L. Pepper and G. V. Johnson - V8

Effluent by Ground -Water Recharge $ Renovating Sewage

Herman Bouwer, J. C. Lance and R. C. Rice - V1

Effluent in the Santa Cruz River $ Transformations in Quality of Recharging

L. G. Wilson, R. A. Herbert and C. R. Ramsey - V5

Effluent Lakes, Puerto Penasco, Sonora, Mexico

$ A Study of Salinity in

Alison L. Dunn - V11

Effluent Recharge S Effect of Illuviated Deposits on Infiltration Rates and Denitrification During

Sewage ... Richard Alan Herbert - 47

Effluent Releases in A Desert Stream Channel

$ Nitrogen Species Transformations of Sewage

P. G. Sebenik, C. B. Cl uff and K. J. DeCook - V2

Effluent

$ Effect of Algal Growth and Dissolved Oxygen on Redox Potentials in Soil Flooded with

Secondary Sewage .

.

.

R. G. Gilbert and R. C. Rice - V8

Effluent

$ Rehabilitation of Copper Mine Tailing Slopes Using Municipal Sewage

Tika R. Verma, Kenneth L. Ludeke and A. D. Day - V7

Effluent

$ The Use of a Computer Model to Predict Water Quality Transformations During Subsurface

Movement of Oxidation Pond

.

G.

G.

Effluent: Water and Energy Conservation

Small and L.

G. Wilson - V3

$ Land Treatment of Primary Sewage

R. C. Rice and R. G. Gilbert - V8

Environment by Water Resources Development (Abstract)

Sol Resnick - V3

$ Impact on the

Environmental Impact Statement (USDA - SCS, 1978): A Look at State -of

Mesa Watershed ... Dale A. Altshul - V9

$ An Examination of the Buckhorn-

Environmental Impact Statement

S Systematic Assessment of Uncertainties in an

Soronadi Nnaji, Donald R.

Davis and Lucien Duckstein - V6

Environmental Perspective

$ Water for Food, Energy and Municipal Use in the Colorado Basin: A Consumer -

Barbara Tellman - V6

Environments

$ Estimating Potential Evapotranspiration in Arid

Z. Osmolski and L. W. Gay - V11

Ephemeral Channels $ A Proposed Model for Flood Routing in Abstracting

Leonard J. Lane - V2

Ephemeral Flow and Water Quality Problems: A Case Study of the San Pedro River in Southeastern

$

S. J. Keith - 88

Ephemeral Flow in the Tucson Basin: Implications for Ground Water Recharge

S Seasonal and Spatial Trends of ... Susan J. Keith - V10

Ephemeral Mountain Stream $ Equilibrium Condition and Sediment Transport in an

Burchard H. Heede - V6

Ephemeral Stream Channels $ Estimating Transmission Losses in

Leonard J.

Lane, Virginia A. Ferreira and Edward D. Shirley - V10

Ephemeral Stream Channels

$ Water Disposition in

T.

W. Sammis - V2

151

Ephemeral Stream

S Bed Material Characteristics and Transmission Losses in an

J. B. Murphey, L. J. Lane and M. H. Diskin - V2

Ephemeral Stream $ Objective and Subjective Analysis of Transition Probabilities of Monthly Flow on an

William Dvoranchik, Lucien Duckstein and Chester C. Kisiel - V2

Erosion and Sediment Control on the Reclaimed Coal Mine Lands of Semiarid Southwest

S Soil

Tika R.

Verma, John L. Thames and John E. Mills - V7

Erosion and Sedimentation in the Upper Gila Drainage, A Case Study

$

R. L.. Kingston and R. M. Solomon - V6

Erosion Index of the Universal Soil Loss Equation S Thunderstorm Precipitation Effects on the Rainfall -

Kenneth G. Renard and J. Roger Simanton - V5

Erosion of a Semiarid Southwestern Rangeland Watershed $ Effects of Brush to Grass Conversion on the

Hydrology and ... J. R. Simanton, H. B. Osborn and K. G. Renard - V7

Erosion Simulation Model S A Sediment Yield Equation From an

E. D. Shirley and L. J. Lane - V8

Error Analysis of Evapotranspiration Measurements

S

Robert K. Hartman - V10

Error Analysis

$ Aspects of Aquifer Test

Ahmed M. Benbarka and Donald R. Davis - V11

Evaporation Via Surface Temperature Measurements

S Assessing Bare Soil

Sherwood B.

Idso, Robert J. Reginato and Ray D. Jackson - V5

Evaporation S Color It

M. J. Dvoracek - V2

Evapotranspiration from Saltcedar S An Energy Budget Analysis of

L. W. Gay, T. W. Sammis and J. Ben -Asher - V6

Evapotranspiration in Arid Environments

S Estimating Potential

Z. Osmolski and L. W. Gay - V11

Evapotranspiration Measurements S Error Analysis of

Robert K. Hartman - ViO

Evapotranspiration Models (Abstract)

S How to Select

T. E. A. van Hylckama, R. M. Turner and O. M. Grasz - V9

Fire on Water Infiltration Rates in a Ponderosa Pine Stand

S Effects of

Malcom J. Zwolinski - V1

Flood Control Problem Area, State of Arizona

S

William D. Mathews - P2

Flood Estimates S Tests on Arizona's New

Brian M. Reich, Herbert B. Osborn and Malchus C. Baker, Jr.

- V9

Flood Estimation

$ A Solution to Small Sample Bias in

William Metler - V2

Flood Management Problems: Kassandra and the Sirens

$ Two Flash -

Susan Zevin and Jose Marrero - P2

Flood Routing in Abstracting Ephemeral Channels

S A Proposed Model for

Leonard J. Lane - V2

Flood Warning System for Tucson Basin

$ Early

Dan Chudnoff and Robert Reynolds - P2

Flooded with Secondary Sewage Effluent S Effect of Algal Growth and Dissolved Oxygen on Redox Potentials in Soil

.

R. G. Gilbert and R. C. Rice - V8

Flooded with Sewage Water

S Addition of a Carbon Pulse to Stimulate Denitrification in Soil Columns

J. C. Lance and R. G. Gilbert - V6

Floodplain Management in Sonora, Mexico S Traditional Technology for

Thomas E. Sheridan and Gary P.

Nabhan - P2

Floodplain Management Within Pima County, Arizona S Present Practices and Future Goals for

Brian M. Reich and Michael E. Zeller - P2

Floodway Delineation

$ Application of Remote Sensing in

Robin B. Clark - V4

Forage Production on a Semiarid Rangeland Watershed $ Increasing

J.

M. Tromble - V4

Forest and Rangelands in Arizona

$ Water Resources Research on

Alden R. Hibbert - V4

Forest Density on Bedload Movement in a Small Mountain Stream $ Influence of

Burchard H. Heede - V7

Forest Lands in Arizona

S Water Yield Opportunities on National

Rhey M. Solomon and Larry J. Schmidt - V11

Forest Management Guidelines for Increasing Snowpack Water Yields $ Progress in Developing

David B. Thorud and Peter F.

Ffolliott - V1

Forest Openings $ A Technique to Evaluate Snowpack Profiles in and Adjacent to

Peter F. Ffolliott and David B.

Thorud - V4

Forest Watershed $ Snowpack Density on an Arizona Mixed Conifer

Peter F. Ffolliott and J.

R. Thompson - V7

Forested Watersheds in Central Arizona S An Interactive Model of Suspended Sediment Yield on

William O. Rasmussen and Peter F. Ffolliott - V9

Forested Watersheds on Sedimentary Soils

Paul

S Water Quality of Streamflow from

W. Gregory and Peter F. Ffolliott - V6

152

Forests f Evaluation of the Use of Soil Conservation Service Snow Course Data in Describing Local Snow

Conditions in Arizona

.

Gerald J. Gottfried and Peter F. Ffolliott - V11

Forests $ Lysimeter Snowmelt in Arizona Ponderosa Pine

Mikeal E. Jones, Peter F. Ffolliott and David B. Thorud - V6

Forests

$ Snowpack Dynamics in Arizona's Aspen

Michael J. Timmer, Peter F. Ffolliott and William O. Rasmussen - V10

Forests $ Windbreaks May Increase Water Yield from the Grassland Islands in Arizona

J. R. Thompson, O. D. Knipe and Phil M. Johnson - V6

Geomorphic and Hydraulic Response of Rivers

$ The

D. B. Simons - V5

Geomorphic Features Affecting Transmission Loss Potential

$

D. E. Wallace and L. J. Lane - V8

Geomorphic Thresholds and Their Influence on Surface Runoff from Small Semiarid Watersheds

$

D. E. Wallace and L. J. Lane - V6

Goals for Floodplain Management Within Pima County, Arizona $ Present Practices and Future

Brian M. Reich and Michael E. Zeller - P2

Goals in Arizona and Oregon

$ A Public Weighting of Four Societal

D. B. Kimball, R. L. Gum and T. G. Roefs - V3

Ground Water in the Santa Cruz Valley

$

Marshall Flug - V9

Ground Water Recharge

$ Seasonal and Spatial Trends of Ephemeral Flow in the Tucson Basin: Implications for .

.

.

Susan J. Keith - V10

Ground Water Systems with Analog Models (Abstract)

E. P. Patten - V3

$ Simulation of

Ground $ An Exchange System for Precise Measurements of Temperature and Humidity Gradients in the Air

Near the .

.

.

L. W. Gay and L. J. Fritschen - V9

Ground- Recharged Water $ Organic Pollutants in

Michael

A. Mikita, Kevin Thorn, James Hobson, Suzanne Lo and Cornelius Steelink - V11

Ground -Water Basins

$ Uncertainties in Digital- Computer Modeling of

Joseph S.

Gates and Chester C.

Kisiel - V1

Ground -Water Recharge $ Renovating Sewage Effluent by

Herman Bouwer, J. C. Lance and R. C. Rice - V1

Ground -Water Reform: Forces and Consequences of Change in State Water Policy

$ Arizona

Floyd L.

Marsh and Scott A.

Hansen - V11

Groundwater Characteristics from Well Driller Logs $ Computerized Depth Interval Determination of

Mike Long and Stephen Erb - V10

Groundwater Contamination in the Cortaro Area, Pima County, Arizona

$

Kenneth D. Schmidt - V2

Groundwater Exploration in Northeastern Arizona Using LANDSAT Imagery

$

Kennith E. Foster and K. James DeCook - V10

Groundwater from Municipal Wells, Flagstaff, Arizona $ Chemistry of Effervescing

John C. Germ and Errol L. Montgomery - V5

Groundwater Geology of Fort Valley, Coconino County, Arizona

$

Ronald H. DeWitt - V3

Groundwater in the Basin and Range Province of Arizona $ The Occurrence of Thermal

Jerome J. Wright - V1

Groundwater in the Parker Strip $ The Effect of Development on

L. G. Everett and T. R. Schultz - V4

Groundwater Law Reform - An Urban Perspective $ Arizona

H. Holub - V8

Groundwater Management for the City of Tucson, Arizona

$ Hydrologic Factors Affecting

R. B. Johnson - V8

Groundwater of the Tulare Lake Basin, California

Kenneth D. Schmidt - V5

Groundwater Quality Control

$ Salt Balance in

$ Management of Artificial Recharge Wells for

L. G. Wilson V1

Groundwater Quality Protection Strategy for Arizona $ Toward Development of a

Marc M. Bennett and Larry K. Stephenson - V11

Groundwater Quality Specialists $ Academic Training for

Kenneth D. Schmidt - V6

Groundwater Quality Studies $ The Use of Chemical Hydrographs in

Kenneth D. Schmidt - V1

Groundwater Recharge From a Portion of the Santa Catalina Mountains

$

R. A. Bel an and W. G. Matlock - V3

Groundwater Requirements in the Tucson Area, Arizona $ Jojoba: An Alternative to the Conflict Between

Agricultural and Municipal

.

Kennith E. Foster and N.

Gene Wright -

P1

Groundwater Resource $ A Method for Maximizing the Present Value of a

Reuben N. Weisz and Charles L. Towle, Jr.

- V6

Groundwater Supply of Little Chino Valley $ The

W. G. Matlock and P. R. Davis - V2

Groundwater Usage from the Navajo Sandstone

F. H. Dove and T. G. Roefs - V3

$ Competitive

153

Groundwaters in Arizona

$ Factors to Consider in Drafting Standards to Protect

Marc M. Bennett - V10

Groundwater f Management Alternatives for Santa Cruz Basin

K. E. Foster - V8

Groundwater S Three -Dimensional Velocity Log in

Richard P. Chagnon - VIO

Hydrology (Abstract)

S The Significance of Logistics to

J. R. McCarthy - V3

Hydrology as a Science?

S

M. J. Dvoracek and D. D. Evans - V2

Hydrology and Erosion of a Semiarid Southwestern Rangeland Watershed

S Effects of Brush to Grass

Conversion on the .

.

.

J. R. Simanton, H. B. Osborn and K. G. Renard - V7

Hydrologic Aspects of Land -Use Planning at Tumamoc Hill, Tucson, Arizona

S

Barney Paul Popkin - V4

Hydrologic Data in Arizona S Role of Modern Methods of Data Analysis for Interpretation of

Chester C. Kisiel, Lucien Duckstein and Martin M. Fogel - V2

Hydrologic Effects of Soil Surface Micro -Flora

$

William F. Faust - V1

Hydrologic Evaluation of Topsoiling for Rehabilitating Black Mesa Coal Mine Lands

S

Frank G. Postillion - V10

Hydrologic Factors Affecting Groundwater Management for the City of Tucson, Arizona

$

R. B. Johnson - V8

Hydrologic Investigations of the Dry Lake Region in East Central Arizo

S

James J. Lemmon, Thomas R. Schultz and Don W. Young - V9

Hydrologic Properties of Diatremes in the Hopi Buttes, Arizona S Preliminary Investigation of the

Kenneth C. Scott, R. J. Edmonds and E. L. Montgomery - V4

Hydrologic Regimes of Three Vegetation Types Across the Mogollon Rim

S

Malchus B. Baker, Jr.

- Vii

Hydrologic Research S Lake Powell Research Project:

Gordon C. Jacoby - V3

Hydrologic Research on Southwest Rangelands S Use of Stock Ponds for

J. R. Simanton and H. B. Osborn - V3

Hydrologic Time Series

S On the Statistics of

Sidney Yakowitz and Jack Denny - V3

Hydrologic Tracers, A New Technology

$ Chlorofluorocarbons as

J. H. Randall and T. R. Schultz - V6

Hydrological Design $ Using Linear Regression in

G. D. Peterson, D. R. Davis and J. Weber - V4

Hydrology: State -of- the -Art $ Urban

Warren Viessman, Jr. - V3

Infiltration and Runoff $ Simple Time -Power Functions for Rainwater

R. M. Dixon, J. R. Simanton and L. J. Lane - V8

Infiltration Characteristics and Water Yield of a Semiarid Catchment $ Variability of

Soronadi Nnaji, Ted W. Sammis and Daniel D. Evans - V5

Infiltration Characteristics of a Ponderosa Pine Soil S Effects of a Wetting Agent on the

Marc G. Kaplan and Malcolm J. Zwolinski - V3

Infiltration Control $ A Land Imprinter for Revegetation of Barren Land Areas Through

R. M. Dixon and J. R. Si manton - V7

Infiltration in Soil Columns $ The Effect of Increasing the Organic Carbon Content of Sewage on

Nitrogen, Carbon, and Bacteria Removal and ... J. L. Lance and F. D. Whisler - V5

Infiltration Rates and Denitrification During Sewage Effluent Recharge

S Effect of Illuviated Deposits on

.

Richard Alan Herbert - V7

Infiltration Rates in a Ponderosa Pine Stand á Effects of Fire on Water

Malcom J. Zwolinski - V1

Infiltration Rates of Contributing Watersheds to the Lower Gila Below S The Use of a Realistic Rainfall

Simulator to Determine Relative

.

C.

B.

Cluff and D.

G.

Boyer - V1

Infiltration Response to Surface Plant Cover and Soil Invertebrate Population

$

Isobel

Infiltration

R. McGowan - V10

$ A Microroughness Meter for Evaluating Rainwater

J. R. Simanton, R. M. Dixon and I. McGowan - V8

Information Sources: Highlights

$ Water -Related

Linda M. White - V6

Information System - 1975 $ The Arizona Resources

Carl C. Winikka - V5

Information System for Water Yield Improvement Practices

$ A Bibliographic

Linda M. White - V4

Information System

$ Design and Pilot Study of an Arizona Water

K. E. Foster and J. D. Johnson - V2

Irrigated Alfalfa S Energy Budget Measurements Over

L. W. Gay and R. K. Hartman - V11

Irrigated Farm with Limited Water

S Planning Models of an

Herbert G. Blank - V6

154

Irrigation (Poster Session)

Barney P. Popkin - V9

$ Augmenting Water Supply for Home

Irrigation and Mining Water $ Collective Utility of Exchanging Treated Sewage Effluent for

Stephen C.

Ko and Lucien Duckstein - V2

Irrigation Management and Water Policy: Opportunities to Conserve Water in Arizona

$

Harry W. Ayer and Paul G. Hoyt - V10

Irrigation Pumping Equipment

$ Solar Powered

Dennis L. Larson and C. D. Sands, Jr. - V9

Irrigation Pumping

$ Feasibility of Using Solar Energy for

Dennis Larson, D.

D. Fangmeier, W.

G. Matlock, John Day and C.

D.

Sands II - V6

Irrigation Water Exchange

$ Metropolitan Operated District for Sewage Effluent -

C. Brent Cluff and K. James DeCook - V4

Irrigation Water Quality $ Sulfuric Acid: Its Potential for Improving

H. L. Bohn and R. L. Westerman - V1

Irrigation Water Source: Pinal County, Arizona and the Central Arizona Project $ Economic Adjustment to a New

.

Mark A. Boster and William E.

Irrigation

$ Conserving Water and Energy in

Martin - V5

J. A. Replogle and D. D. Fangmeier - P1

Irrigation $ Optimal Utilization of Playa Lake Water in

M. J. Dvoracek and T. G. Roefs V1

Irrigation

$ Seasonal Effects on Soil Drying After

B. A. Kimball and R. D. Jackson V1

Lysimeter $ Construction, Calibration, and Operation of a Monolith Weighing

Theodore W. Sammis, Don W. Young and Charles L. Constant - V6

Lysimeter Snowmelt in Arizona Ponderosa Pine Forests

$

Mikeal

E. Jones, Peter F. Ffolliott and David B. Thorud - V6

Lysimeters in an Arizona Mixed Conifer Stand

$ An Evaluation of Snowmelt

Gerald J. Gottfried and Peter F.

Ffolliott - V10

Management Alternatives for Santa Cruz Basin Groundwater

$

K. E. Foster - V8

Management Analysis $ Canyon Creek

L. E. Siverts, R. D. Gale and J. W. Russell - V4

Management for the City of Tucson, Arizona

$ Hydrologic Factors Affecting Groundwater

R. B. Johnson - V8

Management for the San Carlos Apache Indian Reservation: Gila River

$ Application of Multidisciplinary

Water Resources Planning and ... M. E. Norvelle, D. J. Pervious and N. G. Wright V7

Management in Relation to Industrial Development $ Storm Flows

Robert. E. Smith - P2

Management in Sonora, Mexico $ Traditional Technology for Floodplain

Thomas E.

Sheridan and Gary P.

Nabhan - P2

Management Plan for Tucson, Arizona $ Impacts of a New Water Resources

R. Bruce Johnson - V10

Management Problems: Kassandra and the Sirens $ Two Flash- Flood

Susan Zevin and Jose Marrero - P2

Management Systems for the Sonoita Creek Watershed $ Evaluation of Water

Hugh B. Robotham - V9

Management Versus the Reasonable Man Test

$ The Prejudices, Polemics, and Politics of Water

Barbara A. Stribling - V6

Management Within Pima County, Arizona $ Present Practices and Future Goals for Floodplain

Brian M. Reich and Michael E. Zeller - P2

Management $ Evaluating and Displaying Watershed Tradeoffs for

Rhey M. Solomon and Larry J. Schmidt - V10

Management $ Land Treatment for Urban Waste Water

William L. Lorah and Kenneth R. Wright - V3

Management

$ Tucson's Tools for Demand

S. T. Davis V8

Mexico Colorado River Water Salinity Problem

$ Economic Alternatives in Solving the U.S. -

William E. Martin - V4

Mexico Water Agreements and Related Water Use in Mexicali Valley: A S $ United States -

K. J. DeCook - V4

Mexico $ A Study of Salinity in Effluent Lakes, Puerto Penasco, Sonora,

Alison L. Dunn - V11

Mexico $ Exploration for Saltwater Supply for Shrimp Aquaculture, Puerto Penasco, Sonora,

K. J. DeCook, S. Ince, B.

P. Popkin, J. F. Shreiber, Jr. and J. S. Sumner - V10

Mexico $ Traditional Technology for Floodplain Management in Sonora,

Thomas E.

Sheridan and Gary P.

Nabhan - P2

Mine Lands of Semiarid Southwest

$ Soil Erosion and Sediment Control on the Reclaimed Coal

Tika R. Verma, John L. Thames and John E. Mills - V7

Mine Lands $ Optimal Livestock Production of Rehabilitated

Fritz H. Brinck, Martin M. Fogel and Lucien Duckstein - V6

Mine Reclamation Alternative $ The Mound and Valley Water Harvesting System: A Potential

Charles L. Constant and John Thames - V10

155

Mine Sites and Their Effect on the Water Quality of the Lynx Creek Watershed

S Reclamation of Orphaned

Tika R. Verma and Ernesto N.

Felix - V7

Mine Spoils of the Arid Southwest

$ Stochastic Prediction of Sediment Yields from Strip

Mark E. Auernhamer, Martin M. Fogel, Louis H. Hekman, Jr. and John L. Thames - V7

Mine Tailing Slopes Using Municipal Sewage Effluent

$ Rehabilitation of Copper

Tika R. Verma, Kenneth L. Ludeke and A. D. Day - V7

Mines in the Patagonia Mountains, Arizona

$ Acid Drainage From Abandoned

Sheila A. Dean - P3

Mined Lands in Northern Arizona S Water Quality of Runoff From Surface

J. Kempf, L. Leonhart, M. Fogel and L. Duckstein - V8

Mining Activity in the Miami, Arizona Region

$ The Effects on Water Quality by

D. W. Young and R. B. Clark - VB

Mining Activities and Water Quality in the Lynx Creek Watershed

$ Past

E. N. Felix, T. R. Verma, E. E. McCrary and J. L. Thames - V6

Mining District of Arizona - An Institutional Approach

$ Addressing Water Quality Problems in the Globe -

Miami

. Robert J. Cinq -Mars, Daniel R. Mayercek and

Edwin K.

Mining Effects on Water Quality of the Tongue River, Wyoming

Swanson - P3

$ Preliminary Results from a Study of Coal

Richard D. Olsen and Edward H. Dettmann - V6

Mining Operations on the Black Mesa

$ Visual Impacts: Perception and Modification of Surface

Jon Rodiek - V9

Mining Water

$ Collective Utility of Exchanging Treated Sewage Effluent for Irrigation and

Stephen C.

Ko and Lucien Duckstein - V2

Model for Flood Routing in Abstracting Ephemeral Channels $ A Proposed

Leonard J. Lane - V2

Model for Semi -Arid Catchments

$ A Deterministic

S. Nnaji, D. R. Davis and M. M. Fogel - V4

Model of Suspended Sediment Yield on Forested Watersheds in Central Arizona

$ An Interactive

William O. Rasmussen and Peter F. Ffolliott - V9

Model System

$ The Arizona Water Commission's Central Arizona Project Water Allocation

Philip C. Briggs - V7

Model to Predict Water Quality Transformations During Subsurface Movement of Oxidation Pond Effluent

Model s The Use of a Computer .

.

.

G. G. Small and L. G. Wilson - V3

$ A Sediment Yield Equation From an Erosion Simulation

E. D. Shirley and L. J. Lane - V8

Models (Abstract)

$ How to Select Evapotranspiration

T. E. A. van Hylckama, R. M. Turner and O. M. Grasz - V9

Models (Abstract)

$ Simulation of Ground Water Systems with Analog

E. P. Patten V3

Models and Methods for Rivers in the Southwest $ Statistical

Model

Sidney Yakowitz - V7

S Input Specifications to a Stochastic Decision

D. M. Cl ai nos, L. Duckstein and T. G. Roefs - V2

Models of an Irrigated Farm with Limited Water $ Planning

Model

Herbert G. Blank - V6

$ Prediction of the Chemical Quality of Streamflow by an Interactive Computer

William O. Rasmussen and Peter F. Ffolliott - V10

Modeling and Computational Aspects of Dynamic Programming with ApplicaReservoir Control $ On the

Moshe Sniedovich and Sidney J. Yakowitz - V6

Modeling for Capital Improvements Planning $ Hydraulic

Stephen E. Davis - V10

Modeling of a Forward Osmosis Extractor $ Mathematical

C. D. Moody and J. O. Kessler - V6

Modeling of Ground -Water Basins

$ Uncertainties in Digital- Computer

Joseph S.

Gates and Chester C.

Kisiel

- V1

Modeling of the Avra Valley Aquifer

$ Geostatistical Analysis and Inverse

Peter M. Clifton and Shlomo P. Neuman - Vii

Modeling $ Parameter Influence on Runoff

Samual E. Kao, Theodore G. Roefs and Simon Ince - V5

Modeling

$ Solar Radiation as Indexed by Clouds for Snowmelt

D. P. McAda and P. F. Ffolliott - V8

Multiattribute Approach to the Reclamation of Stripmined Lands $ A

Fritz H. Brinck, Lucien Duckstein and John L. Thames - V9

Multidisciplinary Water Resources Planning and Management for the San Carlos Apache Indian Reservation:

G i l a River

$ An Application of ... M. E. Norvelle, D. J. Percious and N. G. Wright -

Multiobjective Approach to Managing a Southern Arizona Watershed $ A

V7

Ambrose Goicoechea, Lucien Duckstein and Martin M. Fogel - V6

Multi- Objective Approach to River Basin Planning $ A

Mark Gershon, Richard McAniff and Lucien Duckstein - V10

Multiple -use Approach to the Reclamation of Strip- mined Lands

$ Decision Making in a

Ambrose Goicoechea, Lucien Duckstein and Martin Fogel - V7

Municipal Groundwater Requirements in the Tucson Area, Arizona

$ Jojoba: An Alternative to the Conflict

Between Agricultural and ... Kennith E. Foster and N.

Gene Wright - P1

156

Municipal Use in the Colorado Basin: A Consumer- Environmental Perspective

$ Water for Food, Energy and

Barbara Tellman - V6

Municipal Waste Water $ Evaluation of a Turfgrass - Soil System to Utilize and Purify

R. C. Sidle and G. V. Johnson - V2

Municipal Waste -Water Utilization in Arizona $ Economic and Energy Opportunities for

E. J. Weber P3

Municipal Wells $ Barometric Response of Water Levels in Flagstaff

Errol

L. Montgomery, Emily Dordosz, Russell O. Dalton, Jr. and Ronald H. DeWitt - V7

Municipal Wells, Flagstaff, Arizona

$ Chemistry of Effervescing Groundwater from

John C. Germ and Errol L. Montgomery - V5

Nitrogen Balance for a 23- Square Mile Minnesota Watershed

$

Jack D. Johnson - V1

Nitrogen Removal from Secondary Effluent Applied to a Soil -Turf Filter

$

E. L. Anderson, I. L. Pepper and G. V. Johnson - V8

Nitrogen Species Transformations of Sewage Effluent Releases in A Desert Stream Channel

P. G. Sebenik, C. B. Cl uff and K. J. DeCook - V2

$

Nitrogen, Carbon, and Bacteria Removal and Infiltration in Soil Columns $ The Effect of Increasing the

Organic Carbon Content of Sewage on .

.

.

J. L. Lance and F. D. Whisler V5

Nutrient Levels on the Verde River Watershed with Recommended Standard

$

Timothy D. Love - V11

Osmosis Extractor

$ Mathematical Modeling of a Forward

C. D. Moody and J. O. Kessler - V6

Osmosis: Design Characteristics for Hydration and Dehydration $ Application of Direct

J. O. Kessler and C. D. Moody V5

Osmosis: Possibilities for Reclaiming Wellton- Mohawk Drainage Water $ Application of Direct

C. D. Moody and J. O. Kessler -

V5

Pine Forest $ A Preliminary Assessment of Snowfall Interception in Arizona Ponderosa

Larry C. Tennyson, Peter F. Ffolliott and David B. Thorud - V3

Pine Soil $ Effects of a Wetting Agent on the Infiltration Characteristics of a Ponderosa

Marc G. Kaplan and Malcolm J. Zwolinski - V3

Pine Stand $ Effects of Fire on Water Infiltration Rates in a Ponderosa

Malcom J. Zwolinski - V1

Plan - Tucson, Arizona $ The Northwest Area Water

Thomas M. McLean - V10

Plan for Tucson, Arizona $ Impacts of a New Water Resources Management

R. Bruce Johnson - V10

Plant Cover and Soil Invertebrate Population $ Infiltration Response to Surface

Isobel R. McGowan - V10

Plans for the Santa Cruz River Basin by Q- Analysis

$ Ranking Alternative

Ronald T. Pfaff and Lucien Duckstein - V11

Planning $ A Multi- Objective Approach to River Basin

Mark Gershon, Richard McAniff and Lucien Duckstein - V10

Planning at Tumamoc Hill, Tucson, Arizona $ Hydrologic Aspects of Land -Use

Barney Paul Popkin - V4

Planning and Management for the San Carlos Apache Indian Reservation: Gila River $ An Application of

Multidisciplinary Water Resources . .. M. E. Norvelle, D. J. Percious and N. G. Wright V7

Planning for the San Tiburcio Watershed $ Land Use

Roberto Armijo and Robert Bulfin - V9

Planning in the Colorado River System $ Salinity Control

John T. Maletic - V4

Planning Methodology: Public Input

$ The Cognitive Strawman

Weston W. Wilson, Russell L. Gum and T.

G. Roefs - V3

Planning Models of an Irrigated Farm with Limited Water

$

Herbert G. Blank - V6

Planning Tool $ Public Perception of Water Quality as a

R. M. Judge and R. L. Gum V3

Planning $ Establishing a Process Framework for Land Use

Lloyd J. Lundeen - V4

Planning $ Hydraulic Modeling for Capital Improvements

Stephen E. Davis - V10

Planning $ State Water

Wesley E. Steiner - V5

Planning

$ The Role of Conservation in Water Supply

Augustine J. Fredrich - P1

Planning $ Wastewater Effluent - An Element of Total Water Resource

J. D. Goff V8

Plants: A Possible Paleohygrometer $ Stable Isotopes of Oxygen in

A. M. Ferhi, A. Long and J. C. Lerman - V7

Policy for Desert Cities

W.

G. Matlock - V4

$ A Rational Water

Policy $ Arizona Ground -Water Reform: Forces and Consequences of Change in State Water

Floyd L.

Marsh and Scott A.

Hansen - V11

157

Policy: Changing Decision Agendas and Political Styles

Hanna J. Cortner and Mary P. Berry - V7

Policy: Opportunities to Conserve Water in Arizona

S Arizona Water

$ Irrigation Management and Water

Harry W. Ayer and Paul G. Hoyt - V10

Policy $ Water Conservation in the President's Water

Gary D. Cobb - P1

Politics and the Colorado River

Wesley E. Steiner - V1

Politics of Water in Arizona

S

Senator Morris Farr - V6

S

Politics of Water Management Versus the Reasonable Man Test S The Prejudices, Polemics, and

Barbara A. Stribling - V6

Political Constraints to Implementation S Action Programs for Water Yield Improvement on Arizona's

Watersheds:

.

.

H. J. Cortner and M. P. Berry - V8

Political Styles S Arizona Water Policy: Changing Decision Agendas and

Hanna J. Cortner and Mary P.

Berry - V7

Pollutants Determine Runoff Source Areas S Nonpoint- Source

L. J. Lane, H. L. Morton, D. E. Wallace, R. E. Wilson and R. D. Martin - V7

Pollutants in Ground- Recharged Water S Organic

Michael A. Mikita, Kevin Thorn, James Hobson, Suzanne Lo and Cornelius Steelink - V11

Pollution Control Program S Highlights of the State's Water

Marc M. Bennett and Larry K. Stephenson - P3

Pollution S Saline and Organic Water

Hinrich L.

Bohn and Gordon V.

Johnson - V2

Precipitation in Lake Powell (Abstract)

S Calcite

Robert C. Reynolds, Jr.

- V3

S Determining Areal Precipitation in the Basin and Range Province of Southern Arizona - So

J. Ben- Asher, J. Randall and

S.

Resnick - V6

Precipitation on a Southeastern Arizona Rangeland Watershed

H. B. Osborn, R. B. Koehler and J. R. Simanton - V9

Precipitation on Rugged Terrain in Central Arizona

S Winter

S Distribution of

Alden R. Hibbert - V7

Price of Water in Western Agriculture

S The

David L. Wilson and Harry W. Ayer - V11

Prices, Water Demand by Peri -Urban Agriculture, and Implications for Urban Water Supply: The Tucson

Case $ Rising Energy .

.

.

H. W. Ayer and D. W. Gapp - V8

Pricing Structures from a Collective Utility Viewpoint

Bill Metter and Lucien Duckstein - V1

$ Comparison of Water

Probability Distribution for Rainfall on a Watershed by Simulation $ The Construction of a

Gary Williamson and Donald Ross Davis - V2

Probability Distributions of Snow Course Data for Central Arizona

S

Lawrence E.

Cary and Robert L.

Beschta - V3

Probabilities of Monthly Flow on an Ephemeral Stream S Objective and Subjective Analysis of Transition

William Dvoranchik, Lucien Duckstein and Chester C. Kisiel - V2

Probabilities $ Conditional Streamflow

T. G. Roefs and D. M. Clainos - V1

Public Input S The Cognitive Strawman Planning Methodology:

Weston W. Wilson, Russell L. Gum and T.

G. Roefs - V3

Public Involvement in Federal Water Resource Projects

S Early

Freda Johnson and Michael Thuss - V9

Public Perception of Water Quality as a Planning Tool

$

R.

M. Judge and R.

L. Gum - V3

Public Weighting of Four Societal Goals in Arizona and Oregon

S A

D.

B. Kimball, R. L. Gum and T. G. Roefs - V3

Pumping Equipment $ Solar Powered Irrigation

Dennis L. Larson and C. D. Sands, Jr. - V9

Pumping Project: Operating Experiences

Dennis L. Larson - Vii

$ Arizona Solar Powered

Pumping Tests for Determining Well Losses in Consolidated Rock Aquifers S The Application of Step -

Drawdown

.

V. W. Uhl, Jr., V. G. Joshi, A. Alpheus and G. Sharma - V5

Pumping S Feasibility of Using Solar Energy for Irrigation

Dennis Larson,

D.

D. Fangmeier, W.

G. Matlock, John Day and C.

D.

Sands II - V6

Quality as a Planning Tool $ Public Perception of Water

R. M. Judge and R. L. Gum V3

Quality Analyses of the Colorado River Corridor of Grand Canyon

Brock Tunnicliff and Stanley K.

Brickler - V10

S Water

Quality by Mining Activity in the Miami, Arizona Region S The Effects on Water

D. W. Young and R.

B. Clark - V8

Quality Considerations for Landfill Siting in Arizona S Water

L. G. Wilson - P3

Quality Control S Management of Artificial Recharge Wells for Groundwater

L. G. Wilson - V1

158

Quality in Air Bubbling to Eliminate Thermal Stratification in Upper L

S Improvement of Water

E. H. McGavock and J. W. H. Blee - V3

Quality in Southeastern Arizona Rangeland

Herbert B.

$ Rainwater

Osborn, Loel R. Cooper and Jeff Billings - V11

Quality in the Lynx Creek Watershed

$ Past Mining Activities and Water

E. N. Felix, T. R. Verma, E. E. McCrary and J. L. Thames - V6

Quality Investigation of Canyon Lake

S A Bacterial Water

W. F. Horak and G. S. Lehman - V4

Quality of Recharging Effluent in the Santa Cruz River

S Transformations in

L. G. Wilson, R. A. Herbert and C. R. Ramsey - V5

Quality of Runoff From Surface Mined Lands in Northern Arizona

J. Kempf, L. Leonhart, M. Fogel and L. Duckstein - V8

Quality of Stock Tanks of Southeastern Arizona

S Water

$ Time -Related Changes in Water

D. E. Wallace and H. A. Schreiber - V4

Quality of Streamflow by an Interactive Computer Model

William O. Rasmussen and Peter F. Ffolliott - V10

$ Prediction of the Chemical

Quality of Streamflow from Forested Watersheds on Sedimentary Soils

Paul

W.

Gregory and Peter F. Ffolliott - V6

Quality of the East Verde River

$ Impact of Recreation on the Water

S Water

Milton R. Sommerfeld, Patrick V. Athey and Bradley C. Mueller - P3

Quality of the East Verde River

S Use of Bacterial Indicators in Assessment of Water

Patrick V. Athery, Marilyn J. Urbina and Milton R. Sommerfeld - V11

Quality of the Lynx Creek Watershed

$ Reclamation of Orphaned Mine Sites and Their Effect on the Water

Tika R.

Verma and Ernesto N. Felix - V7

Quality of the Tongue River, Wyoming

S Preliminary Results from a Study of Coal Mining Effects on Water

Richard D. Olsen and Edward H. Dettmann - V6

Quality Problems in the Globe -Miami Mining District of Arizona - An Institutional Approach

$ Addressing

Water .

.

.

Robert J. Cinq -Mars, Daniel R. Mayercek and Edwin K. Swanson - P3

Quality Problems in the Puerco River, Arizona

$ Water

Edwin K. Swanson - P3

Quality Problems of the Urban Area in an Arid Environment. Tucson, Arizona

G. Hansen - V8

Quality Problems: A Case Study of the San Pedro River in Southeastern

S Water

S Ephemeral Flow and Water

S. J. Keith V8

Quality Protection Strategy for Arizona

S Toward Development of a Groundwater

Marc M. Bennett and Larry K. Stephenson - V11

Quality Sampling Schedules Using Fecal Coliform Concentrations in Sabi

S Evaluating Water

Robert M. Motschall, Stanley D. Brickler and Robert A. Phillips - V6

Quality Specialists

$ Academic Training for Groundwater

Kenneth D. Schmidt - V6

Quality Study of Lake Havasu, Arizona near the CAP Intake Area $ Water

Simon Ince, David L. Kreamer, Don W. Young and Charles L. Constant - V6

Quality Studies Today and Tomorrow $ Water -

John D. Hem - V3

Quality Studies

$ The Use of Chemical Hydrographs in Groundwater

Kenneth D. Schmidt - V1

Quality Transformations During Subsurface Movement of Oxidation Pond Effluent

$ The Use of a Computer

Model to Predict Water .

.

.

G. G. Small and L. G. Wilson - V3

Quality

$ Some Effects of Controlled Burning on Surface Water

Bruce D. Sims, Gordon S. Lehman and Peter F. Ffolliott - V11

Quality

$ Sulfuric Acid: Its Potential for Improving Irrigation Water

H. L. Bohn and R. L. Westerman V1

Rain Gage

$ Development and Testing of a Laser

Arnold D. Ozment - V5

Rainfall in Southeastern Arizona

$ Point- Area -Frequency Conversions for Summer

Herbert B.

Osborn and Leonard J.

Lane - V11

Rainfall in the Southwest

$ Regional Differences in Runoff -Producing Thunderstorms

H. B. Osborn -

V1

Rainfall in the Southwest

$ Stationarity in Thunderstorm

William C. Mills and Herbert B. Osborn - V3

Rainfall Intensity on Runoff Curve Numbers

S Effects of

R. H. Hawkins - V8

Rainfall on a Watershed by Simulation

$ The Construction of a Probability Distribution for

Gary Williamson and Donald Ross Davis - V2

Rainfall Occurrence in Arizona and New Mexico

S Simulation of Summer

Herbert B.

Osborn and Donald Ross Davis - V7

Rainfall Records Relative to Chart Scales

$ Resolutions of Analog

Donald L. Chery, Jr. and Dave G. Beaver - V6

Rainfall Simulating Infiltrometer

$ A Jeep- Mounted

William R. Henkle - V3

Rainfall Simulator to Determine Relative Infiltration Rates of Contributing Watersheds to the Lower

Gila Below

$ The Use of a Realistic ... C. B. Cluff and D. G. Boyer - V1

159

Rainfall- Erosion Index of the Universal Soil Loss Equation

$ Thunderstorm Precipitation Effects on the

Kenneth G. Renard and J. Roger Simanton - V5

Rainfall- Runoff Relation

D. L. Chery, Jr. - V2

S Significance of Antecedent Soil Moisture to a Semiarid Watershed

Rainfall- Runoff Relationships for a Mountain Watershed in Southern Arizona

$

M. Myhrman, C. B. Cl uff and F. Putman - V8

Raingage Networks $ Use of Radar as a Supplement to

Herbert B.

Osborn and J.

Roger Simanton - V10

Rainwater Infiltration and Runoff $ Simple Time -Power Functions for

.

M. Dixon, J. R. Simanton and L. J. Lane - V8

Rainwater Infiltration $ A Microroughness Meter for Evaluating

J. R. Simanton, R. M. Dixon and I. McGowan - V8

Rainwater Quality in Southeastern Arizona Rangeland

S

Herbert B. Osborn, Loel R. Cooper and Jeff Billings - V11

Rangeland Conditions in the Southwest S Applicability of the Universal Soil Loss Equation to Semiarid

K. G. Renard, J. R. Si manton and H. B. Osborn - V4

Rangeland Watershed S Increasing Forage Production on a Semiarid

J.

M. Tromble - V4

Rangeland Watershed

S Winter Precipitation on a Southeastern Arizona

H. B. Osborn, R. B. Koehler and J. R. Simanton - V9

Rangelands in Arizona

$ Water Resources Research on Forest and

Alden R. Hibbert - V4

Rangeland

S Rainwater Quality in Southeastern Arizona

Herbert B.

Osborn, Loel R. Cooper and Jeff Billings - V11

Rangelands $ Application of the USLE to Southwestern

J. Roger Simanton, Herbert B. Osborn and Kenneth G. Renard - V10

Rangelands

S Use of Stock Ponds for Hydrologic Research on Southwest

J. R. Simanton and H. B. Osborn - V3

Recharge S Effect of Illuviated Deposits on Infiltration Rates and Denitrification During Sewage

Effluent

.

Richard Alan Herbert - V7

Recharge From a Portion of the Santa Catalina Mountains $ Groundwater

R. A. Belan and W. G. Matlock - V3

Recharge Through Soils in a Mountain Region: A Case Study on the Empire and the Sonoit $ Evaluation of

U. Kafri and J. Ben -Asher - V6

Recharge Wells for Groundwater Quality Control S Management of Artificial

L. G. Wilson - V1

Recharge S Renovating Sewage Effluent by Ground -Water

Herman Bouwer, J. C. Lance and R. C. Rice - Y1

Recharge

S Seasonal and Spatial Trends of Ephemeral Flow in the Tucson Basin: Implications for Ground

Water . Susan J.

Keith - V10

Recharged Water

$ Organic Pollutants in Ground -

Michael A. Mikita, Kevin Thorn, James Hobson, Suzanne Lo and Cornelius Steelink - V11

Recharging Effluent in the Santa Cruz River $ Transformations in Quality of

L. G. Wilson, R. A. Herbert and C. R. Ramsey - Y5

Recharging the Ogallala Formation Using Shallow Holes

M. J. Dvoracek and S. H. Peterson - V1

$

Reclaiming Wellton- Mohawk Drainage Water

$ Application of Direct Osmosis: Possibilities for

C. D. Moody and J. O. Kessler - V5

Reclamation Alternative

$ The Mound and Valley Water Harvesting System: A Potential Mine

Charles L. Constant and John Thames - V10

Reclamation of Orphaned Mine Sites and Their Effect on the Water Quality of the Lynx Creek Watershed

$

Tika R. Verma and Ernesto N. Felix - V7

Reclamation of Strip- mined Lands

$ Decision Making in a Multiple -use Approach to the

Ambrose Goicoechea, Lucien Duckstein and Martin Fogel - V7

Reclamation of Stripmined Lands

$ A Multiattribute Approach to the

Fritz H. Brinck, Lucien Duckstein and John L. Thames - V9

Recreation on the Water Quality of the East Verde River

$ Impact of

Milton R. Sommerfeld, Patrick V. Athey and Bradley C. Mueller - P3

Recreational Waters of Upper Sabino Creek $ Bottom Sediment Analysis of the

Patrick L.

McKee and Stanley K. Brickler - V7

Regression in Hydrological Design

$ Using Linear

G. D. Peterson, D. R. Davis and J. Weber - V4

Rehabilitated Mine Lands $ Optimal Livestock Production of

Fritz H. Brinck, Martin M. Fogel and Lucien Duckstein - V6

Rehabilitating Black Mesa Coal Mine Lands

$ Hydrologic Evaluation of Topsoiling for

Frank G. Postillion - V10

Rehabilitation of Copper Mine Tailing Slopes Using Municipal Sewage Effluent

$

Tika R. Verma, Kenneth L. Ludeke and A. D. Day - V7

Reservoir Control

S On the Modeling and Computational Aspects of Dynamic Programming with Applica

Moshe Sniedovich and Sidney J. Yakowitz - V6

Reservoir Design under Random Sediment Yield

$

L. Duckstein, F. Szidarovszky and S. Yakowitz - V6

160

Reservoir Operation $ A Utility Criterion for Real -time

Lucien Duckstein and Roman Krysztofowicz - V7

Reservoir: Efficient Water Storage in Flat Terrain Areas of Arizona

C. B. Cluff V8

$ The Compartmented

Residential Water Use: A Cross -Section Time -Series Analysis of Tucson, Arizona $ The Impact of

Socioeconomic Status on ... R.

Bruce Billings and Donald E.

Agthe - V9

$ A Land Imprinter for Revegetation of Barren Land Areas Through Infiltration Control

R. M. Dixon and J. R. Si manton V7

Runoff Curve Numbers $ Effects of Rainfall Intensity on

R. H. Hawkins - V8

Runoff Development $ Legal Aspects of Urban

D. A. Chudnoff - V8

Runoff Forecasts in Arizona

$ Use of Satellite Data to Develop Snowmelt-

Peter F. Ffolliott and William O. Rasmussen - V6

Runoff from Small Semiarid Watersheds $ Geomorphic Thresholds and Their Influence on Surface

D. E. Wallace and L. J. Lane V6

Runoff from Small Watersheds

$ Effect of Urbanization on

Samuel

E.

Kao, Martin M. Fogel and Sol D. Resnick - V3

Runoff From Surface Mined Lands in Northern Arizona $ Water Quality of

J. Kempf, L. Leonhart, M. Fogel and L. Duckstei n - V8

Runoff Modeling s Parameter Influence on

Samual E.

Kao, Theodore G. Roefs and Simon Ince - V5

Runoff Records Using Tree -Ring Data $ Augmenting Annual

Charles W.

Stockton and Harold C. Fritts - V1

Runoff Relation

$ Significance of Antecedent Soil Moisture to a Semiarid Watershed Rainfall -

D. L. Chery, Jr. - V2

Runoff Relationships for a Mountain Watershed in Southern Arizona

S Rainfall -

M. Myhrman, C. B. Cl uff and F. Putman - V8

Runoff Source Areas $ Nonpoint- Source Pollutants Determine

L. J. Lane, H. L. Morton, D. E. Wallace, R. E. Wilson and R. D. Martin - V7

Runoff: A Preliminary Evaluation

Barney Paul Popkin - V2

$ Effect of a Grass and Soil Filter on Tucson Urban

Runoff?

$ Some Legal Problems of Urban

Hugh Holub - V2

Runoff $ Simple Time -Power Functions for Rainwater Infiltration and

R. M. Dixon, J. R. Simanton and L. J. Lane - V8

Runoff -Producing Thunderstorms Rainfall in the Southwest $ Regional Differences in

H. B. Osborn V1

Safe Drinking Water Act on Arizona's Water Systems

Richard S. Williamson - V10

$ Socio- Economic Impacts of the

Salt Balance in Groundwater of the Tulare Lake Basin, California

$

Kenneth D. Schmidt - V5

Salt Replacement Desalination

$ Fresh Water for Arizona by

Anthony B. Muller - V4

Salt Treatment $ Water Harvesting: Soil /Water Impacts of

Albert Todd - V10

Saline and Organic Water Pollution

$

Hinrich L.

Bohn and Gordon V. Johnson - V2

Salinity Control Planning in the Colorado River System

$

John T. Maletic - V4

Salinity in Effluent Lakes, Puerto Penasco, Sonora, Mexico

Alison L. Dunn - V11

$ A Study of

Salinity Loading Relationships in the Lower Colorado River Basin $ Intermittent Flow Events -

William Woessner - V10

Salinity Problem

$ Economic Alternatives in Solving the U.S.- Mexico Colorado River Water

William E. Martin - V4

Salinity Problems of the Safford Valley: An Interdisciplinary Analysis

$

Anthony B. Muller - V3

Saltcedar Thickets $ Antitranspirants as a Possible Alternative to the Eradication of

Robert S. Cunningham, Kenneth N. Brooks and David B. Thorud - V5

Saltcedar $ An Energy Budget Analysis of Evapotranspiration from

L. W. Gay, T. W. Sammis and J. Ben -Asher - V6

Saltcedar $ Diurnal Trends in Water Status, Transpiration, and Photosyntheses of

Mary Ellen Williams and Jay E. Anderson - V7

Saltcedar $ Transpiration and Photosynthesis in

Jay E. Anderson - V7

Saltwater Supply for Shrimp Aquaculture, Puerto Penasco, Sonora, Mexico $ Exploration for

K. J. DeCook, S. Ince, B. P. Popkin, J. F. Shreiber, Jr. and J. S. Sumner - V10

Sediment Analysis of the Recreational Waters of Upper Sabino Creek

$ Bottom

Patrick L.

McKee and Stanley K. Brickler - V7

Sediment Control on the Reclaimed Coal Mine Lands of Semiarid Southwest

$ Soil Erosion and

Tika R. Verna, John L. Thames and John E. Mills - V7

161

Sediment Production from a Chaparral Watershed in Central Arizona

$

Thomas E.

Hook and Alden R. Hibbert - V9

Sediment Sources of Midwestern Surface Waters

Donovan C. Wilkin and Susan J.

Hebel - V11

S

Sediment Transport in an Ephemeral Mountain Stream S Equilibrium Condition and

Burchard H. Heede - V6

Sediment Yield Equation From an Erosion Simulation Model S A

E. D. Shirley and L. J. Lane - V8

Sediment Yield from a Semi -Arid Watershed

S Uncertainty in

J. H. Smith, M. Fogel and L. Duckstein - V4

Sediment Yield on Forested Watersheds in Central Arizona

S An Interactive Model of Suspended

William O. Rasmussen and Peter F. Ffolliott - V9

Sediment Yields from Strip Mine Spoils of the Arid Southwest $ Stochastic Prediction of

Mark E. Auernhamer, Martin M. Fogel, Louis H. Hekman, Jr. and John L. Thames - V7

Sediment Yield S Reservoir Design under Random

L. Duckstein, F. Szidarovszky and S. Yakowitz - V6

Sediments and Soils

S Microtrac: A Rapid Particle -Size Analyzer of

R. L. Haverl and and L. R. Cooper - V11

Sedimentation in the Upper Gila Drainage, A Case Study

R. L.. Kingston and R. M. Solomon - V6

S Erosion and

Seepage Control

S An Evaluation of Current Practices in

D. G. Boyer and C. B. Cluff - V2

Semiarid Catchment S Variability of Infiltration Characteristics and Water Yield of a

Soronadi Nnaji, Ted W. Sammis and Daniel D. Evans - V5

Semi -Arid Catchments S A Deterministic Model for

S. Nnaji, D. R. Davis and M. M. Fogel - V4

Semi -Arid Watershed

$ Uncertainty in Sediment Yield from a

J. H. Smith, M. Fogel and L. Duckstein - V4

Semiarid Rangeland Conditions in the Southwest S Applicability of the Universal Soil Loss Equation to

K. G. Renard, J. R. Si manton and H. B. Osborn - V4

Semiarid Rangeland Watershed S Increasing Forage Production on a

J.

M. Tromble - V4

Semiarid Southwestern Rangeland Watershed S Effects of Brush to Grass Conversion on the Hydrology and

Erosion of a ... J.

R. Simanton, H. B. Osborn and K. G. Renard - V7

Semiarid Urbanized Watershed

S The Effect of an Intensive Summer Thunderstorm on a

D. G. Boyer and K. J. DeCook - V6

Semiarid Watershed S A Water Budget for a

Severo R. Saplaco, Peter F. Ffolliott and William O. Rasmussen - V9

Semiarid Watershed

S Application of a Double Triangle Unit Hydrograph to a Small

M. H. Di ski n and L. J. Lane - V6

Semiarid Watershed S Simulation of Partial Area Response from a Small

Leonard J. Lane and Delmer E. Wallace - V6

Semiarid Watersheds $ Geomorphic Thresholds and Their Influence on Surface Runoff from Small

D. E. Wallace and L. J. Lane - V6

Simulating Infiltrometer $ A Jeep- Mounted Rainfall

William R. Henkle - V3

Simulation of Ground Water Systems with Analog Models (Abstract)

$

E. P. Patten V3

Simulation of Partial Area Response from a Small Semiarid Watershed

S

Leonard J. Lane and Delmer E. Wallace - V6

Simulation of Summer Rainfall Occurrence in Arizona and New Mexico

$

Herbert B.

Osborn and Donald Ross Davis - V7

Simulation

$ The Construction of a Probability Distribution for Rainfall on a Watershed by

Gary Williamson and Donald Ross Davis - V2

Simulator to Determine Relative Infiltration Rates of Contributing Watersheds to the Lower Gila Below

$ The Use of a Realistic Rainfall .

.

.

C. B. Cluff and D. G. Boyer - V1

Snow Course Data for Central Arizona S Probability Distributions of

Lawrence E. Cary and Robert L. Beschta - V3

Snow Course Data in Describing Local Snow Conditions in Arizona Forests S Evaluation of the Use of Soil

Conservation Service ... Gerald J. Gottfried and Peter F.

Ffolliott - VII

Snow Cover from ERTS Imagery on the Black River Basin

Jerry S.

Aul and Peter F.

Ffolliott - V5

Snowfall Interception in Arizona Ponderosa Pine Forest

S Measuring

S A Preliminary Assessment of

Larry C. Tennyson, Peter F. Ffolliott and David B. Thorud - V3

Snowmelt in Arizona Ponderosa Pine Forests $ Lysimeter

Mikeal E. Jones, Peter F. Ffolliott and David B. Thorud - V6

Snowmelt Lysimeters in an Arizona Mixed Conifer Stand

S An Evaluation of

Gerald J. Gottfried and Peter F.

Ffolliott - V10

Snowmelt Modeling $ Solar Radiation as Indexed by Clouds for

D. P. McAda and P. F. Ffolliott - V8

Snowmelt- Runoff Forecasts in Arizona S Use of Satellite Data to Develop

Peter F. Ffolliott and William O. Rasmussen - V6

162

Snowpack Density on an Arizona Mixed Conifer Forest Watershed

$

Peter F. Ffolliott and J.

R. Thompson - V7

Snowpack Dynamics in Arizona's Aspen Forests

S

Michael J. Timmer, Peter F. Ffolliott and William O. Rasmussen - V10

Snowpack Inventory- Prediction Relationships

S An Analysis of Yearly Differences in

Peter F.

Ffolliott, David B. Thorud and Richard W. Enz - V2

Snowpack Mapping $ Aerial

William L. Warskow - V5

Snowpack Profiles in and Adjacent to Forest Openings

$ A Technique to Evaluate

Peter F. Ffolliott and David B.

Thorud - V4

Snowpack Water Yields S Progress in Developing Forest Management Guidelines for Increasing

David B. Thorud and Peter F.

Ffolliott - V1

Soil Columns Flooded with Sewage Water

S Addition of a Carbon Pulse to Stimulate Denitrification in

J. C. Lance and R. G. Gilbert - V6

Soil Drying After Irrigation $ Seasonal Effects on

B. A. Kimball and R. D. Jackson - V1

Soil Evaporation Via Surface Temperature Measurements S Assessing Bare

Sherwood B.

Idso, Robert J. Reginato and Ray D. Jackson - V5

Soil Filter on Tucson Urban Runoff: A Preliminary Evaluation $ Effect of a Grass and

Barney Paul Popkin - V2

Soil Flooded with Secondary Sewage Effluent S Effect of Algal Growth and Dissolved Oxygen on Redox

Potentials in ... R. G. Gilbert and R. C. Rice - V8

Soil Invertebrate Population

S Infiltration Response to Surface Plant Cover and

Isobel R. McGowan - V10

Soil Moisture Remotely

S Assessing

Robert J.

Reginato, Sherwood B.

Idso and Ray D. Jackson - V5

Soil Moisture to a Semiarid Watershed Rainfall- Runoff Relation

D.

L. Chery, Jr. - V2

S Significance of Antecedent

Soil Moisture Under Natural Vegetation S Variations in

T. W. Sammis and D. L. Weeks - V7

Soil Porosity Characteristics of Arizona Soils

S Relationships of Soil Texture with Soil Water Content and .

.

.

Donald F. Post V11

Soil Stabilizer

$ Wax Water Harvesting Treatment Improved with Antistripping Agent and

Dwayne H. Fink - V10

Soil Surface Micro -Flora

S Hydrologic Effects of

William F. Faust - V1

Soil System to Utilize and Purify Municipal Waste Water $ Evaluation of a Turfgrass -

R. C. Sidle and G. V. Johnson - V2

Soil Texture with Soil Water Content and Soil Porosity Characteristics of Arizona Soils S Relationships

Soil of ... Donald F. Post - V11

$ Effects of a Wetting Agent on the Infiltration Characteristics of a Ponderosa Pine

Marc G. Kaplan and Malcolm J. Zwolinski - V3

Soils for Water Harvesting

S Candelilla /Petroleum Wax Mixtures for Treating

Dwayne H. Fink - Vii

Soils for Water Harvesting $ Laboratory Evaluation of Water -Repellent

Dwayne H. Fink - V4

Soils in a Mountain Region: A Case Study on the Empire and the Sonoit $ Evaluation of Recharge Through

Soil

U.

Kafri and J. Ben -Asher - V6

$ Laboratory Weathering of Water -Repellent Wax- Treated

Dwayne H. Fink - V6

Soils Treated for Water Repellency

$ Freeze -Thaw Effects on

Dwayne H. Fink and Stanley T. Mitchell - V5

Soil -Turf Filter

S Nitrogen Removal from Secondary Effluent Applied to a

E. L. Anderson, I. L. Pepper and G. V. Johnson - V8

Soil -Water Content and Soil -Water Pressure $ Field Measurements of

R. J. Reginato and R. D. Jackson - V1

Soil /Water Impacts of Salt Treatment S Water Harvesting:

Albert Todd - V10

Soil -Water Status Via Albedo Measurement $ Assessing

Sherwood B.

Idso and Robert J. Reginato - V4

Soils S Microtrac: A Rapid Particle -Size Analyzer of Sediments and

Soils

R. L. Haverland and L. R. Cooper - V11

$ Penetrability and Hydraulic Conductivity of Dilute Sulfuric Acid Solutions in Selected Arizona

S. Miyamoto, J. Ryan and H. L. Bohn - V3

Soils $ Water Quality of Streamflow from Forested Watersheds on Sedimentary

Paul W.

Gregory and Peter F. Ffolliott - V6

Solar Energy for Irrigation Pumping S Feasibility of Using

Dennis Larson, D.

D. Fangmeier, W.

G. Matlock, John Daffy and C.

D.

Sands II - V6

Solar Powered Irrigation Pumping Equipment

S

Dennis L. Larson and C. D. Sands, Jr. - V9

Solar Powered Pumping Project: Operating Experiences $ Arizona

Dennis L.

Larson - V11

163

Solar Radiation as Indexed by Clouds for Snowmelt Modeling

$

D. P. McAda and P. F. Ffollíott - V8

Stock Ponds for Hydrologic Research on Southwest Rangelands

J. R. Si manton and H. B. Osborn -

V3

$ Use of

Stock Ponds with Soda Ash

$ Effectiveness of Sealing Southeastern Arizona

H. B. Osborn, J. R. Si manton and R. B. Koehi er - V8

Stock Tanks of Southeastern Arizona

$ Time -Related Changes in Water Quality of

D. E. Wallace and H. A. Schreiber - V4

Stochastic Analysis of Flows of Rillito Creek $ A

N. E. Baran, C. C. Kisiel and L. Duckstein - Vi

Stochastic Decision Model $ Input Specifications to a

D. M. Clainos, L. Duckstein and T. G. Roefs -

V2

Stochastic Prediction of Sediment Yields from Strip Mine Spoils of the Arid Southwest

Mark E. Auernhamer, Martin M. Fogel, Louis H.

Hekman, Jr. and John L. Thames - V7

Stock- Water Harvesting with Wax on the Arizona Strip

$

Keith R. Cooley, Loren N. Brazell, Gary W. Frasier and Dwayne H.

Fink - V6

Storm Flows Management in Relation to Industrial Development $

Robert E. Smith - P2

Storm Operations System for Salt River and Verde River Watersheds

Dick Juetten and Don Wessner - P2

Stormflow as a Function of Watershed Impervious Area

$

$

$ Salt River Project Emergency

Jan M. Pankey and Richard H. Hawkins - V11

Stream Discharge in Navajo and Apache Counties, Arizona

Development on .

.

.

T. D. Hogan and M. E. Bond - V9

$ The Effects of Second -Home and Resort -Town

Stream Flows

$ Impact of Development on

Paul D. Trotta, James J. Rodgers and William B. Vandivere - V9

Streamflow Probabilities $ Conditional

T. G. Roefs and D. M. Clainos V1

Streamflow

$ Converting Chaparral to Grass to Increase

Paul

A.

Ingebo - V2

Stripmined Lands

$ A Multiattribute Approach to the Reclamation of

Fritz H. Brink, Lucien Duckstein and John L. Thames - V9

Subsidence Damage in Southern Arizona $

Charles A. McCauley and Russell L. Gum - 42

Temperature and Humidity Gradients in the Air Near the Ground

$ An Exchange System for Precise

Measurements of ... L. W. Gay and L. J. Fritschen - V9

Temperature Measurements $ Assessing Bare Soil Evaporation Via Surface

Sherwood B.

Idso, Robert J. Reginato and Ray D. Jackson - V5

Thunderstorm on a Semiarid Urbanized Watershed

$ The Effect of an Intensive Summer

D. G. Boyer and K. J. DeCook - V6

Thunderstorm Rainfall in the Southwest

$ Stationarity in

William C. Mills and Herbert B. Osborn - V3

Thunderstorms Rainfall in the Southwest $ Regional Differences in Runoff -Producing

H. B. Osborn - YI

Time Series $ On the Statistics of Hydrologic

Sidney Yakowitz and Jack Denny - V3

Time -Related Changes in Water Quality of Stock Tanks of Southeastern Arizona $

D. E. Wallace and H. A. Schreiber - V4

Time- Series Analysis of Tucson, Arizona

$ The Impact of Socioeconomic Status on Residential Water Use: A

Cross- Section ... R. Bruce Billings and Donald E. Agthe - Y9

Tracers for Waste Monitoring

$ New Organic

Stephen L. Jensen and Glenn Thompson - P3

Tracers, A New Technology $ Chlorofluorocarbons as Hydrologic

J. H. Randall and T. R. Schultz - V6

Transmission Loss Potential

$ Geomorphic Features Affecting

D. E. Wallace and L. J. Lane - V8

Transmission Losses in an Ephemeral Stream

$ Bed Material Characteristics and

J. B. Murphey, L. J. Lane and M. H. Diskin - V2

Transmission Losses in Ephemeral Stream Channels $ Estimating

Leonard J.

Lane, Virginia A. Ferreira and Edward D. Shirley - V10

Transmissivity Distribution in the Tucson Basin Aquifer

$

D. J. Supkow - V2

Transmissivity Values in the Salt River Valley Using Recovery Tests

Mary Ann Niccoli and Michael

R. Long - V11

Transpiration and Photosynthesis in Saltcedar

$

$ Determination of

Jay E. Anderson - V7

Transpiration, and Photosyntheses of Saltcedar

$ Diurnal Trends in Water Status,

Mary Ellen Williams and Jay E. Anderson - V7

Transpiration

$ Estimating Phreatophyte

Lloyd W. Gay and Theodore W. Sammis - V7

Transpiration $ Reducing Phreatophyte

David C. Davenport and Robert M. Hagen - V7

164

Tree -Ring Data

$ Augmenting Annual Runoff Records Using

Charles W. Stockton and Harold C. Fritts - V1

Tree -Ring Dating of Colorado River Driftwood in the Grand Canyon

$

C. W. Ferguson V1

Uncertainties in an Environmental Impact Statement $ Systematic Assessment of

Soronadi Nnaji, Donald R.

Davis and Lucien Duckstein - V6

Uncertainties in Digital- Computer Modeling of Ground -Water Basins

$

Joseph S. Gates and Chester C.

Kisiel - V1

Unit Hydrograph to a Small Semiarid Watershed $ Application of a Double Triangle

M. H. Di skin and L. J. Lane - V6

Universal Soil Loss Equation in the Tropics

$ Use of the

Todd C.

Rasmussen and Fred C. Tracy - V11

Universal Soil Loss Equation to Semiarid Rangeland Conditions in the Southwest $ Applicability of the

K. G. Renard, J. R. Simanton and H. B. Osborn - V4

Universal Soil Loss Equation $ Thunderstorm Precipitation Effects on the Rainfall- Erosion Index of the

Kenneth G. Renard and J.

Roger Simanton - V5

Urban Area in an Arid Environment. Tucson, Arizona $ Water Quality Problems of the

G.

Hansen - V8

Urban Area

$ Analysis of Wastewater Land Treatment Systems in the Phoenix

R. L. Ewing - V8

Urban Hydrology: State -of- the -Art $

Warren Viessman, Jr. - V3

Urban Perspective $ Arizona Groundwater Law Reform - An

H. Holub - V8

Urban Runoff Development $ Legal Aspects of

D. A. Chudnoff - V8

Urban Runoff: A Preliminary Evaluation

Barney Paul Popkin - V2

Urban Runoff?

$ Some Legal Problems of

Hugh Holub - V2

$ Effect of a Grass and Soil Filter on Tucson

Urban Waste Water Management $ Land Treatment for

William L. Lorah and Kenneth R. Wright - V3

Urban Water Supply: The Tucson Case $ Rising Energy Prices, Water Demand by Peri -Urban Agriculture, and

Implications for .

.

.

H. W. Ayer and D. W. Gapp - V8

Urbanization on Runoff from Small Watersheds $ Effect of

Samuel

E.

Kao, Martin M. Fogel and Sol D. Resnick - V3

Urbanized Watershed

$ The Effect of an Intensive Summer Thunderstorm on a Semiarid

D. G. Boyer and K. J. DeCook - V6

USLE to Southwestern Rangelands $ Application of the

J. Roger Simanton, Herbert B. Osborn and Kenneth G. Renard - V10

Vegetable Production $ Mulching Techniques for Arid Lands

R.

W. Peebles and Norman F. Oebker - V1

Vegetation Changes Along the Santa Cruz River Channel Near Tumacacori,

$ Hydraulic Effects of

Lee H. Applegate - V11

Vegetation Types Across the Mogollon Rim $ Hydrologic Regimes of Three

Malchus B. Baker, Jr.

- V11

Vegetation Types $ An Analysis of Recession Flows From Different

Wan Norazmin bin Sulaiman and Peter F. Ffolliott - V11

Vegetation

$ Variations in Soil Moisture Under Natural

T. W. Sammis and D. L. Weeks - V7

Wax Mixtures for Treating Soils for Water Harvesting $ Candelilla /Petroleum

Dwayne H. Fink - V11

Wax on the Arizona Strip $ Stock- Water Harvesting with

Keith R. Cooley, Loren N. Brazell, Gary W. Frasier and Dwayne H. Fink - V6

Wax Water Harvesting Treatment Improved with Antistripping Agent and Soil Stabilizer

$

Dwayne H. Fink - V10

Waste Monitoring $ New Organic Tracers for

Stephen L. Jensen and Glenn Thompson - P3

Waste Water Management $ Land Treatment for Urban

William L. Lorah and Kenneth R. Wright - V3

Waste Water $ Evaluation of a Turfgrass - Soil System to Utilize and Purify Municipal

R. C. Sidle and G. V. Johnson - V2

Wasted Waters for Desert -Household Gardening $ Salvaging

D. H. Fink and W. L. Ehrler - V8

Waste -Water Utilization in Arizona $ Economic and Energy Opportunities for Municipal

E. J. Weber - P3

Wastewater Effluent - An Element of Total Water Resource Planning

$

J. D. Goff - V8

Wastewater Land Treatment Systems in the Phoenix Urban Area

$ Analysis of

R. L. Ewing - V8

Wastewater Reuse Alternatives

$

Herman Bouwer - P1

165

Wastewater Reuse $ Heavy Metals 8

T. E. Higgins - V8

Wastewater Reuse- How Viable Is It? Another Look

W. L. Chase and J. Fulton - V8

$

Wastewater to Land S Health Effects of Application of

James D. Goff - V9

Water Consumption in Tucson, 1974 to 1978 $ Changes in Water Rates and

Adrian H. Griffin, James C. Wade and William E. Martin - V10

Water Consumption Patterns of Arizona Second -Home Owners $ Current and Forecasted

M. E. Bond and R. H. Dunikoski - V8

Water Harvesting System: A Potential Mine Reclamation Alternative

Charles L. Constant and John Thames - V10

$ The Mound and Valley

Water Harvesting Treatment Improved with Antistripping Agent and Soil Stabilizer

Dwayne H. Fink - V10

Water Harvesting with Wax on the Arizona Strip

$ Stock -

$ Wax

Keith R. Cooley, Loren N. Brazell, Gary W. Frasier and Dwayne H. Fink - V6

Water Harvesting

$ Candelilla /Petroleum Wax Mixtures for Treating Soils for

Dwayne H. Fink - V11

Water Harvesting $ Laboratory Evaluation of Water -Repellent Soils for

Dwayne H. Fink - V4

Water Harvesting $ Residual Waxes for

Dwayne H. Fink - V7

Water Harvesting: Soil /Water Impacts of Salt Treatment

$

Albert Todd - V10

Water Impoundment Applications for SBR /Asphalt Membrane Systems

$

Carlon C. Chambers - V10

Water Rates and Water Consumption in Tucson, 1974 to 1978

S Changes in

Adrian H. Griffin, James C. Wade and William E. Martin - V10

Water Resource Alternatives for Power Generation in Arizona

$

Stephen E. Smith, K. James DeCook and Rocco A. Fazzolare - V4

Water Resource Leaders

$ Man -Nature Attitudes of Arizona

Roger A. Kanerva and David A.

King - V2

Water Resource Projects $ Early Public Involvement in Federal

Freda Johnson and Michael Thuss - V9

Water Resources Development (Abstract)

S Impact on the Environment by

Sol Resnick - V3

Water Resources Management Plan for Tucson, Arizona

R. Bruce Johnson - V10

$ Impacts of a New

Water Resources of the Inner Basin of San Francisco Volcano, Coconino

E. L. Montgomery and R. H. DeWitt V4

S

Water Resources of the Woody Mountain Well Field Area, Coconino County, Arizona

Errol L. Montgomery and Robert H. DeWitt - V5

Water Resources Research on Forest and Rangelands in Arizona

$

Alden R. Hibbert - V4

Water Resources

$ Collective Utility: A Systems Approach for the Utilization of

Edwin Dupnick and Lucien Duckstein - V1

Water Rights of the Bureau of Land Management in Colorado

$ Federal Reserved

Richard A. Herbert and Anthony L. Martinez - V11

Water Rights: The Bureaucratic Response

Daniel C. McCool - V11

$ Indian

Water Supply Data Base

$ A

J.

F. Nunamaker, David E.

Pingry and Rex Riley - V7

S

Water Supply for Home Irrigation (Poster Session)

Barney P. Popkin - V9

$ Augmenting

Water Supply for the Carefree -Cave Creek Area

Edward A. Nemecek and Philip C. Briggs - V6

S Study of the Adequacy of the

Water Supply Planning $ The Role of Conservation in

Augustine J. Fredrich - P1

Water -Awareness in Tucson, Arizona: A Case Study

$

Kebba Buckley - V10

Wax- Treated Soil $ Laboratory Weathering of Water -Repellent

Dwayne H. Fink - V6

Waxes for Water Harvesting

$ Residual

Dwayne H. Fink - V7

Weather Modification in Arizona, 1971

$

Herbert B. Osborn - V2

Weather Modification S The Role of the States in Control of

Ray Jay Davis - V6

Weathering of Water -Repellent Wax- Treated Soil

$ Laboratory

Dwayne H. Fink - V6

Well Driller Logs S Computerized Depth Interval Determination of Groundwater Characteristics from

Mike Long and Stephen Erb - V10

166

Well Field Area, Coconino County, Arizona S Water Resources of the Woody Mountain

Errol L. Montgomery and Robert H. DeWitt - V5

Well Field Design

S Application of Bayesian Decision Theory in

Charles A. Bostock and Donald R. Davis - V5

Well Field, Coconino County, Arizona

$ Structural Relations Determined from Interpretation of

Geophysical Surveys: Woody Mountain .

.

.

Phyllis K. Scott and E.

L. Montgomery - V4

Well Levels During Coastal Aquifer Tests

$ Correcting Tidal Responses in Observed Water

Barney P. Popkin - V11

Well Losses in Consolidated Rock Aquifers

$ The Application of Step -Drawdown Pumping Tests for

Determining ... V. W. Uhl, Jr., V. G. Joshi, A. Alpheus and G. Sharma - V5

Well -Field Design Criteria for Coastal Seawater Development $

Barney P. Popkin - V10

Wells S Barometric Response of Water Levels in Flagstaff Municipal

Errol

L. Montgomery, Emily Dordosz, Russell O. Dalton, Jr. and Ronald H. DeWitt - V7

Wells, Flagstaff, Arizona $ Chemistry of Effervescing Groundwater from Municipal

John C. Germ and Errol L. Montgomery - V5

Wetlands S The Importance of Arizona's

Jon Rodiek - V1O

167

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