AN ASSESSMENT OF THE PERFORMANCE OF FEDERALLY REGULATED SEDIMENTATION PONDS by

AN ASSESSMENT OF THE PERFORMANCE OF FEDERALLY REGULATED SEDIMENTATION PONDS by
AN ASSESSMENT OF THE PERFORMANCE
OF FEDERALLY REGULATED
SEDIMENTATION PONDS
by
William Benton Vandivere
A Thesis Submitted to the Faculty of the
SCHOOL OF RENEWABLE NATURAL RESOURCES
In Partial Fulfillment of the Requirements
For the Degree of
MASTER OF SCIENCE
WITH A MAJOR IN WATERSHED MANAGEMENT
In the Graduate College
THE UNIVERSITY OF ARIZONA
1980
STATEMENT BY AUTHOR
This thesis has been submitted in partial fulfillment of requirements for an advanced degree at The University of Arizona and is
deposited in the University Library to be made available to borrowers
under rules of the Library.
Brief quotations from this thesis are allowable without special
permission, provided that accurate acknowledgment of source is made.
Requests for permission for extended quotation from or reproduction of
this manuscript in whole or in part may be granted by the head of the
major department or the Dean of the Graduate College when in his judgment the proposed use of the material is in the interests of scholarship. In all other instances, however, permission must be obtained
from the author.
SIGNED:
APPROVAL BY THESIS COMMITTEE
This thesis has been approved on the date shown below:
,
-
7
2
il/A-
.
MARTIN MAI,U FOGEL
Date
gement
IJI-1
GOJ
(
DONALD ROSS DAVIS
Assistant Profess .r of Hydrology
and Wate fesoAices
LOUIS . HEKMAN
Assistant Prof ssor of Renewable
Natur Resources
X/C6/ 3 (t O
-
Date'
Date
ACKNOWLEDGMENTS
The author is greatly indebted to his principal advisor, Dr.
Martin Fogel, for providing the opportunity to develop and expand his
intellectual facilities. His avowed skepticism was at once refreshing
and realistic and will continue to endear him to his students. Additional thanks must be directed toward Dr. Louis Hekman and Dr. Donald
Davis, whose patience and guidance were well appreciated. The periodic
assistance from Dr. John Thames also contributed to the author's pursuit of a practical understanding of the field of hydrology.
Best wishes and sincere affection are ext4nded to friends and
colleagues of the author during his brief tenure with the School of
Renewable Natural Resources. A genuine comaraderie existed, and hopefully will continue between us, expecially Steve Blake, Jeff Franklin,
and Todd Rasmussen. Their input was always informative and much valued.
A special heartfelt thanks goes to Ms. Paula-Ann Cech who faithfully supported the author through good times and bad and without whose
help both his entire graduate and a significant part of his life experience would have been left unfulfulled.
Appreciation is expressed for the timely work done by Phyllis
Miller in preparing the final manuscript.
Also, the author wishes to acknowledge the aid received from
Andy Ward of the Agricultural Engineering Department of the University
of Kentucky who supplied access to the DEPOSITS sedimentation model.
iv
Portions of this study were carried out under grant
#14-34-0001-9056 from the Office of Water Resources Technology
entitled "The Role of Hydrologic Variability in Complying with Regulatory Enforcement Standards for the Rehabilitation of Surface-mined
Coal Lands." The author wishes to thank the taxpayers of this country
for this funding.
TABLE OF CONTENTS
Page
LIST OF ILLUSTRATIONS LIST OF TABLES
ABSTRACT
1.
vii
viii
ix
INTRODUCTION
1
2. REVIEW OF LITERATURE AND PERTINENT
REGULATORY STATUTES 4
Sedimentation Ponds and Manipulated Environments
Animal Feedlots Construction Sites Surface Mining Operations Uncertainty in the Sedimentation Process Applicable Regulatory Statutes 3.
SITE CHARACTERISTICS AND FORMULATION OF STUDY Hypothetical Watershed Development of Hydrologic Inputs
Model Components and Operation:
Program INFLUX Precipitation Infiltration Runoff Sediment Sedimentation Pond Design DEPOSITS Sedimentation Model
4.
RESULTS AND DISCUSSION
Pond Sensitivity Analysis National Soil Material with
Untreated Pond Inflow Hydrologic Uncertainty and Implications
for Pond Performance Model Adaptability and Regional Bias • •
4
5
7
9
13
16
21
21
22
25
25
27
34
36
38
43
49
49
57
66
70
vi
TABLE OF CONTENTS, Continued.
Page
5.
CONCLUSIONS AND RECOMMENDATIONS
72
APPENDIX A: SEDIMENTATION POND DESIGN
77
APPENDIX B: INFLUX VARIABLE DESCRIPTION 109
APPENDIX C: PROGRAM LISTING OF INFLUX 112
APPENDIX D: PROGRAM AND INPUT LISTING OF DEPOSITS 116
LIST OF REFERENCES 137
LIST OF ILLUSTRATIONS
Figure
Page
1. SCS Type I and II 24-hr. rainfall distribution 26
2. Data points and infiltration curve for 0.5 year old
spoil material, J-3 experimental area 29
3. Generalized flowchart for hydrologic linkages . . 31
4.
SCS triangular hydrograph 37
5.
Schematic diagram of sedimentation pond and
dewatering device 44
6. Plug flow routing for DEPOSITS sedimentation
model 7. Predicted peak effluent concentrations and contours
in mg/2 for Black Mesa minspoil with altered inputs and untreated pond inflow
vii
47
58
LIST OF TABLES
Table
Page
1. Point precipitation-frequency values for Black Mesa
Mine, Arizona, in inches
24
2. Discretization of Type II rainfall distribution for
24 hr. duration
28
3. Discretization of J-3 infiltration capacity curve
32
4.
5.
6.
7.
Precipitation characteristics and predicted peak
effluent sediment concentrations for routed
Black Mesa storms, 5-10 yr. return periods:
minespoil with untreated pond inflow
51
Precipitation characteristics and predicted peak effluent
sediment concentrations for routed Black Mesa storms,
12-25 yr. return periods: minespoil with untreated
pond inflow
53
Particle size distributions for undisturbed experimental
waterhseds: Black Mesa, AZ
59
Predicted effluent sediment concentrations for routed
Black Mesa storms: natural soil material with
untreated pond inflow
61
Predicted peak effluent sediment concentrations for
routed, selected Black Mesa storms: minespoil with
chemical treatment of inflow
63
Predicted event sedimPnt yield for simulated conditions
at Black Mesa, AZ: 5-10 yr. return periods
64
Predicted event sediment yield for simulated conditions
at Black Mesa, AZ: 12-25 yr. return periods
65
A.1 Size fraction distributions for sediment production:
J-3 experimental watershed, Black Mesa Mine
84
A.2 Rating relations for final pond design
88
8.
9.
10.
A.3 Stage-discharge relations for final pond design
viii
91
ABSTRACT
A study was undertaken to evaluate the performance of federally
regulated sedimentation ponds, used in conjunction with surface mining
operations in the semi-arid southwest. Emphasis was placed on the assessment of pond performance under conditions of hydrologic uncertainty represented by precipitation inputs of varying frequencies and durations.
A hypothetical watershed with characteristics common to the study area
functioned as the medium for surface water flux to the detention facility.
Pond design was based on accepted hydrologic and engineering procedure
and concurred with published federal reclamation statutes. Computer programs were utilized to model both the temporal characteristics of southwestern convective rainfall and the generation of water and sediment inflaws resulting from the application of storms over the watershed. A
previously developed sedimentation routine was then used to determine
effluent sediment concentrations corresponding to the modeled events.
Three watershed-pond conditions were investigated to assess the efficacy
of the sedimentation pond in meeting effluent quality standards. Results
indicated that poor pond performance ensured unless chemical treatment
was maintained. Since variations in precipitation intensity influenced
predicted pond performance, it was recommended that hydrologic uncertainty be considered in the drafting of regional reclamation statutes.
ix
CHAPTER 1
INTRODUCTION
As natural phenomena the fluvial processes of erosion and
sedimendation proceed at a rate determined by prevailing hydrometeorological and geologic conditions. A quasi-equilibrium is established
over time which affects a balance between hillslope development and
stream regimen. Man's intervention, however, often results in short
term distortions in this delicately adjusting mechanism.
The national addiction to non-renewable fossil fuels has led to
a recent expansion in possibly the most environmentally disruptive of
human activities; the surface mining of coal. An immediate consequence
of this disruption is an acceleration in the rates of erosion and
sedimentation observed in the effected areas. Extensive soil loss from
surface mine sites inhibits generation of protective vegetative cover
and befouls area stream flow, threatening indigenous aquatic life.
In an effort to mitigate the environmental damage wrought by
mining operations, the 95th Congress enacted preventative measures
embodied in the Surface Mining Control and Reclamation Act of 1977.
The Act expressed the intent to assure reclamation of mined land while
not unduly burdening mine operators. Of course, the high priority given
continued access to the coal resource was sustained.
The federal statutes represent baseline criteria for acceptable
mining and reclamation procedures. States have been presented with the
1
2
option of developing their own standards, as long as they are at least
as stringent as those outlined by the Act. In addition, states have
been encouraged to consider regional variabilities in the drafting of
their federal counterparts.
A permanent regulatory program has been published by the Office
of Surface Mining (OSM) for purposes of setting standards for mining and
reclamation practices which are consistent with the legislative intent
of Congress. Considerable attention was paid to the maintenance of the
hydrologic balance in and adjacent to areas subjected to mining disturbances. Central to this concept was the desire to minimize changes in
water quality and quantity, drainage patterns,and groundwater systems.
Consideration of feasible alternatives convinced OSM that the use of
sedimentation ponds in conjunction with other sediment control measures
provided the best available technology for removing suspended solids
from mine site runoff.
In the semi-arid regions of the western U.S., extreme variability
in the occurrence and nature of precipitation introduces an element of
uncertainty into the design process for sedimentation ponds. Since
assessment of the effects of regional hydrologic and climatic uncertainty
on reclamation efforts has been left unaddressed by federal statutes, a
need has arisen for evaluation of the uncertainties and their implications for the design and expected performance of mandated sedimentation
ponds.
The present study attempts to aid in the appraisal of the
effects of hydrologic uncertainty on the performance of federally
regulated sedimentation ponds. Specifically, its purpose is threefold:
3
(1) Compile a model capable of simulating the performance of
sedimentation ponds designed in accordance with federal
statutes and generally accepted engineering-hydrologic
practice.
(2) Assess the effects of precipitation uncertainty, in particular,
the influence of variable rainfall intensity and rainfallrunoff volume on sediment yields from minespoil watersheds
and on the effluent quality of event based discharges from
sedimentation ponds functioning on these watersheds.
(3) Evaluate current federal performance criteria for sedimentation
ponds functioning in a semi-arid environment where precipitation influx is limited and predominantly convective in character.
CHAPTER 2
REVIEW OF LITERATURE AND
PERTINENT REGULATORY STATUTES
The following section is devoted to a review of research and
legislation currently influencing the design and evaluation of the
performance of sedimentation ponds. Initially, studies dealing with the
application of sedimentation ponds to the problem of alleviating pollutant migration under disturbed conditions are summarized. A brief
examination of work aimed at delineating the effects of uncertainty in
the sedimentation process follows. Concluding the chapter is a condensed
review of recently promulgated federal statutes especially relevant to
the present investigation.
Sedimentation Ponds and
Manipulated Environments
Literature pertaining to the design and performance of sedimentation ponds was rather sparse until the advent of federal water quality
legislation in the early nineteen seventies. In response to newly enacted state and federal guidelines for pond design, researchers concerned
themselves with the evaluation of ponds, existing or hypothetical,
which conformed to applicable regulatory statutes. Relevant studies
have focused on the utilization of detention basins for purposes of
mitigating environmental degredation in three disturbed settings:
4
5
(1) animal feedlots; (2) construction sites; and (3) surface mining
operations. The requirement for detention facilities at feedlot locations stems from the desire to limit discharge of organic waste products
as well as nutrient and sediment-laden water into receiving streams.
Discharge from areas disturbed by construction and surface mining, while
also potentially deleterious to existing chemical balance in streams,
is primarily undesirable from the standpoint of the intensive stream
sediment loading it engenders.
Animal Feedlots
Due to the objectionable nature of runoff from animal feedlot
areas, detention facilities are often designed to preclude any discharge
of runoff generated by the 10-yr, 24-hr. or 25-yr., 24-hr. rainfall
event. Wensink and Miner (1975), using simulated rainfall and temperature inputs for Oregon feedlot sites, analyzed the performance of a
hypothetical detention basin. Dewatering of stored runoff was accomplished solely by pumpage in response to irrigation demand which was
dependent upon antecedent temperature and moisture conditions. Reservoir
storage volume was determined using two design methods. A "retention
return period" method, employing the SCS rainfall-runoff relations and
rainfall frequency data published by the National Oceanic and Atmospheric Administration (NOAA) was compared with a "sufficient design"
technique. The latter method sized the facility on the basis of total
storage of all runoff resulting from storms falling within the bounds
of the design event. The authors concluded that for most cases the
6
"return period" design technique produced either insufficient storage or
resulted in unreasonably expensive basins. The "sufficient design
technique, on the other hand, was found to minimize the required pond
volume for the appropriate pumping rate while more adequately satisfying
environmental protection standards.
A similar investigation (Koelliker, Manges, and Lipper, 1975)
carried out in Kansas examined the effect of regional precipitation
variability on detention basin response. Evaporation, as well as
irrigation pumpage, was incorporated into the analysis. Basin performance as measured by frequency of overflow was considerably worse in
regions experiencing lengthly periods of persistent rainfall. Drier
regions generally subject to single rainfall events with longer interarrival times created fewer basin overflows. Consideration of chronic
wet periods was, therefore, viewed as the critical factor in the sizing
of detention facilities. It should also be noted that most discharges
resulted from storms substantially less than the design event.
Hydrologic conditions typical of North Carolina dairy feedlots
were modeled by Overcash and Phillips (1978) to evaluate established
guidelines for the animal production industry. Linear and non-linear
rainfall-runoff models were applied to assess the efficiency of using
the mandated 25-yr., 24-hr. storm for retention basin design. At
representative SCS curve number values for specific feedlot locations,
the rainfall magnitude at which incremental rainfall produced a
correspondingly high (95%) runoff response was determined. This
quantity was found to correlate closely with that corresponding to the
7
appropriate 25-yr., 24-hr. rainfall value extracted from records of the
U.S. Weather Service and HISRAS (Hydrologic Information and Retrieval
System). On this basis, the authors concluded that the 25-yr., 24-hr.
storm appeared justifiable from a basin design viewpoint.
Construction Sites
Construction and urbanization denude substantial areas of land
exposing it to the heightened erosive capabilities of rainfall. Rapid
deterioration of water bodies adjoining these disturbed areas has necessitated regulatory controls directed at easing the impact of
accelerated sediment production on water quality. Because of the
extensive nature of the problem, a multitude of field evaluation and
model studies have ensued. Noteworthy, is the development of a sediment
discharge model (Curtis, 1976) describing water and sediment transport
in urbanizing areas. Model results revealed a tendency for both peak
sediment discharge and total volume of sediment discharge to increase
with increasing rainfall intensities.
The use of sedimentation ponds for reducing sediment concentrations in construction site runoff and the turbidity of receiving streams
has become widespread. Oscanyon (1975) introduced a set of design
criteria for the design of sediment basins on construction sites in
Maryland. It was assumed that even a well designed and adequately maintained structure would remove no smaller than .005 mm diameter sediment.
Alternative on-site measures were cited as offering a greater margin of
sediment control where higher percentages of clay are contained in pond
8
influent. An examination of the relative merits of in-stream and offstream sedimentation ponds was undertaken by Reed (1975). Both types
of ponds performed equally well in removing sediment, with reductions
of 80 percent for most storms. The in-stream pond, however, sustained
higher mean turbidity levels for longer periods of time than its offstream bounterpart. Curtis and McCuen (1977) derived a mathematical
model of a detention basin coupled with a watershed hydrologic model
for assessment of basin hydraulic efficiency. Trap efficiencies for
the basin were found to increase with decreasing proportions of smaller,
lighter particles in the inflow. In addition, both decreased initial
storage and smaller orifice diameters for perforated risers increased
modeled trap efficiencies. Decreased basin depth along with a concommitant increase in surface area also produced increased trap efficiencies. The effect of basin depth and area on performance was reaffirmed
in a study by Bondurant, Brockway, and Brow (1975). Specifically, the
authors recommended that in order to achieve a reduction in forward
velocity and depth of settling, the design would have to include
(1) adequate sediment storage volume, (2) decreasing flow depth towards
the outlet, and (3) a means for reducing entrance velocities to the
pond. Higher removal efficiencies were obtained at higher flow rates
due to the greater relative proportion of finer particles transported
at low flow rates.
9
Surface Mining Operations
Surface mining is one of the single most devastating operations
practiced by man upon his environment. Studies involving the application
of sedimentation ponds to mining operations and subsequent reclamation
efforts have again tended towards either the development of acceptable
guidelines or the appraisal of previously enacted legislation referring
to pond design and performance. Curtis (1974) conducted a study to
determine sediment production from mined areas and to propose criteria
for calculating detention basin storage volume. The first six months
following the termination of mining was indicated as the most critical
period for sediment production. Major factors contributing to sediment
yield were deduced to be methods of mining and handling of overburden
and rapid establishment of vegetative cover. The effectiveness of onsite sediment control measures coupled with an in-stream sedimentation
pond was analyzed by White and Plass (1974) for a mining operation in
West Virginia. It was noted that pond removal efficiency was greatest
for low intensity stormllow.
A review of sedimentation mechanics and earlier methods for
determination of sediment basin trap efficiency was presented by Haan
and Barfield (1978). Among the methods examined were that of the EPA
(1976) and the DEPOSITS sedimentation model (Ward, Haan, and
Barfield 1977a). The EPA (1976) methodology, a derivative of the prior
work of Camp (1945), was described as plausible for steady state flows,
but inadequate in its representation of semi-dry basin performance.
Because of its superior capabilities for handling typical field
10
conditions, the DEPOSITS model (Ward et al., 1977a) was favored by the
authors for more accurately depicting actual basin functioning. Another
conclusion reached by Haan and Barfield (1978) was that given identical
outflow riser configurations, a basin containing a permanent pool capacity will produce higher quality effluent than one lacking permanent
storage. This was attributed in part to the lessened probability that
resuspension of deposited sediments would occur.
The construction of the DEPOSITS model is described in detail
by Ward, Haan, and Barfield (1977b). Model verification was completed
using data published in a report by the EPA by Hittman Associates, Inc.
(1976a). The authors of the DEPOSITS formulation expressed misgivings
over the methods used in the EPA study. In particular, data collection
techniques were deemed unacceptable and the method for determining actual
basin performance was questioned. The equation developed for determination of trap efficiency assumed instantaneous flow through the basin.
This assumption neglected the effect of varying detention times for the
different portions of throughflow and depended entirely on simultaneous
readings of influent and effluent sediment concentrations over a short
time period. Since the DEPOSITS model accounted for varying flow rates
and reservoir detention times, the authors felt that it embodied a more
realistic conception of the actual sedimentation process and was, therefore, of greater value as a tool for evaluation of pond performance.
The ground breaking investigation on the performance of sedimentation ponds at eastern mining sites by Kathuria, Nawrocki, and Becker for the EPA (1976a) contributed much to the recent discussion on
11
performance standards prompted by OSM. In-field evaluation of nine
functioning ponds in W. Virginia, Kentucky and Pensylvania was conducted
in an attempt to determine trap efficiencies and to identify characteristics influencing pond behavior. Sampling was carried out during both
baseline and rainfall operating conditions. Theoretical removal efficiency computed by means of Ideal Settling Theory was compared to a
measure of actual removal efficiency expressed as:
10
c
R(% solids removed) =
1
6
l
X 100
(1)
6
10
C2
where C
1
is the concentration of suspended solids in the influent in
mg/1 and C 2 is the concentration of suspended solids in the effluent in
mg/l. Poor maintainance and lack of conformance to approved design
plans were cited as major factors inhibiting attainment of desired trap
efficiencies. It was recommended that either a ten hour minimum detention time or a maximum overflow velocity of 2 X 10 -5 m/sec. be
maintained in order to achieve higher suspended solids removal efficiencies. Maximization of pond surface area and continuous provision for a
minimum depth of 1.0 m. (3.3 ft.) were advised to limit resuspension of
settled sediment. The authors also acknowledged that in most cases
flocculating agents would be required for removal of fine grained sediments.
12
Inefficiencies inherent in settling finer sediment particles
were again recognized in an EPA study (1976). Referring to Ideal Settling Theory, the study suggested that required settling area for a
sediment detention structure be computed as: A=0 0 /V s , where Qo is the
pond overflow rate and V
s
is the critical settling velocity of the
smallest particle to be retained. Factors causing deviations from Ideal
Settling Theory were outlined. Additionally, a number of design innovations accruing from years of experimentation with existing ponds were
presented.
Ward, Haan and Barfield (1978) furthered understanding of the
basin design process with their work on the hydrology and hydraulics of
sediment basins. Various hypothetical basin geometries together with
different riser configurations were analyzed. Predictive equations for
estimation of peak effluent sediment concentration and basin trap efficiency were derived through regression analysis on data generated by the
DEPOSITS sedimentation model (Ward et al., 1977b). Three baseline conditions for simulation of pond performance were examined: (1) a dry
basin prior to the storm event; (2) a permanent pool below the riser
crest prior to the storm event; and (3) a permanent pool followed by a
base flow event occurring after the storm event. Notably, the authors
were of the opinion that effluent standards could not be met with perforated risers (principle spillway), and thus, they were not evaluated.
A number of illuminating conclusions were advanced regarding basin
design-performance interaction. Where the percentage of finer than 20
micron (II) particles exceeded 30 percent, it was the authors contention
13
that trap efficiencies would not exceed 80 percent in basins providing
a detention time of less than 12 hours for the 10 yr.-24 hr. design
event. Moreover, it was felt that if sediment in the inflow contained
greater than 20 percent of particles finer than 20g, it was unlikely
that water quality standards would be achieved unless flocculating
agents were utilized or storage in excess of 24 hours was possible. An
investigation pursued by McCarthy (1977) was mentioned as having indicated that flocculants could provide an economical solution to achievement
of water quality standards. In his work on sediment control on three
watersheds near Centralia, Washington, the author estimated chemical
treatment costs of $10/ac.-ft. of runoff.
Direct reference to the current federal statutes concerning
sedimentation pond design has been made by Krishnamurthi and Blazer
(1978). The authors contended that trap efficiency was more dependent
on functional design characteristics than on a particular magnitude of
flow. It was recommended that instead of requiring use of the designstorm concept for basin design, modeling of the physical characteristics
of the storm events should dictate design logic. Redirected emphasis on
sediment concentrations in streamflow as opposed to point source
pollutant concentrations in pond effluent was also suggested.
Uncertainty in the Sedimentation Process
Transport of sediment from contributing watersheds to receptor
watercourses is closely correlated with overland water discharge. Thus,
the uncertainties involved in the sedimentation process are related, in
14
part, to those germane to hydrologic systems. There are, however, other
sources of uncertainty introduced when a physical conceptualization of
the process is entailed. No attempt has been made in this review to
encompass all of the existing volumes devoted to empirical and fully
deterministic treatment of reservoir sedimentation. Only those formulations which recognize the uncertainties inherent in the sedimentation
process are surveyed.
Apart from readily discernable sources of random hydrologic
behavior, uncertainty affecting sedimentation also resides in factors
such as type of land use, vegetative cover, soil structure and erodibility, gulley headcutting, and other natural and man-induced processes
which contain elements of randomness (Woolhiser and Renard, 1978). The
uncertainty involved in appraising the erodibility of soil subjected to
the dynamic conditions of surface mining has been acknowledged by field
researchers of the SCS (EPA 1977). Another factor in the determination
of erosion from watersheds is rainfall energy (Wischmeier and Smith,
1965). The effect of regional precipitation uncertainty on the rainfall
erosion index (El) of the USLE has been examined by Renard and Simanton
(1975). Spatial and temporal variability in El values resulting from
air-mass thunderstorms were shown to be considerable even for watersheds located in close proximity to one another.
Woolhiser and Blinco (1975) discussed a study by Krumbein
(1968) in which the author classified three stages of statistical
development in sedimentology; descriptive statistics, analytical
15
statistics, and application of stochastic process models. Descriptive
statistics emphasizes the characteristics of the sample while analytical
statistics concerns itself primarily with extracting sample information
for the purpose of inferring population characteristics. The stochastic
model derives from consideration of the random properties of the
phenomena.
The analytic category is exemplified by the work of Shirley and
Lane (1978), Flaxman (1972), and Weber, Fogel, and Duckstein (1976).
Shirley and Lane (1978) derived a mathematical erosion simulation model
and made a least squares fit to observed data for a small watershed near
Tombstone, Arizona. In his study of sediment yield characteristics
for the western U.S., Flaxman (1972) utilized multiple regression
analysis on logged reservoir and stock pond sedimentation data to derive
an expression for watershed sediment production. Independent variables
were assumed to be: the ratio of average annual precipitation to
average annual temperature, watershed slope, the percent of soil particles coarser than 1 millimeter (mm) in the surface 2 inches of soil,
and a descriptor of aggregation potential in that same 2 inch soil
surface layer.
The utility of multiple regression models for the prediction of
sediment yield has been scrutinized by Weber et al. (1976). Data
obtained from Flaxman's (1972) study was used to assess the applicability
of four linear and logarithmic transformation models. It was concluded
on the basis of regression analysis and economic loss function analysis
that the linear model was preferable to the other log transformation
models evaluated.
16
Referring to the work of Parzen (1962), Woolhisen and Blinco
(1975) state that: "A stochastic process is the dynamic part of probability theory and we observe a stochastic process whenever we examine
a process developing in time in a manner controlled by probabilistic
laws." There exists a number of partial and wholly stochastic models
which can be included in Krumbein's (1968) third category. Model studies
linking stochastic rainfall-runoff relations with deterministic sediment
yield relations have been constructed by Auernhamer et al. (1977),
Renard and Lane (1975), and Fogel, Duckstein and Musey (1976). A methodology for determining reservoir sediment yield based on limited rainfall
data and a derivative of William's (1975) sediment yield model was
elaborated by Smith, Davis, and Fogel (1977). Effective rainfall, event
duration, and number of events per season were viewed as random variables,
thus dictating the random nature of the computed sediment yield.
Mathematical derivation of stochastic process models has appeared in the
work of Woolhiser and Todovoric (1971), Woolhiser and Blinco (1975), and
Woolhiser and Renard (1978). Mathematical representations were advanced
by Woolhiser and Blinco (1975) for the stochastic processes of precipitation influx, evapotranspiration, porous media flow, and surface
streamflow. A distribution function for sediment yield resultant from
the modeling of watershed stochastic processes was also presented.
Applicable Regulatory Statutes
Since the purpose of this analysis is the assessment of sedimentation ponds designed in accordance with federal statues for surface
17
mining and reclamation operations, a brief overview of the applicable
design, performance, and effluent standards set forth in those statues
is offered. All referenced quotations have been excerpted from the
Federal Register (1979). Although more recent editions may have appeared
during the interim period, it is assumed that no major alterations in
the text have ensued.
Perhaps the most straightforward of all the design criteria is
that pertaining to required sediment storage volume for the pond (Federal
Register, p. 15400):
Sedimentation ponds shall provide a minimum sediment storage
volume equal to
(1) The accumulated sediment volume from the drainage area to
the pond for a minimum of 3 years. Sediment storage volume
shall be determined using the Universal Soil Loss Equation,
gully erosion rates, and the sediment delivery ratio converted to sediment volume, using either the sediment
density or other empirical methods derived from regional
sediment pond studies if approved by the regulatory
authority, or
(2)
0.1 acre-foot for each acre of disturbed area within the
the upstream drainage area or a greater amount if required
by the regulatory authority based upon sediment yield to
the pond. The regulatory authority may approve a sediment
storage volume of not less than 0.035 acre-foot for each
acre of disturbed area within the upstream drainage area,
if the person who conducts the surface mining activities
demonstrates that sediment removed by other sediment control measures is equal to the reduction in sediment
storage volume.
More controversial is the detention time provision (Federal Register,
p. 15400):
Sedimentation ponds shall provide the required theoretical
detention time for the water inflow or runoff entering the
18
pond from a 10-year, 24-hour precipitation event (design event).
Theoretical detention time is defined as the average time that
the design flow is detained in the pond and is further defined
as the time difference between the centroid of the inflow hydrograph and the centroid of the outflow hydrograph for the design
event. Runoff diverted under Sections 816.43 and 816.44, away
from the disturbed drainage areas and not passed through the
sedimentation pond need not be considered in sedimentation pond
design. In determining the runoff volume, the characteristics of
the mine site, reclamation procedures, and on site sediment
control practices shall be considered. Sedimentation ponds shall
provide a theoretical detention time of not less than twenty-four
hours, or any higher amount required by the regulatory authority,
except as provided under sub-paragraphs (1), (2), or (3) of
this paragraph.
(3) The regulatory authority may approve a theoretical
detention time of less than 24 hours to any level of
detention time, when the person who conducts the surface
mining activities demonstrates to the regulatory authority
that the chemical treatment process to be used - (i) Will
achieve and maintain the effluent limitations; and (ii)
Is harmless to fish, wildlife, and related environmental
values.
Dewatering requirements governing the design and performance of
the pond spillway systems or other modes of discharging stored storm
runoff are outlined as follows (Federal Register, p. 15400):
The water storage resulting from inflow shall be removed by a
nonclogging dewatering device or a conduit spillway approved
by the regulatory authority, and shall have a discharge rate
to achieve and maintain the required theoretical detention
time. The dewatering device shall not be located at a lower
elevation than the maximum elevation of the sedimentation
storage volume. (e) Each person who conducts surface mining
activities shall design, construct, and maintain sedimentation
ponds to prevent short-circuiting to the extent possible.
(g) There shall be no outflow through the emergency spillway
during the passage of the runoff resulting from the 10-year,
24-hour precipitation event or lesser events through the
sedimentation pond. (h) Sediment shall be removed from
sedimentation ponds when the volume of sediment accumulates
to 60 percent of the design sediment storage volume.
19
(i) An appropriate combination of principal and emergency
spillways shall be provided to safely discharge the runoff
from a 25-year, 24-hour precipitation event, or larger event
specified by the regulatory authority. The elevation of the
crest of the emergency spillway shall be a minimum of 1.0 foot
above the crest of the principal spillway.
Finally, the requirement which ultimately assures compliance with water
quality guidelines (Federal Register, p. 15400):
(0
The design, construction, and maintenance of a sedimentation pond or other sediment control measures in accordance with
this Section shall not relieve the person from compliance with
applicable effluent limitations as contained in 30 CFR 816.42.
The purpose of dictating the use of sedimentation ponds is,
of course, to clarify polluted water delivered from those areas disturbed
by mining. Following are passages associated with water quality standards
and effluent limitations (Federal Register, p. 15398):
(a) (1) All surface drainage from the disturbed area, including
disturbed areas that have been graded, seeded, or planted, shall
be passed through a sedimentation pond or a series of sedimentation ponds before leaving the permit area.
-
(2) Sedimentation ponds and other treatment facilities shall
be maintained until the disturbed area has been restored
and the vegetation requirements of Sections 8.6.111816.117 are met and the quality of the untreated drainage from the disturbed area meets the applicable State
and Federal water quality standards requirements for the
receiving stream.
(7) Discharges of water from areas disturbed by surface mining
activities shall be made in compliance with all Federal
and State laws and regulations and, at a minimum, the
following numerical effluent limitations:
20
Effluent limitations, in milligrams per liter (mg/1) except
for pH
Effluent
characteristics
Iron total
Maximum
allowable
Manganese total
7.0
Average of
daily values
for 30
consecutive
discharge
days
3.5
4.0
Total suspended solids. 7
0.0
pH Within range of 6.0 to 9.0
2.0
35.0
To be determined according to collection and analytical procedures
adopted by the Environmental Protection Agency's regulations for
wastewater analysis (40 CFR 136).
Based on representative sampling, The manganese limitations
shall not apply to untreated discharges which are alkaline as
defined by the Environmental Protection Agency (40 CFR 434).
In Colorado, Montana, North Dakota, South Dakota, Utah and
Wyoming, total suspended solids limitations will be determined
on a case-by-case basis, but they must not be greater than 45 mg/1
(maximum allowable) and 30 mg/1 (average of daily value for 30
consecutive discharge days) based on representative sampling.
(b) A discharge from the disturbed areas is not subject to the
effluent limitations of this Section, if (1) The discharge is demonstrated by the discharger to have
resulted from a precipitation event equal to or larger
than a 10-year, 24-hour precipitation event; and
(2) The discharge is from facilities designed, constructed, and
maintained in accordance with the requirements of this Part.
(c) Adequate facilities shall be installed, operated, and
maintained to treat any water discharged from the disturbed area
so that it complies with all Federal and State laws and regulations and the limitations of this Section.
CHAPTER 3
SITE CHARACTERISTICS AND
FORMULATION OF STUDY
This chapter begins with a description of the hypothetical
watershed which functions as the medium for this study. Regional and
site-specific characteristics which aid in defining the resultant
hydrologic regime are detailed. Next, the procedure followed in
evaluating the magnitude of precipitation associated with particular
frequency-duration storms is outlined. The construction and methodology
of the INFLUX program which generates the required inputs for utilization by the DEPOSITS sedimentation routine is then examined. Procedural
aspects of sedimentation pond design, including composition of rating
curves for the reservoir, are described. A somewhat abbreviated analysis
of the DEPOSITS routine concludes the chapter. The reader is advised
to refer to the appendices for clarification of the computational logic
of the aforementioned routines.
Hypothetical Watershed
The characteristics of the hypothetical watershed developed
herein for hydrologic analysis are indicative of reclaimed surfacemined watersheds on the Black Mesa in northeastern Arizona. Black Mesa
coal seams, being mined presently by Peabody Coal Co., range from 5 to
28 feet in thickness (Fogel, Heckman, and Vandivere, 1979). Following
21
22
the extraction of the mineral, the spoil material is recontoured so as
to approximate, as closely as possible, the original topography.
The study drainage area was assumed to encompass 50 acres of
graded spoil material. Average watershed slopes of 6.7 percent and a
slope length of 250 feet have been chosen. Contour-grid determination
(Williams and Brendt, 1977) of existing basin slopes on experimental
watersheds at Black Mesa was used to calculate the former value while
the latter fell within the range suggested to the author by Hamon (1979).
Spoil material was assumed similar to that found on the J-3 spoils
experimental watershed located on the mesa. Lack of structure,
relatively high clay and low organic content, and low infiltration
capacity distinguish this material from surrounding natural soils.
Natural precipitation which varies from 9 to 13 inches in the Black
Mesa region has been assumed to be the only available source of moisture
for production of water and sediment discharge from the watershed.
Approximately half of the annual moisture influx is derived from summer
convective storm activity. The remaining portion is delivered by frontal
storm systems in the form of rain or snow. Runoff-generating events
are few and often far between, thus delineating the largely ephemeral
nature of streamflow in the area.
Development of Hydrologic Inputs
In order to adequately assess the overall performance of the
sedimentation pond, it was felt that a wide spectrum of hydrologic
events should be incorporated into the investigation. It was deemed
23
appropriate that the precipitation-frequency maps published by NOAA
(1973) be used for determination of point rainfall volumes at the study
site, since it is common practice among designers possessing limited
data to utilize thie material.
An extensive network of both recording and non-recording raingages provided the Weather Bureau (NOAA) researchers who compiled the
maps with point rainfall volumes for specific sites in the western U.S.
Isopluvials were then constructed on the basis of extrapolated data
drawn from multiple linear regression equations relating topographic
and climatologic factors to variations in precipitation frequency values.
Frequency analysis was carried out using the annual series method and
empirically derived factors for conversion to partial duration series.
A total of 38 precipitation events were defined through use of
the maps and accompanying equations and diagrams. Precipitation in
the form of snowfall was neglected under the assumption that runoff and
sediment production resulting from snowmelt at the site is minimal.
Point precipitation values were left unaltered by depth-area analysis
due to the small area of the watershed. The suggested one or two
percent reduction due to areal distribution of rainfall seemed questionable in light of the uncertainties involved in the Weather Bureau
procedure. A summary of these estimated precipitation volumes for the
chosen durations and return periods appears in Table 1.
24
Table 1.
Point precipitation-frequency values for Black Mesa Mine,
Arizona, in inches*.
Duration
hr.
5
8
0.17
0.46
0.52
0.55
0.56
0.59
0.25
0.59
0.66
0.70
0.71
0.75
0.50
0.81
0.92
0.97
0.99
1.04
1.13
1.0
1.03
1.16
1.23
1.25
1.32
1.43
2.0
1.15
-
1.37
-
1.48
1.60
6.0
1.39
-
1.65
-
1.80
1.93
12.0
1.63
-
1.88
-
2.00
2.19
24.0
1.85
-
2.10
-
2.24
2.45
Return period (T), yr.**
10
12
15
*All values were obtained through subjective interpolation of
isopluvial contours.
**T = 1 P E , where P E is the exceedence probability.
1
25
25
Model Components and Operation:
Program INFLUX
The INFLUX program has been composed for this thesis with the
expressed purpose of integrating the limited data base available for
the mine site into the evaluationof storm-watershed response. It was
the intention of the author that the physical characteristics of storm
events be given fuller consideration, at least where the mathematical
modeling was concerned.
Precipitation
As in the case of the methodology picked for determination of
precipitation frequency values, an attempt was made to enlist a scheme
for temporal distribution of rainfall which was founded on essentially
valid statistical analysis. The Type II rainfall distribution developed
by the SCS (Kent, 1973) was chosen due to its large data base and
qualified recognition by the hydrologic community.
Rainfall depth-duration relationships outlined in Weather Bureau
technical papers (1953, 1954, 1956) were applied by the SCS to the
analysis of cumulative rainfall and duration for recorded storms throughout the U.S. The resultant Type II curve represented the curve of best
fit for the bulk of the continental United States, including all of
Arizona. As can be discerned from Figure 1, the greatest 30-minute depth
occurs near the middle of the 24-hour period. Because the selection of
the period of maximum intensity was intentionally related to hydrologic
design considerations, meterological relevance may not always be
retained (Kent, 1973).
26
t7Z
d / xd 1 1V.101. 01. Tit/AN IV
a3ivintAmov ou_va
27
For purposes of modeling, the distribution has been broken down
into 22 intervals of varying lengths. Any storm regardless of duration
can be apportioned through time with the aid of this discretized Type II
distribution. A sample distribution for a storm of 24-hour duration
has been entered in Table. 2. Use of this distribution, in conjunction
with the infiltration component which is discussed in the next section
enables the investigator to determine both the rainfall excess and the
duration of that effective rainfall. This is necessary if the effect
of individualized storm rainfall intensity on sediment yield and subsequent pond performance is to be realized.
An index of maximum storm rainfall intensity has been calculated
as the ratio of the rainfall volume for the fifteenth increment to its
corresponding duration. Its description as an index derives from the
lack of actual influence it exercises over runoff and sediment production
as will become evident later in this chapter.
Infiltration
A component infiltration model which relates infiltration rate
to the availability of soil moisture storage has been applied to the
INFLUX routine. Drawing on the prior work of Blumer (in prep.), an
infiltration curve for the J-3 experimental watershed (see Figure 2)was utilized for determining that portion of storm precipitation which
translated into runoff. The J-3 watershed is monitored for precipitation
runoff, infiltration and sediment yield by the School of Renewable
Resources, University of Arizona. The Blumer data, in lieu of sufficient
28
Table 2. Discretization of Type II rainfall distribution (1) for 24 hr.
duration.
Time
(hrs)
Time
(pdf) (2)
Precip.
(pdf) (2)
Time
(cdf) (3)
0
2.0
4.0
6.0
7.0
8.0
8.5
9.0
9.5
9.75
10.0
10.5
11.0
11.5
11.75
12.0
12.5
13.0
13.5
14.0
16.0
20.0
24.0
0.000
.083
.084
.083
.042
.041
.021
.021
.021
.010
.011
.020
.021
.021
.010
.011
.021
.021
.020
.020
.084
.166
.167
0.000
.022
.026
.032
.020
.020
.013
.014
.016
.009
.009
.023
.031
.048
.104
.276
.072
.037
.027
.027
.060
.072
.048
0.000
.083
.167
.250
.292
.333
.354
.375
.396
.406
.417
.437
.458
.479
.489
.500
.521
.542
.562
.583
.667
.833
1.000
(1) from Kent (1973)
(2) probability density function
(3) cumulative distribution function
Px/P24
(Ratio of accumulated
rainfall to total)
0.000
.022
.048
.080
.100
.120
.133
.147
.163
.172
.181
.204
.235
.283
.387
.663
.735
.772
.799
.820
.880
.952
1.000
29
0
0
0.2
0.4
0.6
0.8
1.0
TIME, hours
Fig. 2. Data points and infiltration curve for 0.5 year old
spoil material, J-3 experimental area.
(Blumer, in prep.)
30
documentation, was assumed to represent an average antecedent soil moisture condition for the watershed. Repeated attempts of fitting this
data to established infiltration models (Huggins and Monke, 1966; Holtan
1961) proved futile owing to the uncharacteristically rapid decay displayed by the J-3 infiltration curve. Consequently, a tabular
representation of infiltration rate vs. available soil moisture storage
was opted for use in the computer routine. A listing of the discretized
time-storage relations for infiltration can be found in Table 3. The
interactive procedure involving the rainfall and infiltration components
is now described. The reader is referred to the flowchart of Figure 3
for clarification during the ensuing discussion.
At the outset of a storm run, an estimate of the initial available moisture volume for the topsoil unit is made. This unit is assumed
to be underlain by a geologic stratum of greatly reduced permeability
which effectively impedes the downward progress of infiltrated water.
Upon saturation of the topsoil unit, additional precipitation influx
is converted entirely to runoff. Available soil moisture was computed
as the difference in stored water between saturation and the wilting
point for plant life. Pressure potentials for these levels were assumed
to be zero and -12 bars, respectively. Since the interarrival time for
convective rainfall activity is generally short, it was felt that this
lower bound for available soil moisture better reflected probable site
conditions. incorporating volumetric water content values for Black Mesa
spoil material developed by Fischer (1976), an available soil moisture
storage volume of 1.8 inches of water was computed for an accompanying
topsoil layer thickness of 6 inches.
31
(
START
Read in parameters
and initialize
/
Increment discretized
rainfall
Compute incremental
rainfall volume and duration
No
Compute
max. storm
intensity
No
Set infiltration rate
steady-state
Yes
•
Determine infil.
rate for computed
deficit
Calculate infiltrated volume
Calculate infiltrated
volume
Updated moisture deficit
Yes
=
Set infiltrated volume
remaining storage
Accumulated stored volume
infil. rate
infil. vol.
Write
Accumulate stored volume
Set moisture deficit
Accumulate
rainfall excess
and duration
=
Yes
Write total rainfall
excess and duration
Construct triangular
hydrograph
Fig. 3. Generalized flowchart for hydrologic linkages.
32
Table 3.
Time
(hr.)
0-.10
.11-.20
.21-.30
.31-.40
.41-.50
.51-.60
.61-.70 **
.71-.80
.81-.90
.91-1.00
1.00
Discretization of J-3 infiltration capacity curve.
Ave. Infiltration Rate
for Interval (in/hr)*
Infiltrated Volume
(in.)
1.93
1.21
.76
.50
.36
.29
.25
.22
.22
.22
.22
* Using trapezoidal approximation for area determination
** Threshold for steady-state infiltration rate
.21
.12
.08
.05
.04
.03
.02
.02**
.02
.02
.02
33
Following initialization of the stored soil moisture variable,
TFILL, the routine enters into a loop which calculates successive incremental values of rainfall volume, RAINV. After each iteration of RAINV,
the infiltration rate corresponding to the present value of the soil
moisture deficit (AVAIL-TFILL), is applied over the proper time increment, RAINPD. An interpolation factor, TERP, has also been included to
better approximate the continuous decay process of infiltration.
A check has been introduced at this juncture to determine whether
or not sufficient storage has accumulated for the steady state infiltration value, SSINF, to be activated. As can be observed in Table 3, the
steady-state infiltration rate corresponds to a cumulative infiltrated
volume of approximately .55 inches of water. The entered value for
SSINF is thus referred to if the computed soil moisture deficit falls
below (1.8 - .55), or 1.25 inches.
Next, the volume of infiltrated water for the interval, FILL, is
added to the preceeding value of TFILL. This volume is equal to the
product of RAINPD and either ACTFIL or SSINF, both of which represent
infiltration rates for non-steady and steady state behavior, respectively.
The updated value of TFILL is then used in evaluating the following
iteration of rainfall. This procedure is repeated until the SSINF is
attained, from whenceforth the infiltrated water is introduced at that
rate and TFILL is set equal to AVAIL, thereby assuring maintenance of
the steady-state condition.
34
Runoff
Once the abstraction is satisfied, if there remains any effective rainfall for the increment, it accumulates as rainfall excess,
TRAINX. In addition, the duration for any increment over which excess
rainfall is generated is added to the value representing the duration
of storm rainfall excess, expressed by the variable, DUREX. As TRAINX
is actually the depth of water per unit area of the watershed which is
available for transport overland, its extrapolation over the entire
basin establishes the volume of total runoff delivered to the detention
facility.
Use of the DEPOSITS sedimentation routine, described at the end
of this chapter, requires as an input the distribution of incoming flows
to the pond. The triangular hydrograph method (Kent, 1973) used by the
SCS for hydrologic design of conservation and drainage structures was
chosen for this purpose because of its simplicity and applicability to
ungaged watersheds. Limitations on its general use include a maximum
drainage area of 2000 acres and average slopes of less than 30 percent.
Calculation of the peak discharge from which constrUction of the inflow
hydrograph.can•be accomplished is expressed by
the
equation:
KAQ
q= t
where
q = peak flow rate in cubic feet per second.
K = watershed parameter, a function of hydrograph geometry
A = watershed area in square miles
Q = volume of rainfall excess in inches over duration D
t = time from initiation of runoff to attainment of peak
flow
35
The time to peak is closely related to the time of concentration
for a watershed and is calculated by the following expression:
D
t = 2
where
+L
D = duration of rainfall excess in hours, and
L = basin lag time in hours.
The drainage basin lag time, L, is computed by the equation:
.8
0.7
(S + 1)
L=
where
1900 Y 0 • 5
L = basin lag time in hours
1 = length of mainstream to farthest divide in feet,
_ 1000
10 ,
CN
CN = A retardance factor approximated by the curve number
representing the watershed hydrologic soil cover complex, and
Y = average slope of watershed in percent
An empirical relationship derived from small watershed data
describes the hydraulic length:
1 = 209a
where
0.6
1 = hydraulic length in feet, and
a = drainage area in acres
When peak flow has been computed for an event, the program simu-
lates construction of the triangular inflow hydrograph at a chosen time
interval of .05 hours. The choice of this particular interval satisfied
the minimum routing requirement of 5-10 time steps for the rising limb
of the hydrograph for all of the storms examined. Two simple linear
36
expressions are necessary for hydrograph constructions:
ORD(J) = PEAK/TPEAK x CUMIN(J), for the rising limb
and
ORD(J) = PEAK - (PEAK/1.67 x TPEAK) x (CUMIN(J) - TPEAK) ),
for the receding limb
where
ORD(J) = the inflow hydrograph ordinate for the jth step
in cfs,
PEAK
= peak flow rate in cubic feet per second,
TPEAK
= time to peak in hours, and
CUMIN(J) = cumulative time at the jth step in hours.
A graphical representation of the triangular hydrograph is presented in Figure 4.
Sediment
Since the primary objective of the study was to assess the
effect of uncertainties in the physical characteristics of precipitation
on sediment yield and pond performance, a desirable sediment yield model
had to incorporate a certain degree of specificty with regard to these
factors. To this end, the modified Universal Soil Loss Equation (USLE)
assembled by Williams (1975) for determination of event based sediment
yield was chosen. A hydrologically more specific formulation of the
USLE, the modified equation is given as:
. 56
xKxLSxCxP
Y = 95x(Qxq)
where
Y = the event sediment yield in tons,
Q = runoff volume in acre-feet
q = peak flow rate in cfs
K = soil erodibility factor,
37
_ 484 A(Q)
A g ap
L
INCREMENT OF EXCESS
RAINFLOW OR INFLOW
D
OUTFLOW HYDROGRAPH
I-
<
TIME
/ID
Tp
tbi
Fig. 4. SOS triangular hydrograph.
38
LS = length-slope factor
C = crop management factor, and
P = erosion control practice factor
The last four variables are equivalent to those utilized in the USLE and
their values must be estimated according to the methods outlined by the
SCS. Peak flow rate and runoff volume are obtained from earlier program components.
The modified USLE resulted from experiments conducted on small
watersheds in the Texas Blacklands which are also part of the semi-arid
zone of the Western U.S. Uniform prediction accuracy was maximized in
development of the equation. Predictive ability was found to be greater
for larger storms than for smaller ones. This, however, coincides with
the importance ascribed to larger storms in the production of sediment.
Because the formulation was based on sediment yields and not gross
erosion, use of the modified equation negates the requirement for application of a delivery ratio for the purpose of determining the transport
efficiency of overland flow.
Sedimentation Pond Design
Upon completion of computer evaluation of the 10-yr., 24-hr.
design storm event, sufficient information exists to enter the pond design process. A trapezoidal basin configuration has been chosen which,
within the restrictions of the study, offered a simplified, yet not
overly inaccurate, representation of actual pond geometries.
39
A detailed description of the design procedure is presented in
the DEPOSITS design manual (Ward, Haan, and Tapp 1979), therefore, only
highlights of the procedure are addressed here. The reader is referred
to Appendix A which contains the final design aspects for the pond used
in subsequent analysis.
There are six basic steps involved in the design procedure used
herein:
(1) Determination of design storm characteristics including water and
sediment volume and the accompanying inflow hydrograph. In addition, accumulated 3-yr. sediment storage volume must be computed
using the USLE and a sediment delivery ratio. Due to difficulties
in determining the sediment volume derived from gully erosion,
that factor has been neglected.
(2) Site selection based on surrounding topography, location with
respect to disturbed area and active alluvial systems, and hydraulic design considerations. (Basin length, as measured from inlet
to outlet, should equal or exceed twice the average basin width).
(3) Preliminary design of dam embankment with provision for an emergency spillway and freeboard, and delineation of
the
prinipal
spillway configuration.
(4) Compilation of operating curves for the reservoir, specifically
those relating reservoir stage to surface area and spillway
discharge.
40
(5) Routing of the design storm through the reservoir using any established procedure- The DEPOSITS sedimentation routine was applied
in this case.
(6) Repetition of steps 2-5 until sufficient detention time has been
achieved.
Keeping with the practice of using established methods for actual pond
design, inflow volume was computed with the aid of the SCS rainfallrunoff equation described by Kent (1973). The SCS equation is given as:
where
Q = accumulated direct runoff in inches
P. = accumulated rainfall in inches
I
a
= initial abstraction including surface storage,
interception, and infiltration.
S = potential maximum retention
The initial abstraction has been empirically approximated as a fraction
of the potential maximum retention by the relation:
I
a
= .2S
Therefore, the resultant expression for determination of runoff volume
is:
Q =
(P - .2S)
(P + .8S)
2
A great deal of freedom has been allowed by the regulatory
agency in working out the particulars of pond design. Prudent
41
engineering practice is relied upon to minimize inefficiencies in
hydraulic behavior, consequently providing a maximum of design flexibility.
Some assumptions adopted in the process of modeling the hydraulic
behavior of the dewatering system used for pond simulation should be
stated. A perforated pipe spillway was employed because of the ease it
exhibited in achieving adequate detention times for routed basin inflows.
Characteristics of the structure include a corrugated metal riser and
two sets of circular perforations comprised of three perforations per
set, each perforation measuring two inches in diameter.
Three hydrau-
lic conditions are assumed to adequately describe flow through the
principle spillway.
Initially, as the reservoir stage exceeds that corresponding to
the successive dewatering sets, the discharge can be described by the
orifice flow equation:
= Ca (2gH)
where
05
Q = discharge in cubic feet per second,
C = orifice discharge coefficient, assumed = .60,
a = cross-sectional area of orifice in square feet,
g = acceleration due to gravity in feet per second
squared, and
H = head on the orifice, measured from the orifice center
to reservoir water level, in feet.
When water level adjacent to the riser transcends the spillway
crest elevation, weir flow ensues. Morris and Wiggert (1972) suggest
use of the following equation for description of this condition:
42
1/2
Q=
where
a(2gH)
(1 +K+K+ K L ) 1/2
e
b
c
H = head on conduit outlet measured from the reservoir
level to six-tenths the conduit diameter above the
invert.
K
e
= entrance loss coefficient,
Kb = correction factor for energy losses in bends, and
K
c
= friction factor
The pipe flow values were extraced from Table 5.3 of the DEPOSITS user's
manual (Ward et al.,1979) which presents discharge values as a function
of conduit diameter, head, and conduit length for (K e + K b ) = 1.0.
As is true of larger impoundment structures, the hydraulically
active portion of the pond excludes that volume which must be allocated
for deposited sediment, referred to as "dead storage." Some of the design details affecting hydraulic performance have been set out in the
regulatory statutes, highlighted in Chapter 2, however, others such as
positioning of the spillway and maintainance of minimum depths or
permanent pool volumes have been neglected. The accumulations of
further data on actual and simulated pond performance may expectedly
lead to amendments to the current criteria covering pond design.
To enable relative differentiation between storm characteristics,
and their effect on pond performance, maintainance of a baseline condition for the pond was essential. Established federal statutes relating
to pond design and effluent limitations convinced the author that a
"critical" condition is defined by the following elements: (1) a dead
storage equal to 60 percent of the calculated 3-year sediment
43
accumulation corresponding to the specified cleanout level
for the pond;
and (2) a permanent pool consisting of the volumetric difference between
the cleanout level and that of the first orifice set. A
graphic representation of general pond features is presented in Figure 5.
DEPOSITS Sedimentation Model
The DEPOSITS sedimentation routine (Ward et al.,1977b) is a
mathematical model used to describe the transport and deposition of sediment delivered to and routed through a sedimentation pond. Impetus
for model development came mainly from the desire to provide a means
with which the user could more adequately assess the prospective performance of sedimentation ponds, and as a gage to weigh the necessity of
additional or alternative methods of sediment control. The model has
been verified using data from 11 functioning ponds and was found to explain greater than 90 percent of the variation in basin trap efficiency.
Flow within the pond is described in terms of the idealized plug
flow concept. This assumes that no mixing takes place between plugs and
that each successive plug entering the pond assumes the position maintained by its immediate predecessor. Although it simulates basin
performance, the model does not pretend to describe the complexities of
actual hydraulic behavior in the basin.
The sedimentation process defined in the model can be elucidated
by tracing the movement of a sediment-laden plug of inflow through the
basin. Upon entering the pond, the plug is assumed to possess a specified sediment distribution with depth. Furthermore, each plug is
subdivided into four layers at 0.125, 0.375, 0.625, and 0.875 of the
44
La
Lu
o
>0
Lu
<
tx
o
co
0
I—
E
ww
0 (r)
I.
O
I.
(,)
>>
45
average flow depth. As the plug progresses, fall velocities required
for particles to reach these distances are computed as the depth traversed divided by the detention time for the plug. Particle diameters
corresponding to the computed fall velocities are then determined by
applying Stokes Law of Ideal Settling:
D where
.5
V x
51.5 x (SG -1)
D = particle diameter in millimeters,
V = corrected fall velocity in feet per hour,
= water viscosity in centimeters squared per second
SG = particle specific gravity, and
51.5 is equal to 0.8 times the gravitational acceleration (32.3 ft/sec)
times a conversion factor to achieve equation dimensionality. The
correction factor of 0.8 compensates for the effect of non-spherical
particles on settling theory.
The proportion of sediment remaining in any layer of the plug is
subject to the law of continuity:
I - 0 = ds
—
dt
where
I = mass of incoming sediment
0 = mass of outgoing sediment
dl= differential of mass of
stored sediment with respect
dt
to time
Deposition occurs and is assumed irreversible as soon as a particle
reaches the reservoir bed.
46
When the plug is discharged, its sediment concentration is thus
dependent not only on the withdrawal characteristics employed, but also
on the detention time and the redistributed sediment profile within the
plug. A graphic conceptualization of the plug flow routing process is
presented in Figure 6.
Required inputs to the DEPOSITS model are readily available and
are minimally dependent on in-field evaluation:
1.
Inflow hydrograph.
2. Viscosity of the flow.
3.
Stage-area curve for the basin.
4.
Stage-discharge curve for the basin.
5.
Stage-discharge distribution curve.
6. Degree of dead storage or short circuiting.
7.
Sediment inflow graph or load.
8. Particle size distribution and specific gravity of the suspened sediment.
Stage, as referred to in the model, is the depth of water above
the lowest level on the basin bed. A uniform outflow rate with depth
is assumed by the model if a stage-discharge distribution curve for the
basin is not specified.
If sediment distribution data is lacking, sediment concentration
is made proportional to the water inflow rate. For effluent concentrations to be determined, the total incoming sediment load must be inputed.
In addition, the model has the capability to simulate changes
in basin geometry resulting from deposition during the event. This makes
47
o
SAO 31V2:1 MO 1 A
48
it especially desirable from the standpoint of prospective time series
analysis of hydrologic events and corresponding pond performance.
A caveat should be inserted here concerning the computation
of detention time in the DEPOSITS routine. As is required by the regulatory statutes, detention time is calculated as the time between the
centers of mass of the inflow and outflow hydrographs and is represented
by the program variable, CENTME. In situations where a permanent pool
exists, which remains as storage after dewatering, the computed centroidal detention time will only approximate the average theoretical
detention time for the storm event. This is due to the fact that the
detention time for the volume of stored flow discharged during the
routing process has been maintained for an extended period of time. The
DEPOSITS routine has included another measure of detention time which
gives special consideration to the permanent pool volume, identified in
the program as the variable STRMTM. Because of the complexity and sheer
bulk of the DEPOSITS sedimentation model responsibility for a more detailed explanation of program operation has been delegated to the
DEPOSITS Design Manual (Ward et al., 1979).
CHAPTER 4
RESULTS AND DISCUSSION
The following pages document the results of model runs for the
Black Mesa hypothetical watershed and companion sedimentation pond. A
discussion addressing the implications of hydrologic uncertainties on
pond performance is then offered. The chapter ends with some thoughts
on model adaptability and regional bias.
Pond Sensitivity Analysis
Prior to initiation of the present study, the author, along with
his colleagues, expected that only one watershed condition would need
be examined in order to assess the effect of hydrologic variability on
pond performance. This, as the study unfolded, turned out not to be
the case. To, in effect, unmask the hydrologic uncertainties as they
affected the efficacy of basin performance, two additional sets of runs
had to be made. Thus, the following modeling schemes were investigated:
(1) minespoil material with untreated pond inflow,
(2) natural soil material with untreated pond inflow, and
(3) minespoil material with chemically treated pond inflow.
The reader is directed to Appendix B for a sample listing of required
DEPOSITS input parameters and their associated values.
49
50
Minespoil Material with Untreated Pond Inflow
A total of 38 precipitation events encompassing varying
frequency-duration relationships were evaluated for this condition
using the INFLUX and DEPOSITS models. Peak effluent
sediment concentra-
tions resulting from routing the specified event flows through
the pond
are listed along with precipitation characteristics
in Tables 4 and 5,
while sediment yields for all conditions simulated are compiled in
Tables 9 and 10, pages 64 and 65.
Since the Williams equation (1975) for event-based sediment
yield was used in generating incoming sediment loads, estimates had to
be made for the equation's variables corresponding to the proper siteinflow conditions. These values were based on projected 3-yr. averages
as follows: K = 0.35, LS = 1.26, C = 0.63, P = 0.35. The estimated
crop management factor (C) value of 0.63 represents an assumption that
during the first year no vegetative growth occurred, while in the second
and third years, a meager 10 percent cover was established. Justification for the remaining variable values listed can be found in Appendix
A covering pond design. On first inspection, these values may appear
low, however, it must be remembered that irrigation has been neglected
and natural rainfall is limiting. The distribution used in apportioning incoming sediment is equivalent to that utilized in the pond design
process and appears in Appendix A.
Data presented in Tables 4 and 5 suggest that pond performance
is linked less to rainfall volume than to its intensity, represented by
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the aforementioned intensity index. This index, as previously defined,
represents the ratio of the rainfall depth to duration for the critical
intensity index. This index, as previously defined, represents the
ratio of the rainfall depth to duration for the critical fifteenth
time increment of the discretized SCS Type II rainfall distribution.
The standard rainfall intensity expressed as the rainfall rate
in inches/hr. over the corresponding time period was felt to be too cumbersome for comparative purposes. Consequently, the cited intensity
index was chosen in its stead. Readers are cautioned not to confuse the
two concepts, lest unwarranted protests ensue.
Tracing causal connections, it becomes evident that the link
between intensity and pond performance is due to the ability of short
duration-high intensity storms to generate relatively large amounts of
sediment accompanied by high peak discharge rates and short inflow hy-
drograph base times. Examination of successively routed plugs through
the reservoir indicates an accelerated introduction of the plug corresponding to the observed peak inflow rate and peak influent sediment
concentration. Because the shortened time base of the inflow hydrograph, this rapidly introduced plug affects a greatly reduced detention
time which is responsible for the higher peak effluent sediment concentrations simulated by the model. Low intensity-longer duration storms,
on the other hand, display the attenuated inflow hydrograph characteristics which contribute to the attainment of increased plug detention
periods, especially for the plug associated with peak inflow rate and
sediment concentration.
55
In both cases, the clay fraction was responsible for the bulk of
that sediment extant in the pond effluent. There was, however, a
greater percentage of silt-sized particles in the effluent of simulated
low intensity-longer duration events. Although an apparent inconsistency,
this appears to accrue from the difference in discharge characteristics
associated with the two storm types. The greater volume of stormflow
produced by the low intensity-extended duration events results in an
increased time period over which higher stage levels and subsequent
discharge rates are registered. Since the increased range of depths
associated with these events now encompasses both dewatering orifice
sets, relatively greater plug detention times are offset by the increased
settling depths which must be traversed by entrained particles to avoid
incorporation into the pond effluent.
Another aspect of data listed in Tables 4 and 5 which merits
attention is the gulf which separates the peak effluent concentrations
computed for all the events modeled and the current OSM-EPA effluent
water quality standard of 70 mg/l. This is attributable to two interrelated factors. Coincidental with the required 24-hr. theoretical
detention time is the notion that sedimentation ponds can only be
depended upon to remove sediment corresponding to minimum particle size
of 20 g (0.02 mm). Corresponding to the middle of the silt sized
particle range, this lower limit precludes the maintainance of high
trap efficiencies for watershed soils with a high proportion of particles residing in the clay and lower silt fractions. Thus, ponds
56
designed according to the federal guidelines cannot be expected to
even remotely approach Federal effluent limitations where these conditions are present.
In an effort to clarify the projected effect storm characteristics have on the actual attainment of pond effluent standards, it was
necessary to negate the overriding influence of the soil particle size
distribution on simulated pond performance. A sensitivity analysis was
conducted on pond peak effluent concentrations to determine the size
fraction distribution and crop management factor value which when
inputed would enable differentiation between storms that successfully
achieved water quality standards and those which failed. The results of
this analysis are shown in Figure 7. A clear distinction can now be
made between the two storm regimes studied.
Inspection of Tables 4 and 5, listing storm characteristics and
peak effluent concentrations from which Figure 7 was derived, provides
further evidence of the critical nature of high intensity-short duration
storms with regard to pond performance. For the particle size distribution and "C" factor value noted in Figure 7, intensity index (PINTMX)
values in excess of 40 in/hr. resulted, for all but one case, in a
failure to meet the 70 mg/1 standard. Conversely, all modeled events
which were calculated to have intensity index values less than 40 in/hr.
satisfied the requirement. The crop management factor value used
represented cover conditions which in the opinion of the study
advisers could exist only under irrigated conditions. Even for these
conditions, the resulting particle size distribution would in reality be
unattainable.
57
The most obvious departure the data exhibit from the stated OSM
performance criteria relates to the water quality exemption for storms
possessing proven generated inflow volumes in excess of that produced
by the applicable 10 yr.-24 hr. event. The demarcation of event concentrations represented by the vertical line in Fig. 7 suggests a marked
preference for the exempted stormf lows in attaining effluent sediment
concentration standards. Moreover, a substantial number of storms which
exhibited high effluent concentrations spawned only nominal inflow
volumes.
National Soil Material with Untreated
Pond Inflow
Because of the overwhelming failure of all routed stormflows in
achieving federal water quality statutes, modeling of a control situation for comparative purposes was viewed appropriate. All factor values
included in the sediment yield prediction equation, with the exception
of the "C" factor, were left unchanged for condition 2 model runs. The
"C" value chosen, 0.09, correspond to a cover percentage of 40, describing
a vegetal mix of grassy surface and limited canopy. In addition, the
particle size distribution calculated for the incoming sediment was
derived from data for natural experimental watersheds located at Black
Mesa. A tabulation of this data appears in Table 6.
Generally, similar observations can be made in viewing natural
condition data as for those concerning untreated minespoil conditions.
Although peak effluent sediment concentrations are somewhat lower than
those resulting from minespoil simulation, they still exceed the
58
90.0
PARTICLE SIZE DISTRIBUTION:
80.0
<.002 mm = 0 %
.002 mm 5- X 5 .063 mm = 5 %
.063mm <X 5-.125 mm =87%
>.125 mm = 8 %
70.0
Crop management factor = .09
60.0
I,
111.3
102.2
100
50.0
• 94.4
0. q
90
>F—
ET) 40.0
80
70
LLI
1—
Z
30.0
ca.;
60
50
40
20.0
•
• 40.4
44: 1
10.0
0.0
0.0
3170 493
1.0
2.0
3.0
4.0
5.0
INFLOW VOLUME, AC.-FT.
Fig. 7. Predicted peak effluent concentrations and contours
in mg/2. for Black Mesa minespoil with altered inputs
and untreated pond inflow-
59
Table 6. Particle size distributions for undisturbed experimental
watersheds: Black Mesa, AZ.
Watershed
Event Date
*
*
%Clay%Silt
*
*
%V.f.Sand%Sand
7-11-77
14.6
62.0
12.1
11.3
8-12-77
22.7
32.0
32.6
12.7
8-15-77
40.6
36.4
18.5
4.5
8-15-77
16.7
49.7
27.5
6.1
8-15-77
36.9
29.0
28.4
5.7
8-12-77
37.6
30.8
22.2
9.4
8-7-77
32.4
39.1
19.1
9.4
J-3 Natural
J-7 Natural
8-12-77
13.4
6.7
33.1
46.8
8-15-77
16.2
33.9
29.8
20.1
8-15-77
27.7
43.0
14.2
15.1
8-17-77
42.2
38.0
9.4
10.4
8-17-77
37.3
20.8
23.4
18.5
7-22-77**
47.1
31.9
13.0
8.0
8-5-77**
51.6
17.3
7.6
23.5
8-16-77**
71.5
5.5
17.6
5.4
28.2
35.1
22.5
14.2
Average fraction %:
*clay: <.002 mm
.002 mm
x < .063 mm
silt:
v.f. sand: .063 mm < x < .125 mm
sand: >.125 mm
**assumed outliers
60
effluent standard by two orders of magnitude. The precipitation
characteristics were unaltered for those runs, therefore, it is not
surprising that the previously cited tendencies relating storm characteristics to pond performance are again evident. A listing of effluent
concentrations can be found in Table 7.
The question which begs attention here is: given the magnitude
of sediment concentrations in runoff generated under natural conditions,
why should sediment concentrations in runoff from disturbed areas be
required to register at levels corresponding to two orders of magnitude
less? Rationale for such a restriction seems to derive more from
difficulties inherent in determining ambient stream sediment concentrations than from any conceptual analysis of the hydraulic regime. Even
a cursory review of current sediment transport theory reveals the longaccepted principle that a stream-hillslope system will strive towards
maintenance of a dynamic equilibrium between the supply of sediment and
the stream's capacity to transport it. Thus, it appears conceivable
that the high quality water discharged from sedimentation ponds into
streams or appurtenant drainageways carrying natural runoff could
actually lead to downstream scouring which in turn could result in resuspension of previously deposited channel material. Acceptance of
Federal rationale aside, the inadvertant distortion of the existing
hydrologic regime in this manner seems a distinct possibility.
Minespoil Material with Chemically Treated Pond Inflow
A selected group of representative storms was simulated for
minespoil conditions and the introduction of a cationic polyelectrolyte
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62
into the pond influent. The addition of a flocculant of
this type
affects a change in the effective particle size distribution
which
defines the settling characteristics of incoming sediment.
Actual determination of the effects of a coagulant or flocculant
on particle size distributions should be based on
lab experimentation.
Explanation of this procedure is presented in Ward et al. (1979).
For
study purposes, and estimate of the flocculant effect was made as a
result of conversations the author had with Rick Ellwagner (1980), a
sales representative for the Tucson office of American Cyanamid. These
discussions produced the following estimates:
clay fraction -> reduced to 0.1%
silt fraction -> effective size increased to 0.1 mm.
The value listed for the unaffected clay fraction percentage is a conservative one, and should produce equally conservative peak effluent
concentrations. The amount of flocculant required to produce this
change was quoted to the author at 0.1 lb./ton of solids at a cost
of $.60/1b.
Results for scheme 3 runs appear in Table 8. Pond trap
efficiency for all routed events was extremely high, on the order of
99.9%. Only one of the events resulted in abrogation of the effluent
standard. For the above mentioned rate of application and per pound
cost of flocculant, the total cost for treatment of an event which
generates on incoming sediment load of 30 tons is approximately
63
Table 8. Predicted peak effluent sediment concentrations for routed,
selected Black Mesa storms l : minespoil with chemical
treatment of inflow. 2
Storm Event,
Peak Effluent Sediment
frequency-duration Concentration, mg/),
'
2
5 yr. - 1 hr.
53.5
8 yr. - .50 hr.
63.7
10 yr. - 2 hr.
44.3
10 yr. - 24 hr.
46.8
15 yr. - .17 hr.
112.2
25 yr. - .50 hr.
65.8
25 yr. - 24 hr.
40.1
Event sediment yields appear in Tables 9 and 10.
Estimated effective particle size distribution: < .002 mm =
.1%
>
.1
mm
=
99.9%
Crop management factor, C = .63
Precipitation characteristics for all storms
appear in Tables 4 and 5.
64
Table 9. Predicted event sediment yield for simulated conditions at
Black Mesa, AZ.: 5-10 yr. return periods. 1
Storm Event
frequency-duration
Event Sediment Yield, tons
condition 1 2
5 yr. - .17 hr.
88.5
12.6
5 yr. - .25 hr.
112.7
16.1
5 yr. - .50 hr.
133.5
19.1
5 yr. - 1 hr.
157.7
22.5
5 yr. - 2 hr.
132.0
18.0
5 yr. - 6 hr.
125.5
17.9
5 yr. - 12 hr.
121.7
17.4
5 yr. - 24 hr.
113.5
16.2
8 yr. - .17 hr.
101.8
14.5
8 yr. - .25 hr.
126.9
18.1
8 yr. - .50 hr.
161.4
23.1
8 yr. - 1 hr.
186.3
26.6
10 yr. - .17 hr.
110.9
15.8
10 yr. - .25 hr.
138.9
19.8
10 yr. - .50 hr.
174.8
25.0
10 yr. - 1 hr.
197.7
28.2
10 yr. - 2 hr.
170.7
24.4
10 yr. - 6 hr.
153.4
21.9
10 yr. - 12 hr.
136.8
19.5
10 yr. - 24 hr.
137.2
19.6
lYields for condition 3 are equivalent to those cited for condition 1,
unaltered.
Yields for condition 2 are equivalent to those cited for condition 1,
altered
2
Minespoil material without treatment of inflow for original and altered
inputs, respectively.
65
Table 10. Predicted event sediment yield for simulated contitions at
Black Mesa, AZ: 12-25 yr. return periods.*
Storm Event
frequency-duration
Event Sediment Yield, tons
condition 1
12 yr. - .17 hr
114.0
16.3
12 yr. - .25 hr.
141.9
20.3
12 yr. - .50 hr.
180.2
25.7
12 yr. - 1 hr.
202.2
28.9
15 yr. - .17 hr.
122.3
17.5
15 yr. - .25 hr.
153.9
22.0
15 yr. - .50 hr.
193.8
27.7
15 yr. - 1 hr.
218.0
31.1
15 yr. - 2 hr.
190.4
27.2
15 yr. - 6 hr.
166.1
23.7
15 yr. - 12 hr.
139.0
19.9
15 yr. - 24 hr.
150.6
21.5
25 yr. - .50 hr.
218.5
31.2
25 yr. - 1 hr.
237.8
34.0
25 yr. - 2 hr.
190.3
27.2
25 yr. - 6 hr.
158.2
22.6
25 yr. - 12 hr.
159.6
22.8
25 yr. - 24 hr.
144.4
20.6
*Footnotes are equivalent to those cited in Table 9.
66
$2.00/event. Initial capital investment to cover purchase
of the
application mechanism would be the only significant additional cost
required. The resultant reduction or elimination
of pollution fines
would accelerate the expected amortization of this expenditure.
It can therefore be inferred that under the conditions applied
in this investigation, the addition of chemical flocculants is
absolutely necessary to approach a no-risk situation for fully contained
(no emergency spillway overflow) pond inflows. Of course, federal
regulatory policy has rarely, if ever, been directed towards a total
elimination of risk.
The next few paragraphs address the consequences
of hydrologic uncertainty for pond performance.
Hydrologic Uncertainty and Implications
for Pond Performance
In assessing the uncertainty in modeling any natural phenomena,
three sources must be considered: (1) uncertainty in model choice,
(2) sample uncertainty, and (3) imperfect understanding of the physical
process itself. Of the three, only the first two are partially controllable by the modeler.
The models used for rainfall distribution and sediment yield
are both indicative of the uncertainty involved in model selection.
It is entirely possible that the SCS rainfall distribution scheme
utilized in the determination of rainfall excess fails to adequately
describe the temporal characteristics of southwestern convective storms.
Other distributions are available which differ in the timing and extent
67
of the high intensity burst exhibited by observed storms. This could
have a significant effect on production of runoff and sediment yield,
because of the effects of varied intensities on infiltration rates and
satisfaction of prevailing soil moisture deficits. At best, these projected scenarios would only slightly reduce the measured pond effluent
concentrations, for their effects would be damped by the persistence
of the large clay fraction.
Another model application providing a source of uncertainty
for the study is that of the modified USLE (Williams, 1975). George
Foster, a hydraulic engineer with the U. S. Department of Agriculture,
who specializes in the use of soil loss equations, has stated that
Williams' (1975) formulation may not perform well in situations where
raindrop impact accounts for a significant portion of soil erosivity,
since this factor is neglected in Williams' equation (oral communication
1980). However, sediment yields computed via Williams' (1975) equation
are well within the range of 3-4 tons/acre observed by members of the
University of Arizona research team at Black Mesa (Fogel, 1980).
Model uncertainty also enters into consideration in the case of
the DEPOSITS sedimenation model (Ward et al.,1977b). As acknowledged
by its developers, the plug flow concept used for the routing process
is an imperfect device for modeling actual basin hydraulic and sedimentation processes. The authors feel that a partial mixing model
would provide a more accurate description of pond performance but its
comparable complexity would be substantial. Inclusion of a partial
68
mixing model could be expected to result in no more than a moderate
reduction in simulated peak effluent concentrations because of the mixing which would take place between incoming sediment-laden plugs and
the better clarified water stored in the permanent pool.
Differences in the relationships describing Black Mesa sediment
yields for the present study and previous work by Fogel et al. (1979)
exemplify the uncertainty involved in the use of sampled data. Limited
data utilized in the prior study suggested a linear relationship between
event sediment yield and the product of runoff volume and peak flow.
This study, however, employs the non-linear relation between the aforementioned variables cited by Williams (1975). Both the uncertainty
inherent in the limited amount of data available to Fogel et al. (1979)
and that residing in the infiltration data used herein make determination
of the actual sediment yield relationship difficult. Retention of the
linear relation for sediment yield computation in this investigation
would have led to inordinately high sediment yields and correspondingly
high effluent sediment concentrations. Due to the lack of adequate data,
the non-linear sediment yield relationship was assumed to satisfactorily
represent existing conditions at Black Mesa.
Uncertainty due to an imperfect understanding of the physical
phenomena is extreme for the examined processes linking rainfall with
erosion sediment transport and reservoir sedimentation. It must be
remembered that the precipitation events modeled in the study are
relevant in the statistical sense. That is, their occurrence is not
an established certainty. An idea of this variability is provided
69
by computation of the probability associated with at least one 5 yr.
return period storm occurring in the next 10 years: Assuming independence of annual rainfall and a probability of exceedance, p, equal to
the reciprocal of the return period:
P E = 1/T = 0.20
For a geometric distribution:
p (at least one 5 yr. storm occurs in 10 yrs.) =
1-p (no occurrences in 10 yrs.) = 1 - (1-p) 10
= 1 - (0.80) 10
= 0.89
Entire summers void of any runoff producing rainfall whatsoever
are not unheard of for the region. Conversely, storm sequences could
occur during which overlapping of storm routing periods might produce
emergency spillway discharges. Moreover, all individual inflow volumes
within the sequence could conceivably fall below that of the computed
design storm, resulting in simultaneous satisfaction and abridgement of
federal statutes. The stochastic nature of precipitation characteristics
such as intensity and rainfall depth should also be recognized since
their association has been shown by this investigation to greatly influence the predicted performance of sedimentation ponds.
Other variable factors which contribute to the uncertain comprehension of physical phenomena include soil erodibility, complex
hillslope flow systems, gully formation, and the degree to which natural
70
in-pond aggregate formation affects settling rates. Vandivere,
Davis,
and Fogel (1979) investigated the uncertainty involved in applying
the
USLE to semi-arid surface mining sites. Results of hydrologic simulation on Black Mesa spoils showed an extremely large variance in the predicted 3-yr. sediment yields. The USLE overpredicted the 3-yr. sediment
accumulation. This means that for the present study the basis for allocation of dead storage for the pond entails additional uncertainty. Also,
variation in the particle size distribution with flow rate makes obtaining a representative size distribution problematic (dilmoth, Hill, and
Ettinger, 1979).
Model Adaptability and Regional Bias
This model has been designed with general application in mind.
Use of accepted mathematical descriptions for the component parts should
assure it a high degree of adaptability to strip mine situations throughout the semi-arid U. S. Its reliance on field data is minimal, therefore, a limited data base should not preclude its utilization. As pond
sampling data increases, verification of the model can be undertaken
along with regional optimization of parameter values. Lack of verification notwithstanding, the model appears to perform satisfactorily in
generating sediment yields and simulating basin trap efficiencies consistent with the imputed particle size distributions.
Inherent regional bias is evident in all phases of the model due
primarily to the simplicity afforded the present study in neglecting
winter precipitation and spring snawmelt. For application to areas where
frontal storm systems produce a significant portion of annual
71
precipitation, runoff, and sediment yield, a winter precipitation model
coupled with a snawmelt accounting procedure can be added to the SCS
Type II rainfall model used herein for convective storm activity. Alternative sediment yield models can also be substituted for the one used
for this study, although regionalization of the parameters in the Williams
(1975) equation is fairly straightforward, given adequate erosion and
sediment yield data.
Regardless of the methods used for determining water and sediment
inflows to the sedimentation pond, the DEPOSITS routine (Ward et al.,
1979) can be applied with equivalent accuracy to any region, as long as
the modeled pond is designed properly. Provisions are available for
simulating chemical treatment, density currents and short-circuiting and
numerous withdrawal conditions. An additional attribute of the routine
lies in its ability to model reservoir deposition over time. This enables its conjunctive use for purposes of hydrologic time series analysis,
especially where event sequences related to frontal storm systems are
simulated.
The application of the INFLUX program in its present form is
limited to small watersheds of 2000 acres or less where the bulk of
runoff and sediment yield is derived from summer convective storms.
Also, an infiltration curve based on representative field conditions is
required.
Computer time and consequent costs for the model are low. The
combined cost of INFLUX and DEPOSITS models for the 38 selected precipitation events was under $1.50 per run, excluding print costs. This
should make the package more desirable to prospective users.
CHAPTER 5
CONCLUSIONS AND RECOMMENDATIONS
A model has been compiled herein which enables simulation of
sedimentation pond response to inflows generated by selected precipitation events on surface mined and natural watersheds. Procedures utilized in design of the pond reflect both the consideration of published
federal criteria and recognition of current engineering practice. In
the development of hydrologic inputs to the model, attention was directed
toward an adequate description of the physical characteristics of convective precipitation. Application of the model is limited to small watersheds where spring snowmelt is negligible in the production of sediment
and convective rainfall accounts for the bulk of annual runoff. The
model was shown to successfully reproduce observed sediment yields and
simulate pond effluent sediment concentrations which coincided with
computed trap efficiencies.
Simulation was undertaken for three watershed-pond conditions:
(1) minespoil material with untreated inflow; (2) natural soil material
with untreated inflow; and (3) minespoil material with treated inflow.
Results indicated that in every case pond discharge for conditions 1 and
2 grossly exceeded federal standards for concentrations of suspended
solids. Only when condition 3 was evaluated did a majority of routed
pond inflows succeed in meeting the established standards. This suggests
that in most semi-arid mining environs, current Federal guidelines for
72
73
the design of sedimentation ponds are totally incompatible with the
attainment of established effluent quality criteria. Therefore, if the
logic of a national effluent water quality standard is upheld, mine
operators will have to rely heavily on additional measures in order to
both reduce erosion and create depositional opportunities for transient
flaw.
For the semi-arid regions of the west, precipitation uncertainty
makes it highly improbable that the healthy vegetative cover required
to forestall excessive erosion and sedimentation can be achieved without
an effective irrigation schedule. However, as the present study has
shown, maintenance of a good stand of vegetation by no means assures
compliance with published Federal effluent criteria. A crop management
factor as low as 0.09 which corresponds to irrigation-derived vegetal
cover proved insufficient in attaining Federal standards under prevailing
soil and precipitation conditions. The overriding factor affecting pond
performance is the character of the incoming sediment. In situations
where the clay fraction of the particle size distribution is as clearly
dominant as that observed in runoff from graded minespoils at Black Mesa,
attainment of the desired effluent sediment concentrations will definitely
require the addition of flocculants or coagulating agents to pond inflows.
Application of chemical additives results in a significant increase in
pond trap efficiencies due to the effective redistribution of particle
sizes. Acceptance of this prerogative would assure compliance with
federal regulations at minimal cost. Furthermore, the initial capital
74
expenditure required would likely be offset by a concomitant elimination
of federally or state imposed pollution fines.
In an effort to clarify the effect of precipitation uncertainty
on projected pond performance, an alteration of documented sediment and
management characteristics was applied to condition 1. Analysis of subsequent runs revealed a tendency for high-intensity-short duration storms
accompanied by lesser inflow volumes to exceed effluent limitations. Conversely, the low intensity-long duration storms associated with greater
inflow volumes which are exempted from federal regulations consistently
displayed pond effluent concentrations within the allowable limits.
Thus, the use of the 10 yr-24 hr. rainfall event as a design criteria
for sedimentation ponds which do not operate according to a total containment policy appears to be unsubstantiated. The obvious dependence
of predicted pond performance on the characteristics of individual precipitation events along with the uncertainty associated with the occurrence of these events offers ample justification for the consideration
of hydrologic uncertainty in the sedimentation pond design process.
Only then will designers and regulators be able to assess their position
in the light of hydrologic reality.
It must be recognized that even conditions existing on reclaimed
watersheds are dynamic over time. Changing cover densities and the initially accelerated transport of fines could affect a substantial reduction in the influent clay fraction for a large portion of the projected
pond lifetime. This decrease, however, would have relatively little
influence on observed peak effluent sediment concentrations.
75
The poor quality of pond effluent simulated for undisturbed
natural watershed conditions calls into question the applicability of
current federal statutes pertaining to pond effluent limitations to the
semi-arid regions of the western U. S. Ambient sediment concentrations
measured in eastern streams are indicative of the comparatively lush
vegetative cover and overlying canopy which effectively reduce both rainfall energy and the overland transport of sediment. Typically, semiarid zones exhibit sparse vegetal cover and a restricted protective
canopy which effectively reduce both rainfall energy and the overland
transport of sediment. Typically, semi-arid zones exhibit sparse vegetal
cover and a restricted protective canopy, conditions which favor greater
erosive activity, transport capacities, and consequently, higher ambient
stream sediment concentrations. In addition, releasing effluent at concentrations considerably below that of ambient levels may lead to changes
in downstream channel morphology as adjustments are made to accommodate
the new flow regime. It seems sensible, therefore, to encourage the consideration of regional diversity in the establishment of effluent criteria
for state regulatory proposals.
Further research is required to assess the probabilities associated with the occurrence of rainfall events incorporating specific
intensity-volume relationships. Risk analysis could then be attempted
so that the effect of hydrologic uncertainties on the design and expected
performance of detention facilities can be concretized. Since the highest
intensity storm events have been shown to produce the highest peak effluent sediment concentrations, the critical precipitation scheme for
76
semi-arid regions would most likely include a close sequence of these
events. Consecutive days of runoff-producing rainfall would lead to
an overlapping of routing periods. Greatly reduced detention times for
the routed inflows could then result in pipe discharge of heavily
sediment-laden flow through the principal spillway and eventual emergency
spillway overflow.
Another subject which requires investigation is the principle of
total containment regarding all inflows less than that corresponding to
the computed design event. Although this design would produce increased
detention times for runoff generated by the high intensity precipitation
events, the critical scenario outlined above still applies because storage
capacity is limiting and the potential for emergency spillway discharge
remains. Moreover, despite reassurances to the contrary (Nadolski, 1980),
the author suspects that resuspension of deposited sediments by the accompanying horizontal dewatering device is likely, therefore increasing the
risk of violating water quality standards.
The model described in this study maintains a slight regional
bias, but can be easily adapted to other areas and conditions. It retains enough flexibility to enable its use in the analysis of hydrologic
time series and is also relatively inexpensive to run. Because of its
lack of reliance on recorded data, the model is applicable to ungaged
watersheds, thereby increasing its range of utilization. Validation of
the model in its present form is necessary so that expansion of the data
base for semi-arid lands can be realized. This is important if the
western states are to draft mining and reclamation regulations which are
relevant to native conditions.
APPENDIX A
SEDIMENTATION POND DESIGN
A comprehensive discussion of the procedural elements contributing
to the finalized sedimentation pond design is presented below. The design
process is subdivided into three components. Determination of water
storage volume is followed by a description of the procedure used to compute the required sediment storage volume. The basin dimensioning is
outlined and the operating characteristics of the reservoir, in the form of
stage-area-storage volume and stage-discharge relationships, are formulated.
A listing of DEPOSITS output resulting from routing the design storm
through the basin not only confirms the legitimacy of the design, but also
provides the reader with a feeling for the power of the model in describing
basin performance. References are cited in parenthesis adjacent to the
source material used for design purposes.
Basin Capacity and Dimensioning
The procedure outlined here for calculation of basin storage
volume is presented in Ward et al. (1979). Based on an approximation of
inflow-outfow relationships by triangular hydrographs, the required design
storage volume is given as:
V = 0.0413 tb. (qpi. - qpo)
1
s
where
77
78
V
s
= water storage volume in acre-feet,
-bi =
base time for the inflow hydrograph in hours,
and
q . ,q
= peak inflow and outflow rates, respectively, in
p,
i po
cubic feet per second.
As pointed out in Chapter 3, the design method used for
computation of the inflow hydrograph was the SCS triangular
hydrograph method
described by Kent (1973). The geometry of the hydrograph dictates
the
following relationship for its time base:
T = AD
— +L
p
2
where
AD = duration of rainfall excess in hours, and
L = basin lag time in hours.
A 30 minute storm duration was assured representative for design pruposes
and the lag time was calculated to be .17 hours, therefore:
T=
0.5
2
+ 0.17 = .42 hours
and
t
bi
= 2.67 x .42 = 1.12 hours.
Runoff was determined with the use of the SCS rainfall runoff
relation (Kent, 1973):
(P - .2S) 2
= (1) + .8S)
where the maximum potential retention, S, is related to a curve number
index which assesses the runoff producing potential of the watershed.
79
Based on soil type, vegetative cover, and antecedent moisture
condition,
the relationship is expressed as:
S = 1000
CN - 1 0
where CN represents the watershed curve number.
For average antecedent conditions and characteristics common to
graded spoil material at Black Mesa, a curve number of 89 was estimated.
Thus, a value of 1.24 was calculated for the variable S. The resultant
runoff volume was computed as:
Q
(2.10 - .2(1.24))
2
2.10 + .8(1.24)
= 1.12 inches
Next, using the SCS equation for peak runoff determination,
KOA
where
. = peak inflow rate in cubic feet per second,
K = a watershed parameter, assured equal to 484
for chosen hydrograph geometry,
Q = rainfall excess in inches, and
A = drainage area in square miles.
Substituting for equation unknowns:
80
484(1.12)(.078)
q pi
.42
= 100.83 cfs
The remaining factor in the storage volume equation is the projected peak outflow rate from the reservoir given by Ward et al. (1979):
q
= t . q ./t
P0bi pl bo
where
q = peak outflow rate,
po
t
bo
= time base of outflow hydrograph in hours, and
t bo = (3 x t d ) + tbi
where
t
d
= required detention time in hours.
As stated in the federal statutes (Federal Register, P. 15400), a theoretical detention time of 24 hours is the minimum acceptable period for
pond design, therefore:
t
bo
= (3 x 24) + 1.12
= 73.12 hours
Additionally:
q
po
= (1.12 x 100.83)/73.12
= 1.54 cfs
Inflow runoff volume for a triangular hydrograph is:
V = 1/2 q . t .
Pi bi
where
V = inflow volume in cfs-hr.
81
V - 100.83 X 1.12
2
Thus,
= 56.5 cfs-hr.
Converting to acre-feet:
V = 56.5 cfs-hr. X ac-ft.
12 cfs-hr.
= 4.7 ac.-ft.
In lieu of the aforementioned storage equation, empirical relationships
for
inflow and storage volumes on page 57 of the design
manual are used:
S/V
=
for q
.83
=
.015
This results in a required storage capacity, neglecting sediment storage,
of:
S =
.83(4.7)
= 3.9 ac.-ft.
Sediment Storage Volume
The level of the lowest dewatering device is required to be no less
than that corresponding to 100% of the 3-year accumulated sediment storage
volume. Since the regulations state that the Universal Soil Loss Equation
(USLE) and an appropriate delivery ratio must be utilized for this calculation (Federal Register, p. 15400) its application to the hypoethetical
situation is now developed.
The USLE is an empirically derived formula based on thousands of
plot years of data including natural and simulated rainfall conditions for
82
a variety of cultivation and management practices. Recent
accumulation
of data has provided for an extension of its usage to surface mine conditions (EPA 1977). The USLE is expressed as follows:
A =
where
RxKxLSxCxP
A = annual soil loss in tons per acre,
R = rainfall erosion index,
K = soil-erodibility factor,
LS = length and steepness of slope factor,
C = cropping management factor and
P = erosion control practice factor
The equation is dimensionally correct and the reader is referred to the
current USDA-ARS users guide (Wischmeier and Smith, 1978) for a detailed
discussion of factor development and application.
Selection of parameter values was predicated upon 2 assumptions:
1.
Only post-mining conditions were to be examined and no unnatural
disturbances or hydrologic inputs were affected.
2.
Essentially no vegetative cover is established during the first
year and only 10% cover is generated over the next two years.
Estimated factor values and justification for the choices made are:
R
=
30 evaluated from isoerodent map for Arizona
(SCS 1976)
K
=
.35 estimated value for Black Mesa grade spoil
material (Fogel et al., 1979)
LS
=
1.26 derived from estimated average slopes of 6.7%
and a slope length of 250 ft.
83
C = 1.0, .45 estimated values for zero and 10% cover
respectively (EPA, 1977)
P = .35
estimate based on practice of contour
gouging or pitting currently employed
at Black Mesa (EPA, 1977)
Thus, yearly annual soil loss per acre for the 3 years is:
A = (30 x .35 x 1.26 x 1.0 x .35) .9 = 4.17 tons/acre/year
1st year
A = (30 x .35 x 1.26 x .45 x .35) .9 = 1.88 tons/acre/year
2nd, 3rd years
where .9 represents the assumed delivery ratio defined as the ratio of
sediment delivered to the watershed outlet to the gross watershed erosion.
Over the entire extent of the 50-acre watershed the expected 3-yr. sediment yield would be:
50 ac.(4.17 tons/ac./yr. x 1 yr. + 1.88 tons/ac./yr./x 2 yr.)
= 396.5 tons
For storage to be allocated in the pond, the sediment yielded must be
converted into a volumetric quantity reflecting the properties of the
incoming sediment (Federal Register, p. 15400). An accounting of recorded incoming sediment size fraction distributions for the J-3 experimental watershed is offered in Table A.1. Particle diameters in
millimeters for the size fraction descriptors appearing in the table
are:
coarse-medium:
> .125
sand:
very fine:
silt:
clay:
.063 < x < .125
.002 < x < .063
< .002
84
Table A.1. Size fraction distributions for sediment
production:
J-3 experimental watershed, Black Mesa Mine.
Storm date
Size fraction, % of total
Sand
Silt
Clay
Coarse-med. Very fine
7-11-77
7-11-77
7-11-77
7-11-77
7-19-77
7-19-77
7-19-77
7-19-77
7-22-77
7-22-77
7-22-77
7-22-77
8-05-77
8-05-77
8-05-77
8-05-77
8-12-77*
8-12-77*
8-12-77*
8-15-77
8-15-77
8-15-77
8-15-77
8-22-77
8-22-77
8-22-77
8-22-77
Average
14.5
1.9
2.9
4.3
2.4
5.5
5.7
8.0
2.9
2.4
4.3
2.7
5.4
5.7
11.4
3.9
1.6
.8
2.8
.5
2.2
.5
.7
.4
.4
2.6
2.9
2.3
2.0
2.0
2.2
3.0
2.9
1.9
2.7
1.8
1.5
2.9
.9
2.4
2.2
6.3
1.7
2.3
.9
1.6
.9
1.9
.8
1.2
.8
.8
2.1
1.8
39.1
47.4
45.4
48.0
48.9
44.8
46.4
43.8
36.6
40.1
36.7
28.8
41.1
41.2
24.7
40.7
10.3
4.7
2.5
51.7
49.8
36.9
44.0
52.3
51.1
45.5
51.3
44.1
48.7
49.7
45.5
45.7
46.8
46.0
45.5
58.7
56.0
56.4
67.6
51.1
50.9
57.6
53.7
85.8
93.6
93.1
46.9
46.1
61.8
54.1
46.5
47.7
49.8
44.0
3.9
2.0
43.2
50.9
*Unrepresentative, assumed outliers.
P age Missing
in Original
Volume
86
An obvious inconsistency appears in the computed
average size fraction
percentages when matched against those used below in figuring the sediment density value. This is the result of assumptions made later
in the
study regarding the possibly anamolous character of the indicated measured sediment distributions for the indicated storm events. This, however, only lends to the conservative nature of the pond design.
The density of stored sediment is assumed to accrue from conditions
outlined in the DEPOSITS manual (Ward et al., 1979) for "reservoir operation type III" representing a normally dry reservoir:
W = WP +WP +WP
cc
mm
s s
where
W = density of sediment in pound per cubic foot,
Wc,W
m Ws
unit weights for clay, silt, and sand fractions,
respectively, for a dry reservoir in pounds per
cubic foot, and
P P P = proportion of each of the same three above
c m s
mentioned constituents, expressed as a decimal
fraction.
Therefore:
W = 40(.553) + 72(.39) + 97(.06)
= 55.7 lb/ft
3
Finally, the required sediment storage volume is:
ft 3-ac.-ft.
396.5 tons x 2000 lb/ton x 55.7
lb. x
43,560 ft j = .33 ac. ft.
When the required water storage capacity is combined with the sediment
storage volume, the total design storage capacity results:
87
Total storage volume = 2.9 + .33
= 4.23 ac.-ft.
Stage area-discharge Relations
-
Assuming the reservoir bed is constant at stage 0.00 feet, the
surface area and storage capacity are listed as a function of elevation
above the bed in Table A.2. The required sediment storage volume evidently corresponds to a stage of .97 feet. This stage height was designated as the location of the first de-watering orifice set. Results of
earlier trial designs suggested a riser crest elevation of approximately
9.0 feet. A second orifice set was also added at a stage level of 6.0
feet.
With the riser configuration set, the only information lacking
in the determination of the stage-discharge relationship is that of the
head relation for pipe-full flow as described in Chapter 3. This entails
completion of a preliminary basin dimensioning and embankment design so
that the positioning of the culvert and its outlet elevation can be obtained.
Given the computed basin capacity, dimensioning of the basin can
be undertaken. Assuming a trapezoidal configuration with bottom width,
b o , length, 1, and design depth, y d , accompanied by embankment slopes of
1 vertical to 2 horizontal (Federal Register, p. 15400), the following
dimensions have been chosen:
yd
=
15 ft.
b
=
50 ft.
=
285 ft.
o
L
88
Table A.2.
Stage
(ft.)
Rating relations for final pond design.
Surface Area
(ac.)
Storage Capacity
(ac.-ft.)
0.00
.33
0.00
0.97
.35
0.33
1.00
.35
0.34
2.00
.38
0.71
3.00
.40
1.10
4.00
.43
1.52
5.00
.46
1.96
6.00
.48
2.43
7.00
.51
2.93
8.00
.54
3.45
9.00
.56
4.00
9.50
.58
4.29
10.00
.59
4.58
11.00
.61
5.18
12.00
.64
5.81
13.00
.67
6.46
14.00
.69
7.14
15.00
.72
7.85
Trapezoidal Basin:
Surface Area =
(b + 4)L
o
Y
Storage Capacity =
b L + 2 2 L
0 y
y
89
Check for length to width ratio at design depth:
b
L/b
15
• 50 + 2(15 x 2) = 110 ft.
15
• 285/110
•
2.6 which satisfies the suggested ratio of greater
than 2.0 (Ward et al., 1979).
Allowing 5 ft for embankment freeboard and emergency spillway
section:
H = total height of embankment = 20 ft.
Minimum top width must be >((H + 35)/5) (Federal Register, p.
15400)
(H + 35)/5 = 55/5 = 11 ft.
Total width of the embankment = 2(2 x 2) + 11 ,-. 90 ft.
Assume a culvert length = 90 ft. and culvert diameter = 8 in.
Optimum critical slope to produce
pipe full flow (S )
c op.
= 111
n
2
D 1/3
(Portland Cement Association, 1964)
where n = Manning's roughness factor, assumed = .024
D = culvert diameter in feet
(S c ) op for an 8 inch diameter corrugated metal pipe = .079 ft/ft.
Fall height of conduit over projected length = 90 x .079 = 7.1 ft.
Assuming a distance of .5 ft. between the center of the lowest
dewatering orifice and the center of the culvert at its connection with
the riser,
90
head for pipe flaw condition = 7.1 + .5 + 8.03 + h
= (15.6 + h) ft.
where h is the head on the spillway crest.
Stage-discharge relations based on the hydraulic equations given
in Chapter 3 for the finalized pond design are presented in Table A.3.
This information, along with the stage-area data appearing in Table A.2,
provides the primary inputs required by the DEPOSITS model for routing
of sediment laden water through the reservoir. An output generated by
the DEPOSITS routine for the 10 yr-24 hr. design event is listed in the
following pages. Variables appearing in the output are defined in the
DEPOSITS "glossary of terms" which is located in Appendix C.
91
Table A.3. Stage-discharge relations for final pond design.
Q orifice
Q
Stage
weir
(cfs.)
(cf s)
(ft.)
head
1
a1
head
2
Q pipe
total
(cfs.)
(cfs.)
a2
head
a
H
-pipe
-
-
-
-
-
0.00
0.00
-
-
0.97
-
-
-
-
-
-
-
-
0.00
1.00
0.03
.05
-
-
-
-
-
-
0.05
2.00
1.03
.32
-
-
-
-
-
-
0.32
3.00
2.03
.44
-
-
-
-
-
-
0.44
4.00
3.03
.54
-
-
-
-
-
-
0.54
5.00
4.03
.63
-
-
-
-
-
-
0.63
6.00
5.03
.70
-
-
-
-
7.00
6.03
.77
1.0
.31
-
-
-
-
1.08
8.00
7.03
.83
2.0
.44
-
-
-
-
1.27
9.00
8.03
.89
3.0
.54
-
-
-
-
1.43
9.50*
8.53
.09
3.5
.06
0.5
2.44*
16.1
2.51*
2.66
10.00
9.03
.09
4.0
.06
1.0
6.91
16.6
2.54
2.69
11.00
10.03
.10
5.0
.07
2.0
19.54
17.6
2.62
2.79
12.00
11.03
.10
6.0
.08
3.0
35.90
18.6
2.70
2.88
13.00
12.03
.11
7.0
.08
4.0
55.28
19.6
2.77
2.96
14.00
13.03
.11
8.0
.09
5.0
77.26
20.6
2.84
3.04
15.00
14.03
.12
9.0
.09
6.0 101.56
21.6
2.90
3.11
0.70
*Transition to pipe flow occurs at stage = 9.5 ft; orifice discharge
at stages > 9.5 ft. are reduced by 90% due to submergence of orifices.
92
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APPENDIX B
INFLUX VARIABLE DESCRIPTION
Program INFLUX computes event-based rainfall, infiltration,
runoff, sediment yield, and the inflow hydrograph required for utilization of the DEPOSITS sedimentation routine. Included within are component models which are described in Chapter 3. The program requires
the following inputs: event return period, precipitation volume and
duration, and infiltration rates and corresponding soil moisture storage
values. The variables appearing in INFLUX are defined below. Where
appropriate, values for the hypothetical watershed and units of the
variables are noted. Arrays are indicated by an asterisk.
Variable
*ACTFIL
Definition
Value and
Units
Actual value for infiltration
rate for a time increment
in./hr.
Initial soil moisture storage
capacity.
inches
Cumulative time for inflow
hydro graph
hours
Draingage area for hypothetical
watershed.
50.0 acres
Duration of precipitation event
hours
DUREX
Duration of rainfall excess
hours
FACTC
USLE crop management factor
FACTK
USLE soil erodibility factor
AVAIL
*CUMIN
DAREA
*DURA
109
110
Variable Definition
FACTLS
USLE length-slope factor
FACTP
USLE erosion control practice
factor
*FILL
Volumetric infiltration for a time increment
*ORD
Discharge corresponding to .05 hr.
increments
*PCTDC
Cumulative density function for
total rainfall duration
*PCTDP
Probability mass function for
rainfall duration
PCTR
PEAK
PINTMX
Value and
Units
inches
Proportion of total rainfall for
time increment
Peak flow rate for the event
cfs
Intensity index representing
the highest storm rainfall
intensity
*PRECIP
Total rainfall volume for the event
inches
*RAINCD
Cumulative density function for
duration of rainfall
hours
*RAINEX
Volume of rainfall excess for an
increment
inches
*RAINPD
Probability mass function for
duration of incremental rainfall
hours
*RAINV
Volume of rainfall occurring over
a time increment
inches
*RETURN
Return period for a precipitation event
years
RUN VOL
Runoff volume for a precipitation
event
ac.-ft.
111
Value and
Units
Variable Definition
SEDYD
SSINF
*STOFIL
Sediment yield for a precipitation
event
tons
Steady-state infiltration rate
in./hr.
Infiltration rate corresponding
to the prevailing soil moisture
deficit for an increment
in. /hr.
Available moisture storage capacity for an increment
inches
TBASE
Time base of the inflow
hydrograph
hours
TERP
An interpolation factor
for infiltration rate
computation
TFILL
Accumulated soil moisture storage volume
inches
TLAG
Watershed lag time
hours
Time to reach peak flow
rate for a precipitation
event
hours
Volume of rainfall excess
for a precipitation event
inches
*STORE
TPEAK
TRAINX
APPENDIX C
PROGRAM LISTING OF INFLUX
112
113
PROGRAM INFLUX (INPUT,OUTPUT,TAPE 5.INPUT,TAPE 6 -OUTPUT)
C THIS COMPONENT ANALYZES PRECIPITATION EVENTS OF CERTAIN FREQUENCY AND
C DURATION AND DETERMINES CHARACTERISTICS OF MATER AND SEDIMENT INFLUX
C TO THE SEDIMENTATION POND
DIMENSION PCTR(22),PCTDP(22),PCTDC(22),ACTFIL(22),FILL(22)
DIMENSION RAINP0(22),RAINCD(22),RAINV(22),RAINEX(22),STORE(8)
DIMENSION STOFIL(8),RETURN(38),DURA(38),PRECIP(38)
DIMENSION CUMIN(100),ORD(100)
READ(5,1)(PCTR(I),PCTDP(I),PCTDC(I),I.1,22)
1 FORMAT(3F10.3)
READ(5,2) STOFIL
2 FORMAT(8F5.2)
READ(5,3) STORE
3 FORMAT(8F5.2)
DO 150 M..1,38
READ(5,4) RETURN(M),DURA(M),PRECIP(M)
4 FORMAT(I3,2F7.2)
WRITE(0,9) RETURN(M),OURA(M)
9 FORMAT("1",20X,"**** HYDROLOGIC SUMMARY:",I4," YR.",F6.2," HR. EVE
).NT ****")
DUREX.0.0
JRAINX.0.0
SSINF..22
C SSINF REPRESENTS STEADY STATE INFILTRATION RATE IN INCHES/HR.
TFILL.0.0
C AVAIL REPRESENTS INITIAL MOISTURE STORAGE CAPACITY IN INCHES
AVAIL-1.8
C STORE REPRESENTS AVAILABLE MOISTURE STORAGE CAPACITY IN INCHES
FILL IS THE VOLUMETRIC INFILTRATION IN INCHES FOR THE TIME INCREMENT
C APPORTION RAINFALL VOLUME AND DURATION ACCORDING TO SCS TYPE II
C STORM DISTRIBUTION
WRITE(6,10)
lù FORMAT(////, 5X," RAINPD(N)",10X," RAINCD(4)",10X," RAINV(N)",10X,"
I INFIL. RATE"plUX," INFIL. VOLUME")
WRITE(6,11)
11 FORMAT(6X,9("-"),11X19("-."),11X,8("- - "),11X , 11(" - ") , 11X ,13 (" - "))
DO 80 N.1,22
RAINPD(N)=PCTDP(4)*DURA(M)
RAINCD(N)=PCTDC(N)*DURA(M)
RAINV(N).PRECIP(M)*PCTR(N)
IF(N •NE. 15) GO TO 13
MAX. PRE:IF • INTENSITY, PINTMX, OCCURS AT 15TH DURATION INCREMENT
PINTMX.RAINV(N)/RAINPO(N)
13 WRITE(6,15) RAINPD(N),RAINCD(N),RAINV(N)
15 FORMAT(8X,F5.2,14X,F5.2,16X , F5.2)
C FIND 'NFU-. RATE CORRESPONDING TO ACTUAL AVAILABLE MOISTURE STORAGE
IF((AVAIL-TFILL) .GT. 1.25) GO TO 18
C ACTFIL IS THE ACTUAL VALUE FOR INFILTRATION RATE OVER THE INTERVAL IN
C INCHES/HR.
AZTFIL(N).SSINF
FILL(N).SSINF*RAINPD(N)
GO TO 30
18 DO 2 0 K=1,8
IF((AVAIL-TFiLL) •GE. STORE(K)) GO TO 23
20 CONTINUE
23 IF(K .EQ. I) GO TO 25
TERP.((AVAIL-.TFILL)-STORE(K))/(5TOREST 0 RE ( K ))
ACTFIL(N)=STJFIL(K)+TERP*(STOFIL(K - 1) - STUFIL ( K ))
GO TO 26
25 ACTFIL(N)=STOFIL(K)
26 FILL(N).ACTFIL(N)*RAINPD(N)
IF(CAVAIL-•(TFILL+FILL(N))) .LE. 0.00) GO TO 27
TFILL=TFILL+FILL(N)
114
GO TO 45
27 FILL(N)wAVAILTFILL
30 TFILLwTFILL+FILL(N)
AVAIL.TFILL
45 WRITE(6,50) ACTFIL(N),FILL(N)
50 FORMAT("+",63X,F9.2,15XpF8.2)
C CALCULATE VOLUME OF RAINFALL EXCESS FOR INCREMENT
RAINEX(N)=RAINV(N)FILL(N)
IF(RAINEX(N) .GT. 0.0) GO TO 70
GO TO 80
70 DUREX.DUREX+RAINPD(N)
TRAINX.TRAINX+RAINEX(N)
80 CONTINUE
WRITE(6,82) PRECIP(M),PINTMX
82 FORMAT("0"," PRECIP. VOLUME • " 1 F6.2," INCHES",/," MAXIMUM PRECIP.
1INTENSITY •",F6.2," IN./HR.")
WRITE(8,85) DUREX,TRAINX
85 FORMAT("0"," DURATION OF RAINFALL EXCESS w",F5.2," HRS.",/p" TOTAL
2 RAINFALL EXCESS P",F5.2," INCHES")
C CALCULATE PEAK FLOW RATE, TIME TO PEAK, AND TIME OF HYDROGRAPH BASE
DAREA-50.0
C TLAG REPRESENTS THE LAG TIME IN HRS. FROM CENTROID OF RAINFALL EXCESS
C DURATION TO HYDROGRAPH PEAK
TLAGw.17
C TPEAK REPRESENTS TIME IN HRS. FROM THE INITIATION OF RUNOFF TO THE
C HYDROGRAPH PEAK
C TBASE REPRESENTS TIME IN HRS. CORRESPONDING TO THE HYDROGRAPH BASE
TPEAKm(DUREX/2+TLAG)
PEAKw(484.0*DAREA/64000*TRAINX)/TPEAK
TBASE.2.67*TPEAK
C CALCULATE EVENT BASED SEDIMENT YIELD VIA REGIONALIZED WILLIAMS EQN.
C RUNVOL REPRESENTS RUNOFF VOLUME IN AC. FT.
RUNVOLw(TRAINX*DAREA)/12.0
FACTLS.1.26
FACTCw.09
FACTKw.35
FACTPw.35
C SEDYD 15 THE EVENT SEDIMENT YIELD IN TONS
5EDYUw95.0*(RUNVOL*PEAK)*w.564.FACTC1FACTK*FACTLS*FACTP
WRITE(6,90) PEAK
90 FORMAT("0"," PEAK FLOW FOR EVENT • "..F7.2," CFS")
WRITE(6p93) TPEAK
93 FORMAT(" "p" TIME TO PEAK DISCHARGE w",F5.2," HRS.")
WRITE(6,95) RUNVOL
95 FORMAT(" "." VOLUME OF INFLOW TO POND • ",F5.2," AC. FT.")
ORITE(6,96) TBASE
96 FORMAT(" "," TIME BASE OF INFLOW HYDROGRAPH • ",F5.2p" HRS.")
WRITE(0/98) SEDYD
;a FoRmArin 1 SEDIMENT YIELD FROM WATERSHED FOR EVENT • ",F9.1," TON
3S")
C CUMIN REPRESENTS THE CUMULATIVE TIME FOR THE INFLOW HYDROGRAPH
C CALCULATE ORDINATES OF INFLOW HYDROGRAPH
C WITH 4 TIME INCREMENT OF .05 HRS.
WRITE(6,110)
£10 FORMAT("1"p2OX," INFLOW HYDROGRAPH COORDIUTES")
WRITE(6,111)
111 FORMAT(21Xp29("".."))
"
"
WRITE (6,112)
112 FORMAT("0",22X," TIME(HRS.)",1X," DISCHARSE(CFS)")
WRITE(8,113)
113 FORMAT(24X,4("-"),8X,9("-"))
INPERwINT(TBASE/.05+1.0)
DO 140 .1.1,INPER
115
CUMIN(J).J/20.0
IF(CUNIN(J) • GT. TBASE) GO TO 150
IF(CUMIN(J) .GT. TPEAK) GO TO 115
C Q0(J) REPRESENTS THE DISCHARGE CORRESPONDING TO J INCREMENTS OF .05HR
ORD(J)*PEAK/TPEAK*CUMIN(J)
GO TO 120
115 ORD(J).PEAK....(PEAK/(1.67*TPEAK)*(CUMIN(J)-TPEAK))
120 WRITE(15 125)CUMIN(J).ORD(J)
125 F3RMAT("0",22X,F5.2.11X,F5.1)
140 CONTINUE
150 CONTINUE
,
STOP
END
APPENDIX D
PROGRAM AND INPUT LISTING OF DEPOSITS
Input Listing of Deposits
The following is a listing and description of the inputs required
by the DEPOSITS sedimentation model (Ward et al., 1977b). Typical variable values are presented, and their implications for model functioning
appear parenthetically.
VariableDefinition Value
NSTORM
Number of inflow events required
1.0
CONSED
Control variable determining the
calculation of the inflow sediment
concentrations. (concentrations
are approximated by the model)
1.0
DEPOST
Control on use of the deposition
option. (no deposition option)
1.0
MASS
Total mass of incoming sediment
in tons
FLOW
Indicator of desired outflow con-
ditions. (uniform withdrawal)
1.0
TRP
Control variable providing for
testing of several outlet structures
(model straightforwardly determines
trap efficiency)
1.0
FILTER
Enables alteration of initial stage-
discharge curve due to deposition.
(no disposition effect considered)
1.0
DENSTY
Density of deposited sediment
SG
Specific gravity of sediment par-
ticles in g/cm3
116
16.1
.89
2.65
117
VariableDefinitionValue
Viscosity of the flow in cm 2 /sec.
VISCOS
DELTAT
DELPLG
SET
SHORT
Time increment for the inflow hydro-
graph and inflow sediment-graph in
hours.
.20
Time increment for outflow plug rou-
ting in hours
.20
Dictates the relationship between the
sediment load and the inflow rate.
(Sets inflow sediment concentration
proportional to the inflow rate)
.0152
Basin short-circuiting option
(plug flow through basin is
assumed)
2.0
1.0
FIX
Correction factor for simulation
of turbulence or flocculation
(turbulence and flocculation are
neglected)
1.0
FLOWAV
Determines how particle size distribution varies with flaw rate.
(one representative distribution
is maintained throughout)
0.0
FRACTN
Control variable defining the sediment distribution during inflow to
the basin. (sediment load is completely mixed with storm inflow)
0.0
SLAG
Simulates a lag between peak inflow
rate and peak inflow sediment concentration. (effect is neglected)
0.0
DEAD
Volume of stored flow and/or sediment bypassed during routing, in
ac.-ft. (volume set equal to 60%
of calculated 3-yr. sediment storage)
MP
Number of outflow distribution points
18
Number of inflow hydrograph values
(inflow hydrograph constructed from
2 values)
>2
.20
118
Variable
Definition
Number of stage-area and stage discharge values
Value
18
NS
Number of particle size fractions
MS
Number of outflow hydrograph points
(set equal to maximum allowable)
LS
Number of values required to fill
the permanent pool volume (pool is
filled internally by the program)
PERCNT
Percent finer values inputed for
particle size distribution
0.0, 28.2,
63.3, 85,8,
100.0
SIZE
Particle sizes corresponding to
inputed percent finer values in
millimeters
0.0, .002,
.063, .125,
1.00
STGI
Stage values at the riser used
for rating curves
AREA
Area values corresponding to inputed stage values
DISCHB
Discharge values corresponding to
inputed stage values
INFLOW
Inflow hydrograph values for the
storm
5
400
0
119
PROGRAM SEDIMT (INPUT OUTPUT,TAPE5.INPUT,TAPE6.OUTPUT)
,
* **** ********* ***** ************** **************** ***** ***** **** ***** ******
THE DEPOSITS PROGRAM
APRIL 1979
THE DEPOSITS PROGRAM WAS DEVELOPED AT THE AGRICULTURAL ENGINEERING
DEPARTMENT AND THE INSTITUTE FOR MINING AND MINERALS RESEARCH AT THE
UNIVERSITY OF KENTUCKY, LEXINGTON KENTUCKY. THE UNIVERSITY OF KENTUCKY
ASSUMES NO RESPONSIBILITY FOR ANY RESULTS OBTAINED WITH THE MODEL.
THE DEPOSITS COMPUTER PROGRAM IS A SIMULATION MODEL FOR ESTIMATING THE
PERFORMANCE OF A SEDIMENT DETENTION BASIN. THE MCDEL WILL DETERMINE THE
BASIN TRAP EFFICIENCY, CHANGE IN BASIN GEOMETRY DUE TO SEDIMENT DEPOSITS
AND THE EFFLUENT SEDIMENT CONCENTRATIONS FOR A GIVEN STORM EVENT.
************************************************** ***** ********* ******* ***
****** **** ** * ******* *** ***** ****** ******* ******* ********** ******* ***** ****
GLOSSARY OF TERMS
ACINFL
ACOUT
• ACCUMULATED INFLOW VOLUME (ACRE-FEET)
• ACCUMULATED DISCHARGE FROM THE RESERVOIR. (ACRE-FEET)
ACT
CONTROL FLAG USED TO TERMINATE SIMULATION. (ACRE-FEET)
AR
AREA CONTROL VALUE USED IN DEVELOPING NEW AREA CURVE.
ARA•
AREA CONTROL VALUE USED IN DEVELOPING NEW AREA CURVE.
• AREA CONTROL VALUE USED IN DEVELOPING NEW AREA CURVE.
ARC
= AREA CONTROL VALUE USED IN DEVELOPING NEW AREA CURVE.
ARE
AREAA
• SURFACE AREA OF SURFACE PLUG LAYER. (ACRES)
AREA•
BASIN SURFACE AREA AT EACH STAGE POINT. (ACRES)
AREAC
SURFACE AREA OF THIRD PLUG LAYER. (ACRES)
AREAB
• SURFACE AREA OF SECOND PLUG LAYER. (ACRES)
AREAD
• SURFACE AREA OF BED PLUG LAYER. (ACRES)
• DESIGN BASIN SURFACE AREA AT EACH STAGE POINT. (ACRES)
AREAS
AROLD
• SURFACE AREA AT EACH STAGE POINT PRIOR TO DEPOSITION. (ACRES)
• AVERAGE DEPTH OF FLOW AT EACH INFLOW TIME STEP. (FEET)
AVDEP
AVDPTH
• AVERAGE DEPTH AT EACH STAGE POINT. (FEET)
AVETME
• DETENTION TIME OF FLOW CONTAINING SEDIMENT. (HRS)
AVSTG
• AVERAGE DEPTH AT EACH INFLOW TIME. (FEET)
AVTME
• SUM OF THE PRODUTS OF THE PLUG VOLUMES TIMES THE PLUG DETENTION
TIMES. (ACRE-HRS)
SPOOL• VOLUME OF INFLOW USED TO FILL THE PERMANENT POOL. (ACRE-FEET)
= VOLUME OF SEDIMENT DEPOSITED BELOW EACH STAGE VALUE.(ACRE-FEET)
CAP
CAPAC
• DESIGN CAPACITY OF THE BASIN AT EACH STAGE VALUE. (ACRE-FEET)
• BASIN CAPACITY AT EACH INFLOW TIME. (ACRE-FEET)
CAPACA
CAPCH
• VOLUME CONTROL VALUE USED TO DEVELOP NEW STAGE CAPACITY CURVE.
120
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
• DESIGN CAPACITY OF THE BASIN AT EACH STAGE VALUE. (ACRE—FEET)
• VOLUME CONTROL VALUE USED TO DEVELOP NEW STAGE CAPACITY
CURVE, (ACRE—FEET)
CAPMAX
• MAXIMUM VOLUME OF RESERVOIR BASIN. (ACRE—FEET)
CAPNW
• RESERVOIR VOLUME AT EACH STAGE POINT FOLLOWING DEPOSITION.
(ACRE—FEET)
CAPOOL
• VOLUME OF THE PERMANENT POOL. (ACRE—FEET)
CAPO
• CALCULATED CAPACITY VALUES BEFORE SMOOTHING. (ACRE—FEET)
CAPREM
. TOTAL VOLUME OF SEDIMENT DEPOSITED BY STORM. (ACRE—FEET)
CAPSAV
• VOLUME OF THE BASIN AT THE PEAK STAGE. (ACRE—FEET)
CENTME
• DETENTION TIME FROM HYDROGRAPH CENTERS. (HRS)
CHECK
• AREA CONTROL VALUE USED TO DEVELOP NEW AREA CURVE. (ACRES)
CONCED
• INFLOW SEDIMENT CONCENTRATIONS. (MG/L)
CONSED
• CONTROL VARIABLE DETERMINING THE INPUT OF INFLUENT SEDIMENT
CONCENTRATIONS. (MG/L)
COR • CONTROL VALUE USED TO SMOOTH NEW STAGE—CAPACITY CURVE.
DEAD • DEAD STORAGE VOLUME. (ACRE—FEET)
DELPLG • TIME INCREMENT OF EACH OUTFLOW PLUG. (HRS)
DELTAT a INFLOW HYDROGRAPH TIME INCREMENTS. (HOURS)
DENSTY • DENSITY OF THE SEDIMENT DEPOSITS.
DEP • VOLUME OF SEDIMENT DEPOSITED DURING EACH DISCHARGE
INCREMENT. (ACRE—FEET)
DEPCAP . CHANGE IN STORAGE CAPACITY DUE TO SEDIMENT DEPOSITS.
(ACRE—FEET)
DEPI • CHANGE IN STORAGE CAPACITY FOLLOWING SMOOTHING
COMPUTATIONS. (ACRE—FEET)
DEPOC
. SMOOTHING CONTROL VARIABLE.
DEPO
• CONTROL VARIABLE USED IN SMOOTHING OF NEW BASIN GEOMETRY
CURVES.
DEPOST
. CONTROL VARIABLE DETERMINING USE OF THE DEPOSITION OPTION.
DEPTH
• AVERAGE DEPTH DURING DETENTION OF EACH PLUG. (FEET)
DEPTH1
• DEPTH OF THE SECOND PLUG LAYER. (FEET)
DEPTH2
• DEPTH OF THE THIRD PLUG LAYER. (FEET)
DEPTH3
• DEPTH Of THE BOTTOM PLUG LAYER. (FEET)
DETAVE
= AVERAGE DETENTION TIME OF DISCHARGED FLOW. (HRS)
DETTME
• DETENTION TIME OF EACH PLUG. (HOURS)
DIAMTR
• PARTICLE SIZE WITH A FALL VELOCITY OF VELOC. (MM)
DIFF
• CONTROL VALUE USED TO SUBDIVIDE THE TOP LAYER.
DISCH
• DISCHARGE RATE AT EACH STAGE VALUE. (CFS)
DISCHA
. DESIGN DISCHARGE RATE AT EACH STAGE VALUE. (CES)
DISCHB
• DISCHARGE VALUE FOR EACH STAGE POINT. (CES)
DPTH
• STAGE DEPTH FOR EACH DISCHARGE AND AREA VALUE. (FEET)
DPTH
• DEPTH VALUES ON THE OUTFLOW DISTRIBUTION CURVE. (FEE)
EFLNT
• EFFLUENT CONCENTRATION FOR EACH OUTFLOW INCREMENT. (MG/L)
ERROR
• ERROR IN DETERMINING THE NEW BASIN CAPACITY. (ACRE—FEET)
FALL
• REQUIRED DEPTH OF SETTLING. (FEET)
• CONTROL VARIABLE DETERMINING THE USE OF AN OUTLET FILTER.
FILTER
FIX
• CORRECTION FACTOR TO MODIFY THE FALL DEPTH.
FLOWIN
• FLOW RATE AT WHICH THE SEDIMENT DISTRIBUTION WAS DETERMINED.
C
FLOW•
C
C
C
C
C
C
C
C
C
C
FRACTN
INFLOW
LS
LLS
MASS
M
MS
MS
N
C
NFLNT
•
C
NS
•
CAPCO
CAPC
(CFS)
•
.
•
•
•
•
•
.
•
CONTROL VARIABLE DETERMINING THE INPUT OF AN OUTFLOW DEPTH
DISTRIBUTION.
IF FRACTN GREATER THAN 0.1 FLOW OCCURS AS A DENSITY CURRENT.
INFLOW RATE AT EACH INFLOW TIME. (CES)
NO OF INFLOW VALUES USED TO FILL THE PERMANENT POOL.
NO OF INFLOW VALUES USED TO FILL THE PERMANENT POOL. (LLS=LS)
SEDIMENT INFLOW LOAD. (TONS)
NUMBER OF INFLOW VALUES.
NUMBER OF OUTFLOW ROUTING VALUES.
NUMBER OF OUTFLOW ROUTING VALUES.
NUMBER OF STAGE VALUES.
THE INFLUENT CONCENTRATIONS AT EACH INFLOW TIME PCINT. (MG/L)
NUMBER OF PARTICLE SIZE DISTRIBUTION VALUES.
121
C
NSTORM
COUTFL1
COUTFL2
COUTFL3
COUTFL4
C
OUTPCT
CPCT
CPCTOUT
C
PEAKIN
CPEAK•
CPERCNT
•
•
•
•
.
•
•
•
•
.
CINDICATED
PFLNT
C
C
PLGCEN
C
PLGTME
C
PLGVOL
C
PSTAGO
C
SED
C
SEDAVE
C
C
SEDAV2
C
SEDEND
C
SEDMNT
C
SEDOUT
C
SEDPLG
CSEDTOT
C
SEDT
CSET
C
C
C
C
SFLNT
SG
SHORT
SIZES
CSIZEST
C
C
C
SIZE
SIZOUT
SLAG
•
•
•
•
•
•
.
•
•
•
.
.
•
•
.
.
•
.
=
•
•
.
•
CSMOOTH •
C
C
C
C
C
C
SMOTH2
STAGE•
STAGEA
STAGO
STAG•
STAREA
CSTARTV
C
STGAR
C
STGIN
C
STGOUT
C
STG1
C51 G2
C
STG3
STORM•
C
SIP
C
STPV
C
CSTRMOT
CSTRMTM
SUMTME
C
SUMVOL
C
•
•
•
•
•
.
•
•
•
•
=
.
.
.
•
•
•
.
•
•
.
c
sum:.
C
C
SUM2
T
TMEIN
TOTAL•
.
TOTVOL
c
c
C
CONTROL VARIABLE DETERMINING THE NUMBER OF STORM EVENTS.
OUTFLOW DISTRIBUTION FOR THE TOP PLUG LAYER. ( )
OUTFLOW DISTRIBUTION FOR THE SECOND PLUG LAYER. ( )
OUTFLOW DISTRIBUTION FOR THE THIRD PLUG LAYER. ( )
OUTFLOW DISTRIBUTION FOR THE BOTTOM PLUG LAYER. ( )
FINER OF SEDIMENT IN THE POND EFFLUENT.
PERCENT OF SEDIMENT REMAINING IN SUSPENSION IN EACH LAYER.
SEDIMENT LOAD FOR EACH PARTICLE SIZE IN THE EFFLUENT.
PEAK INFLOW RATE. (CES)
PEAK DISCHARGE RATE. (CFS)
PERCENT OF PARTICLES CAPABLE OF FALLING THE RESPECTIVE
DEPTH DURING THE PLUG DETENTION TIME.
PEAK INFLOW SEDIMENT CONCENTRATION. (MG/L)
THE TIME OF INFLOW OF EACH PLUG OF OUTFLOW. (HOURS)
THE TIME OF OUTFLOW FOR EACH PLUG. (HOURS)
THE VOLUME OF EACH PLIG. (ACRE-FEET)
PEAK STAGE VALUE. (FEET)
PERCENT OF THE TOTAL SEDIMENT INFLOW CONTAINED IN EACH PLUG.
AVERAGE EFFLUENT SEDIMENT CONCENTRATION OF FLOW CONTAINING
SEDIMENT. (MG/L)
AVERAGE EFFLUENT SEDIMENT CONCENTRATION OF ALL FLOW. (MG/L)
ACCUMULATIVE TOTAL PERCENT OF THE INITIAL SEDIMENT DISCHARGED.
PROPORTION OF SEDIMENT ASSOCIATED WITH EACH INFLOW INCREMENT.
FRACTION OF SEDIMENT CONTAINED IN EACH PLUG. ( 1
PERCENT OF SEDIMENT DISCHARGED IN EACH PLUG.
ACCUMULATED VOLUME OF SEDIMENT INFLOW.
ACCUMULATED VOLUME OF SEDIMENT DISCHARGED.
EXPONENT OF FLOW SEDIMENT LOAD RELATIONSHIP.
INFLOW SEDIMENT CONCENTRATIONS. (MG/L)
SPECIFIC GRAVITY OF THE SEDIMENT PARTICLES.
SHORT-CIRCUITING CONTROL VARIABLE.
FINER OF INFLOW DETERMINED AT PEAK INFLOW RATE. ( )
INFLOW PARTICLE SIZES DETERMINED AT PEAK INFLOW RATE. (MM)
PARTICLE SIZE ASSOCIATED WITH EACH PERCENT FINER. (MM)
FINER OF EFFLUENT SEDIMENT PARTICLES.
LAG INCREMENTS OF TIME OF FLOW PEAK BEHIND SEDIMENT PEAK.
AREA SMOOTHING FUNCTION.
AREA SMOOTHING FUNCTION.
DEPTH OF FLOW FROM THE LOWEST BED ELEVATION. (FEET)
STAGE AT EACH ROUTING TIME. (FEET)
STAGE AT EACH OUTFLOW TIME. (FEET)
STAGE VALUES PRIOR TO EACH STORM EVENT. (FEET)
AREA UNDER THE AVERAGE DEPTH-TIME CURVE. (ACRE-FEET)
VOLUME OF INFLOW AT THE START OF THE ROUTING CYCLE. (ACRE-FEET)
AVERAGE STAGE AFTER EACH INCREMENT OF INFLOW. (FEET)
STAGE DURING INFLOW OF EACH PLUG. (FEET)
STAGE DURING THE PLUG OUTFLOW. (FEET)
DESIGN STAGE VALUES. (FEET)
STAGE CONTROL VARIABLE USED IN SMOOTHING CALCULATION.
STAGE CONTROL VARIABLE USED IN SMOOTHING CALCULATION.
STORM INFLOW VOLUME. (ACRE-FEET)
ACCUMULATED VOLUME OF OUTFLOW. (ACRE-FEET)
ACCUMULATED INFLOW AT TIME Ti. (ACRE-FEET)
STORM VOLUME DISCHARGED. (ACRE-FEET)
DETENTION TIME INCLUDING STORED FLOW. (HRS)
VARIABLE USED IN EVALUATING THE STORM DETENTION TIME.
VOLUME OF FLOW DISCHARGED. (ACRE-FEET)
DEPO**2.0*(AREA(J)-AREA(J-1))+SUM2
DEP0*(AREA(J)-AREA(J-1))+SUM2
TIME TAKEN TO FILL PERMANENT POOL. (F R S)
TIME DURING INFLOW. (HOURS)
VOLUME OF DISCHARGE USED IN COMPUTATION OF CENTME.
VOLUME OF DISCHARGE USED IN COMPUTATICN OF CENTME.
122
C
TRAP
C
TRP
C
Ti•
C
VAR
C
VELOC
C
VISCOS
C
VOL
C
VOLACT
C
VOLA•
CVOLS•
C
VOLE•
C
VOLD
C
VOLC
C
VOLIN
C
VOLOUT
C
C
VOLSED
C
VOLTME
C
VOLTOT
C
VOLUME
C
X1
C
X2
C
. TRAP EFFICIENCY. ( )
• INPUT VALUE OF REQUIRED TRAP EFFICIENCY. ( )
TIME SINCE THE START OF INFLOW. (HRS)
• VARIABLE USED IN SMOOTHING CALCULATION.
• FALL VELOCITY. (FEET/HOUR)
• VISCOSITY OF THE FLOW. (CM.SO./SEC)
• VOLUME OF EACH PLUG LAYER. (ACRE FEET)
• INCREMENTAL CHANGE IN BASIN VOLUME. (ACRE FEET)
—
—
•
•
•
•
•
•
•
•
•
•
VOLUME OF EACH PLUG. (ACRE—FEET)
VOLUME OF FLOW BELOW THE SURFACE PLUG LAYER. (ACRE—FEET)
VOLUME OF FLOW BELOW THE SECOND PLUG LAYER. (ACRE—FEET)
VOLUME OF FLOW BELOW THE THIRD PLUG LAYER. (ACRE—FEET)
VOLUME OF EACH LAYER ALLOWING SETTLING INTO THE NEXT LAYER.
VOLUME OF INFLOW ACCOUNTED FOR AFTER EACH PLUG DISCHARGES.
FRACTION OF INFLOW SEDIMENT LOAD ROUTED AT THE END OF EACH
TIME POINT.
CALCULATED CAPACITY AT EACH STAGE VALUE STAGO. (ACRE FEET)
AVERAGE TIME DURING THE INFLOW OF EACH INCREMENT OF FLOW.
TOTAL VOLUME OF INFLOW (ACRE—FEET)
VOLUME OF INFLOW DURING EACH INFLOW TIME INCREMENT. (ACRE—FEET)
ROUTING VOLUME USED TO SOLVE CONTINUITY EQUATION. (ACRE—FEET)
ROUTING VOLUME USED TO SOLVE CONTINUITY EQUATION. (ACRE FEET)
—
COMMON/HOLD/INFLOW,MXPLLS/DELTAT
DIMENSION FLOWIN(400),SIIEST(10,400),SI2OUT(10,400),PCTOUT(10p400)
DIMENSION DEPTH1(400) , DEPTH2(400),DEPTH3(400)PDEPTH(400)
DIMENSION PERCNT( 4 00) , X1(400),X2(400),SEDPLG(400),SFLNT(400)
DIMENSION PLGVOL( 4 00),AROLD(400)/CAPNW(400),DIFF1400),STP(400)
DIMENSION ACINFL(400),VOLUME(400)pSTARTV(400),STPV(400),STAGE(400)
DIMENSION STAGEA( 4 00),CAPACA(400),T1(400),DISCHA(400),CAPAC(400)
DIMENSION DISCH(400) , NFLNT(400),EFLNT(400),CAPC0(400),CONCED(40C)
DIMENSION AREAA(400),AREAB(400),AREAC(400),AREAD(400),INFLOW(400)
DIMENSION VOL(4,400),SED(4,400),VELOC(4,400),FALL(4,400)
DIMENSION VOLC(3,400),DEP(4,400),PCT(4,400),PERCT(5,400)
DIMENSION AREAS(50)PSIZE(50),OUTFL1(50),OUTFL2(50),OUTFL3(50)
DIMENSION OUTFL4(50),STG1(50),DISCHB(50),AREA(50),DPTH(50)
DIMENSION SI2ES(50),VOLA(400),VOLB(400),VOLE(400),VOLD(400)
DIMENSION DIAMTR(5,400),VOLSED(400),VOLACT(400),SEDMNT(400)
DIMENSION AVDPTH(400),AVSTG(400),STGIN(400),STGOUT(400),STAGO(400)
DIMENSION STAREA(400),STGAR(400),ACOUT(400),VOLOUT(400),TMEIN(400)
DIMENSION VOLTME(400),SEDTOT(400),SEDOUT(400),OUTPCT(20)
DIMENSION PLGTME(400),VOLIN(400),DETTME(400),PLGCEN(400)
DIMENSION STAG(400),AVDEP(400),SEDEND(400),SEDT(400)
REAL OUTFL1pOUTFL2pOUTFL3p0UTFL4
REAL NFLNIPMASSPINFLOWPNSTORM
READ(5,5100)NSTORM,CONSED,DEPOST,MASS,FLOW,TRP,FILTER,DENSTY,SGPVI
1SCOS
IF(NSTORM.LT.0.0) DELTAT.CONSED
IF(NSTORM.LT.0.0) LLS.0.0
IF(NSTORM.LT.0.0) CALL WASH
IF(NSTORM .LT. 0.0) GO TO 3950
READ(5,5000) DELTAT,DELPLG,SET,SHORT,FIX,FLOWAV,FRACTN,SLAG,DEAD
5000 F0RMAT(9F8.0)
READ(5,5200)MP,M,NsNS,MS,LS
READ(5,5100)(PERCNT(NL),NL*1,NS)
READ(5,5100)(SIZE(NL),NL•liNS)
READ(5,5100)(STG1(I),I*1,N)
READ(5,5100)(AREAS(I),I*1,N )
20 READ(5 , 5100)(DISCHB(I),I*1,N)
5100 FORMAT(10F8.0)
PO 40 I*1,N
—
123
AREA(I)AREAS(I)
OISCH(I)=DISCH8(I)
STAGE(I)=STG1(I)
40 CONTINUE
NNNeNSTORM
DO 3900 IN=1,NNN
READ (5,5100) NSTORM , CONSED , DEPOSTJMASSPFLOW,TRP,FILTER,DENSTY,SGoVI
1SCOS
READ(5,5000) DELTAT , DELPLG , SET,SNORT,FIX,FLOWAV,FRACTNPSLAGsDEAD
READ(5,5200)MP,M,NoNS,M5,LS
LLS=LS
IF(M.GT.LS) READ(5,5100)(INFLOW(I),I=1,M)
IF(M.LE.LS.AND.LS.GT.0.0)READ(5,5100)(INFLOW(I),I=1,M)
1F(M.LE.LS) CALL WASH
IF(M.LE.LS)M=MX
IF(CONSED.GT.1.99.AND.CONSEO.LE.2.01) GO 10 60
GO TO 80
60 READ( 5, 5100) (CONCED(I),I.1,M)
80 CONTINUE
DO 100 I=1,N
AROLD(I)=AREA(I)
STAG(I)=STAGE(I)
100 CONTINUE
CAPC0(1)=0.0
PEAKIN=0.0
DO 120 .1=1), M
•
IF(INFLOW(J) .GT. PEAKIN .AND. J•GT. LS) PEAKIN=INFLOW(J)
120 CONTINUE
DO 140 1=1,N
DPTN(I)=STG1(I)
140 CONTINUE
IF(FLOW.GT.3.99.AND.FLOW.LE.4.01) GO TO 260
DO 160 I=1,MP
OUTFL1(I)=25.0
OUTFL2(I)=25.0
OUTFL3(I)=25.0
OUTFL4(I)=25.0
160 CONTINUE
IF(FLOW.GT.2.99.AND.FLOW.LE.3.01) GO TO 200
DO 180 I=1,MP
IF(FLOW.GT.0.99.AND.FLOW.LE.1.01) GO TO 240
OUTFL1(I)=0.0
OUTFL2(I)=0.0
OUTFL3(I)=0.0
OUTFL4(I)=100.0
180 CONTINUE
GO TO 240
200 DO 220 I=1,MP
OUTFL1(I)=100.0
0UTFL2(I)=0.0
OUTFL3(I)=0.0
0UTFL4(I)=0.0
220 CONTINUE
240 CONTINUE
GO TO 280
260 CONTINUE
5200 FORMAT(6I8)
READ(5,5100)(DPTN(I),I=1,MP)
READ(5,5100)(OUTFL1(I),I=1,MP)
RE4D(5,5100)(OUTFL2(I),I.1.01P)
READ(5,5100)(OUTFL3(I),I=1,MP)
READ(5,5100HOUTFL4(I),I.1,MP)
280 CONTINUE
124
WRITE (5,5300)
5300 FORMAT(1H1)
WRITE(6.5400)
5400 F 0 RMAT(// , 15X,"*************** ******* ********* THE DEPOSITS MODEL.
1 JANUARY 1979 «)
WRITE (6,5500)
5500 FORMAT(////,45X,"***** INPUT CONTROL VARIABLES *****")
WRITE (5,5500)
5600 FORMAT(//,15X,"MP",BX,"M",9X,"N",10X."NS",7X."MS",7X,"LS")
WRITE(6 , 5700)MP,M.N,NS.MS,LS
5700 FORMAT(//p7X,6I10)
WRITE (6,5800)
5800 FORMAT(//,15X,"NSTORM",4X,"CONSED",4X,"DEPOST",4X,"FLOW".6X,"TRP".
17 X , "FILTER" ,4 X , "FIX",7X,"FRACTN",7X,"FLOWAV")
WRITE (6,5900 )NSTORM , CONSED , DEPOST.FLOW,TRP,FILTER,FIX,FRACTN
1 .FLOWAV
5900 FORMAT(//p9X,8F10.2,6X,F10.2)
IF(FRACTN.LE.0.1) GO TO 300
WRITE (5,6000)
6000 FORMAT(//,15WINFLOW SEDIMENT DISTRIBUTION",10WDENSITY CURRENT"
1)
GO TO 320
300 WRITE(6,6100)
6100 FORMAT(//p15X,"INFLOW SEDIMENT DISTRIBUTION",10WCOMPLETE MIXING"
1)
320 CONTINUE
WRITE( 5,6200)
6200 FORMAT(// , 15X , "MASS",7X."VISCOS",5X,"DELTAT",4X,"DELPLG",4X
1 "DENSTY" , 6X,"SG",8X,"SET",6X,"SHORT",6Xs"SLAG",6X,"DEAD")
WRITE(6,6300) MASS , VISCOS,DELTAT,DELPLG,DENSTY,SG,SET,SHORT,SLAG,
10E AD
6300 FORMAT(//,11X,F10.3,2X,F10.408F10.2)
WRITE(6,6400)
6400 FORMAT(//,45X,"***** DEPOSITS ERROR MESSAGES *****")
IF(VISCOS.LE.0.005) WRITE(6,6500)
IF(VISCOS.GE.0.2) WRITE( 6,6500)
IF(M .GT. 400) WRITE(6,6450)
6450 FORMAT(//.15X,"***** ERROR ***** • INFLOW ARRAY STORAGE EXCEEDED.
1")
6500 FORMAT(//,15X," ERROR ***** • USE DEFAULT VISCOS • 0.0114 CM.
1S0./SEC.")
IF(SG.LE.1.0) WRITE(6,6600)
IF(SG•GE.4.0) WRITE(6,6600)
IF(MS.GT•400) WRITE(6,6550)
6550 FORMAT(//,15X,"***** ERROR ***** • OUTFLOW ARRAY STORAGE EXCEEDED.
1")
6600 FORMAT(//p15X,"***** ERROR ***** • USE DEFAULT SG • 2.65 •")
IF(SG.LE.1.0) 5G-2.65
IF(SG•GE.4.0) SG-2.65
IF(VISCCS•LE.0.005) VISCOSm0.0114
IF(VISCOS.GE.0.2) VISCOS .0.0114
IF(N.GT•50) WRITE( 6,6550)
IF(M.GT•400) Mm399
IF(MS•GT•400) MS.399
IF(N.GT•50) Nm49
THE VALUE OF NS CANNOT EXCEED 10.
IF(NS.GT•10) NSm10
6650 FORMAT(//,15X," ERROR ***** • BASIN GEOMETRY ARRAY STORAGE
1 EXCEEDED.")
IF(STAGE(1).GT.0.001) WRITE (5,6700)
6700 FORMAT(//p15X,"***** ERROR ***** • ELEVATION VALUES CHANGED TO STA
1GE VALUES.")
DO 340 I•lsN
125
STAGE(I).STAGE(I)—STAGE(1)
340 CONTINUE
AVDEP(1).0.0
X1(1).0.0
X2(1).0.0
FLOWIN(1).INFLOW(1)
AVTME=0.0
CAPAC(1)80.0
CAPNW(1).0.0
AVDPTH(1)=0.0
DO 360 J.2,N
CAPAC(J) . (AREA(J)+AREA(.1-1))*(STA6E(J)-5TAGE(J-1))/2.04.CAPAC(J-1)
CAPNW(J).CAPAC(J)
IF(DISCH(J).E0.0.0) VAR-STAGE(J)
X 1 (J)=CAPAC(J)—(DISCH(J)/2.0)*DELTAT*.08264
X 2 (J).CAPAC(J)+(DISCH(J)/2.0)*DELTAT*.08264
CAPCO(J) . (AREAS(J)+AREAS(J-1))*(STG1(J)—STG1(J-1))/2.0+CAPCO(J-1)
360 CONTINUE
C
C
C
C
IF
NO
LS
IF
THE PERMANENT POOL IS TO BE FILLED INTERNALLY BY THE PROGRAM
DUMMY VALUES SHOULD BE ENTERED TO FILL THE PREMANENT POOL.
MUST BE ENTERED AS ZERO.
YOU USE THE WASH MODEL, M MUST ALSO BE SET TO ZERO.
DO 980 J.1,N
IF(DISCHB(J) • LE. 0.001) CAPOOL.CAPAC(J)
980 CONTINUE
AVSTG(1)=0.0
C SEDMNTs SEDEMENT CONCENTRATION FOR EACH TIME INCREMENT (VOLUMETRIC).
NFLNT(1)-0.0
CAP-0.0
SEDMNT(1).0.0
SEDTOT(1)=0.0
TOTVOL.0.0
CENTME.0.0
TOTAL-O.0
STORM.0.0
SEDOUT(1).0.0
VOLSED(1).0.0
ACINFL(1)=0.0
MM.M+1
DO 440 I.2,N
SUM1.0.0
SUM2.0.0
DO 380 J.2,I
IF(AREA(J).EQ.AREA(J —1)) GO TO 460
DEPO. STAGE (I)—(STAGE(J)+STAGE(J-1))/2.0
SUM1.DEPO**2.0*(AREA(J)—AREA(J-1))+SUM1
SUM2.0EP0*(AREA(J)—AREA(J-1))+SUM2
380 CONTINUE
IF(SUM2.LE.0.0) GO TO 400
AVDPTH(I).SUM1/SUM2
GO TO 420
400 AVOPTH(1).0.0
420 CONTINUE
440 CONTINUE
GO TO 540
460 DO 520 J.2,N
IF(CAPAC(J).LE.0.0) GO TO 480
AVDEP(J).(CAPAC(J-1)IAVDEP(J-1)+(CAPAC(J)—CAPAC(J-1))*(STAGE(J)+ST
1AGE(J-1))/2.0)/CAPAC(J)
AVDPTH(J).(STAGE(J)—AVDEP(J))*2.0
GO TO 500
480 AVDPTH(J).0.0
AVDEP(J)-0.0
126
500 CONTINUE
520 CONTINUE
540 CONTINUE
DO 560 S.MM,MS
INFLOW(I).0.0
560 CONTINUE
ACINFL(1)=CAPOOL
BPOOL.CAPOOL
VOLUME(1).CAPOOL
DO 580 1=2,MS
ACINFL I
ACINFL(I 1)+C(INFLOW(I-1)+INFLOW(1))/2.0)*OELTAT*.08264
VOLUME(I)=ACINFL(I)-ACINFL(I-1)
580 CONTINUE
STAREA(1).0.0
STP(1)=CAPOOL
STGAR(1).0.0
SUMTME.0.0
VOLTOT=0.0
STARTV(1)=CAPOOL
STAGEA(1).0.0
CAPACA(1)=0.0
DISCHA(1).0.0
T1(1).0.0
MR.(MS)/(DELPLG/DELTAT)+.01
PEAK-C. 0
DO 600 I=MM,MS
CONCED(I)=0.0
600 CONTINUE
IF(CONSED.GT.1.99.AND.CONSED.LE.2.01) MASS-0.0
DO 740 4=2.MS
IF(CONSED.GT.1.99.AND.CONSED.LE.2.01) GO TO 620
IF(SET .LT. 1.0) ST-Z.0
SEDMNT(J)*(VOLUME(J)**SET)
IF(LS.GE.J) SEDMNT(J)=0.0
IF(SLAG.GT.O.O.AND.SLAG.LT.1.01) 5EDMNT(J-1).SEDMNT(J)
IF(SLAG.GT.1.01.AND.J.GT.2) SEDMNT(J-2)=SEDMNT(J)
IF(J.EO.MS.AND.SLAG.GT.0.0) SEDMNT(J).0.0
IF(J.EO.MS.AND.SLAG.GT.0.0) SEDMNT(J-1)-0.0
GO TO 640
620 SEDMNT(J).(CONCED(J)+CONCED(J-1))*VOLUME(J)/(SG*2000.0)
MASS.MASS+0.001359*(CONCED(J)+CONCED(J-1))*VOLUME(J)/2.0
640 CONTINUE
IF(J.GT.LS) STORM • STORM + VOLUME(J)
SEDTOT(J)=SEDTOT(J-1)+5EDMNT(J)
IF(CONSED.GT.1.99.AND.CONSED.LE.2.01) GO TO 650
IF(SLAG.GT.O.O.AND.SLAG.LT.1.01) SEDTOT(J-1)=SEDTOT(J)
IF(SLAG.GT.1.01.4ND.J.GT.2) SEDTOT(J-2)=SEDTOT(J)
650
STP(J).STP(J-1)+VOLUME(J)
STPV(J-1)=STARTV(J-1)+VOLUME(J)
C DO AN ITERATION TO FIND STAGE FROM STPV
DO 660 K.2,N
IF(STPV(J-1).LT.X2(K))G0 TO 680
IF(STPV(J-1).GT.X2(N)) GO 10 3860
660 CONTINUE
680 STAGEA(J).STAGE(K-1)+((STPV(J-1)-X2(K-1))/(X2(K)-X2(K-1)))*(STAGE(
1K)-STAGE(K-1))
AVSTG(J)=AVOPTH(K-1)+USTPV(J-1)-X2(K-1))/(X2(K)-X2(K-1)))*(AVDPTH
1(K)-AVDPTH(K-1))
CONTINUE
DO 700 KK.2,N
IFISTAGEACJI.LT.STAGE(KK)) GO 10 720
IF(STAGEA(J-1).GT.STAGE(N) ) GO 10 3860
700 CONTINUE
(
).
-
127
720 CAPACA(J).X1(KK-1)+((STAGEA(J)—STAGE(KK--1))/(STAGE(KK)...STAGE(KK-1)
1))*(X1(KK)-•X1(KK-1))
C DO AN ITERATION TO FIND DISCHARGE FOR STAGEA
DISCHA ( .1). DISCH(KK - 1)+USTAGEA(J)—STAGE(KK-1))/(STAGE(KK)—STAGE(KK
1 - 1)))*(DISCH(KK)—DISCHMK--1))
IF(DISCHA(J).GT.PEAK)PEAK.DISCHA(J)
CONTINUE
STARTV(J).CAPACA(J)
IF(STARTV(J).LT.0.0) STARTV(J).0.0
1 1( 4 ).(J..-1)*0ELTAT
IF(J.GT.LS) SUMTME.SUMTME+(4-1.-LS)*DELTATSVOLUME(J)
1F(J.GT.LS) VOLTOT.VOLTOT+VOLUME(J)
STAREA(J) . ABSUAVSTG(J)+AVSTG(J-1))*(DELTAT/2.0))
STGAR(4).STAREA(J)+STGAR(J-1)
C THIS PART OF THE PROGRAM DIVIDES THE OUTLET HYDROGRAPH INTO PLUGS OF EQUAL
C TIME INCREMENT DELPLG. THE PLUG IS THEN ROUTED THROUGH THE RESERVOIR AND
C THE DETENTION TIME,STAGE AT OUTFLOW, AVERAGE DEPTH AND THE VOLUME OF
C THE PLUG IS DETERMINED.
740 CONTINUE
PFLNT.0.0
IF(CONSED.GT.1.99.AND.CONSED.LE.2.01) GO TO 860
C PFLNT WILL BE THE PEAK INFLOW CONC_
DO 820 JS.2sM
IF(VOLUME(JS).E0.0.0) GO TO 780
NFLNT(JS).(SEDMNT(JS)*1.*MASS*735.48)/(VOLUME (4 S)*SEOTOT(M))
IF(NFLNT(JS).GT.PFINT) GO TO 760
GO TO 800
760 PFLNT.NFLNT(JS)
GO TO 800
780 NFLNT(JS).0.0
800 CONTINUE
820 CONTINUE
14.0
DO 840 IK.2,M
IF(NFLNT(IK).E0.0.0) GO TO 840
IJ.IJ+1
SFLNT(IJ).NFLNT(IK)
840 CONTINUE
GO TO 900
860 DO 880 J 5 .1,M
NFLNT(JS)=CONCED(JS)
IF(NFLNT(JS).GT.PFLNT)PFLNT.NFLNT(JS)
880 CONTINUE
900 CONTINUE
DO 920 J.J.MM,MS
NFLNT(44).0.0
920 CONTINUE
DO 940 1.1,4
SED(I,J).0.0
DIAMTRUI,J).0.0
VELOC(I,4).0.0
FALL(I,J).0.0
VOL(I,J)=0.0
PCT(I,J).0.0
VOLC(I,J).0.0
940 CONTINUE
SEDPLG(1).0.0
SUMVOL.0.0
STRMOT=0.0
SEDEND(1).0.0
DEPTH(1).0.0
ACOUT(1) . 0.0
128
PLGVOL(1).0.0
PLGTME(1).0.0
VOLOUT(1).0.0
VOLIN(1).DEAD
TMEIN(1).0.0
SEDT(1).0.0
DETTME(1)=0.0
PLGCEN(1).0.0
VOLTME(1)=0.0
AREAA(1).0.0
AREAB(1).0.0
AREAC(1).0.0
AREAD(1).0.0
VOLA(1).0.0
VOLB(1).0.0
VOLE(1).0.0
VOLD(1).0.0
DEPTH(1)80.0
DEPTH2(1)=0.0
DEPTH3(1).0.0
DO 960 Lm2,MS
ACOUT(L).ACOUT(L 1)+((DISCHA(L-1)+DISCHA(L))/2.0)*DELTAT*.08264
-
960 CONTINUE
PSTAGO.0.0
PEFLNT-0.0
C PEFLNT WILL BE THE PEAK EFFLUENT CONC.
C PSTAGO WILL BE THE PEAK STAGE
DEL.0.0
DO 2420 NN.21MR
PLGTME(NN).PLGTME(NN -1) + DELPLG
LR.(DELPLG+.01)/DELTAT
P.LR*(NN -1)+1
PLGVOL(NN).ACOUT(P)-ACOUT(P-LR)
VOLIN(NN).VOLIN(NN-1)+PLGVOL(NN)*SHORT
IF(VOLIN(NN).GT.CAPOOL.AND.VGLIN(NN-1).LT.CAPOOL) T.PLGTMENN)
IF(T.GT.DEL) TwDEL
IF(SHORT.LE.1.000)SHORT.1.0
PLGCEN(NN) • (PLGTME(NN) + PLGTME(NN-1)1/2.0
C DO AN ITERATION TO FIND TMEIN FROM VOLIN
DO 1000 NP.2..M
IF(VOLIN(NN) .LT. STP(NP) .AND. VOLIN(NN) .LE. STP(NP-1)) GO TO 10
125
IF(VOLIN(NN).LT.STP(NP)) GO 10 1020
1000 CONTINUE
GO TO 1025
1020 TMEIN(NN)=T1(NP-1)+((VOLIN(NN)-STP(NP- 1) )/(STP(NP)-STP(NP-1)))*DEL
1TAT
GO TO 1035
1025 TMEIN(NN)-0.0
1035 CONTINUE
FLOWIN(NN)=INFLOW(NP)
IF(FLOWAV.GT.0.0) GO TO 1040
GO TO 1120
1040 DO 1060 I•1,NS
IF(FLOWIN(NN).E0.0.0.AND.FLOWIN(NN-1).EC.0.0) GO TO 1080
SIZEST(I,NN).(2.*FLOWAV/(FLOWIN(NN)+FLOWIN(NN-1)))**.3*PERCNT(I)
IF(SIZEST(1,NN).GT.100.) SIZEST(IpNN)=100.
1060 CONTINUE
GO TO 1100
1080 SIZEST(I,NN).PERCNT(I)
1100 CONTINUE
1120 CONTINUE
VOLTME(NN)m(TMEIN(NN)+TMEIN(NN-I))/2.0
129
DETTME(NN).PLGCEN(NN)-VOLTME(NN)
IF(DETTME(MN).LT.0.0) DETTME(NN).0.0
SEDTINN) . SEDTOT(NP - 1)+((VOLIN(NN)-STP(NP-1))/(STP(NP)-STP(NP-1)))
1*(5EDTOT(NP)-SEDTOT(NP-1))
IF((VOLIN(NN)-STP(NP -1)) .LT. 0.0) SEDTINN)80.0
SEDOUT(NN).(SEDT(NN)-SEDT(NN-1))/SEDTOT(M)
STGIN(1).0.0
STGOUT(1).0.0
STAGO(1).10.0
DO 1140 II.2,MS
IF(VOLTME(NN).I.T.T1(II)) GO 10 1160
IF(VOLTME(NN).GE.T1(MS)) GO TO 2080
C DO AN ITERATION TO FIND DEPTH FOR VOLTME
1140 CONTINUE
1160 STGIN(NN).STGAR(II-1) 4. A8S(UVOLTMENN)-T1(II-1))/(71(II)-T1(II-1))
1)*(STGAR(II)-STGAR4II-1)))
CONTINUE
DO 1180 II.2,MS
IF(PLGCEN(NN).LT.T1(II)) GO TO 1200
C DO AN ITERATION TO FIND DEPTH FOR PLGTME
1180 CONTINUE
1200 STGOUT(NN).STGAR(II-1)+((PLGCEN(NN)-T1(II-1))/(71(II)-71(II-1)))*(
1STGAR(II)-STGAR(II-1))
STAGO(NN).STAGEACII-1)+((PLGCEN(NN)-71(II-1))/(71(II)-T1(II-1)))*(
1STAGEA(II)-STAGEA(II-1))
IF(DETTME(NN).LE.0.0) DETTME(NN).0.0
IF(STAGO(NN).GT.PSTAGO) GO TO 1220
GO TO 1240
1220 PSTAGO.STAGO(NN)
1240 IF(DETTME(NN).E0.0.0) GO TO 2120
DEPTH(NN).(STGOUT(NN)-STGIN(NN))/DETTME(NN)
If(DEPTH(NN).LE.0.0) DEPTH(NN)=0.0
DEPTH1(NN)*0.75*DEPTH(NN)
DEPTH2(NN)=0.5*DEPTH(NN)
DEPTH3(NN)=0.25*DEPTH(NN)
DO 1260 LM=2,N
IF(DEPTH(NN).LT.STAGE(0)) GO 10 1280
1260 CONTINUE
1280 VOLA(NN). CAPAC(LM-1)+((DEPTH(NN)-STAGE(LM- 1))/(STAGE(LM)-STAGE(LM
1-1)))*(CAPAC(LM)-CAPAC(LM -1))
AREAA(NN)=AREA(LM-1)+((DEPTH(NN)-STAGE(LM-1))/(STAGE(LM)-STAGE(LM 11)))*(AREA(LM)-AREA(LM-1))
CONTINUE
C CAPSAV WILL COMPUTE THE CAPACITY AT PEAK STAGE
DO 1300 I.1.2,N
IF(PSTAGO.LE.STG1(IJ)) GO TO 1320
1300 CONTINUE
GO TO 1340
1320 CAPSAV.CAPAC(IJ-1)+ ((PSTAGO-STG1(IJ-1))/(STG1(IJ)-STG1(IJ-1)))
1*(CAPAC(IJ)-CAPACCIJ-1))
1340 DO 1360 LM=2,N
IFIDEPTH1(NN).LT.STAGE(LM)) GO 10 1380
1360 CONTINUE
CONTINUE
1380 VOLUNN)=CAPAC(LM-1)+C(DEPTH1(NN)-ST4GE(0-1))/(STAGE(LM)-STAGE(LM
1-1)))*(CAPACUM)-CAPAC (LM-1)/
AREAB(NN)RAREAUM-1)+C(DEPTH1(NN)-STAGE(LM-1)1/(STAGE(LM)-STAGE(LM
1-1)))*(AREA(LM)-AREA(LM-1),
CONTINUE
DO 1400 LM=2,N
IF(DEPTH2(NN).LT.STAGE(LM)) GO TO 1420
1400 CONTINUE
1420 VOLE(NN). CAPAC(LM-1)+((DEPTH2(NN)-STAGE(LM-1,)/(STAGE(LM)-STAGE(1.
130
1M - 1)))*(CAPAC(LM)—CAPACUM —1))
AR E AC(NN)*AR EA ( LM -1) + ( lDEPTH 2 (NN) — STAGE(LA-1))/(STAGE(LM)—STAGEILM
1 - 13))*(AREA(01)4.AREA(M-1))
CONTINUE
DO 1440 LM=2,N
IF(DEPTH3(NN).LT.STAGE(LM)) GO TO 1460
1440 CONTINUE
1460 VOLD(NN)* CAPAC(LM-1)+((DEPTH3(NN)—STAGE(LR-1))/(STAGEUM)—STAGEIL
1M - 1)))*(CAPAC(LM)—CAPACILM-1))
AREAD ( NN )= AREA(LM -1 )+C(DEPTH3(NN)—STAGE(LM-1))/(STAGE(LM)—STAGE(LM
1 .41)))*(AREAILM).4AREA(01-1))
CONTINUE
VOL(1,NN).VOLA ( NN)—VOL8(NN)
VOL(2 , NN).VOLB(NN)—VOLE(NN)
VOL(3,NN).VOLE(NN)—VOLD(NN)
VOL(4,NN).VOLD(NN).
FALL(1,NN).0.875*DEPTH(NN)*FIX
fALL(2,NN)=0.625*DEPTHINN)*FIX
FALL(3,NN).0.375*DEPTH(NN)*FIX
FALL(4,NN).0.125*DEPTH(NN)*FIX
IF(PLGVOL(NN).1T..00001) GO TO 2080
VELOC(1,NN).FALL(1,NN)/(DETTME(NN))
VELOC(2,NN)-FALL(2)NN)/(DETTME(NN))
VELOC(3,NN).FALL(3,NN)/IDETTMECNN))
VELOC(4,NN)=FALL(4,NN)/(DETTME(NN))
DIAMTR(1 , NN).30RT(VELOC(1,NN)*VISCOS/(51.5*(SG-1)))
DIAMTR(2 , NN).SORTIVELOC(2,NN)*VISCOS/(51.5*(SG-1)))
DIAMTR(3 , NN)=SORTCVELOC(3,NN)*VISCOS/(51.5*(SG-1)))
DIAMTR( 4, NN)=SORT(VELOC(4,NN)*VISCOS/(51.5*(SG-1)))
CONTINUE
IF(FLOWAV.GT.0.0) GO TO 1640
DO 1480 LP.2,NS
IF(DIAMTR(1,NN).L.T.SIZE(LP)) GO TO 1500
1480 CONTINUE
1500 PERCT(1 , NN).PERCNTUP - 1)+( (DIAMTR(1,NN)—SI2E(LP-1))/(SIZE(LP)—SIZE
1(LP —1)))*(PERCNT ( LP)—PERCNT(LP —1))
DO 1520 LP*2,NS
IF(DIAMTR(2/NN).LT.SI2E(LP)) GO TO 1540
1520 CONTINUE
1540 PERCT(2,NN)=PERCNT(LP-..1)+((DIAMTR(2,NN)—SIZE(LP-1))/(SI2E(LP)—SIZE
1(LP*1))).0(PERCNTUP) —PERCNT(LP —1))
DO 1560 LPs2,NS
IF(DIAMTR(3pNN).LT.SIZE(LP)) GO TO 1580
1560 CONTINUE
1580 PERCT(3,NN).PERCNT(0-1)+I(DIAMTR(3,NN)—SIZE(LP-1)3/(5IZEILP)—SIZE
1(LP-1)))*(PERCNT(LP)—PERCNT(0-1))
DO 1600 LP.2,NS
IF(DIAMTR(4,NN).I.T.SIZE(LP)) GO TO 1620
1600 CONTINUE
1620 PERCT(4,NN)=PERCNT(LP-1)+((DIAMTR(4,NN)—SIZE(LP-1))/(SIZE(LP)—SI2E
l(LP-1)))*(PERCNT(LPC—PERCNT(LP-1)/
GO TO 1820
1640 DO 1660 LP.2/N5
IF(DIAMTR(1,NN).LT.SIZE(LP)) GO TO 1680
1660 CONTINUE
1680 PERCT(1,NN).SIZEST(LP-1,NN) .0(IDIAMTR(1,NN)—SIZE(LP-1))/(SIZE(LP)
1— SIZE( LP-1)))*(SIZEST(LP,NN)—SIZEST(LP-1,NN))
DO 1700 LP.2,NS
IftDIAMTR(2,NN).I.T.SIZE(LP)) GO TO 1720
1700 CONTINUE
1720 PERCT(2,NN).SI2EST(LP-1,NN) +((DIAMTR(2,NN)—SIZE(LP-1))/(SIZE(0)
1 —SIZE( 0-1 )))*(SIZEST(LP,NN)—SIZEST(LP-1,NN))
00 1740 LP=2,NS
131
IF(DIAMTR(3,NN).LT.SIZE(LP)) GO TO 1760
1740 CONTINUE
1760 PERCT(3,NN).SIZEST(LP-1,NN) +((DIAMTR(3,NN)—SIZE(LP1))/(SIZE(LP)
1— SIZE( LP• 1 )))*(SIZEST(LP,NN)—SIZEST(LP-....1,NN))
DO 1780 LF*2,NS
IF(DIAMTR(41,NN).LT.SI7E(LP)) GO TO 1800
1780 CONTINUE
1800 PERCT( 4, NN).SIIEST(LP1,NN) +((DIA)TR(4 , NN)SIZE(LP-1))/(SIIE(LP)
1 SIZE(LP1)))*(SIZEST(LP,NN)-4SIZEST(LP1,NN))
1820 CONTINUE
VOLC( 1, NN).V0L(1 , NN)*(2.0*AREAB(NN)/(AREAA(NN)+4REA8(NN)))
VOLC( 2, NN) . V01(2 , NN)*(AREAC(NN)*2.0/(AREAC(NN)+AREA8(NN)))
VOLC(3 , NN).VOL(3,NN)*(2.0*AREAD(NN)/(AREAC(NN)+AREAD(NN)))
IF(VOL(2,NN).LE.0.0) GO TO 2080
IF(FR#CTN.GT.0.0j) GO TO 2000
PCT(1,NN) .PERCT(4,NN)
0IFF(NN).(STAGO(NN)...-VAR)4.2.0
IF(DIFF(NN).GT.0.0.AND.DIFF(NN).LT..125*DEPTH(NN)) GO TO 1840
GO TO 1980
1840 DIAMTR(5 , NN)*SORT(DIFF(NN)*VISCOS/(51.5*(SG-1)*DETTME(NN)))
IF(FLOWAV.GT.0.0) GO TO 1900
DO 1860 LP=2,NS
IF(DIAMTR(5,NN).LT.SIZE(LP)) GO TO 1880
1860 CONTINUE
1880 PERCT(5,NN).PERCNT(Lp1)+((OIAPjTR(5,NN)—SIZE(1.1 1-.- 1) )/(SIZE(LP)SIZE
l(LP ..1)))*(PERCNT(LP)PERCNT(LP —1))
GO TO 1960
1900 DO 1920 LP.2,NS
IF(DIAMTR(5,NN).LT.SIZE(LP)) GO TO 1940
1920 CONTINUE
1940 PERCT(5,NN)=SIZEST(LP-.-1,NN) +((DIAMTR(5,NN)—SIIE(LP-1))/(SIZE(LP)
1 —SIZE(LP1)))*(SIZEST(LPoNN)—SIZEST(LP...1,NN))
1960 CONTINUE
IF(DIFF(NN).1.7.0.125*DEPTH(NN))PCT(1,NN).PERCT(5,NN)
1980 CONTINUE
IF(PERCT(1,NN).I.T.O.0)PERCT(1,NN).0.0
IF(PERCT(2,NN).LT.0.0)PERCT(2,NN).0.0
IF(PERCT(3,NN).L7.0.0)PERCT(3,NN).0.0
IF(PERCT(4,NN).LT.0.0)PERCT(4,NN).0.0
IF(PERCT(1,NN).GT.100.)PERCT(1,NN).100.
IF(PERCT(2,NN).GT.100.)PERCT(2,NN)=100.
IF(PERCT(3,NN).GT.100.)PERCT(3,NN).100.
IF(PERCT(4,NN).GT.100.)PERCT(4,NN).100.
PCT(2,NN).(VOL(2,NN)*PERCT(4,NN)+VOLC(1,NN)*(PERCT(3,NN)..-PERCT(4,N
1N)))/VOL(2,NN)
PCT(3,NN).(VOL(3,NN)*PERCT(4,NN)+VOLC(2,NN)*(PERCT(2,NN)—PERCT(4,N
1N)))/VOL(3,NN)
PCT(4,NN).(VOL(4,NN)*PERCT(4,NN)+VOLC(3,NN)*(PERCT(1,NN)—PERCT(4,N
1N)))/VOL(4,NN)
GO TO 2020
2000 PCT(1,NN)•0.0
PCT(2,NN)80.0
PCT(3,NN).0.0
PCT(4,NN).PERCT(4,NN)
2020 CONTINUE
DO 2040 LM-2,N
IF(STAGO(NN).LT.DPTH(LM)) GO TO 2060
2040 CONTINUE
2060 SED(1,NN).PCT(1/NN)*SE0OUT(NN)*(OUTFL1(LM-1)+((STAGO(NN)—OPTH( L M-1
1))/(OPTH(LM) OPTH(LM-11))*(OUTFL1(LM)—OUTFL1(01-1 ) ))
SED(2,NN)=PCT(2,NN)SEEDOUT(NN)*(OUTFL2(LM-1)+(ISTAGO(NN)—DPTH(LM-1
1))/(DFTH(LM) — OPTH(LM .-1)))*(OUTFL2(LM)-0UTFL2(04-1)))
SED(3 , NN).PCT(3JINN)*SEDOUT(NN)*(0UTFL3(LM..-1)+((STAGO(NN).-..DPTH(L-1
—
132
1))/(DPTH(LM) DPTH(LM ...1)))*(OUTFL3(LM)OUTFL3(01-+1)))
SED(4,NN)*PCT(4,NN)*SEDOUT(NN)*(OUTFL4(LM-1)+((STAGO(NN) —DPTH(LM-1
1))/(OPTH(LM) OPTH(LM-1)))*(OUTFL4(LM)—OUTFL4(LM-1)))
SEDPLG(NN )•(SED(1,NN)+SED(2,NN)+SED( 3,NN )+SED(4oNN) ) /100.0
IF(SEDPLG(NNI.GT.SEDOUT(NN)*100.)SEDPLG(NN).100.4.SEDOUT(NN)
GO TO 2100
2080 SEDPLG(NN).0.0
PCT(1,NN).0.0
PCT(2,NN)=0.0
PCT(3,NN).0.0
PCT(4,NN).0.0
2100 CONTINUE
GO TO 2140
2120 SEDPLG(NN).100.0*SEDOUT(NN)
PCT(1,NN).100.0
PCT(2yNN).100.0
PCT(3,NN).100.0
PCT(4,NN)*100.0
IF(DEPTH(NN).LE.0.0) DEPTH(NN).0.0
2140 CONTINUE
SEDEND(NN).SEDEND(NN-1)+SEDPLG(NN)
DO 2200 L5=1,NS
IF(FLOWAV.LE.0.0) SIZEST(LS,NN).PERCNT(LS)
PCTOUT(L.S,1).0.0
IF(SEDPLG(NN).LE.0.0) GO TO 2160
SUOUT(LSAN).100.*SEDOUT(NN)*SIIEST(LS,NN)/SEDPLG(NN)
IF(SIZOUT(LS,NN).LE.0.0)SIZOUT(LS,NN).0.0
GO TO 2180
2160 SIZOUTILS,NN)=SIZEST(LSPNN)
SEDPLG(NN).0.0
2180 CONTINUE
IF(SIZOUT(LS,NN).GT.100.),SIZOUTILS,NN).100.
PCTOUT(LS,NN)=PCTOUT(LS,NN-1)+SEDPLG(NN)+SIZOUT(LS,NN)
2200 CONTINUE
VOLOUT(NN)=SEDOUT(NN)+VOLOUT(NN-1)
ACT.1.001*(STRMOT+CAPOOL—DEAD)
IF(ACT •GT. STORM) GO TO 3440
IF(PLGVOL(NN).E0.0.0) GO TO 2240
EFLNT(NN)u(SEDPLG(NN)/PLGVOL(NN))*MASS*7.3548
IF(EFLNT(NN).GT.PEFINT) GO TO 2220
GO TO 2260
2220 PEFLNT.EFLNTINN)
GO TO 2260
2240 EFLNT(NN).0.0
2260 CONTINUE
IF(PLGTMEINN) •GT. DEL) TOTAL.TOTAL+PLGCEN(NN)*PLGVOL(NN)
IF(PLGTME(NN).GT.DEL) TOTVOL • TOTVOL +PLGVOL(NN)
IF(TOTVOL.GT.0.0) CENTME.TOTAL/TOTVOL—SUMTME/VOLTOT
IF(VOLIN(NN) .GT. 8POOL) AVTME.AVTME+(DETTME(NN))*PLGVOL(NN)
IF(VOLIN(NN).GT.E(POOL) SUMVOL.SUMVOL+PLGVOL(NN)
IF(SUMVOL.GT.0.0) DETAVE+AVTME/SUMVOL
IF(VOLIN(NN).GT.BPOOL) STRMOT.STRMOT+PLGVOL(NN)
IF(CENTME.LE.0.0) CENTME.DETAVE
STRMTM.(CENTME*STRMOT+(DETTME(NN-1)*(STORM—STRMOT)))/STORM
AVETMEs(DETAVE*STRMOT+DETTME(NN-1)*(STORM STRMOT))/STORM
IF(STRMOT.GT.STORM/AVETME.DETAVE
IF(STRMOT.GT.STORM) STRMOT-STORM
IF(DEPOST.LT.1.99) GO 10 2420
DEP(1,NN)=MASS+0.0007360*(100.0—PCT(1,NN))*SEDCUT(NN)*(CUTFL1(LM 1
1)+( CSTAGOINNi—OPTHUM-1))/(OPTH(LM)—DPTH(LM-1)))*(OUTFL1(01) OUTFL
11(LM-1)))1(10U00.0*DENSTY)
DEP(2,NN).MASS*0.0007360*(100.0—PCT(2,NN))*SEDOUT(NN)*(OUTFL2(LM 1
1)+USTAGO(NN)—DPTH(LM-1))/(DPTH(LM)—OPTH(LM-1)))*(OUTFL2(LM)—OUTFL
—
.
—
—
-
—
-
133
1) +I(STAGO ( NN) - DPTH(LM- 1))/(DPTH(LM) - DPTH(L(j-1)))*(OUTFL3(LM)-OUTFL
13(LM-1)))/(10000.0*DENSTY)
DEP (4, NN ) =MASS* 0 . 0007360 *(100.0- PCT(4,NN))*SEDOUT(NN)*(OUTFL4(LK-1
1) +USTAGO(NN) - DPTH(LM - 1))/(DPTH(LM)DPTH(LM-1)))*(OUTFL4(LM)-OUTFL
14(LM-1)))/(10000.0*DENSTY)
C THIS PART OF THE PROGRAM DETERMINES THE CHANGE IN BASIN CAPACITY
C DUE TO DEPOSITION.
DO 2400 I=1,N
1F(AVDPTH(I).LT.DEPTH3(NN)) GO TO 2320
IF(AVDPTH(I).LT.DEPTH2(NN)) GO TO 2340
IF(AVOPTH(I).LT.DEPTH1(NN)) GO TO 2360
IF(AVDPTH(I).L.T.DEPTH (NN)) GO TO 2380
CAPNW(I)=CAPNW(I)-(DEP(4,NN)+DEP(3,NN)+DEP(2,NN)+DEP(1,NN))
GO TO 2400
2320 CAPNW(I)=CAPNW(I)-DEP(4,NN)*AVDPTH(I)/DEPTH3(NN)
GO TO 2400
2340 CAPNW(I)=CAPNW(I)-(DEP(4,NN)+DEP(3,NN)*(AVDPTH(I)-DEPTH3(NN))/DEPT
1H2(NN))
GO TO 2400
2360 CAPNW(I)=CAPNW(I)-(DEP(4,NN)+DEP(3,NN)+DEP(2,NN)..(DEP(2,NN)*(AVOPT
1H(I)-DEPTH2(NN))/DEPTH1(NN)))
GO TO 2400
2380 CAPNW(I)=CAPNW(I)-(DEP(4,NN)+DEP(3.NN)+DEP(2.NN)..(DEP(1.NN)*(AVOPT
1H(I)-DEPTH1(NN))/DEPTH(NN)))
2400 CONTINUE .
2420 CONTINUE
3440 NE=NN-1
DO 3500 I=1.NS
IF(NN.LT.MR) GO TO 3460
IF(SEDEND(MR).LE.0.0) GO TO 3460
OUTPCT(I)=PCTOUT(I,MR)/SEDEND(MR)
GO TO 3480
3460 IF(SEDEND(NN).LE.0.0) OUTPCT(I)=0.0
IF(SEDEND(MR).LE.0.0) OUTPCT(I)=0.0
IF(SEDEND(NN).GT.0.0) OUTPCT(I)=PCTOUT(I,NN)/SEDEND(NN)
3480 CONTINUE
3500 CONTINUE
TRAP.(100.0-SEDENDINN-1))
SEDAV2=(SEOEND(NN-1)/(STRMOT+BPOOL-DEAD))*MASS*7.358
IF(STRMOT.GT.0.0) SEDAVE=SEDEND(NN-1)*MASS*7.358/STRMOT
IF(STRMOT.LE.0.0) SEDAVE=0.0
WRITE (6,6900)
6900 FORMAT(1H1)
WRITE (6,7000)
7000 FORMAT(45X,"***** STORM EVENT SUMMARY *****")
WRITE(67100) CAPOC).
7100 FORMAT(//,15X."PERMANENT POOL CAPACITY",18X,"=",F10.2,5X,"ACRE -FT"
1)
WRITE(6,7200) DEAD
7200 FORMAT(//,15X,"DEAD STORAGE".29X."=",F10.2,5X,"ACRE-FT")
WRITE(6,7300) STORM
7300 FORMAT(//,15X,"STORM RUNOFF VOLUME".22X,"8",F10.2,5WACRE-FT")
WRITE(6,7400) STRMOT
7400 FORMAT(//.15X,"STORM VOLUME DISCHARGED ".17X."=".F10.2,5WACRE-FT
1")
WRITE(6.7500) CAPSAV
7500 FORMAT(//,15X,"POND VOLUME AT PEAK STAGE".16X,"=",F10.2,5X,"ACRE-F
IT")
WRITE(6,7800) PSTAGO
WRITE(6,7600) PEAKIN
INFLOW RATE",25X."="pF10.2.5X,"CFS")
WRITE(6,7700) PEAK
7700 FORMAT(//,15X,"PEAK DISCHARGE RATE"..22X."="5, F10.2,5X."CFS")
7600 FORMAT(//,15X,"PEAK
134
7800 FORMAT(//,15X,"PEAK STAGE",31X,".",F10.2,5X,"FT")
WRITE(6,7900) PFLNT
7900 FORMAT(//015X,"PEAK INFLOW SEDIMENT CONCENTRATION",7X,"•",F10.1,5X
1,"MG/L")
WRITE(6,8000) PEFLNT
8000 F0RMAT(//,15X,"PEAK EFFLUENT SEDIMENT CONCENTRATION",5X,".",F10.1,
15X,"MG/L")
WRITE(6,8050) SEDAVE
8050 FORMAT(//,15X,"STORM AVERAGE EFFLUENT CONCENTRATION", 5X,".",
1F10.1,5WMG/L")
WRITE(6,8100) SEDAV2
8100 FORMAT(//,)_5X,"AVERAGE EFFLUENT SEDIMENT CONCENTRATION",2X,".",
1F10.1,5X,"MG/L")
WRITE(6,8200) TRAP
8200 FORMAT(//,15X,"BASIN TRAP EFFICIENCY",20X,".",F10.2,5X," ")
WRITE(6,8300) AVETME
8300 FORMAT(//,15X,"DETENTION TIME OF FLOW WITH SEDIMENT",5X,".",F10.2,
15X,"HRS")
WRITE(6,8400)CENTME
8400 FORMAT(//,15X,"DETENTION TIME FROM HYDROGRAPH CENTERS",3X,".",F10.
12,5X,"NRS")
WRITE(6,8450) STRMTM
8450 FORMAT(//,15X,"DETENTION TIME INCLUDING STORED FLOW",5X,".",F10.2,
15X, "MRS")
WRITE(6,8500) MASS
8500 FORMAT(//,15X,"SEDIMENT LOAD",28X,".",F10.215X,"TONS")
WRITE (6,9200)
IF(FLOWAV.EQ.0.0) GO TO 3540
WRITE(6,8600) FLOWAV
8600 FORMAT(//,15X," PARTICLE SIZE DISTRIBUTION AT INFLOW RATE
1 •",F10.2,2X,"CFS *****")
WRITE(6,8700)(SIZE(I),Ia1,NS)
8700 FORMAT(///,15X,"SIZE (MM)", 10F8.4)
WRITE(6,8800)(PERCNT(I),I=1,NS)
8800 FORMAT(/ ,15X," FINER",1X,10F8.1)
DO 3520 I.1,NS
SIZES(I).(FLOWAV/PEAKIN)**.3*PERCNT(I)
IF(SIZES(I).GT.100.) SIZES( 1)-100.
3520 CONTINUE
WRITE(6,8900) PEAKIN
8900 FORMAT(//,15X," ***** PARTICLE SIZE DISTRIBUTION AT INFLOW RATE
1 .",F10.2,2X,"CFS *****")
WRITE(6,8700)(SIZE(I),I.1,NS)
WRITE(6,8800) (SIZES(I),I.1,NS)
GO TO 3560
3540 WRITE(6,9000)
9000 FORMAT(//p15X,"***** PARTICLE SIZE DISTRIBUTION OF SEDIMENT INFLOW
1 WRITE(6,8700)(SIIE(I),I.1,NS)
WRITE(6,8800)(PERCNT(I),I.1,NS)
3560 CONTINUE
WRITE (6,9100)
9100 FORMAT(//,15X," ***** PARTICLE SIZE DISTRIBUTION OF EFFLUENT 1")
WRITE(6,8700)(SIZE(I),I.1,NS)
WRITE(6,8800)(OUTPCT(I),I.1,NS)
9200 FORMAT(1H1)
WRITE (6,9300)
le)
9300 FORMAT(//,32X,"***** OUTFLOW WITHDRAWAL DISTRIBUTION WRITE(6,9400)
9400 FORMAT( ///,15X, "STAGE",10X, "OUTFLOW 1", 10X, "OUTFLCW 2", 10X, "OUTFLO
1W 3",10X,"OUTFLOW 4")
WRITE (6,9500)
135
9500 FORMAT(/,16X,"(FT)",13X,"( )",16X,"( )",16x,"( )",16x,"( )•)
DO 3580 IR=1,MD
WRITE(6,9600) DPTH(IR),OUTFL1(IR),OUTFL2(IR),OUTFL3(IR),OUTFL4(IR)
9600 FORMAT( 10X,F10.2,7X,F10.2,9X,F10.2,9X,F10.2,9X,F10.2)
3580 CONTINUE
WRITE(6,9700)
9700 FORMAT(1H1)
WRITE (6,9800)
9800 FORMAT(//y42X," BASIN GEOMETRY *****")
IF ( DEPOST.GT.1.99.AND.MASS.GT.0.01) GO TO 3640
IF(MASS.GT.0.0) GO TO 3720
WRITE (6,9900)
9900 FORMAT ( //// , 15X,STAGE",10X,"AREA",7X,"AVERAGE DEPTH",5X,"DISCHARG
lE",7X,"CAPACITY")
WRITE (6,10000)
10000 FORMAT(/#16X,"(FT)",9X,"(ACRES)",10X,"(FT)",10X,"(CFS)",9X,"(ACRES
1—FT)")
DO 3600 IL•1,N
W R ITE (6,10100) STG 1( IL) , AREAS(IL),AVDPTH(IL),DISCHB(IL),CAPAC(IL)
10100 FORMAT(/ ,10X,F10.4, 5 X , F1 0 .2,5X,F10.2,5X,F10.2,5X,F11.4,5X)
3600 CONTINUE
WRITE (6,10200)
10200 FORMAT(1H1)
WRITE(6,10300)
WRITE(6,10400)
10300 FORMAT(//p45X,"***** STORM HYDROGRAPHS E SEDIMENTGRAPHS to)
10400 FORMAT ( ////s 8 X , "7/ME" , 8WINFLOW",7X,"DISCHARGE",6WDETENTION TIM
E"
,
3X , "STAGE",8X,•DEPTH",8X,"SEDIMENT")
1
WRITE(6,10500)
10500 FORMAT(/,8X,"(HRS)",8X,"(CFS)",9X,"(CFS)",11X,"(HRS)",9X,(FT)",9X
1,"(FT)",11X,"( )")
DO 3620 LL=2,NE
JM=(DELPLG/DELTAT)*(LL-1)+1.0
WRITE (6,10600 )PLGTME(LL),INFLOW(JM),OISCHAUM),DETTME(LL),STAGO(LL
1),DEPTH(LL),SEDEND(LL)
10600 FORMAT ( /y 5 X , F 7 .2 , 6X,F7.2,8X,F7.2s8X,F7.2,7X,F7.2,7X,F7.2,7X,F7.2)
3620 CONTINUE
GO TO 37C0
3640 WRITE(6,10700)
10700 FORMAT(//,6X, "STAGE", 9X,"DEPTH",6X,"DESIGN AREA",5X,"NEW AREA",
15WAVERAGE DEPTH",5X,"DISCHARGE",3X,"DESIGN CAPACITY",3X,"NEW CAP
2ACITY")
WRITE (6,10800)
10800 FORMAT(/, 6X , "(FT)" , 11X , "(FT)",9X,"(ACRES)",8X,"(ACRES)",10X,"(FT)
1",11X,"(CFS)",7X,"(ACRE—FT)", 7X,"(ACRE—FT)")
DO 3660 IL=1,N
WRITE(6,10900) STG1(IL),STAGE(IL),AREAS(IL),AREA(IL),AVDPTH(IL),DI
1SCH(IL),CAPCO(IL),CAPACCIL)
10900 FORMAT(
F10.2,5X,F10.2,5X,F10.2,5X,F10.205X,F10.2,5X,F10.2,5
1X,F10.2,5X,F10.2)
3660 CONTINUE
WRITE (6,11000)
11000 FORMAT(1H1)
WRITE (6,11100)
.)
11100 FORMAT(//,45X," STORM HYDROGRAPHS E SEDIMENTGRAPHS WRITE(6111200)
11200 FORMAT ( / ,3 X , "TIME" , 8WINFLOW",7X,"DISCHARGE",5X,"DETENTION TIME",
14)( r"STAGE" ,8 X , "DEPTH" , 8X,"SEDIMENT",8X,"INFLUENT",7X,"EFFLUENT")
WRITE(6,11300)
11300 FORMAT ( / ,3 X , "(HRS)" ,8 X , "(CFS)",9X,"(CFS)",11X,"(HRS)",9X,"(FT)",10
1X,"(FT)",10)(,"( )" , 11X , "(MG/L)",9X,"(MG/L)")
DO 3680 LL=2,NE
JM=(DELPLG/DELTAT)*(LL-1)+1.0
136
WRITE(6,11400)PLGTME(LL),INFLOW(JM),DISCHA(JM),DETTME(LL),STAGO(LL
1),DEPTH(LL),SEDEND(LL),NFINT(JM),EFLNT(Li)
11400 FORMAT(
F7.2,6X,F7.2,8X,F7.2,8X,F7.2,7X,F7.2,7X,F7.2,7XpF7.2,9
1X,F8.1,8X1F7.1)
3680 CONTINUE
3700 CONTINUE
GO TO 3780
3720 WRITE(6,11500)
11500 FORMAT(//,15X,"STAGE",10WAREA",7WAVERAGE DEPTH",5WDISCHARGE"
1,7X, "CAPACITY")
WRITE (6,11600)
11600 FORMAT(/,16X,"(FT)",9X,"(ACRES)-",10X,"(FT)",10X,"(CFS)",9X,"(ACRES
1—FT)")
DO 3740 Itml,N
WRITE(6,11700)STG1(IL),AREAS(IL),AVDPTH( IL),DISCH8(IL),CAPACCIL)
11700 FORMAT(/ $10X,F10.4, 5X,F10.5,5X,F10.2,5X,F10.2,5X,F11.5,5X)
3740 CONTINUE
WRITE (6,11800)
11800 FORMAT(1H1)
WRITE (6,11900)
11900 FORMAT(//,45X,"***** STORM HYDROGRAPHS I SEDIMENTGRAPHS *****")
WRITE(6,12000)
12000 FORMAT(/p3X,"TIME"s8X,"INFLOW",7X , "DISCHARGE"y 5 WDETENTION TIME",
14X,"STAGE",8X,"DEPTH",8X,"SEDIMENT",8WINFLUENT" ,7 X , "EFFLUENT" )
WRITE (6,12100)
12100 FORMAT(/,3X,"(HRS)",8X,"(CFS)",9X,"(CFS3" , 11X , "(HR5)" ,9 X , "(FT)" ,10
1X,"(FT)",10X,"( )",11X,"(MG/L)",9X,"(MG/L)")
DO 3760 LL.2,NE
4MA(DELPLG/DELTAT)*(LL-1)+1.0
WRITE(6,12200)PLGTME(LL),INFLOW(JM) , DISCHAUM) , DETTME(LL) , STAGO ( IL
1),DEPTH(LL),SEDEND(LL),NFLNT(JM) , EFLNT(LL)
f7.2,6X,F7.2,8X,F7.2,8X,F7.2,7X,F7.2,7X,F7.2,7X,F7.2,8
12200 FORMAT(
lx,F8.0,8X,F7.0)
3760 CONTINUE
3780 CONTINUE
3800 CONTINUE
12300 FORMAT(1H1)
WRITE (6,12300)
IF(TRP.GT.1.0) GO TO 3820
GO TO 3840
3820 IF(TRP.GT.TRAP) GO TO 20
3840 CONTINUE
GO TO 3880
3860 WRITE(6,12400)
12400 FORMAT(//,15X,"*#*** ERROR **A** • THE RESERVOIR CAPACITY IS EXCEE
1DED")
3880 CONTINUE
3900 CONTINUE
3950 STOP
END
SUBROUTINE WASH
RETURN
END
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spoils of the arid southwest. Proceedings of the 1977 Meetings
of the Arizona Section - AWRA, Vol. 7, Las Vegas, Nevada,
pp. 33-40.
Blumer, S. In preparation. Master's thesis. School of Renewable
Natural Resources. University of Arizona, Tucson.
Bondurant, J. A., C. E. Brockway, and M. J. Brown. 1975. Some aspects
of sedimentation pond design. Proceedings, National Symposium
on Urban Hydrology and Sediment Control, Lexington, Kentucky,
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Camp, T. R. 1946. Sedimentation and the design of settling tanks.
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Curtis, D. C. 1976. A deterministic urban storm water and sediment
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Curtis, D. C., and R. H. McCuen. 1977. Design efficiency of stormwater
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Curtis, W. R. 1974. Sediment yield from strip-mined watersheds in
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Fischer, J. N. 1976. Simulation of hydrologic processes for surfacemined lands. Ph. D. dissertation, The University of Arizona,
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138
Fogel, M. M., L. Duckstein, and A. Musey. 1976. Event-based formulation of watershed management. Proceedings, ASCE Specialty Conference on Environmental Impact of Irrigation and Drainage,
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Fogel, M. M., L. H. Hekman, and W. B. Vandivere. 1979. Sediment yield
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the
1979 Winter Meeting, American Society of Agricultural Engineers,
New Orleans, La., 7 pages.
Fogel, M. M. 1980. Professor of Watershed Management, School of Renewable Natural Resources, University of Arizona. Oral communication.
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