AGRICULTURAL ADJUSTMENTS TO A FALLING GROUNDWATER TABLE IN CENTRAL ARIZONA by

AGRICULTURAL ADJUSTMENTS TO A FALLING GROUNDWATER TABLE IN CENTRAL ARIZONA by
AGRICULTURAL ADJUSTMENTS TO A FALLING
GROUNDWATER TABLE IN CENTRAL ARIZONA
by
Kenneth John Hock
A Dissertation Submitted to the Faculty of the
DEPARTMENT OF ECONOMICS
In Partial Fulfillment of the Requirements
For the Degree of
DOCTOR OF PHILOSOPHY
In the Graduate College
THE UNIVERSITY OF ARIZONA
1973
THE UNIVERSITY OF ARIZONA
GRADUATE COLLEGE
I hereby recommend that this dissertation prepared under my
direction by
Kenneth J. Hock
entitled A ricultural Adjustments to a Fallin Groundwater
Table in Central Arizona
be accepted as fulfilling the dissertation requirement of the
degree of Doctor of Philosophy
763 .0(EL z ?
Dissertation Director
/îi
Date
After inspection of the final copy of the dissertation, the
following members of the Final Examination Committee concur in
its approval and recommend its acceptance:*
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This approval and acceptance is contingent on the candidate's
adequate performance and defense of this dissertation at the
final oral examination. The inclusion of this sheet bound into
the library copy of the dissertation is evidence of satisfactory
performance at the final examination.
STATEMENT BY AUTHOR
This
requirements
is deposited
rowers under
dissertation has been submitted in partial fulfillment of
for an advanced degree at The University of Arizona and
in the University Library to be made available to borrules of the Library.
Brief quotations from this dissertation 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:
PREFACE
This dissertation presents results of research into the impact
of declining water tables on agricultural organization and resource
use in those areas of Maricopa County, Arizona primarily dependent
upon groundwater for irrigation. It is a part of a comprehensive
interdisciplinary study entitled "Water in Relation to Social and
Economic Growth in an Arid Environment" conducted by researchers from
various departments of The University of Arizona under the general
leadership of Dr. M. M. Kelso of The Department of Agricultural
Economics.
The overall study consisted of two broad phases with the first
phase divided into two parts. The first part involved the construction of an input-output model for the entire economy of Arizona. The
second part of the first phase was concerned with determining the
economic impact of diminishing available groundwater supplies on the
agricultural sector of the economy. To accomplish this, the agricultural sector was divided into four major and three minor study areas
characterized by differing climates, cropping patterns, and sources,
availability and costs of water for irrigation. The four major areas
were Yuma County, Pinal County, the Maricopa County surface water
region and the Maricopa County groundwater region. The three minor
areas consisted of the Sulphur Springs Valley in Graham and Cochise
iii
iv
Counties, the Gila Valley in Graham and Greenlee Counties, and the irrigated areas of Pima County. Each area was the subject of a separate,
detailed study designed to measure and predict adjustments in crop
enterprises, resource use, and incomes in response to changing land
and water availability and increasing water costs over time.
The second phase of the overall study involved the incorporation
of data from these detailed agricultural sector studies with data from
other sectors of the economy into the input-output model in order to
measure the aggregate impact of changing water availability and costs
on the economy of the state.
To insure comparability of data from the various agricultural
sector studies, a common interview questionnaire was used to collect
information in all seven study areas. Consistency in methods of analysis and reporting of results was maintained by means of regular
seminars in which all contributing researchers participated and through
coordinating efforts of the project supervisors. However, each
researcher was responsible for developing economic models relevant
to his particular study area and for reporting pertinent findings on
an individual basis.
I wish to express my sincere gratitude to my dissertation
director, Dr. William E. Martin, for the patience and understanding
he displayed during the long process of developing this dissertation
and for his expert assistance in bringing it to a rapid completion
in the final stages. A debt of gratitude is also due Dr. Philip G.
Hudson for his sage guidance and assistance throughout the course of
my graduate studies and to Dr. Robert H. Marshall for his guidance
in completing requirements for the minor field of study. A special
note of thanks likewise goes to Dr. Robert C. Angus for his constructive suggestions during the preparation of this dissertation.
To Dr. Maurice M. Kelso go my admiration and respect for the
inspiring example he presented as an instructor and as a person. My
sincere thanks also to Dr. Robert A. Young for his unstinting
assistance as adviser in the early years of this project.
To Dr. Lawrence E. Mack I extend a warm, personal "thank you"
for his expert assistance in developing functional linear programming
models and for the many small favors which only a true friend would
extend and which can never be fully repaid. Drs. Harold M. Stults and
Douglas M. Jones also contributed greatly through their groundbreaking
efforts in some phases of the project to which we all contributed.
I sincerely appreciate the diligent efforts of Paula Tripp in
typing the dissertation. The many hours of consultation and vast
amounts of information provided by Cooperative Extension personnel,
irrigation district managers, and Maricopa County farmers cannot be
forgotten nor can the financial assistance provided by the Rockefeller
Foundation and The University of Arizona.
Finally, to my wife, Barbara, daughter, Kathy, and son, Steven,
go a loving tribute for the many lonely days they have endured without
vi
the company and assistance of a husband and father which they so
richly deserve.
TABLE OF CONTENTS
Page
LIST OF TABLES LIST OF ILLUSTRATIONS xiii
ABSTRACT xiv
CHAPTER
I
INTRODUCTION Problem Orientation
Physiographic Setting
Water Supply Sources
Soils and Land Use
Objective of Study
Method of Analysis
Assumptions
Sources of Data
2
3
3
3
7
8
9
13
II WATER SUPPLY SITUATIONS 15
History of Irrigated Agriculture in
Maricopa County
Stage 1: Diversion of Normal Flow
Surface Waters
Stage 2: Surface Water Impoundment
Stage 3: Groundwater Development
Stage 4: A Stage of Decline?
Water Resource Areas
Area A Area B Water Quality
Water Supply Situations
Buckeye Irrigation District (BID)
Roosevelt Irrigation District (RID)
Arlington Canal Company (ARL)
Maricopa County Municipal Water Conservation
District Number One (MCMWCD #1)
Adaman Mutual Water Company (ADAM) Privately Owned Farm Wells vii
15
18
18
20
28
30
31
32
32
34
35
38
38
39
39
40
viii
TABLE OF CONTENTS--Continued
Page
III
THE REPRESENTATIVE FARM MODELS
41
Criteria and Procedure for Farm Model
Specification Characteristics of Model Farm Resources Land Irrigation Water Distribution Facilities Irrigation Wells Farm Buildings Machinery and Custom Operations Labor Capital Management Alternative Crop Enterprises Costs and Returns Yields, Product Prices, and Gross Returns
Net Returns Over Variable Costs Fixed Costs IV
THE LINEAR PROGRAMMING MODEL
81
Components of the Models The Objective Function Activities Restrictions Land Availability Restrictions
Water Availability Restrictions Crop Enterprise Restrictions Projection Procedures Urbanization of Cropland Cotton Allotment Transfers
Sugar Beet Allotment Transfers Water Table Decline Rates Well Replacement Decisions V
41
45
47
47
50
53
55
55
56
56
56
58
59
66
69
106
RESULTS AND CONCLUSIONS Projected Adjustments: 1967-2015
Crop Enterprise Combinations
Cotton Allotment Transfers Net Incomes Water Use Pumping Lifts and Water Costs
Number of Farms and Land Use
Urbanization of Cropland • • • •
82
83
83
84
84
85
86
89
90
91
94
95
97
106
108
121
124
126
129
131
139
ix
TABLE OF CONTENTS--Continued
Page
Summary Conclusions and Implications LIST OF REFERENCES 141
145
148
LIST OF TABLES
Table
1.
Page
Estimated Annual Groundwater Withdrawals by Aquifer:
1945-67 27
2.
Water Situation Code and Source of Water, Areas A and B . . • 36
3.
Farm Model Size, Cropland Acreage, and Number of Sample
Farms, Area A 44
4.
Farm Model Size, Cropland Acreage, and Number of Sample
Farms, Area B 44
5.
Number of Farms by Farm Model Size and Water Situation,
1967, Area A 46
6.
Number of Farms by Farm Model Size and Water Situation,
1967, Area B 46
7.
Inventory of Irrigation Water Distribution Systems for
Typical Farm Models, Areas A and B 49
8.
Selected Irrigation Well Data by Farm Size Group and
Water Situation, Area A 51
9.
Selected Irrigation Well Data by Farm Size Group and
Water Situation, Area B 52
10.
Alternative Crop Enterprises Available to Typical Farm
Models, Areas A and B 57
11.
Yields, Prices, and Gross Returns Per Acre, Maricopa
County Groundwater Region, Area A 62
12.
Yields, Prices, and Gross Returns Per Acre, Maricopa
County Groundwater Region, Area B 64
13.
Farm Model Gross Returns, Total Variable Operating Costs,
and Net Returns Over Variable Costs Per Acre for Selected
Crop Enterprises, Area A 67
Farm Model Gross Returns, Total Variable Operating Costs,
and Net Returns Over Variable Costs Per Acre for Selected Crop Enterprises, Area B
68
14.
xi
LIST OF TABLES--Continued
Table
15.
16.
17.
18.
19.
20.
Page
Water Use Per Crop Acre and Net Returns Over Variable
Costs Per Acre-Foot of Water Used, Area A 70
Water Use Per Crop Acre and Net Returns Over Variable
Costs Per Acre-Foot of Water Used, Area B 71
Annual Cost of Buildings, Machinery, Vehicles, Ditches,
and Insurance, Area A 73
Annual Cost of Buildings, Machinery, Vehicles, Ditches,
and Insurance, Area B 76
Annual Fixed Costs Per Farm by Size and Water
Situation, Area A, 1967 77
Annual Fixed Costs Per Farm by Size and Water
Situation, Area B, 1967 79
21.
Break Even Pumping Lifts Based on Net Returns Over
Variable Costs by Crop Enterprise and Farm Size, Area A . . . 99
22.
Break Even Pumping Lifts Based on Net Returns Over
Variable Costs by Crop Enterprise and Farm Size, Area B . . . 101
23.
Break Even Pumping Lifts Based on Net Returns Over
Variable Costs Plus Fixed Well Costs by Crop Enterprise and Farm Size, Area A 102
Break Even Pumping Lifts Based on Net Returns Over
Variable Costs Plus Fixed Well Costs by Crop Enterprise and Farm Size, Area B 104
Projected Adjustments in Crop Acreages, Gross Returns,
and Net Returns over Variable Costs by Water Resource
Area and Groundwater Region 107
Projected Adjustments in Crop Acreages, Gross Returns,
and Net Returns Over Variable Costs by Water
Situation, Area A 110.
Projected Adjustments in Crop Acreages, Gross Returns,
and Net Returns Over Variable Costs by Water
Situation, Area B 111
Reported and Projected Acreages for Selected Crops
in Maricopa County: 1967-2015 116
24.
25.
26.
27.
28.
xii
LIST OF TABLES--Continued
Table
29.
Page
Projected Long Staple Cotton Allotment Transfers
by Water Resource Area and Water Situation 122
30.
Projected Short Staple Domestic Cotton Allotment
Transfers by Water Resource Area and Water Situation . . . . 123
31.
Projected Annual Water Use by Water Situation, Area A . . . . 127
32.
Projected Annual Water Use by Water Situation, Area B . . . . 128
33.
Projected Average Increase in Depth to Water by Water
Situation, 1967-2014, Areas A and B 130
Projected Variable Costs of Water Per Acre-Foot by
Water Situation, Areas A and B 132
34.
35.
Projected Adjustments in Number of Farms, Acres of
Cropland, and Cropped Acres by Water Situation, Area A . . . 135
36.
Projected Adjustments in Number of Farms, Acres of
Cropland, and Cropped Acres by Water Situation, Area B . . . 136
37.
Projected Urbanization of Cropland in Maricopa County
by Water Situation and Farm Size 140
Percent Change in Cropped Acreage, Water Use, Cotton
Acreage, and Net Revenues by Area and Water
Situation: 1967-2015 143
38.
LIST OF ILLUSTRATIONS
Figure
Page
4
1.
Water Provinces of Arizona
2.
Groundwater Basins and Aquifers in Arizona
3.
Maricopa County Irrigated Acreage, 1880-1969 and
Groundwater Withdrawals, 1945-1967 17
4.
Irrigated Areas and Major Dams in Arizona 19
5.
Study Areas Within Maricopa County
6.
Critical Groundwater Areas in Central Arizona 5
22
26
ABSTRACT
The level of future agricultural production in Central Arizona
depends upon the availability of land and water, the cost of water, and
opportunities to grow crops yielding high returns per acre-foot of
water. Suitable land is abundantly available but groundwater appurtenant to these lands is becoming increasingly costly. Opportunities
to grow high-value crops are subject to the vagaries of commodity
markets and government programs.
This study estimates the direction and magnitude of expected
agricultural adjustments in response to a declining land and water
base, increasing water costs, and intra-county transfer of cotton
allotments. The study region, encompassing all areas of Maricopa
County relying solely or primarily upon groundwater for irrigation,
is divided into two water resource areas. Area A has low-cost, poor
quality water and only cotton for a high-value crop. Area B has highcost, good quality water and cotton, vegetables, and citrus for highvalue crops.
Nine representative farm models are developed characterizing
the structure of the agricultural sector of the economy in these two
areas. Data for ten crops grown by these nine farm size groups are
incorporated into linear programming models to make projections for 18
water situations distinguished on the basis of source, availability, and
cost of water. Projections are made for the period 1967 to 2015.
xiv
Projected adjustments show over 20 percent declines in land and
water use and a 13 percent decline in net revenues over variable costs
of production for the study region by 2015. These declines occur due to
a loss of 68,000 acres of land to urban uses, and the abandonment of lowvalue crops made unprofitable by rising water costs. Declines in resource
use and incomes are mitigated by a 10,000 acre increase in cotton production due to transfers of allotments from an adjacent region experiencing greater losses of land and water to urban uses.
Projections by water resource area and water situation show 7
and 13 percent decreases in land and water use and a 7 percent increase
in net revenues over variable costs for Area A. This divergent movement
of resource use and revenues occurs because a 64 percent increase in
cotton acreage offsets substantial reductions in sorghum and safflower
acreages. Area B projections show approximately a 30 percent reduction
in land and water use and a 23 percent reduction in net revenues over
variable production costs. These reductions occur because all resources
lost to urban uses come from this area and large acreages of low-value
crops go out of production due to rising water costs. Only small
acreages of short staple cotton allotments are transferred to Area B
farms because Area A farmers can afford to pay more for surplus
allotments. Area B experiences a net loss of cotton acreage because
long staple allotments are transferred to Area A ferns when water
costs make this variety of cotton unprofitable in Area B water situations. Projections by water situation within the two water resource
areas vary from increases in resource use and net incomes to large
decreases.
xvi
The agricultural sector of Maricopa County expands until 1960,
then enters a stage of decline, accelerated by large losses of land and
water resources to urban uses in one irrigation district with adequate
supplies of low-cost water. A comprehensive land use plan with zoning
restrictions preventing urbanization of low-cost water areas would help
maintain agricultural resource use and incomes at levels higher than
will otherwise occur. Such a plan would also help maintain the quality
of Che urban environment in Maricopa County.
CHAPTER I
INTRODUCTION
The Central Arizona economy, and its agricultural sector in
particular, depend heavily upon the use of a rapidly declining stock
of groundwater. According to Harshbarger et al. (1966:5), 4 million
acre-feet or approximately 57 percent of the total 7 million acre-feet
of water used annually in Arizona represents net withdrawals from the
supply of water stored in underground aquifers. Another report, The
Fourth Arizona Town Hall on Arizona's Water S
(Arizona Town Hall,
1964:145), indicates that crop production accounts for 93 percent of
all water used in the state. A bulletin entitled Mineral and Water
_Resources of Arizona (1969:529-39) further indicates that about 75
percent of all groundwater pumped in the State is pumped from aquifers
in Maricopa and western Pinal Counties in Central Arizona. The annual
rate of withdrawal greatly exceeds the rate of recharge and in places
water levels are declining as much as 20 feet per year. In some areas
water levels have declined to the point where the cost of pumping prohibits the use of groundwater for production of some agricultural crops.
In addition, some lands, along with the surface and groundwater supplies
available to them, are being transferred from agricultural to urban
uses. These trends are expected to continue.
As water costs increase and available land and water supplies
decrease, future income generated and the quantity of other resources
1
2
used in the agricultural sector are expected to decline. These adjustments will directly and indirectly affect the level of economic activity
in other sectors of the Arizona economy. To assess the impact of these
adjustments on the economy of the State, the Department of Agricultural
Economics at The University of Arizona undertook the comprehensive study
described in the Preface. The research reported in this dissertation,
along with studies by Stults (1967), Jones (1968), Mack (1969), and others
listed by the Department of Agricultural Economics (1972), is an integral
part of the comprehensive study. Data from these studies form the basis
for making long-term projections of aggregate changes in levels of economic activity due to increasing water costs and the shift of land and
water resources from agriculture to other sectors utilizing an inputoutput model of the Arizona economy (Tijoriwala, Martin, and Bower,
1968).
Problem Orientation
This study is concerned with those areas of Maricopa County,
Arizona which are primarily or solely dependent upon groundwater for
irrigation. The study region includes five irrigation districts and
nine areas relying solely upon private farm wells. These fourteen
areas are distinguished on the basis of source and quality of water,
pumping lifts, farm sizes, and cropping patterns. This groundwater
study region accounts for all irrigated areas in Maricopa County except
two irrigation districts which rely heavily upon surface water for
irrigation. The surface water region, serviced by the Salt River
Project and the Roosevelt Water Conservation District, was dealt
with in a separate but related study (Mack, 1969).
3
Physiographic Setting
Maricopa County is located mostly in the Desert Lowlands water
province of Arizona (Figure 1) characterized by broad alluvial-floored
basins surrounded by high mountains. Most of the County consists of
hot, dry desert flatlands. Average January temperature is 50 ° Fahrenheit and average summer temperatures are in the 90 ° range.
Water Supply Sources
Annual precipitation is less than 10 inches and of minor consequence to agricultural production. Surface waters from the Salt and
Verde Rivers, which arise in the Central Highlands water province to
the north and east, supply most of the water needs for two irrigation
districts, the Salt River Project and the Roosevelt Water Conservation
District. However, the remaining areas of the County obtain virtually
all of their irrigation water from groundwater aquifers underlying the
areas numbered 1, 5, 7, 8, and 9 in Figure 2. Area 1, the Salt River
Valley aquifer, encompasses the surface water study region as well as
much of the groundwater region dealt with in this study. However, the
characteristics of this aquifer vary significantly from one subarea to
another such that fairly distinct subaquif ers have been defined by the
United States Geological Survey (White Stulik, and Rauh, 1964). This
)
facilitated the separation of the surface and groundwater study regions
of the County.
Soils and Land Use
The Red Desert soils which predominate in the study region are
"characteristically low in organic matter and therefore in reserve
4
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Figure 1. Water Provinces of Arizona.
Source: Cross, Shaw, and Scheifele, 1960.
5
114°
32 .
r
A
Navajo sandstone
LEGEND
1.
2.
3.
4.
5.
Salt River Valley
Lower Santa Cruz Basin
South Gila Valley
Palomas Plain area
Gila Bend area
6. Ranegras Plain area
7. McMullen Valley
8. Harquahala Plains area
9. Waterman Wash area
10. Upper Santa Cruz basin
11. Douglas basin
12. Willcox basin
12. Bowie-San Simon area
IL.
Safford Valley
15. Duncan Valley
16. Wellton-Mohawk area
17. Big Sandy Valley
S. Chino Valloy
19. Coconino sandtsone
20. Navajo sandstone
21. Mesaverde group
Figure 2. Groundwater Basins and Aquifers in Arizona.
Source: Arizona Town Hall, 1964 as adapted from Cross, et al., 1960.
6
nitrogen," but, "they are among the most productive in the world when
irrigated" (Cross et al., 1960:134-136). Cropping patterns are quite
diverse. Cotton, alfalfa, and small grains can be grown throughout the
study region. Vegetables, grapes, citrus, safflower, and sugar beets
are, or have been, important crops in parts of the region where water
quality or local climatic conditions are particularly suited to their
production and when existing market conditions made them a profitable
enterprise.
Examples of the effect of market conditions on cropping patterns
are the rise and decline of vegetable acreages in the Aguila area during
the late 1950's and early 1960's and the destruction of grape vineyards
in the Litchfield Park area during the late 1960's following several
years of low prices. A more striking example is the violent fluctuation
in safflower acreages in Maricopa County between 1960 and 1968 ranging
from 4,000 to 70,000 acres as the price bounced between 70 and 100
dollars per ton (Arizona Agriculture, 1959-70). Another factor which
had a bearing on acreage fluctuation was government programs which
restricted cotton and feed grain acreages during this time. Sugar
beets were grown in the Salt River Valley around the turn of the century for processing at a plant in Glendale (Forbes, 1911). Production
of beets for sugar later ceased but was revived in 1967. Although less
than 20,000 acres are grown annually in Maricopa and Pinal Counties, it
reflects the constant search of farmers for crops which can be grown
more profitably than alfalfa and feed grains in the face of rising
water costs, restrictions such as on cotton allotments, and the limited
rate of increase in demand for vegetables and other high value crops.
7
One final factor which, until recent years, has not had a particularly significant effect on total crop acreages, but which is expected
to in the future, is the urbanization of agricultural lands. In the
past, most of the urban growth has occurred in the surface water study
region of Maricopa County. With the concurrent reduction in cotton
allotments, remaining agricultural lands in that part of the County
could absorb most of the cotton allotments and other crops released
from urbanized land. However, urbanization is continuing and in recent
years has moved outside the boundaries of the surface water study region.
A report by John Carollo Engineers (1968) indicates that 64,000 acres
of agricultural land in the groundwater study region north and west of
the Salt River Project are expected to be transferred to urban uses by
the year 2000. Up to the time this study was made the most noticeable
effect of urbanization on land use patterns in the groundwater study
region has been the relocation of citrus groves, which seem to be prime
lands for subdividing, from the vicinity of Deer Valley north of Phoenix
to other areas. However, as urbanization continues in both the surface
and groundwater study regions, it is anticipated that cotton allotments
released from these lands in future years will of necessity be transferred to other areas in the groundwater study region where they can
be accommodated and will be sought after to replace lower value crops.
Objective of Study
The purpose of this study is to project probable adjustments in
crop acreages, value of output, net incomes and water use in response to
increasing water costs as groundwater tables decline over time. These
projections will simultaneously take into account the loss of agricultural
8
land and appurtenant groundwater rights to urban uses and the transfer of
cotton allotments from urbanized lands in both the surface and groundwater regions of the County to areas remaining in agriculture within the
groundwater study region. Projections will be made for the period 1967
to 2015.
Method of Analysis
Projections of probable adjustments are made utilizing linear
programming models of representative farm firms. A field survey of
sample farms in the study area provided the necessary data for determining farm size distribution, crop enterprise combinations, types and
quantities of resource inputs, and production procedures utilized in
producing all crops of any consequence grown in the study region. These
data were used to synthesize representative models of farms by size
classes and organizational characteristics determined to be typical of
farms in the study region. Calendars of operation and technical and
financial budgets were then developed for each crop grown by each of
the representative farm model size groups. Where a crop, such as cotton,
was grown in more than one way, a separate budget was developed for each
method used to produce that crop in each of the relevant farm models.
Finally, linear programming models of the representative farm
firms were constructed. Once constructed, these linear programming
models were used to project agricultural adjustments to a declining
groundwater table and increased availability of cotton allotments
transferred from lands being urbanized in both the surface and groundwater study regions of Maricopa County.
9
Assumptions
The above mentioned linear programming models include certain
assumptions basic to their functioning as analytical tools. These
assumptions are well documented in Dorfman, Samuelson, and Solow (1958),
Heady and Candler (1958) and other standard references on this form of
mathematical programming. Other assumptions, recognized as departures
from real world conditions, were also required to simplify a complex
situation in order to pinpoint the effects of changes in the cost of
water and the acquisition of cotton allotments from the urbanized areas.
The basic assumption made is embodied in the classic economic term,
ceteris paribus, meaning all other relevant factors remain unaltered.
Some of the more important of these relevant factors which could independently cause a change in cropping patterns, resource use, levels of
output, and economic returns, and are assumed to remain constant at the
1967 levels, are: (1) prices of inputs and outputs or at least the ratio
of any one to another; (2) technological methods of production which
could change the quantity or proportion of inputs for a given level of
output or, conversely, the level of output obtained from a given package
of inputs; (3) government acreage controls on crops such as cotton,
sugar beets, wheat, and feed grains; (4) quality of irrigation water
which, if deteriorated, could require additional costly inputs or, if
improved, might result in a cost saving due to a reduction in water
requirements or use of fewer practices currently employed to insure
percolation of dissolved salts below crop plant root zones; and (5)
irrigation district policies regarding water allocation among district
landowners. Two other important assumptions made in the analysis, not
10
of the ceteris paribus character, are that farmers face an economic
shortage rather than a physical shortage of water within the time span
covered and that they act so as to maximize economic returns to production in the short run rather than the long run.
In addition to the need for keeping the linear programming models
to a manageable size and capable of isolating the effects of the selected
independent variables in the models, the above departures from real world
conditions are justifiable on other grounds. First, there is no way one
can accurately predict the direction and magnitude of changes in technology or the policies of government and irrigation districts short of
being a soothsayer. It appears that the margin for error in prediction
is greater than by assuming they remain constant.
Secondly, as to the problem of water quality, a review of information in Geological Survey reports, irrigation district well tests, and
data obtained from farmers indicates a likelihood that there is a greater
difference in water quality between aquifers or subaquifers at given
depths than between different depths within a given aquifer. Given the
interfingering of various bands of alluvium with different textures at
different depths within an aquifer, one cannot with confidence say that
water quality will deteriorate or improve over an entire aquifer as
water is pumped from ever greater depths. Well tests are as likely
to show poor quality water and low well yields at shallow depths as
at deeper depths. The more significant factors seem to be the aquifer
examined or the location within a given aquifer at which tests are
made, and therefore the type of water bearing alluvium found at a
given depth.
11
The problem of poor water quality was being discussed when irrigation from groundwater aquifers in Arizona was in its infancy. Skinner
(1903:283-4) indicates that some wells in the Salt River Valley were
producing water "containing sufficient alkali to make it a serious consideration indeed, if such waters alone are to be relied upon for irrigation purposes" and "with very few exceptions, the black-alkaline wells
are shallow." He specified "shallow" as being less than 100 feet deep.
Speaking of the total dissolved salt content, Skinner notes that, "The
groundwaters of Salt River Valley, generally speaking, are relatively
high in their content of soluble salts, varying from 27.6 to 531.8 parts
per 100,000." This level of soluble salts is no less than found in Salt
River Valley waters today even though they come from greater depths.
Apparently the farmers of the valley have been obtaining "poor quality"
water from all depths but have been using it successfully for some 70
years in spite of Skinner's warning that, "The deep well waters so far
developed probably contain too high a percentage of soluble salts to
be used continuously as a source of irrigation supply" (1903:285).
Thirdly, information from numerous Geological Survey reports,
summarized in Mineral and Water Resources of Arizona (1969:529-39), concerning the period of time various aquifers have experienced significant
withdrawals, the amount of water withdrawn prior to 1966, and estimated
quantities of water remaining at depths less than 1,000 feet indicate
that above this depth there is enough water remaining in the five aquifers in the study region to last approximately 100 years or more if
annual withdrawals continued at levels occurring in the early 1960's.
These are admittedly rough, but probably conservative, estimates.
12
Nevertheless it would seem to be ample justification for the assumption
that farmers on lands overlying these aquifers face an economic rather
than physical shortage of water over the period of time dealt with in
this study.
Finally, the assumption that farmers act to maximize profits in
the short run is based on the fact that water tables are declining.
Therefore, farmers must make production decisions each year based upon
a new set of water costs. The water in an aquifer is conventionally
thought of as a "stock resource" which for all practical purposes is
fixed in quantity during any relevant time period considered due to
the very low rates of recharge relative to aggregate withdrawals. However, because groundwater flows from one part of an aquifer to another,
it is a community resource owned as tenants-in-common by all landowners
on the surface. Water at any given level in an aquifer is available to
an individual landowner only until it flows away into cones of depression
created by more rapid withdrawals in other parts of the aquifer. Therefore, groundwater to the individual farmer is a flow resource subject to
the law of capture like unimpounded water in a surface stream. To obtain the economic profit available from an acre-foot of water at a given
depth, it must be pumped at the point in time when it is available at
that depth or it is lost forever. Attempts of an individual to maximize profit over time by conserving water will be ineffective. Therefore, the rational individual bases his water use decisions upon short
run variable costs of pumping.
In the long run all costs become variable and must be considered.
However, once installed, a well will be used so long as returns to water
13
as a resource exceed the short run variable costs of pumping. The fixed
costs of installing the well become relevant to the decisions of what,
how, and how much to produce only at the point in time when the well must
be replaced. Well replacement decisions will be dealt with in the discussion of the Linear Programming models.
Sources of Data
The primary source of data used to develop input coefficients
for the linear programming models was a field survey of 84 sample farm
operators in the study region. The survey farm population was taken
from a list of farms obtained from the Maricopa County Agricultural
Stabilization and Conservation Service (ASCS). This list included all
farms in the County having a cotton or wheat allotment or an established
feed grain base. The list was correlated with the U.S. Census of Agriculture: 1959 (U.S. Bureau of the Census, 1961) and found to be quite
complete. The County list was then divided into surface and groundwater
study region populations along ASCS district lines which conformed
closely to the surface-groundwater regional boundaries.
The list of farms for the groundwater region was arrayed by
size according to cropland acres. Those farms with less than 30 acres
of cropland were excluded from the survey population. This was based
upon the determination that 30 or more cropland acres were required for
a general crop farm to qualify as a commercial farm. The survey population was then stratified by size of farm and sampling ratios for each
strata determined on the basis of concentration of farm numbers and total
cropland acreages. A systematic procedure involving a random start was
used to draw a sample from each farm size group. Larger farms were
14
sampled at a higher rate than smaller farms to provide for adequate
representation with respect to both number of farms and cropland acreages
in each size group. If a complete interview could not be obtained from a
selected sample farm operator, a procedure was followed whereby the next
largest and then the next smallest farms in the array were drawn for
first and second alternates. The 84 farms for which interviews were
obtained accounted for approximately 25 percent of the farms and 57
percent of the cropland acreage in the study region.
The farm survey questionnaire (Hock, 1971:416-32) provided for
a complete description of farm organization, cropping program, labor,
machinery, irrigation wells, and all other resources utilized and costs
incurred in the farm operation. Separate questionnaires were used to
obtain a complete calendar of operations and inputs for each crop grown
until sufficient information was collected to ascertain what constituted
typical practices for the study region.
Additional information was obtained from irrigation districts.
custom operators, agricultural supply firms, Maricopa County Extension
personnel, the United States Geological Survey, and specialists in the
fields of Agronomy, Soils, Horticulture, Agricultural Engineering, and
Farm Management at The University of Arizona. Much of the data concerning machine accomplishment rates and variable operating costs was
obtained from Young, Martin, and Shaw (1968). Numerous other secondary
sources, published and unpublished, were also used when necessary.
Most of the basic data assembled from these various sources is embodied
in the 118 unit budgets and other tables found in Hock (1971).
CHAPTER II
WATER SUPPLY SITUATIONS
The actions of any individual, firm, or sector of an economy
using large quantities of water will be affected by the water supply
situation within which it operates. The following description of the
development of irrigated agriculture and the various individual water
supply situations found in Maricopa County is presented in order to
better define the framework within which this study was conducted.
His tory ofIrr-ture
in Maricopa County
Historical accounts by Cross et al. (1960:4-20,116) indicate
that about 500 A.D. the Hohokam Indians began irrigating crops from
canals in the Salt and Gila River Valleys. By 1200 A.D., these canals
had been developed into an intricate system which according to Forbes
(1911:9) "aggregated a length of 150 miles and were sufficient for the
irrigation of 250,000 acres, although it is not likely that the whole
of this area was watered at one time." The extent of irrigation was
drastically curtailed about 1400 A.D., possibly due to prolonged
drought conditions, and the Hohokam civilization eventually disappeared. However, the Pima and other Indian tribes were diverting
water from streams on a small scale when Spanish explorers entered the
region in the 1500's.
15
16
White settlers entered the Salt River Valley in significant numbers after the Civil War and found a ready market for crops and produce
at the army posts established to secure the Arizona Territory. The
first successful canal company, The Swilling Irrigation Canal Company,
was organized in 1867 and enlarged upon the prehistoric ditches in the
valley. By 1880, there were ten canals and 55,000 acres under cultivation. By 1900 the irrigated acreage had doubled and it doubled again
by the time statehood was achieved in 1912. Data taken from the 10th
Arizona Town Hall (1967) and presented in graphic form (Figure 3) show
that irrigated acreage increased at a steady pace from 1912 to 1930,
dropped sharply during the Great Depression of the 30's, then rose
rapidly again, with some fluctuations, until in 1967 it stood at
about 510,000 acres.
The tenfold increase in irrigated acreage from the 1880's to the
1960's can be divided into three stages related to irrigation water
supply development (Figure 3). Stage 1, lasting until 1911, was based
upon the diversion of freely flowing river water into canals by means
of small diversion dams. Stage 2 of the irrigated acreage expansion,
extending from 1911 to 1940, was supported primarily by additional
surface water impounded behind a series of dams built on the Salt,
Verde, and Agua Fria Rivers. Significant amounts of groundwater were
used from the Salt River Valley aquifer during the latter part of
Stage 2, but Stage 3, dating from 1940 to 1960, was based almost
entirely upon large scale development and utilization of groundwater
reserves. About 1960, however, it appears that irrigated agriculture
in Maricopa County may have entered Stage 4, a stage of decline.
•
17
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18
Stage 1: Diversion of Normal Flow Surface Waters
Development of surface waters for irrigation in Maricopa County
began in early territorial days. As described by Forbes (1911:11),
Canal construction was rapid, beginning with the old Swilling
Ditch in 1867, and 20 years later about as much land had been
reclaimed as could be irrigated from the Salt River in seasons
of scant flow. Nevertheless, during a series of wet years that
followed, additional areas were put under cultivation until
more ground was nominally reclaimed than could be irrigated by
the 'critical minimum' water supply. The inevitable hardships
which resulted during ensuing years, especially 1898-1904, led
to anxious discussion of remedial measures . . .
McClatchie (1902), reporting on an exhaustive study of the
problem made between 1895 and 1901, indicated that the average annual
supply of water that could be counted on was 550,000 acre-feet. With
this water he estimated that approximately 110,000 acres could be properly irrigated under existing conditions. However, 120,000 acres had
been irrigated in 1901 and there were 275,000 acres in the areas served
by the canal system. He concluded that the most effective means of
solving the water scarcity problem was through the construction of a
proposed dam on the Salt River which he estimated would store enough
water to adequately irrigate 160,000 to 180,000 acres of land.
Stage 2: Surface Water Impoundment
In 1902, the year McClatchie published his study, Congress
enacted the Reclamation Act authorizing federal government financing
for reclamation of desert land and establishment of the Salt River
Project. Roosevelt Dam, dedicated in 1911, intercepted 70 percent of
the Salt River runoff (Forbes, 1911:41). A series of five other dams
built on the Salt and Verde Rivers between 1927 and 1946 (Figure 4)
now enable almost 100 percent utilization of runoff from the 13,000
19
LATE WAD
°AVIS DAM
PARKEFI
PAM
eaDAarc
wocot
NORSESM0404M
ar_e.,..andr
DAM
S.VG.W.LW
CAPE
FIG. A
Mli.
Aff:1541,111.. ReS
FIG. B
SOMAW A.ANLE
MIMMLAI,_ 0.4
MITTAY LANE
RoosEVEcr-Larez
050
woosnec
oz
10 20 30
IRRIGATED AREAS
DAms
I
STORAGE
DIVERSION
J OR FLOOD CONTROL.
SOURCES:
AGRICULTURAL EXPERIMENT STATION, UNIVERSITY OF ARIZONA,
Li S. DEPARTMENT OF INTERIOR, BUREAU OF RECLAMATION
MIIN
MAP "IRRIGATED AREAS IN ARIZONA"
Figure 4. Irrigated Areas and Major Dams in Arizona.
JL
20
square mile watershed of the Salt and Verde Rivers for irrigation and
power generation (Cross, et al., 1960:117 and Salt River Project:
Major Facts In Brief, 1962). Only Horseshoe Dam on the Verde River was
completed after 1940. Water collected in the system is used almost
exclusively in the surface water study region of Maricopa County (see
Mack, 1969).
Two dams were constructed in the groundwater study region of the
County, the region on which this study focuses, during this period. One,
Carl Pleasant Dam, was constructed on the Ague Fria River in 1927 to
provide irrigation water for Maricopa County Municipal Water Conservation
District Number One located northwest of Phoenix. The other, Gillespie
Dam on the Gila River below Arlington, was not a storage dam. It was a
diversion structure built in 1921 to irrigate 10,000 acres in the Gila
Bend Basin. However, due to the subsequent development of storage dams
upstream, the Gila River only rarely flows at this point. Gillespie
Dam was not used for many years and was finally destroyed.
Stage 3: Groundwater Development
Groundwater was being pumped for irrigation in various parts of
Arizona, including the Salt River Valley, before 1900. However, the
wells were few in number and highly variable in efficiency. Pumping
costs varied from 4 to 29 cents per acre-foot per foot of lift (Woodward,
1904:463) compared to a range of 2 to 4 cents per acre-foot per foot of
lift in recent years (Lamoreaux, 1966:68). Therefore, groundwater could
be economically used only on a highly selective basis; primarily as an
emergency water supply for high value crops such as fruits and vegetables
21
where the pumping lift was less than 50 feet (McClatchie, 1902:129).
According to Skinner (1903:286), the high cost of operating pumping
plants made it impractical for most small farmers.
Groundwater lay within 50 feet of the surface over considerable
areas of the Salt River Valley aquifer along the Salt, Gila, New, Agua
Fria, and Hassayampa Rivers. By 1910 the application of large quantities
of surface water to the land had caused the water table to rise to the
surface in some places (Forbes, 1911:53). Water levels rose steadily
until 1924, causing widespread water logging of cropland. However, by
1920, drainage wells had been drilled and began pumping in the Salt
River Project (SRP) service area (Figure 5). This marked the beginning
of groundwater development on a significant scale in the Salt River
Valley.
Within just a few years, substantial amounts of land had been
brought into production based solely or primarily upon groundwater for
irrigation. In 1920, the Roosevelt Water Conservation District (RWCD)
to the east of the SRP was formed covering some 39,000 acres. It immediately began drilling wells and currently obtains about two-thirds of
its supply of water from underground. In 1923, the Roosevelt Irrigation
District (RID) was formed to the west of the SPI'. Its 38,000 acres were
all irrigated with groundwater, most of it obtained from drainage wells
drilled in the west end of the SRI' service area near Tolleson.
The Buckeye Irrigation District (BID), located between the RID
and the Gila River just west of where the Agua Fria River joins the Gila,
has approximately 18,000 acres within its borders. The present company
was formed in 1907 but the first notice to serve water in the area was
22
Groundwater Region - Area B
Groundwater Region - Area A
Surface Water Study Region
Water Situation Boundaries
Figure 5. Study Areas Within Maricopa County.
23
filed as early as 1885. The district is entitled to up to 80 miners
inches per quarter section (3.9 acre-feet per acre) per year of normal
flow water from the Gila and Agua Fria Rivers under the Benson Allison
Decree of 1917. However, this limit has not been approached in recent
years (Goss, 1968:56). Whether this was due to the building of Carl
Pleasant Dam on the Agua Fria River in 1927 and the San Carlos Project
on the Gila River in Pinal County in 1928 is not clear from the literature. Nevertheless, the Buckeye Irrigation District now gets most of
its water from underground sources within the district.
The Arlington Canal Company (ARL), located southwest of the BID,
on the Gila River was formed in 1899. Like the BID, it used water from
the Gila. However, it had no normal flow rights and, as upstream development took place, the river water it obtained was mostly return flow
from the BID and some floodwater during seasons of peak flow. This
being inadequate to irrigate the 4,250 acres in the service area, nine
company wells were drilled to serve as the major source of water supply.
All of the above mentioned groundwater development was done
within the framework of irrigation districts and, with the exception of
the Roosevelt Irrigation District (RID), all of these districts had some
access to, or at least a nominal claim to, surface water supplies.
Furthermore, much of this early groundwater aquifer development was
stimulated by, or at least made possible by, high water tables which
resulted from the application of surface water to overlying or adjacent
lands. This early surge of agricultural expansion based on groundwater
aquifer development subsided with the onset of the Great Depression of
24
the 1930's and the alleviation of the water-logged soil problem encountered through the early 1920's.
With the onset of World War II the demand for agricultural
products increased. Prices and acreages of crops responded accordingly.
At the same time significant improvements in pumping technology took
place. As a result, groundwater aquifer development began to increase
rapidly. Maricopa County Municipal Water Conservation District Number
One (MAR) found the water supply from Lake Pleasant inadequate and
drilled its first wells in 1940. The Adaman Mutual Water Company
(ADAM), covering 2,493 acres, was established immediately adjacent to
MAR in 1943 and began actively delivering water from its wells in
1944 (Goss, 1968:63). Other areas of the Salt River Valley aquifer,
outside the boundaries of districts supplied with surface water, also
began developing; areas such as Queen Creek (CRIC), the lands around
Litchfield Park, Marinette, and Peoria (LMP), the lower Salt River
Valley southwest of the SRP service area (SRV), the Arlington Valley
(ARV), and the Gila Bend (GB) area (see Figure 5). This was the beginning of what the author has designated as Stage 3 in the expansion of
Maricopa County irrigated agriculture.
Post World War II prosperity and the Korean War pushed demand
even higher. The overall price received for cotton in Arizona rose from
13 to 33 cents per lint pound between 1940 and 1953. Cotton acreage more
than tripled. During this same time period, the price and acreage of
barley and grain sorghum more than doubled (Arizona Agricultural Statistics
)
1966). Most of this acreage expansion took place in Central
Arizona; a large part of it in Maricopa County. The result was that
25
water tables dropped rapidly, generating a great deal of concern over the
future existence of agriculture in these areas.
In 1948, the State Legislature passed a Groundwater Code which
gave the State Land Department responsibility for gathering data concerning groundwater aquifers in the state, designating the boundaries of
aquifers or subdivisions thereof, and declaring any of these areas a
"critical groundwater area" when and if conditions warranted it. A
"critical groundwater area" means "any groundwater basin . . . or any
designated subdivision thereof not having sufficient groundwater to provide a reasonably safe supply for the irrigation of the cultivated
lands in the basin at the then current rates of withdrawal" (Arizona
State Land Department, n.d.:3). The primary purpose of the code is
" . . . to regulate the pumping and use of water for irrigation in
critical areas in an attempt to slow down the exhaustion of groundwater"
(Arizona Town Hall, 1964:57). Regulation is accomplished by allowing
the replacement of existing wells but prohibiting the drilling of
additional irrigation wells in the critical areas.
Between 1951 and 1956 the State Land Department declared most of
the Salt River Valley aquifer a critical groundwater area (Figure 6,
areas 1, 2, A, B, K, and M). However, the relatively favorable prices
received for cotton and other crops during the late 1940's and early
1950's had already prompted farmers to move into and sink wells in these
areas. Throughout the 1940's the annual withdrawal of groundwater
in the Gila Bend Basin had increased gradually. But, between 1949 and
1952 it more than doubled (Table 1). About this time, large scale
development was also begun in four new areas, the Tonopah area at the
26
5
4
3
2
IN
S LT RIVER VALLEY CRITICAL AREA
SEPT 1 1951
CREATED
QUEEN CREEH-SURERSTITION CRITICAL AREA
cREATED
3
4___ Stin
5
6
7
-
JAN 16 1951
G,L-s„,,,, CRUZ CRITICAL AREA
CREATED JUNE 19 195i
CLOY CRITICAL AREA
CREATED APRIL 4 1949
- -1=1 MARANA CRITICAL AREA
CREATED OCT 15 i954
4•4 Jon EN
LA sOmortAmm
22
ED TUCSON CRITICAL AREA
CREATED OCT
15 1954
___= 541-1UARiTA-CONTINENTAL CRITICAL AREA
CREATED OCT
15 1954
A
C
B
• --
SALT RIVER VALLEY CRITICAL AREA
COLOR=
ADDED AUG 14 1956 -ED ADDITIONS TO
D___= ADOITIONS TO ELOY CRITICAL AREA
_ COLOR=
ADDED OCT 15 1954 -
EFGHJ___
KLMN___ I
ADDITIONS TO GILA - SANTA
ADDED OCT ID 1954_
1
_
CRUZ CRITICAL AREA
.coLOR
ADDITIONS TO QUEEN CREEK-SUPERSTIT1ON CRITICAL A
ADDED OCT 15 1954
=
COLOR =
61AP OF
PORTION OF CENTRAL ARIZONA SHOWING
CRITICAL AREA BOUNDARIES AS DESIGNATED
OCTOBER 15. 195 4
a..
!- FoANGE
c",Zo,;.11
—-
SROUNDLV•TE9 D.VIS n ON -STATE LAND DEPARTMENT
FAAoNN
CNEDAED A
..C.LA
OCT. ID.
Figure 6. Critical Groundwater Areas in Central Arizona.
Source: Arizona State Land Department, n.d.
27
Table 1. Estimated Annual Groundwater Withdrawals by Aquifer: 1945-67.
Year
Salt
River
Valley
Gila
Bend
Harquahala
Valley
Waterman
Wash
McMullen Maricopa
County
Valley
thousands of acre-feet
1945
1143
20
1
2
1166
1946
1360
33
1
2
1396
1947
1406
40
1
2
1449
1948
1670
61
1
1
2
1735
1949
1644
67
1
1
2
1715
1950
1852
59
5
5
2
1923
1951
1910
104
7
10
2
2033
1952
2020
120
10
17
5
2172
1953
2300
145
20
28
6
2499
1954
2300
139
33
30
7
2509
1955
2240
140
30
40
9
2459
1956
2300
180
40
40
15
2575
1957
2300
180
50
40
21
2591
1958
2300
200
60
45
38
2643
1959
2206
250
95
50
50
2651
1960
2005
250
125
60
60
2500
1961
2178
200
100
65
70
2613
1962
1976
170
200
50
65
2461
1963
2134
130
200
50
75
2589
1964
1972
130
200
50
90
2442
1965
1500
115
200
45
90
1950
1966
1350
145
160
45
105
1805
1967
1763
198
170
52
98
2281
Sources:
C. J. Cox and others (1968:41) and H. M. Babcock (1969:29-38).
28
west end of the Salt River Valley (TON), the Harquahala Valley (HAR),
Rainbow Valley (RAN) at the north end of Waterman Wash, and the east
end of McMullen Valley (AGA) near Aguila (Figure 5 and Table 1). As a
result, irrigated acreages and groundwater withdrawals in Maricopa County
continued a steady upward trend during the 1950's (Figure 3 and Table 1).
Stage 4: A Stage of Decline?
From the standpoint of acres irrigated and groundwater use, it
appears that agriculture in Maricopa County entered a stage of decline
about 1960 (Figure 3). Actually, this may have begun earlier. The data
used to construct Figure 3 are plotted at 5 year intervals which removes
much of the year to year fluctuations in crop acreages due to changing
weather, market prices, and government programs. The yearly data show
that irrigated acreage in the County peaked in 1953 at 560,000 acres,
then dropped sharply through 1956, rose again through 1960 and started
an irregular but fairly steady decline through 1967.
A large part of the decline from 1953 to 1956 was caused by
reductions in cotton acreages which were "cut almost 40 percent from
1954 through 1960 as acreage allotments went into effect" (Arizona Town
Hall, 1967:126). For a time, farmers substituted crops such as alfalfa,
feed grains, and safflower for cotton. However, by 1960 the water table
had dropped below 400 feet around the edges of the Salt River Valley
basin in the Queen Creek, Deer Valley, and MCMWCD #1 areas (White,
Stulik, and Rauh, 1964:Figure 3). This made it unprofitable to pump
water to grow alfalfa and some grain crops under existing market conditions. The consequence was that more land was left idle or fallow,
at least until another alternative was found.
29
The newly developed areas were experiencing similar problems.
Heavy pumping made water tables decline very rapidly in these smaller
aquifers. By 1965
)
pumping lifts in these areas were equal to or
approaching those in the deeper areas of the Salt River Valley. Rainbow
Valley had 19,000 acres of land cleared for cultivation but only 10,000
acres were being irrigated (Denis, 1968:3). Harquahala Valley had
reached the peak of its annual pumping levels (Table 1). The Aguila
area had lost much of its high value vegetable crops due to various
market factors.
Another factor involved in the decline of irrigated acreages in
the County was the conversion of agricultural lands to urban uses in the
Phoenix metropolitan area. Mack (1969:7), citing annual records from
the Salt River Project, indicates that approximately 18,000 acres were
subdivided in the Project service area between 1962 and 1968. Other
areas located in the groundwater study region to the east, north, and
west of the SRF near Mesa, Deer Valley, Sun City, and Litchfield Park
were also experiencing some losses of cropland to subdividers.
Given the above historical evidence, it appears that irrigated
acreage and groundwater pumped for crop irrigation is declining and will
continue to decline barring some rather significant changes in market
situations or institutional restrictions affecting crop acreages. It is
the purpose of this study to estimate the nature and magnitude of adjustments, by water situation within the groundwater study region, as water
tables continue to decline and land is transferred to urban uses,
assuming other independent factors remain constant at the 1967 level.
30
Water Resource Areas
The groundwater study region, as defined for this report, includes all lands in the Salt River Valley extending from Queen Creek on
the east to the Arlington and Tonopah areas on the west, with the exception of the Salt River Project (SRP) and Roosevelt Water Conservation
District (RWCD) which constitute the surface water region of Maricopa
County dealt with by Mack (1969). In addition, it includes the Gila
Bend Basin, Rainbow Valley, Harquahala Valley, and the upper reaches of
the McMullen Valley in the vicinity of Aguila (Figure 5). These latter
areas overlie well defined individual aquifers separated from other areas
by geologic formations which make the rate of decline in the water tables
almost entirely dependent upon the quantity of water pumped for irrigation in the area immediately overlying the aquifer.
The Salt River Valley portion of the study region consists of
five irrigation districts and five areas not organized into districts
which overlie one large aquifer made up of valley lands in the Salt,
Gila, Agua Fria, New, and Hassayampa River drainage systems which have
their confluence west of Phoenix (Figures 4 and 5). However, despite
being interconnected via underground water movement, the various subareas of this Salt River Valley aquifer exhibit a wide range of characteristics with respect to quantity and quality of groundwater obtainable,
depth to water, rates of decline of the water table, and means of obtaining this water by the individual users. This made it necessary to
deal with each of these ten subareas an individual water resource
areas rather than as one integrated unit.
31
The farm survey data indicated that the study region was also
quite diverse with respect to farm size and organization, and crops
grown. The sample farms in the region ranged from 30 to over 30,000
acres of tillable land per farm. Examination of the data by various
farm size groupings for the entire study region showed no discernible
patterns with respect to crop enterprise combinations and resources used.
However, scrutiny of the data by water resource area revealed significant
differences in cropping patterns, farm sizes, water quality, depth to
water, and rate of decline in the water table. Therefore, the study
region was divided into two major areas, based upon these characteristics. This division led to groupings of farms with greater homogeneity of organizational characteristics which facilitated the
construction of representative farm models and analysis of changes in
their organization over time. The two major water resource areas of
the groundwater study region were labeled Area A and Area B. The subareas included in each of these major areas are shown in Figure 5.
Area A
Area A consists of farms in the Roosevelt Irrigation District,
the Buckeye Irrigation Company, and Arlington Canal Company service
areas plus farms relying solely upon private farm wells located in the
vicinity of the Gila River from the southern edge of the Salt River
project to the Painted Rock Dam west of Gila Bend. This major area is
characterized by a cropping pattern consisting chiefly of cotton,
alfalfa, and grains. Pumping lifts in this area averaged less than 300
feet in 1967. Rates of decline in water levels were relatively small,
generally 4 feet per year or less. Quality of water is relatively poor
32
and the quantity of water applied per acre of crop grown was measurably
higher than in Area B. Most of the water in this area contains more
than 1,500 parts per million (PPM) of total dissolved salts, which puts
it in the high to very high salinity hazard range for irrigation water
(Smith, Draper, and Fuller 1964).
)
Area B
Area B consists of farms in the areas serviced by Maricopa County
Municipal Water Conservation District Number One and the Adaman Mutual
Water Company, plus ferns relying solely upon private farm wells in
McMullen Valley near Aguila, Harquahala Valley, the Tonopah area, Rainbow Valley, the Litchfield Park-Marinette-Peoria area, and the Queen
Creek area in the southeastern part of Maricopa County. Cropping
patterns in this area include substantial acreages of vegetables, grapes,
and citrus fruits as well as cotton, grains, and forage. Pumping lifts
generally were 300 feet or greater. Rates of decline in the water table
were quite high, with the bulk of these areas declining at a rate of 7
feet or more per year. Water quality was quite good, with moderate
=punts of total dissolved salts, and the rate of water application
per acre of crop grown was somewhat less than in Area A.
Water Quality
Data collected in the farm survey indicated that the amount of
water used to grow an acre of a particular crop was approximately 15
percent higher in Area A than in Area B. Two factors seemed to account
for this difference. These were poorer quality water in Area A and
higher water costs in Area B.
33
Water quality with respect to salinity is evaluated by means of
electrical conductivity at a temperature of 25 degrees centigrade.
According to Smith, et al. (1964:4), "waters in the conductivity range
of 750 to 2,250 micromhos (500 to 1500 parts per million) may be used
satisfactorily, provided good management is practiced, internal drainage
of the soil is good, and salt-sensitive crops are avoided." Citing
Richards, et al. (1954), Smith, et al. (1964:4) go on to say that "most
irrigation waters which have been used successfully for a period of years
have conductivity values less than 2250 micromhos/cm. (1500 parts per
million). Waters having higher conductivity values may be used occa-
sionally, but unless drainage is exceptionally good and sufficient
water is available for leaching purposes, disappointing results may
be expected."
- Most chemical analyses of irrigation waters reported by Area A
farmers ranged from 1,000 to 3,500 parts per million (PPM) of total
dissolved salts and averaged approximately 2,500 PPM. The majority of
Area B operators reported salt contents in the 500 to 1,200 PPM range
with an average of 850 PPM. Reference to a diagram classifying irrigation water according to salinity hazard (Smith, et al., 1964:13) indicates that Area A irrigation waters fall in the high to very high
salinity hazard class 'while most Area B waters present a medium to high
salinity hazard. The higher salt content made it necessary for Area A
farmers to apply more water to leach excess salts out of the plant root
zones to avoid or reduce detrimental effects on crop production. They
also incurred extra costs for chemicals added to the irrigation water
periodically to facilitate salt leaching.
34
The second reason for the substantial difference in water appli-
cation rates between areas is the higher cost of water in Area B due to
the greater depths from which groundwater has to be pumped. Average
pumping lifts in 1967 for all water situations in Area A were less than
300 feet whereas Area B average lifts were all in excess of 300 feet with
several subareas pumping from depths greater than 500 feet. The higher
cost of water placed greater pressure upon Area B operators to conserve
water through more careful control of quantities applied to fields as
well as through increased investments in water distribution facilities
such as concrete ditch lining, tail water return systems, pipe lines,
and shorter field runs as reflected in more miles of ditch per acre of
cropland in Area B (Hock, 1971:Table 4).
Water Supply Situations
Having explained the basis for dividing the groundwater study
region into two major water resource areas, it remains to describe the
various water supply situations encountered within each water resource
subarea. In general, the water situations correspond to the water
resource subareas described earlier and pictured in Figure 5. However,
some farmers in the Buckeye Irrigation District (BID), Roosevelt Irrigation District (RID), and Arlington Canal Company (ARL) service areas
in Area A, and in the Maricopa County Municipal Water Conservation
District Number One (MAR) in Area B have their own farm wells in
addition to district water rights. This creates an additional water
situation to be dealt with in each of these areas.
35
The code letters used to designate each water situation in tables
to be presented hereafter and the source or sources of irrigation water
for each water situation are presented in Table 2.
Buckeye Irrigation District (BID)
This district holds adjudicated rights to normal flow water from
the Gila and Agua Fria Rivers but this is an erratic and undependable
supply which for years has not approached the annual limit to which the
district is legally entitled. The company also has a contract under
which it receives 1.1 percent of the Salt River Project diversions made
for agricultural purposes at its Granite Reef Dam. The SRP delivers
this water to the Buckeye district upon demand (Goss, 1968:56). The
district has also been obtaining sewage effluent from the City of
Phoenix. However, these sources only average about 20 percent of the
district's annual water deliveries. The remaining 80 percent is supplied
from 48 wells located within the district boundaries. There are also
between 15 and 20 privately owned wells in the district.
Due to some difficulty experienced in supplying customers with a
large enough head of water in the summer months, the district uses a twoprice system for selling water whereby summer water (April through
September) is priced higher than winter water (October through March).
In 1967 the respective prices were $2.75 and $2.25 per acre-foot. This
system is used to encourage farmers to keep water orders to a minimum
during the summer peak demand period. In addition to the water charge
per acre-foot, there is a basic assessment of $2.00 per acre of land in
the district.
36
Table 2. Water Situation Code and Source of Water, Areas A and B.
Code
Source of Water
Area A
BID
Buckeye Irrigation District
BIDW
Buckeye Irrigation District plus farm wells
Roosevelt Irrigation District
RID
RIDW
ARL
ARLW
SRV
ARV
GB
Roosevelt Irrigation District plus farm wells
Arlington Canal Company
Arlington Canal Company plus farm wells
Farm wells in the Salt River Valley south of the Salt
River Project and BID Service areas a
Farm wells in the Arlington Valley or Lower Centennial
Wash Area of the Salt River Valley a
Farm wells in the Gila Bend Basin along theb Gila River
between Gillespie Dam and Painted Rock Dam
Area B
MAR
Maricopa County Municipal Water Conservation District
Number 1 (MCMWCD #1)
MARW
MCMWCD #1 plus farm wells
ADAM
Adaman Mutual Water Company
LMP
Farm wells around Litchfield Park, Marinette, and
Peori a ac
AGA
HAR
Farm wells in the McMullen Valley near Aguila d
Farm wells in the Harquahala Valley e
TON
Farm wells in the Tonopah area a
RAN
Farm wells in the lower reaches of Waterman Wash locally
known as Rainbow Valley f
CRK
Farm wells in the Queen Creek-Higley-Gilbert-Magma area
of the Salt River Valley between the Roosevelt Water
Conservation District and the Final County line a
a. For a complete description of the Salt River Valley by
aquifer subarea see White, Stulik and Rauh, 1964, pages 9-17 and
Figures 2 and 3.
37
Table 2. (continued)
Footnotes (cont'd)
b. See Stulik and Mooseburner, 1969 for maps and description
of hydrologic characteristics of the basin.
c. This water situation covers farms located primarily between
the Salt River Project and MCMWCD #1 service areas. For a detailed
description of hydrologic characteristics see Kam and others, 1966.
d. Briggs, 1969.
e. Stulik, 1964.
f. Denis, 1968.
38
Roosevelt Irrigation District (RID)
The entire water supply for the RID is obtained from 101 district-owned wells. Fifty-four of these wells are located east of the
Agua Fria River in the Salt River Project Service area. Originally the
wells were drilled to alleviate a serious drainage problem existing in
that area in the early 1920's and there was no limit on the amount of
water which could be pumped. However, since 1950 the agreement between
the two districts limits the amount which can be pumped to 155,000 acrefeet per year and a maximum of 725,000 acre-feet in five consecutive
years. In addition to 47 district wells, there are approximately 65
privately-owned wells within the district boundaries.
Salt content of water from district wells ranges from 500 to
6,000 PPM. As a result, the district has a dual price system based upon
water quality. In 1967 the prices were $5.00 per acre-foot for water
with less than 2,500 PPM of dissolved salt and $3.50 per acre-foot for
water containing more than 2,500 PPM. In addition, lands in the district are charged a basic assessment of $4.88 per acre per year.
Because of water shortages, the district also invokes a "prorate" system during the summer months. Each farmer may receive up to
4 inches of water per acre every 16 to 21 days, depending upon the
acreage of crops by type being grown in any particular year.
Arlington Canal Company CARL)
The ARL obtains some surface water in the form of return flow to
the Gila River from the Buckeye Irrigation District upstream. Some flood
water is also occasionally received. However, the major portion of its
water is pumped from nine wells operated by the company.
39
The river water has a high salt content and was priced at $1.50
per acre-foot in 1967. Water supplied from wells was priced at $3.50
and there was a basic assessment of $2.00 per acre on all irrigable lands
in the district. The company did not find it necessary to prorate water.
Some farmers in the district also have their own private wells.
Maricopa County Municipal Water Conservation
District Number One (MCMWCD #1)
This district obtains some of its water from Lake Pleasant on
the Agua Fria River. However, the annual supply fluctuates widely and
averages only about 20 percent of total water use in the district. The
remaining 80 percent is pumped by 57 district wells. There are also 62
privately owned wells in the district.
Pumping lifts in some parts of the district were over 500 feet
in 1967 and water yields have been declining for years. As a result,
farms in the district were alloted .15 acre-feet per acre per month
throughout most of the 1960's. Surface water is reserved for use during
the peak demand period from July to September and is prorated among
users on the basis of the annual available supply.
Water was priced at $10.00 per acre-foot regardless of source
until 1966 and then lowered to $9.00 per acre-foot in 1967. The basic
assessment per acre was $9.00 per acre.
Adaman Mutual Water Company (ADAM)
All water used on the 2,493 acres in this district is supplied
from district wells. There is about one well for every 160 acres in the
district. These wells have in the past produced an adequate supply of
water and no prorate was necessary prior to 1967. Water charges in 1967
40
were $10.00 per acre-foot for water and $6.457 per acre basic assessment
on lands in the district.
Privately Owned Farm Wells
With the exception of the Adaman Mutual Water Company, privately
owned wells on farms supplement the water supplied by each of the irrigation districts in the study region. In these districts two on-farm water
supply situations exist. Some farms obtain water only from the district
and must operate within whatever limitations on water deliveries the
district finds it necessary to impose. Other farms possess the same
water rights per acre with respect to the availability of district water
but also have wells of their own. This gives these farmers a larger
total supply of water per acre and greater flexibility in their cropping
pattern adjustments. Hence, as indicated in Table 2, two water situations
are dealt with in each of these four irrigation districts.
The remaining nine water resource areas in the groundwater study
region all depend solely upon privately owned farm wells as a source of
irrigation water. However, each of these is located over an individual
aquifer or subarea of the Salt River Valley aquifer which has distinctive characteristics with respect to depth of water, rate of decline in
the water table, and cost of pumping. Each of these also represents a
separate water supply situation, making a total of 18 separate situations
dealt with in this study.
CHAPTER III
THE REPRESENTATIVE FARM MODELS
Experience has shown that operating units with similar characteristics tend to respond to a given stimulus in very much the same way.
This makes it unnecessary to project adjustments for a large number of
units on a case by case basis and then sum the results for all units to
obtain an accurate picture of what is likely to occur in the aggregate.
Instead, it is possible to separate the study population into groups
possessing similar characteristics and to synthesize a model unit for
each group possessing only those structural characteristics relevant
to the problem being studied and which are typical of the group. Projected adjustments for such a representative model, if properly constructed, can be expanded to cover all units in the group and projections
by group can then be aggregated to give an accurate representation of
what would take place for the entire population studied.
Criteria and Procedure for
Farm Model S ecification
When identifying a representative model, it is important that
the population studied be grouped on the basis of those factors or characteristics which are likely to most strongly influence the outcome of
the decision-making process being examined. With respect to farms in
Central Arizona, such factors may be size of farm, soil fertility, availability of labor, capital, and irrigation water, education or management
41
42
ability of the operator, and acreage allotments or other factors
affecting the amount and type of crops included in the enterprise mix.
Ideally, sufficient information concerning each relevant factor
should be available prior to sampling to permit determination of the
stratification to be dealt with in the final analysis. In this study,
however, information was not available concerning all of these factors
and the sample was drawn primarily on the basis of farm size in terms of
cropland acres. Cropland acreage was chosen over total farm acreage as
the unit for measuring size because it appeared that cropland acres were
more closely related to crop allotments and would serve as a better proxy
for other variables which affect economies of size in production. Hence,
farms were arrayed according to cropland acreage and a 20 percent sample
drawn according to the procedure described in Chapter I.
As indicated in Chapter II, preliminary examination of survey
data arrayed on the basis of cropland acreage revealed significant differences in farm characteristics with respect to source, quality, cost,
and quantity of water used, and crop enterprise mix. Given this diversity, the sample farms were divided by water resource areas and again
arrayed by cropland acreage. This time the data displayed patterns with
respect to crop enterprise mix and a significant correlation between
cropland acres and four other factors of production which influence
economies of size in production. These factors were: number of wheel
tractors, number of crawler tractors, number of full-time hired
laborers, and number of hired supervisors.
Nine different farm models were specified, four in Area A and
five in Area B. By inspection, several sets of possible breaking points
43
were identified for stratification of farms in each study area. These
possible breaking points were based upon cropland acreage but the other
four factors were then used to determine the final strata boundaries.
Analysis of variance was used to determine the within-group
variance of each possible set of breaking points for each of the five
variables. The possibility sets were numerically ranked for each variable based on the sum of within-group variances for each set. The best
ranking was assigned to the set with the lowest sum of within-group
variances for a given variable. The five rankings for each possibility
set were then compared with those for each of the other sets of possible
farm size groups. The set with the greatest number of "best" rankings
was selected as the basis for developing representative farm models in
each area. This procedure served to further increase the homogeneity
of characteristics of farms in each size group within the two areas.
Representative farm model size, aggregate cropland acreage, and number
of sample farms by farm size groups for Areas A and B are presented in
Tables 3 and 4.
Once the farm models had been specified it remained to determine
the number of farms in each size group by water situation. This was
done by using information from the ASCS list of farms from which the
study sample was drawn, irrigation district lists of water users which
showed the total acreage of farms eligible for district water, and
information gathered in the course of the farm survey concerning the
proportion of total cropland in sample farms by location. The latter
information was necessary because some farms combined land in two irrigation districts or an irrigation district and one or two areas overlying
44
Table 3. Farm Model Size, Cropland Acreage, and Number of
Sample
Farms, Area A.
Farm
Size
Group
Cropland
Acreage
Range
Farm
Model
Size
Aggregate
Cropland
Acreage
Number of
Farms in
Sample
acres
II
30-325
160
13,972
11
326-700
540
29,592
16
III
701-2,800
1,200
60,151
14
IV
Over 2,800
9,500
36,780
2
Table 4. Farm Model Size, Cropland Acreage, and Number of Sample
Farms, Area B.
Farm
Size
Group
Cropland
Acreage
Range
Farm
Model
Size
Aggregate
Cropland
Acreage
Number of
Farms in
Sample
acres
II
30-250
130
8,851
8
251-610
430
15,981
8
III
611-1,435
1,000
41,225
11
IV
1,436-2,800
2,200
38,843
7
V
Over 2,800
6,000
85,941
7
45
other groundwater aquifers. Tables 5 and 6 show the number of farms by
representative farm model size and water situation used in this analysis.
The 195 and 215 farms shown for Areas A and B respectively closely
approximate the number of farms and cropland acreages found using the
various sources described above.
Characteristics of Model Farm Resources
A detailed description of all major production resources, procedures, costs, and returns by farm size and crop enterprise can be
found in Hock (1971). Normally this type of information would be included as an appendix to the dissertation. However, because much of
the detail regarding production inputs and procedures may be of interest
to others, but not readily available elsewhere, and because of the large
volume of material involved, it was reproduced as one of a series of
File Reports by the Department of Agricultural Economics. Copies are
available from the Department upon request. While not formally a part
of this dissertation, the File Report is frequently referred to and
appropriate parts are extracted for further discussion here. The File
Report should be considered a supplement to this dissertation.
The remainder of this chapter will be devoted to a brief review
of the relevant characteristics and assumptions regarding the major
production resources, enterprise combinations, costs, and returns for
the representative farm models. Data developed here and in the supplemental report provide the production coefficients and revenue coefficients utilized in the linear programming models discussed in Chapter IV.
46
Table 5. Number of Farms by Farm Model Size and Water Situation,
1967, Area A.
Water
Situation
Farm Model Size
160
540
1,200
9,500
acres
BID
24
7
BIDW
27
3
9
RID
9
11
10
27
18
5
RIDW
ARL
3
ARLW
3
SRV
1
1
10
ARV
13
GB
11
3
Table 6. Number of Farms by Farm Model Size and Water Situation,
1967, Area B.
Water
Situation
Farm Model Size
130
430
1,000
2,200
6,000
acres
MAR
4
MARW
20
ADAM
18
LMP
12
8
15
30
15
1
5
2
AGA
HAR
TON
11
18
11
3
6
1
3
1
5
2
9
RAN
CRK
4
11
47
Land
It is recognized that soil type, slope, texture, water, holding
capacity, and natural fertility levels may differ substantially throughout the study region. However, survey data showed these differences
to be as great within a farm as between farms or between areas of the
study region. Moreover, past and current management practices such as
land leveling, ripping, and addition of organic matter and fertilizer
have in many cases reduced the differentials in yield obtained from
various soils.
What differences in yield remained more often seemed to be
related to management or other factors rather than differences in soil.
Therefore, it is assumed that all lands in the study region are homogeneous with respect to productive capacity.
Irrigation Water Distribution Facilities
Significant differences in facilities were found both between
farms of similar size ranges in Area A and Area B, and among farms
within a given size group within each area. These differences may be
due to one or more of several factors which include but may not be
limited to: differences in hydrologic characteristics of the aquifer
or subaquifer over which the farms are located, the period of time an
area had been in agricultural production, existence or lack of an
organized irrigation district from which farms may obtain water,
limitations on quantity of water available from district sources,
presence or lack of institutional restrictions on irrigation well
drilling, differing water requirements of various crop enterprise
48
mixes, soil texture and rate of water absorption, and source of power
for pumping.
Miles of irrigation ditches and pipelines per farm and per acre,
percent of the distribution system consisting of concrete lined ditches
or pipelines, and investment per acre of cropland are shown in Table 7.
Farms in Area B were found to have approximately 70 percent more miles
of ditch per acre than Area A farms. Some type of pipeline for delivering water to fields, either from irrigation wells or tailwater
collection sumps, were typically found on Area B but not Area A farms.
Tailwater return systems were found on Area A farms, but were not
prevalent enough to be considered a typical facility for any of the
four farm size groups when interviewed in 1964.
Not only did Area B farms have more miles of delivery systems,
but more of the system was concrete lined ditches or pipe lines rather
than dirt ditches. In Area A, 42 to 70 percent of the ditches in the
four farm size groups were lined with concrete. In Area B, percentages
ranged from 52 to 92 percent by size group. As a result of having more
ditches and more of them lined with concrete, investment per acre of
cropland was two to almost four times as great on Area B versus Area A
farms. In both areas the lowest investment per acre was found in the
largest farm size groups. However, to some extent this was offset by
substantial investments in large earth-moving equipment shown in the
machinery inventories for large farms (Hock, 1971). Among other things,
this heavy machinery was used to build and rebuild dirt ditches. It
would appear that one of the areas where large farms may achieve significant economies of size is by only lining frequently used head
49
Table 7.
Farm
Model
Size
Inventory of Irrigation Water Distribution Systems for
Typical Farm Models, Areas A and B.
Irrigation Ditches
and Pipeline
TotalaPer Acre
Acres
Percent
Concrete
Ditch or
Pipeline a
Miles
Investment
Per Acre
of Cropland a
Dollars
Area A
160
1.1
.007
55
25.75
540
4.3
.008
70
38.14
1,200
8.0
.007
68
30.89
9,500
61.9
.007
42
18.58
130
2.2
.017
77
95.87
430
4.6
.011
74
55.26
• 1,000
10.1
.010
90
66.16
2,200
15.4
.007
92
43.56
6,000
74.5
.012
52
43.36
Area B
a. Miles of concrete and dirt ditches, miles of pipeline, and
total investment per farm are shown in Table 4 of Hock (1971).
50
ditches and laterals, utilizing some of the capital not invested
in other
ditches for equipment to maintain them, and using the remainder to
ftlance
other investments where the marginal return on investment is greater.
Irrigation Wells
Because water availability and costs were the critical elements
in this study, farms in each size group were differentiated according to
water situation based upon source or combination of sources used to obtain irrigation water. These various water situations were described in
Chapter II and summarized in Table 2. Only those situations using onfarm wells to supply part or all of their irrigation water will be
discussed here.
Tables 8 and 9 present information on number and depth of wells
and investment per well and per cropland acre by farm size group and water
situation. Those situations ending in the letter W are farms located in
an irrigation district which use on-farm wells to supply water on additional lands they operate outside of the district boundaries or to
supplement the supply obtained from the district on their lands within
the district boundaries. All other situations rely solely upon farm
wells for irrigation water.
Number of wells per farm is primarily affected by the availability or lack of district irrigation water and the rate at which the
aquifer yields water. Generally more wells per farm were found in CRK,
MARW, and LMP situations in Area B where water yields in gallons per
minute usually were lower than other areas. Areas with coarser sediments in the strata from which water was being pumped yielded water
51
Table 8. Selected Irrigation Well Data by Farm Size Group and Water
Situation, Area A.
Farm Size and
Water Situation
Number
of Wells
Depth
Drilled
Feet
160
Investment
Per Well
Per Acre
Dollars
Acres
BIDW
1.0
560
16,882
105.51
RIDW
1.0
720
23,706
148.16
BIDW
2.0
478
15,516
57.47
RIDW
2.0
772
25,144
93.16
ARLW
1.0
500
17,812
32.99
SRV
2.0
355
13,117
48.58
BIDW
3.0
450
15,297
38.24
RIDW
4.0
728
25,066
83.55
ARV
4.5
645
32,475
121.78
GB
7.5
583
23,562
147.26
RIDW
28.0
787
26,394
77.79
GB
34.0
693
24,967
89.36
540
Acres
1,200
9,500
Acres
Acres
Source: Table 6, Hock (1971).
52
Table 9. Selected Irrigation Well Data by Farm Size Group and Water
Situation, Area B.
-------Farm Size and
Number
Depth
Investment
Water Situation
of Wells
Drilled
Per Well
Per Acre
Feet
130
Acres
MARW
LMP
TON
430
Dollars
1.0
1.0
1.4
950
650
1,035
37,522
32,380
33,316
288.63
249.08
358.78
2.0
2.0
3.0
2.0
1,125
602
617
985
40,610
34,288
28,152
51,588
188.88
159.48
196.41
239.94
1.7
5.0
4.0
3.0
5.0
1,002
983
1,329
1,500
873
42,288
36,085
59,068
49,917
43,869
71.89
180.43
236.27
149.75
219.35
5.0
5.5
5.0
9.0
1,430
945
964
933
45,795
57,752
48,708
44,562
104.08
144.38
110.70
182.30
17.0
37.0
16.0
15.0
20.0
15.0
1,012
793
1,500
1,400
1,154
787
41,888
35,253
61,255
48,622
48,045
43,960
118.68
217.39
163.35
121.56
160.15
109.90
Acres
MARW
LMP
TON
HAR
1,000
Acres
MARW
LMP
HAR
AGA
CRK
2,200
Acres
MARW
HAR
RAN
CRK
6,000
Acres
MARW
LMP
HAR
AGA
RAN
CRK
Source: Table 7, Hock (1971).
53
faster and required fewer wells to capture an
equivalent amount of water
in a given period of time.
Costs of wells are very closely related to depth drilled and, to
a lesser extent, to the depth from which the water is being pumped.
Three water situations, Arlington Valley (ARV) in Area A and the Harquahala CHAR) and Rainbow (RAN) Valleys in Area B, also have higher well
investments because in these areas natural gas engines were typically
used to pump water rather than electric motors (Hock, 1971, Tables 6
and 7). The natural gas engines were more expensive to purchase but
variable cost of the gas was less than that for electricity to run
pumps operated by electric motors (Nelson and Busch, 1967 and Lamoreaux,
1966).
Farm Buildings
Building inventories for the typical farm models were synthesized
from data obtained from each of the sample farms surveyed. Individual
sample farm inventories varied considerably within size groups with
respect to number and type of buildings and the purpose for which they
were used. Part of this variation reflected differences in the period
of time various areas had been developed for agricultural production.
Areas such as the Harquahala Valley, McMullen Valley, and Rainbow Valley
had undergone large scale expansion of lands devoted to crop production
as recently as 5 to 10 years prior to the farm survey. Hence the character of farm buildings in such areas was closely related to current
enterprise mix and methods of production. Lands in the Salt River Valley,
however, had been in agricultural production much longer. Many individual operating units had undergone a great deal of transformation as farms
54
were consolidated to achieve economies of size or were reorganized to
accommodate new enterprises. Many of these farms had buildings which
were no longer used or had converted buildings to uses other than that
for which they were originally constructed. Particularly evident was
a surplus of housing for hired labor created as production was increasingly mechanized.
Most operators placed a very low value on such buildings and
indicated that many of them would not be replaced. Therefore, when
farm model building inventories were synthesized, buildings not
currently in use and not expected to be replaced were excluded from
the model farm building inventory. Also excluded were barns, corrals,
and other structures used in connection with livestock enterprises
which are relatively small direct users of water and hence were
excluded from this analysis.
Almost all farms had some type of building used as a farm shop.
Most size groups also had one or more buildings designated as storage
sheds. The majority of operators in all but the 160 acre size group
of Area A indicated they were maintaining and would replace one or
more units for housing hired labor. However, a definite trend to replacing permanent types of structures with mobile home units was
evident. Housing for hired supervisors was typically present only on
farms with 1,000 acres or more and only the largest farms in both
Area A and B typically had farm office buildings. A few farms in the
1,000 acre size group in Area B also had office buildings but not
enough of them to consider it a typical structure. Farms in that size
group having an office building invariably were those specializing in
55
the production of vegetable crops. A detailed breakdown of typical
inuse building data for Area A and B farm models is presented in Table 8
of Hock (1971). Building values by representative farm model
are
presented later in this chapter.
Machinery and Custom Operations
A complete inventory of machinery by type and size synthesized
from farm survey data is presented for each representative farm model
in Tables 9 through 17 of the supplemental report (Hock, 1971). These
machine inventories provide the basis for selecting implements and
power units for the various operations indicated in the crop enterprise
budgets discussed in the next section of this chapter. If a required
machine did not appear in a farm inventory, the operation was assumed
to be done on a custom basis. Operations typically performed on a
custom basis are shown by farm size group in Table 18 of the supplemental report (Hock, 1971).
Consistent with the overall assumption of ceteris paribus, it
is assumed that this machinery inventory and costs of machine operation
remain constant throughout the period covered by this analysis. Fixed
costs of machinery are presented in the section of this chapter on costs
and returns.
Labor
In addition to the assumption that wage rates will remain constant throughout the study period, it is also assumed that sufficient
quantities of all classes of labor can be employed at the prevailing
rates. A complete description of the five classes of labor employed
56
and wage rates paid them is presented on page 38 and in Table 21
of the
supplemental report (Hock 1971).
)
Capital
In reality a variety of capital sources are available and indiv-
idual farm operators may obtain more funds only by paying higher interest
rates. However, for purposes of this study, it is assumed that an average efficiency for obtaining capital prevails among farm operators in
the aggregate. No overall shortages of capital were disclosed by the
farm survey and the assumption is consistent with previous assumptions
regarding constant prices for production inputs.
Management
While management abilities may vary significantly, particularly
between farm size groups, the various levels of ability had been to a
large extent sorted in the process of farm size classification. There-
fore, it is assumed that management for each of the farm models is uniformly capable of achieving the specified levels of output and technology
and that an adequate supply of management talent will continue to be
available.
Alternative Crop Enterprises
Differences in cropping patterns between Areas A and B of the
study region were described in Chapter II. Substantial differences in
crop enterprise combinations also existed within and between farm size
groups in the two areas, especially in Area B. Table 10 shows the
various crop enterprises which were found to be grown in significant
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quantities by farm size groups in each area. However, all crops listed
as alternatives for a group were not grown by every farm in that group.
In Area A, most farms in all size groups grew a combination of
cotton, alfalfa, and one or more grains, with the larger farms being
most diversified. In Area B, the tendency to specialize was more evident,
especially among the smaller farms. Several of the smallest farms in
certain water situations grew only cotton. Many grew one of the other
crops for the 130 acre farm size group shown in Table 10 in competition
with cotton, but few of them grew more than two crops. In the 430 acre
size group, some farms located in the Harquahala Valley were growing
grain or alfalfa exclusively or a combination of the two because they
had no cotton allotment and lacked some essential production or marketing input necessary to grow grapes or vegetables. Many farms in the
1,000 acre size group specialized in vegetables and cotton. Other
1,000 acre farms were highly diversified as were the 6,000 acre
operations.
Likewise, not all crops were grown in all water situations.
Sugar beet production centered in the BID, RID, RAN, and CRK water
situations. Vegetables were concentrated in the MARW, ADAM, LMP, and
CRK situations in the Salt River Valley and in the Harquahala Valley
CHAR). Citrus was grown in the Rainbow Valley (RAN) in addition to
the four areas of the Salt River Valley just named. Grape production
centered in the ADAM, MARW, TON, and HAR water situations.
Costs and Returns
Per acre unit budgets including a complete calendar of operations, units of inputs, costs and returns for each crop grown on farms
59
represented by each typical farm model are found in the supplemental
report (Hock, 1971:Tables 27-144). The unit budgets are accompanied by
a detailed explanation of various factors affecting inputs, costs and
returns which will not be dealt with here. Only major assumptions and
methodological procedures are discussed herein along with summaries of
the relevant data concerning costs and returns associated directly with
each crop enterprise, plus certain fixed costs which enter into the
linear programming models discussed in Chapter IV.
Yields, Product Prices, and Gross Returns
Crop yields used in preparing the unit budgets were obtained
primarily from farm survey data. These yields were checked against
data from other sources such as the Arizona Agricultural Statistics
(1966, 1967, and 1968), Arizona Aarisulture (1959-1970), and Arizona
Fruits and Vegetables (1962-1967). In most cases the reported crop
yields from various sources were quite comparable. However, where
published sources indicated substantial variation in yields from year
to year as was the case with safflower and vegetable crops, an average
of the most recent 3 to 5 years was taken as the basis for developing a
budget for that crop. If a definite upward trend in yields was evident
then the yield of that crop was adjusted for trend by using the higher
yields reported for the study region or area rather than the average.
In this case, the calendar of operations and inputs utilized in pre-
paring the unit budgets were those which corresponded to the higher
yields. Likewise, if a definite trend in technology was evident from
the farm survey, such as rapid adoption of precision planters by farmers
60
in the larger size groups for planting cotton, this was incorporated
into the crop budgets where pertinent.
Only one level of output is specified for each crop enterprise.
Production theory indicates that optimum input-output ratios vary with
the availability and cost of inputs. However, this relationship was
not evident in the region even though water costs ranged from less than
$3.00 to $10.00 per acre-foot between water situations.
Hobart and Harris (1950) found that a diversified crop enterprise
mix gave the greatest returns from a given available supply of water.
"However," (they observe) "with reduced water supplies (and no possibility of increase) careful reduction of acreage will result in greater
total production from the limited water, than if this were spread over
the entire land holding." When faced with water shortages the farmers
interviewed followed this principle by dropping enough of the lowest
value crop competing for water during the critical use period to permit
maintaining water application rates on the remaining acreages.
When faced with sufficiently high water costs, farmers apparently
reacted first by lining ditches, installing sumps and pumpback systems,
leveling fields, and shortening the length of fields by installing more
ditches or pipelines. These measures reduced water losses from seepage
in ditches, from tailwater run-off at the ends of fields, and from percolation of water below the plant root zones within the fields. However, they did not reduce the amount of water made available to the
growing plants. When water costs became high enough to push total
variable costs above returns for a given crop, the crop was dropped
61
from the enterprise mix rather than attempt to produce it at lower wateryield levels.
In effect, these farmers were acting as if they had found a
single optimum per acre level of water use for the various crops grown,
given the physical, technological, and economic conditions under which
they were operating. Information gleaned from at least one enterprising
manager, operating under conditions of both scarcity and high cost of
water, who was willing to risk substantial loss by experimenting, indicated that it was economical to reduce water application rates on
cotton and grapes. Nevertheless, almost all operators interviewed acted
as if this could not be done or they were unwilling to risk possible
financial loss to find out how far it could be carried. Therefore,
since the purpose of this study is to project farmer's responses to
increasing water costs, it is assumed that they will continue to react
to increasing water costs by reducing acreage of the lowest value crop
competing for water rather than decreasing water application per acre.
Product prices used in the budgets are those reported in Arizona
Azriculture (1967) and Young et al. (1968) except where recent historical data showed substantial fluctuations in price for a crop. In such
cases an average price is used. Government price support and acreage
diversion payments are included as a separate item when calculating
gross returns. A summary of yields, prices and gross returns for each
crop grown in Areas A and B are presented in Tables 11 and 12,
respectively.
62
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Net Returns Over Variable Costs
Variable costs are those costs directly related to the production
of a specific crop. In addition, certain other costs are incurred which
are not directly allocable to specific crops but vary with the crop
enterprise mix and total level of farm operation in the short run. They
include supervisory labor, transportation, and various other miscellaneous costs which must be covered so long as the farm continues to operate. These additional costs, called cash overhead costs, were broken
down using various criteria and added to the direct costs in the unit
budgets to obtain total variable operating costs per acre for each crop
enterprise. Total variable operating costs subtracted from the gross
returns provides net returns per acre. These quantities are summarized
for each crop enterprise by farm size group in Tables 13 and 14.
Because the cost of water changes over time in this analysis,
it was not included in the total variable operating costs developed in
the unit budgets. Instead, water cost is brought into the analysis as
a negative quantity in the objective function of the linear programming
matrices at a different level for each time period considered. Hence,
the net returns over variable costs per acre shown in Tables 13 and 14
will be reduced by successively larger amounts equal to the cost of
water for each acre of crop grown in the linear programming models as
water costs increase over time.
The net returns in Tables 13 and 14 do not always show economies
of size in all enterprises. Larger farms frequently used power-driven
machines to perform certain operations which were more costly than the
method used by smaller farms or the saving they effected with one
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operation was largely offset by additional costs of another type. Furthermore, some economies of size known to occur due to large scale
purchase of inputs and sale of products could not be built into the
representative farm models because it could not be determined at what
size of operation these economies became operative and in what magnitudes they occurred. Finally, farm survey data indicated that the size
II farms (430 acre model in Area B and the 540 acre model in Area A)
usually employed one general farm worker to perform all types of labor
operations, including crop irrigation while other farm size groups
hired temporary or permanent irrigators at lower wage rates. Hence,
on crops where irrigation labor constituted a significant portion of
variable operating costs (primarily grain crops) size II farms showed
smaller net returns per acre over variable operating costs than did
size I farms.
Dividing the net returns over variable costs per acre by the
acre-feet of water used per acre, yields net returns per acre-foot of
irrigation water. This in effect represents the breakeven price or the
maximum amount a farmer can afford to pay for water used on any given
crop before total variable costs equal total revenues with no returns
to the fixed factors of production. Water use per crop and net returns
over variable costs per acre-foot of water are presented in Tables 15
and 16 for crops grown in Areas A and B, respectively.
Fixed Costs
Fixed costs are those costs which are incurred so long as the
basic farm unit exists regardless of the level of crop output. They
cannot be varied within the short run period of time represented by
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the normal cropping season or yearly production period for a double
crop
system. In the long run the size of the farm unit can be changed
and
all costs become variable. However, this study is concerned with the
action of farmers in the aggregate, not as individuals. Therefore,
fixed resources will always exist so long as agricultural production
continues to take place in the study region.
Fixed costs which are of a common magnitude for all farms
represented by each typical farm model are presented in Tables 17 and
18 for Area A and B farm models. Each farm represented by the model
typically incurred these costs regardless of the water situation in
which it was found. However, the source of water supply strongly
affected fixed costs of a farm operation. Farms relying solely upon
farm wells for their irrigation water had annual amortization and tax
costs on wells. Those getting all their water from an irrigation
district paid annual assessments on all lands in the district. Others
incurred both types of charges if they had wells in addition to district water rights. Furthermore, assessed valuations of land for
property taxes varied significantly by water resource area. These
various types and magnitudes of fixed costs by farm size group and
water situation are shown in Tables 19 and 20 for Areas A and B of the
study region. Total annual fixed costs by farm size and water situation are also shown in Tables 19 and 20.
•
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CHAPTER IV
THE LINEAR PROGRAMMING MODEL
The purpose of this study is to determine the approximate nature
and magnitude of adjustments in crop enterprises, resource use, value of
output, and net returns in response to increasing water costs, a declining cropland base, and increased availability of cotton allotments to
remaining farm operations. The study is conducted under the assumption
that all conditions affecting farm operations will stay constant at the
1967 level except those mentioned above. It is further assumed that
the overriding motivation governing the actions of farm operators is
the desire to maximize economic returns to limited resources. While
individuals may deviate from this goal, farmers as a whole do not.
In the long run, the unprofitable firms are replaced by those who can
survive by seeking to maximize profits.
If only a few resources and alternative enterprises are involved, the optimum allocation of resources can be determined by a
budgeting process. However, when large numbers of resources and
alternative uses are involved, budgeting becomes an unwieldy and inefficient means of determining optimum resource allocation. Linear
programming is a form of mathematical programming or activity analysis
designed to provide solutions to problems of what decision makers ought
to do under a set of prescribed conditions when the number of alternatives is large. Hence, it is well adapted to the problem of determining
81
82
how farmers seeking to maximize profits are
likely to adjust their crop
enterprise mix and resource inputs in response to an
anticipated set of
conditions defined by the availability and cost
of certain key resources.
Components of the Models
The linear programming (LP) models developed for this analysis
are composed of the following five elements: (1) an objective
function
consisting of the net returns from each activity, the sum of which is to
be maximized, (2) real activities which represent alternative methods of
obtaining the objective, (3) artificial activities providing for required
solutions and computational convenience, (4) disposal activities which
allow the nonuse of resources, and (5) restrictions specifying the
maximum quantities of resources available to the model.
The program employed for the models is Alphac, Version I,
developed by Thomas Zierer at the University of California, Berkeley
for use on the 6400 Control Data Computer. The usual format for an LP
matrix is followed, with column vectors representing alternative activities and resource constraints indicated by row vectors. The resource
constraint levels appear in the column vector referred to as the "right-
hand-side" and the objective function constitutes the top row of the
matrix. The supplemental report (Hock, 1971) contains two matrices
representative of those developed for farm models found in Areas A and
B of the study region.
Forty-three operational models were developed, one for each farm
size-water situation encountered in the study region. Nineteen of these
represented Area A and 24 Area B operations. The farm size-water
83
situations and number of farms represented by each operational model
are
shown in Tables 5 and 6 of Chapter III.
The Ob ective Function
The objective of the model is to determine the crop enterprise
mix which yields maximum economic returns from the resources available.
The objective function for any given farm model contains the net revenue
coefficients, excluding the cost of water, for each crop enterprise
available to the model. In addition, the objective function contains
the cost of water per acre-foot as negative quantities to be deducted
from net revenue as the optimum solution is obtained. The net revenue
coefficients, shown rounded to the nearest dollar in Tables 13 and 14,
remain the same throughout the period of analysis. Water costs increase
as depth to water increases with each succeeding time period.
Activities
The real activities in each model consist of the crop enterprises
shown in Table 10 for the farm size group corresponding to any given farm
size-water situation model. In addition to crop enterprises, which are
revenue-generating activities, the models also contain numerous water-use
activities. These water-use activities specify the per unit cost of
water by type or source of supply that is to be deducted from net reve-
nues generated by crop enterprise activities brought into the model.
Thus, the solution generates net revenue over total variable costs, including water costs. This procedure is necessary because water costs
entering the models change over time as pumping lifts increase. Therefore, water costs could not be deducted from crop enterprise budgets
84
before entering net revenue coefficients into the
linear programming
model. In addition to these real and artificial activities, each model
includes disposal activities which provide for the nonuse of resources.
Disposal of unused resource units balances use against the available
supply of each resource.
Restrictions
Restrictions are applied to each model for cropland, availability of water in total and by time of year, crop acreage allotments,
cropland diversion requirements imposed under the 1966 government program for support of short staple cotton prices, and crop rotations.
Only the cropland diversion requirement under the cotton program is
included as a numerical element in the linear programming models because
it remains constant throughout the analysis. Since all the other
restrictions may change each time the model is run on the computer,
these restrictions are brought into play between model runs by projection period. A discussion of the basic nature of these restrictions by type follows, and the manner in which they are changed between
projection periods is presented in the next section of this chapter.
Land Availability Restrictions
Total cropland available to each farm model in the 1967 base
year is equal to the farm model size in terns of cropland multiplied by
the number of farms. This conforms closely to the acreage in the farm
survey population for each size group and water situation less acreage
allocated to specialty crops not included in the crop enterprise alternatives for the model. Crops such as citrus, grapes, roses, and
85
miscellaneous vegetables are found in only a few water situations and
usually constitute only a small proportion of the total acreage where
they are found. Therefore, rather than include activities for these
operations in the basic model applied to each farm size-water situation,
the amount of land and water utilized by these crops are calculated for
each period and deducted from the total available before the model is
run through the computer. These types of crops occur in about half of
the water situations in Area B.
Water Availability Restrictions
Irrigation water available to each farm model is limited in
total by the water allotment per acre from district sources, if available to the water situation in question, and by total annual pumping
capacity of farm wells. Pumping capacities by farm size-water situation are based upon the number of wells available (Tables 9 and 10),
average well outputs reported in the sample farm data used to construct
the representative farm models, and a weighted average pumping time per
well of 3,760 hours per year calculated from data presented by
Lamoreaux (1966:46).
In addition, the total annual water supply available to a farm
model is restricted by five time periods during the year. The first of
these is a six week period from mid-January through February when water
demand is heavy for preirrigation of cotton and irrigation of winter
grains and vegetables. The remaining four water use periods consist of
the months of June, July, and August and a "remaining use" period
covering the remainder of the year.
86
The months of June, July, and August each constitute a separate
use period because of both supply and demand conditions. On the demand
side, June frequently found farmers pumping wells to capacity or using
all available district water for cotton, alfalfa, sugar beets, and a
last irrigation on some grains. July and August brought heavy demands
for water to irrigate cotton and late sorghum, or a preirrigation for
some fall vegetables (Hock, 1971:Tables 23-24).
Because of these heavy demands, the Roosevelt Irrigation District (RID) and Maricopa County Municipal Water Conservation District
Number 1 (MAR) apply a prorate which limits water deliveries per acre
during the summer months as described in Chapter II. In addition, the
MAR and the Buckeye Irrigation District (BID) each reserve their surface water supplies for the summer months when it is needed most. As
a result, the amount of water available per acre is substantially
greater for these water use periods than for other periods in these two
water situations. The BID also charges a higher price for water used
during the period from April through September. Therefore, restrictions on water supply available by time period and, where applicable,
by price of water are built into the linear programming models in an
effort to represent actual conditions as closely as possible.
Crop Enterprise Restrictions
Restrictions on crop acreages for the most part are established
at the 1967 base year level. Crops available to each model are those
found in the farm survey except for sugar beets grown for sugar which
were first grown in 1967. In the case of upland (short staple) cotton,
the acreage allotment available to the models is set at 65 percent of
87
the total allotment. This reflects the 35 percent reduction in acreage
made by farmers in response to the 1966 and 1967 government price support
and acreage diversion programs. Cropland diversion requirements and
acreage measurement rules under the program are accounted for in the
land use coefficients of the models rather than including them as a
separate activity. Construction of these elements of the linear programming models and the cotton budgets in the supplemental report (Hock,
1971) are based upon a complete description of the 1966 cotton program
presented by Pawson and Nelson (1966a).
There was no diversion or support payments program for AmericanEgyptian (long staple) cotton in 1967. However, government acreage
allotments and measurement requirements were in effect. These are also
accounted for in the LP models for the study.
Sugar beets had not been grown for sugar in Maricopa County for
many years. However, farmers grew their first crop for delivery to a
new processing plant in the County in 1967. Therefore, acreage allotments for sugar beets are entered in those farm models which could conceivably grow beets profitably based upon information concerning allotment allocations by area of the County obtained from the Spreckles Sugar
Company and production cost information found in Campbell, Pawson, and
Nelson (1965) and Pawson and Nelson (1966a) plus direct consultation with
these authors.
Safflower acreages in the study region had fluctuated widely
over the years preceding this study. Therefore, acreages entered in
the LP models are based upon the average of total acreages for the years
88
1963 through 1967 allocated proportionally among the models for farms
which had a history of growing safflower.
Restrictions on vegetable crops are set at the levels grown in
1967 or an average of previous years if wide fluctuations had occurred
in the past. These are high value-high risk crops whose level of production is determined by market forces of supply and demand. Therefore,
vegetable crop acreages had to be restricted to keep vegetables from
using most of the resources available to the models.
Wheat acreages are limited to those grown in 1967. A wheat
allotment program was in effect. However, farmers actions with respect
to wheat acreage grown seemed to be governed only partially by the program. Since wheat and barley are highly competitive with respect to
resources used, and since net revenue coefficients for wheat were
slightly higher than for barley, restrictions had to be imposed upon
wheat to keep it from forcing all barley out of the models. Current,
1973, conditions show that wheat is replacing barley. Since growing
practices, costs, and returns are quite similar between the two crops,
estimates of "barley" and "wheat" acreages could better be interpreted
as acreage of "small grains."
Initially alfalfa, barley, and sorghum crops were left unrestricted in the models. However, a preliminary test run of the base
year model showed that due to the drastic reduction in cotton acreages,
rather large surpluses of land and water resources were available to
the models. This resulted in acreages of unrestricted crops being blown
drastically out of proportion from what occurred in the real world where
large amounts of land were left idle, even in areas where these crops
89
could be grown profitably at prevailing prices. Apparently farmers were
unwilling to risk financial loss on these marginal crops by expanding
acreage too much.
As a result, acreage restrictions were entered into the models
which made maximum acreages of all crops conform to what existed in
reality. It was reasoned that most of the land and water development
had taken place in the past primarily for production of cotton. Therefore, with cotton acreages limited, some irrigation wells would not be
replaced and the marginal cropland would be dropped from production over
time in an effort to cut fixed overhead costs. This adjustment would
eventually bring land and water resource supplies into balance with
demands for them unless some unforeseen and unpredictable alternative
use for these resources came on the scene.
Projection Procedures
This section presents procedures used in making projections of
agricultural adjustments to changing resource availability and costs
over approximately a fifty-year time horizon. The initial step in the
process is the specification of (a) net revenues for each crop enterprise; (b) water costs by water situation, source of supply, and time
of use; and (c) the necessary restrictions on availability of cropland,
water, and crop allotments for the linear programming models to represent
real world conditions as closely as possible. Factors considered when
making these initial specifications for the 1967 base year were discussed in the preceding section of this chapter.
Solution of the models on the digital computer yield the acreages
of various crops which constitute the optimum enterprise mix, the gross
90
and net revenues obtainable from and the units of resources used by this
enterprise mix, and the marginal value product of output from the last
unit of each resource used. The quantities of groundwater used by all
farms in a given water situation are then aggregated and used to compute
the decline in the water table which has occurred and the cost per acre-
foot of pumping water at the new depth. The new water cost Is then
inserted in the model to be solved for the next ten-year time period.
This process is repeated until the entire time horizon of the study
has been covered.
In addition, several adjustments in resource restrictions which
are influenced both by factors endogenous and exogenous to the model run
for the preceding time period are made between runs. The remainder of
this chapter is devoted to a discussion of each of these factors and the
procedure used in making these adjustments between projection periods
of the study.
Urbanization of Cropland
The metropolitan area of Phoenix grew rapidly during the 1960's
and is expected to continue a high rate of growth. One study (John
Carollo Engineers, 1968:119) projects agricultural land diversions
by ten-year periods to the year 2000. These projections for the western
portion of the Valley Metropolitan Statistical Area were converted to
cropland acreage, using information from the farm survey concerning the
proportion of total farmland that constitutes cropland by farm size,
and extended to the year 2015 which was the last year for which pro-
jections were made in this study. These cropland acreages are deducted
from the total acreage available to the various models affected by
91
urbanization each time adjustments are made between computer solutions.
The farm models affected are all located in the MAR and LMP water
situations.
At the same time, a proportionate share of the groundwater
pumping capacity (irrigation wells) is transferred to urban use. Also,
a proportionate share of the long staple and short staple cotton allot-
ments in the model restrictions and the citrus acreage attendant to the
models are released for transfer to other areas of the study region.
Citrus, not being an activity included in the models, is arbitrarily
transferred to those water situations where it can be grown, and allocated among them on the basis of the proportionate amount of idle cropland and surplus water shown in the preceding time period solution. At
that time cropland available to the models receiving the citrus is reduced by an amount equal to the citrus acreage received. Water availability in total and by water need period is also reduced to allow for
consumption by the citrus acreage.
Cotton Allotment Transfers
At the same time that cotton allotments are being released from
also being reurbanized lands within the study region, allotments are
leased in the adjacent surface water region of Maricopa County (Mack,
1969). Prior to 1985 the surface water region is capable of absorbing
However, after 1985 it is prothe released allotments on other lands.
jected that allotments would be released for transfer out of the region
the proportion of cropland
due to crop rotation requirements which limit
which may be allocated to cotton. Since Maricopa County farmers had
County prior
not approved the transfer of cotton allotments out of the
92
to 1967, the entire amount of surplus cotton allotments in the surface
water region are assumed to be available for transfer to farms in the
groundwater study region.
The allotments released from urbanized lands in the two regions
are allocated to remaining farms in the groundwater region on the basis
of the marginal value productivity of an additional acre of cotton
allotment indicated by the model solutions for the previous time period.
Allotments are transferred first to farms in the model with the highest
marginal value productivity or "shadow price" for cotton allotments.
Transfers are limited to 100 acres of long staple cotton and 65 acres
of short staple domestic allotment (100 acres of total allotment) per
farm in accordance with a ruling by the Agricultural Stabilization and
Conservation Service in effect in 1967 on cotton allotment transfers.
If farms in the model with the highest marginal value productivity for
cotton cannot accommodate all of the surplus allotments available, the
balance of the allotments are allocated to farms in the model with the
next highest marginal value productivity. This procedure continues
until all surplus cotton allotments available for the time period are
accounted for.
In addition to the per farm acreage limitation, allotment transfers are governed by a crop rotation restriction that limits total cotton
acreage to 35 percent or less of the cropland available to the model.
This rotation restriction is applied because crop rotation is commonly
credited with helping to control insects and disease on cotton and with
improving soil tilth when a crop such as alfalfa is included in the rotation. Most farm models had less than 20 percent of their cropland
93
planted to cotton under the 1967 government cotton program and several
were below 10 percent. However, the rotation restriction is applied to
insure that some models do not obtain a disproportionate share of surplus
cotton allotments, thus eliminating crop rotation practices in future
time periods.
One exception is made to this rule. Farm survey data showed
that the 130 acre farms in the MARW water situation had in excess of 50
percent of their cropland planted to cotton, even with the 35 percent
reduction in short staple cotton acreage under the 1966 and 1967 programs. Throughout the 1950's these farms had grown alfalfa and grains
in addition to cotton. Crop reports from the Maricopa County Municipal
Water Conservation District Number One (1955-65) show that high water
costs due to increased pumping lifts and shortages of surface water from
the district forced these operators to discontinue growing these low-
valued crops in the early 1960's. Most of the operators then reduced
the size of their cropland base by renting land to vegetable growers
in the 1,000 acre farm size group but retained their cotton allotments.
The lands were usually leased on an annual or crop season basis.
The next year these farmers would move their cotton to the lands which
had been leased for vegetables and lease out the land where cotton had
been grown the year before. Hence these operators maintained a rotation
under a single crop system without having large amounts of idle cropland
as a financial burden. Similar benefits were obtained by the lessees to
the agreement. This situation is accounted for in the study by making
an exception to the 35 percent restriction on cotton cropped land in
this one farm model.
94
Sugar Beet Allotment Transfers
Sugar beets for sugar were first grown in Maricopa County in
1967 after many years during which no processing plant was in operation
to process beets. During this first year "proportionate share" limitations were in effect which limited beet allotments to approximately 80
acres per farm. However, due to difficulties in getting farmers to grow
beets, the Agricultural Stabilization and Conservation Service (ASCS)
Committee for Maricopa County removed the allotment acreage restriction
for the 1968, 1969, and 1970 harvest seasons. As of July 1970, the
Maricopa County ASCS office could give no indication if or when acreage
limits might be imposed or on what basis they might be imposed.
Nevertheless, beet allotments are not directly transferrable
between farm operators. Under the proportionate shares procedure, any
surplus allotments available for distribution or redistribution is
allocated among growers on the basis of the acreage they grew in the
past 3 years. Other farmers may make application to the County ASCS
Committee for a beet allotment, but farmers with a history as beet
growers are given first priority.
Therefore, for purposes of this study, it is assumed that (a)
total beet allotments available to the surface water region will remain
constant at the 1969 level of approximately 8,266 acres; (b) in the event
that it becomes unprofitable for farmers in one area of the study region
to continue growing beets, the allotment acreage released will be reallocated among the other growers in the region having an established allotment history who can most profitably grow them.
95
Transfers of beet allotments between farm models in the study are
made primarily on the basis of the marginal value productivity or "shadow
prices" for beet allotments shown in the solutions to the models for
the time period preceding the adjustment in farm model restrictions and
water cost coefficients. However, some weight is also given to the
availability of surplus cropland and water in the models with which additional sugar beets could be grown without displacing large amounts of
lower return crops such as alfalfa or grains.
Because it seemed likely that the "proportionate shares" rule
would be reimposed if significant amounts of acreage allotments were to
be transferred, a restriction is also imposed limiting beet allotments
to 15 percent of cropland in any farm model. This restriction is imposed to insure the spreading of allotment allocations over more than
one farm size group and water situation, yet allow the major portion of
such reallocations to go to areas and farm sizes which can most profitably continue to grow beets.
Water Table Decline Rates
The annual rate of decline in the water table and the associated
increase in pumping costs experienced by farmers depends upon the characteristics of the aquifer or subaquifer from which they are pumping and
the total quantity of water withdrawn each year. Using information
taken from the many U.S. Geological Survey reports cited throughout
Chapter II, a rate of decline in feet per 1,000 acre-feet of water withdrawn was calculated for each aquifer or subaquifer dealt with in this
study. In most cases the published sources provided sufficient information to make these calculations. If not, annual water withdrawals were
96
estimated from irrigation district reports on annual water deliveries or
from data on crop acreages and water use per acre by type of crop for the
area. These data coupled with the reported annual decline rates yielded
an estimate of the decline per 1,000 acre-feet of water withdrawn. For
Area A the estimate declines per 1,000 acre-feet of water withdrawn by
water situation are: RID = .0173; BID, ARL, SRV, and ARV = .0153; and
GB = .0171. For Area B the estimated decline rates are: MAR, ADAM, and
LMP = .025, TON = .235, HAR = .096, AGA = .15, RAN = .10, and CRK =
After computer solutions for all models are obtained for a given
projection period, the total amount of water used by all farms in a water
situation is determined. Where applicable, the amount of surface water
used is deducted. The amount of groundwater pumped for urban lands,
not included in the models, is also added to the total for the MAR and
acreLMP water situations. Water use by urban lands is estimated at 2.3
feet per gross acre, based upon information presented by John Carollo
Engineers (1968:iv) and C. L. Smith (1968:149).
Total net groundwater withdrawals by aquifer are then rounded to
the nearest 1,000 acre-feet and multiplied by the appropriate decline
rate per 1,000 acre-feet to obtain the total annual decline. Annual
decline times the number of years in the projection period yields total
decline. Total decline is then added to the pumping lift for the projection period to obtain the new pumping lift used to calculate the cost
of pumped water for the next projection period.
This procedure assumes that all wells in a water situation are
pumping from the same weighted average depth determined for the aquifer.
Hence, when the cost of water per acre-foot exceeds the net returns per
97
acre-foot of water for any given crop and farm model shown in Table 16,
all farms in that size group and water situation will cease to grow that
crop. However, due to economies of size, farms of different size will
cease growing the given crop at different points in time.
A similar procedure was used to determine water costs from irrigation districts. Examination of district water charges in 1967 showed
that in all cases charges closely approximated the variable costs of
pumping water. This cost structure existed even in the districts which
had access to some surface water, since groundwater still constituted
about 80 percent of annual deliveries. Amortization of fixed costs to
the districts were covered by the annual per acre assessment on lands
served by the district. Therefore, for purposes of this study, it is
assumed that district water charges will increase by an amount equal to
the increased cost of pumping for each time period in the analysis as
is the case with private farm well costs.
Well Replacement Decisions
In the short run only the variable costs of water are considered
in the decision-making process concerning which crop enterprise mix will
maximize net returns. Variable water costs include the cost of power,
operation and maintenance, and the cost of lowering bowls as water tables
decline to assure efficient operation of the pumps. As long as variable
costs per acre-foot are less than the net returns per acre-foot of water,
shown in Tables 15 and 16 by crop enterprise and farm model, the farms
represented by a particular model will continue to grow the crop in
question. The depths from which water can be pumped on the basis of
98
net returns over variable costs is shown by crop enterprise and farm
model size in Tables 21 and 22 for Areas A and B, respectively.
In the long run the cost of replacing wells, considered fixed
in the short run, must also be considered. If it is not profitable to
replace a well, and water available from remaining wells or irrigation
district sources is not sufficient to grow all crops that are profitable
when only variable costs are considered, then some farmland will be
abandoned and some crop acreage dropped from production.
The profitability of replacing a well in this study is determined
by comparing the net revenue over variable costs per acre-foot of water
for those marginal crops which would go out of production if the well
were not replaced, with the average future cost per acre-foot of water,
including well replacement costs, for the period of time the well would
be in operation. This decision-making process is facilitated by converting returns per acre-foot to break even lifts including fixed well
costs and comparing these break even lifts with the average future
pumping lifts over the life span of the well if it were replaced. The
life of a well is assumed to be 40 years. The average future lift is
calculated on the basis of the cropping pattern that could be expected
to be maintained if the well were replaced. Break even lifts based on
net returns over variable costs plus fixed well costs are shown by crop
enterprise and farm size in Tables 23 and 24.
Due to economies of size, large farms can sometimes afford to
replace a well to grow marginal crops when a smaller farm cannot. When
this situation occurs a proportionate amount of cropland, water resources
and crop acreage allotments are transferred to the most efficient farm
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105
model in the water situation which can afford to replace the wells.
Since the largest sized farms can best afford to acquire these resources
or represent the structure which offers the greatest economies to small
farms being aggregated into larger units, the resource transfers are
made to the largest farm size group in the water situation concerned.
CHAPTER V
RESULTS AND CONCLUSIONS
This chapter presents the results obtained from solution of
the linear programming models. The first section presents projections
of adjustments in crop enterprises, income, and resource use which can
be expected to occur within the framework of the various assumptions
made when constructing the models. These assumptions were explained
in previous chapters. Chief among them are the assumptions that farm
operators are profit-maximizing entrepreneurs and that all factors
affecting farmer decisions, except the availability of land, water, and
cotton allotments to the agricultural sector of the study region,
remain constant at 1967 levels. The second section of the chapter
summarizes these findings and presents some conclusions which may be
drawn from them.
Projected Adjustments: 1967-2015
Table 25 presents projected adjustments in optimum crop enterprise combinations, the monetary returns obtainable from them and
changes in agricultural land use due to changing cropping patterns for
the groundwater study region as a whole, and by water resource areas
within the region.
106
107
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108
Crop Enterprise Combinations
For the region as a whole, Table 25 shows that all crop acreages
except cotton, vegetables, and sugar beets are smaller at the end of the
time horizon than at the beginning. Except for the loss of grapes from
Area B in the first two projection periods due to negative net incomes,
"other crops" which include citrus, grapes, and miscellaneous vegetable
or specialty crops grown only in Area B would show constant acreages for
all six projection years. Long staple cotton acreages also remain constant, except for a one acre increase due to rounding numbers as allotments shift from one water situation and representative farm model to
another.
Short staple cotton acreages show a sharp increase due to
absorption of allotments released by the Maricopa County surface water
region (Mack, 1969) into the groundwater region. Also, the planting
of short staple cotton in the skip-row pattern in which sets of four
rows are alternately planted and skipped has declined to an insignificant amount by the year 1985. This occurs as rising water costs coupled
with higher water application rates for skip-row planting (Tables 15
and 16, Chapter III) overcome the gains in revenue due to higher yields
obtained from the skip-row versus the solid planting pattern. Another
factor affecting cotton planting patterns in some models is the opportunity cost of using the added water required for skip-row planting on
other crops and/or extra acres of solid planted cotton as additional
cotton allotments are acquired. The acquisition of cotton allotments
in significant quantities from the surface water region begins to occur
in 1995. This is about the time that surplus water supplies disappear
109
as unneeded wells are not replaced and when returns from marginal crops
such as sorghum and safflower alone can no longer justify replacing
wells which are needed to sustain them.
Sorghum and safflower are the two crops for which acreages decline most. In Area B, early sorghum is non-existent by 1975 and late
sorghum disappears by 1995. Safflower persists in some parts of the
region until 2005, being grown primarily with surplus water during the
winter months where pumping capacities have been maintained for peak
summer demands by cotton. However, for the most part safflower too
can no longer justify well replacement by 1995.
Substantial quantities of alfalfa, barley, and wheat are grown
throughout the 50-year projection period. However, most of the acreage
is found in Area A where water costs are low. Even sugar beets and long
staple cotton cannot persist in some parts of Area B. Sugar beets are
transferred to lower water cost situations in Area A as early as 1975
and large scale transfers of long staple cotton occur in 1995.
That adjustments in cropping patterns differ significantly
within water resource areas as well as between them is shown by the
same data broken down by water situation in Tables 26 and 27. In Area
A (Table 26) the BID and BIDW water situations primarily show a large
increase in cotton acreage by utilizing idle land and by dropping some
acreages of low-value crops such as safflower, sorghum, and barley out
of production in 1995. In the last two time periods we see short staple
cotton replacing long staple cotton, even though the long staple allotments may be transferred to areas with higher water costs. This replace-
ment occurs because the BID water users have relatively large supplies of
110
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113
low-cost water available to them. Therefore, the marginal value product
of additional short staple cotton allotments is higher than other areas.
Thus, farmers in the BID water situation can afford to outbid other areas
for the surplus allotments. However, the large transfer of cotton allotments into the BID situation in 1995 raised cotton acreages to the 35
percent of total cropland limit for all cotton set under the crop rotation restriction. Hence, the profit maximizing entrepreneurs will replace relatively lower return long staple cotton with high return short
staple cotton to the extent that they are able to do so. Similar phenomena occur to a lesser extent in other Area A water situations. However,
higher water costs or different crop enterprise combinations make them
less competitive for cotton allotments until after the BID firms have
been allocated their limit of cotton allotment transfers.
In almost all Area A situations, well replacements cannot be
justified for sorghum after 1975 and for safflower after 1985. However,
the reduction of cotton acreages by 35 percent in 1966 left large amounts
of surplus water available in the early years of the projection period.
Hence, these crops persist into the later years of the period until they
can no longer cover the variable costs of pumping. In the RID situations sorghum cannot pay the variable cost of pumping by 1995 and
safflower by the year 2005 and therefore go out of production even if
surplus water is available. By 2005 wheat and barley can no longer
justify well replacement in the RIDW situations but can still cover
the variable cost of pumping if surplus pumping capacity is available
during the winter months due to heavy demands for water by cotton in
the summer months.
114
Most of the Area B water situations do not acquire additional
short staple cotton allotments until the year 2015, after all the Area A
situations have reached their rotation limit or per farm allotment
restriction on cotton. In the meantime, most of them have been forced
to give up sorghum, safflower, alfalfa, barley, sugar beets, and long
staple cotton due to high water costs. In all situations except TON
barley and wheat persist after 1985 entirely on surplus pumping capacity
available to meet peak summer demands for water by cotton. Only the
RAN and TON water situations can afford to acquire long staple cotton
or sugar beet allotments and grow these crops through the year 2015.
The LMP water situation shows a steady decline in all crop
acreages due to urbanization of cropland and the MAR, LMP, ADAM, and
TON situations show a drop in "other crops" between 1967 and 1975 due
to the arbitrary removal of grape acreages. This enterprise had shown
negative net returns for several years prior to 1968 and vineyards were
being destroyed. In keeping with this trend and the assumptions of
ceteris paribus and profit-oriented entrepreneurs, this unprofitable
enterprise was liquidated in all water situations where it was found in
1967. The subsequent increases in "other crops" in the ADAM and CRK
water situations occur due to the transfer of citrus acreage to these
areas as citrus groves in the LMF water situation succumb to the subdivider's bulldozer.
It is realized, of course, that grapes are not likely to be completely removed from all areas and that the citrus groves destroyed may
not be replaced within the study region or all of Maricopa County.
Nevertheless, the disposition of these crops is in accordance with
115
information available from growers and Maricopa County Extension personnel concerning trends and conditions existing just prior to time the
linear programming models were constructed and used to obtain the results
indicated in Tables 25-27.
Table 28 presents the combined total projected acreages of
selected crops for the surface and groundwater study regions of Maricopa
County for the projection years 1967 and 1975. It also shows the reported acreages of crops grown in the County for the years 1967 to 1972.
The crops represented are those for which comparable data were
available.
Examination of these data shows that the total reported acreages
of these crops have declined steadily between 1967 and 1972. Also, the
reported acreage for 1972 falls between the projected values for 1967
and 1975. However, a comparison of reported and projected acreages for
1967 show that acreages grown were almost 66,000 acres greater than the
projected acreages.
About two-thirds of this discrepancy is accounted for by safflower. The 70,000 acres produced in 1967 were the highest on record
while the linear programming models for the groundwater study region
were restricted to the previous five-year average of 26,300 acres shown
for the 1967 projection. The remainder of the discrepancy between
reported and projected total 1967 acreages is largely accounted for by
sorghum. Examination of sorghum acreages reported in Arizona Agriculture (1959-70) show that only in 1958 and 1967 did they exceed 60,000
acres and that from 1960 to 1965 they had been below 50,000 acres. Crop
reports from the Salt River Project (1962-68) and the Roosevelt Water
▪
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117
Conservation District (1963-68) show a rapid increase in sorghum acreages
in the surface water region between 1964 and 1967. The linear programming models for the surface water
•;ion, however, limited sorghum
acreages to 12 percent of availab, cropland which it was believed
reflected the typical acreages of sorghum grown (Mack, 1969:61).
These facts account for the entire discrepancy between 1967 reported
and projected acreages.
Data obtained from Arizona A ricultural Statistics (1972) show
that sorghum yields per acre in Maricopa County increased from 3,500 to
4,200 pounds per acre during the time acreages increased in the surface
water region. After 1968, they dropped to their pre-1965 levels. This
drop in yield coupled with the rapidly declining acreages of sorghum
shown in Table 28 between 1967 and 1972 would seem to indicate that most
of the decline in acreage took place in the surface water region and that
the restrictions placed on sorghum acreages in the LP models for that
study were in accord with long run historical evidence. By 1972 the
reported acreages of sorghum had dropped to levels that are quite consistent with the 1967 and 1975 projected acreages for the County.
The 1967 projected cotton acreages are slightly below the
reported acreages. This is accounted for by the fact that the LP models
showed all long staple cotton being grown in a skip-row planting pattern
when in fact much of it was grown in the solid planting pattern. The
discrepancy in acreage occurs due to an acreage measurement requirement
imposed under the 1966 and 1967 cotton programs which reduced skip-row
planted acreage by 15 percent but not solid planted acreage.
118
The changes in reported cotton acreages between 1967 and 1972 are
largely explained by information presented by Firch (1973) concerning
changes in cotton programs and prices. The 1966-67 cotton programs provided strong incentives to growers to reduce acres planted in the form
of low price supports and direct payments to growers. The 1968 increase
in cotton acreage shown in Table 28 may have been a reaction to a price
increase of several cents a pound for cotton between 1966 and 1967 and
speculation of further price increases due to the rapid reduction in
surplus stocks of cotton under the 1966-67 cotton programs. The further
increase in acreage in 1969 is probably explained by a change in the
cotton program which gave cotton producers substantial freedom to plant
acreages of cotton in excess of that required for full participation in
the benefits of the government program. However, by 1970 the previous
two years of low cotton prices had apparently removed the incentive for
growers to plant much more than the domestic allotment covered by the
support payments. Another factor is that costs of production have been
increasing in recent years due to insect control and other problems.
Hence it appears that in future years the projections from the linear
programming models may be very much on target with respect to acreages
111
of cotton grown in Maricopa County.
The 1967 reported and projected acreages for alfalfa, barley,
and wheat correspond very closely. For alfalfa, the 1975 projected
acreage also approximates the 1972 reported acreage quite well. However, for barley and wheat there is a substantial discrepancy between
reported and projected acreages. From 1967 to 1972 reported barley
acreages declined by almost one-half while wheat acreages increased over
119
fourfold. This is explained largely by the fact that during this time
period farmers began producing new varieties of wheat suited for livestock feed. As a result, between 1967 and 1972, wheat yields rose from
2,940 to 4,200 pounds per acre (Arizona Agricultural Statistics, 1972)
while barley yields stayed fairly constant at around 3,500 pounds per
acre. Over this same period the prices of these two grains paralleled
each other quite closely. Wheat moved from $51 per ton in 1967 to $54
in 1972. Barley moved from $49 to $55 per ton during this period. The
bulk of the increases in prices for both crops occurred between 1970 and
1971.
Given this high substitutability of wheat for barley as a feed
and their common use of production resources, acreages of these two
crops in Table 28 probably should be combined as "small grains." When
this is done, projected acreages from the LP models fall short of
acreages produced by 20,000 to 35,000 acres. However, the market price
for feed grains in 1971 was pushed sharply upward by low corn yields
due to a corn blight infestation in the Midwest. In 1972 prices went
higher due to large sales of feed grains to the Soviet Union and loss
of much of the corn crop due to poor weather during the harvest season.
Hence, it is believed that removal of these unusual influences on market
prices for barley and wheat in future years will cause the acreage of
these grains grown in Maricopa County to drop closer to the levels projected by the LP models. However, due to the yield differentials,
wheat acreage will likely continue to exceed barley acreage.
Discrepancies between projected and reported data for sugar
beets is explained by the fact that net revenue coefficients entered
120
into the LP models were based upon data developed after only two years
of growing experience in 1969. At this point in time the number of
acres grown in Maricopa County were at their peak. Subsequent problems
with disease and insect control, and low yields in 1970 have resulted
in a sharp curtailment of acres grown.
Maricopa County vegetable acreages have been declining slowly
since 1960 (Arizona Agriculture, 1959-70). Acreages dropped at the rate
of about 1,000 acres per year between 1960 and 1967. However, the rate
of decline increased sharply after 1967 as shown in Table 28.
The chief crop among vegetables in Maricopa County is lettuce.
Data from Arizona Fruits and Ve etables (1950-72) show that between 1967
and 1972 the number of firms shipping fall lettuce also declined from 46
to 24. Part of the decline in acreage may be due to a decline in the
number of growers. However, a more plausible explanation is that the
decline in acreages and growers are both due to changes in the market
for head lettuce and increased competition from other areas in Arizona
and surrounding states. A publication by Firch and Mathews (1971) indicates that shipments of lettuce from the more southerly parts of
Arizona were increasing at the same time that shipments from Maricopa
County growing areas were decreasing. Other areas in New Mexico and
California have also increased lettuce production. As pointed out by
Firch and Mathews, lettuce growers are constantly trying new producing
areas and those proving to have economic advantages displace the older
areas. This shifting of the market to new producing areas would seem
to be the major factor explaining why projected acreages from the LP
models deviate significantly from reported acreages in 1972.
121
Cotton Allotment Transfers
Tables 29 and 30 show the projected source and destination of
long and short staple cotton allotments respectively by water situation.
Long staple allotment transfers occur within the groundwater study
region only, with a strong shift from Area B to Area A. The loss of
long staple allotments from the LMP water situation in the 1975 and 1985
time periods are due to urbanization of farmland. All other transfers
out of Area B occur because returns from long staple cotton can no longer
justify replacement of wells to grow this crop. Negative transfers in
Area A occur when long staple cotton is replaced by short staple allotment acquisitions shown in Table 30. This occurs due to the 35 percent
limit on cropland covered by cotton under the crop rotation restriction
placed on the models.
In Table 30, all negative transfers of short staple cotton
allotments occur due to urbanization of land in the water situations
indicated. A total of 10,458 acres of short staple domestic cotton
allotment is released from the Salt River Project service area of the
surface water study region according to projections by Mack (1969:89).
Of this total, 9,085 acres go to Area A and 1,373 acres to Area B of
the groundwater study region. These transfers take place under the
assumption that Maricopa County farmers have not voted and will not vote
approval for transfer of allotments outside the County except by an
existing owner in the County.
Even if such transfers by sale were approved, it is likely that
a high proportion of surplus allotments from urbanized lands would
remain in the surface water region or be transferred to Area A of the
122
Table 29. Projected Long Staple Cotton Allotment Transfers by Water
Resource Area and Water Situation.
Area and
Water Situation
1975
1985
Year
1995
2005
2015
- 146
- 313
Acres
Area A
BID & BIDW
+1863
RID & RIDW
+100
ARL & ARLW
+
SRV
+559
-132
ARV
+1300
+ 355
GB
+300
+841
+764
+4132
+ 695
+ 508
-2769
- 558
- 925
-
Total Area A
-166
10
Area B
MAR & MARW
LMP
- 194
- 113
18
HAR
Total Area B
-219
-334
+ 100
+ 469
- 695
- 508
+ 431
TON
CRK
68
- 575
AGA
RAN
-
+ 194
+ 113
+ 100
- 969
-4132
123
Table 30.
Projected Short Staple Domestic Cotton Allotment Transfers
by Water Resource Area and Water Situation. a
Area and
Water Situation
1975
Year
1995
1985
2005
2015
Acres
Area A
BID & BIDW
+2382
+ 146
+ 313
RID & RIDW
+1040
+1143
+1381
ARL & ARLW
+
65
+390
SRV
+ 518
ARV
+ 845
GB
+193
+
2
+535
+1038
+3424
+2732
Total Area A
+
65
MAR & MARW
-
95
LMP
- 527
+ 132
+1826
Area B
,-2015
- 914
- 914
- 152
AGA
+1040
+ 455
HAR
+ 297
+
TON
77
+1028
+ 585
RAN
+260
CRK
+ 698
Total Area B
.SRP
-
65
- 914
- 252
+ 876
+1728
- 124
-3172
-3608
-3554
a. Domestic allotments are equal to 65 percent of total
allotments. Representative farm budgets and linear programming
models were constructed on this basis.
b.
Surface water region projections from Mack (1969:89).
124
groundwater region. Both areas have low cost water compared to most
areas of the State, therefore should be able to pay more for allotments
based upon their expected future return. The areas of Arizona outside
of Maricopa County which would probably be best able to compete for
these surplus cotton allotments are areas which have direct access to
low-cost surface water from the Colorado River and get high yields from
cotton.
Data presented by Firch (1973:Figures 7-8), however, indicate
that between 1969 and 1972 Arizona cotton producers lost some of their
comparative advantage in cotton production with respect to areas in
other states. Hence, if inter-state transfers of cotton allotments
should be approved in the future, it appears that a large proportion of
cotton allotments released for transfer in Maricopa County may be purchased by out-of-state cotton growers.
Net Incomes
The above information on crop enterprise combinations and cotton
allotment transfers helps to explain the direction and magnitude of the
changes in gross and net incomes which are shown in Tables 25-27 along
with the optimum crop enterprise mix. Turning to Table 25, it can be
seen that both gross and net returns are projected to decline for the
region. However, the projected decline in net revenue of less than $3
million is small compared to the $8 million decline projected by Mack
(1969:98) for the surface water region. This difference is largely due
to the transfer of the 10,458 acres of cotton allotments from the surface
to the groundwater region.
125
Data in Table 25 also indicate that, within the groundwater
region, Area A farm operations are expected to show a half-million dollar
increase in net returns over variable costs over the projection period
while Area B farms can be expected to suffer a $3 million reduction in
net returns. Again, this can be directly related to the direction of
cotton allotment movements indicated in Tables 29 and 30. However, part
of this difference is attributable to higher water costs which caused a
much larger proportion of the barley, wheat, and alfalfa acreages to go
out of production in Area B than in Area A.
In Table 26 it can be seen that, within Area A, the influx of
cotton allotments is the major factor in keeping net revenues over
variable costs at approximately the 1967 level for all water situations.
Only the RID situation suffers a slight drop in net returns. All others
experience a very slight to modest increase in net returns.
The movement of net incomes shown in Table 27 for Area B water
situations is more varied. The sharp rise in net returns from a negative $79,000 to a positive $395,000 in the ADAM water situation is due
to the replacement of highly unprofitable grapes with citrus. The TON
situation shows a substantial increase in net returns due to a large
increase in cotton allotments. All other water situations show varying
degrees of decline in net revenues as increased short staple cotton
allotments in the later projection periods only partially offset the
increasing costs of water and loss of other crops including long staple
cotton. Net revenues in the LIR situation hold up well in spite of a
large loss of resources to urban uses. This stability is due to the
126
fact that vegetable and cotton production is maintained by the farms
which remain in production.
Water Use
Given the projected adjustments in crop enterprise combinations
and allotment transfers discussed above, annual water use can be expected
to change as indicated in Tables 31 and 32 for Areas A and B, respectively. In Area A, water use stays relatively constant in all situations
except BID, RID, and GB. The latter two situations have the highest
water costs in Area A and relatively large acreages_ of low value crops
such as sorghum and safflower in 1967. The Gila Bend situation is
particularly hard pressed because its one high value crop, cotton,
accounted for just 5 percent of the total cropland. The BID situation,
however, is projected to show a small increase in water use as all cropland is utilized in future years to grow the increased cotton acreages
it acquires.
Data in Table 32 indicates that in Area B the TON situation is
expected to increase water use due to addition of future cotton allotments. The replacement of grapes with citrus in the ADAM situation
would leave water use there almost constant throughout the projection
period. The decline in agricultural use of water in the LMP situation
is largely offset by increasing urban uses in that area. Transfers of
land to urban uses results in a net reduction of about 26,000 acre-feet
per year for the area. The CRK situation decreases water use only
slightly due to replacement of sugar beets and small acreages of other
low-value crops with citrus. Farmers in this area had already reduced
▪
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their crop enterprise mix to primarily high-value crops before 1967 due
to high water costs.
However, the projections indicate large declines in water use
will occur in the MAR, AGA, HAR, and RAN water situations between 1967
and 2015. In the MAR and AGA situations water use declines because all
crops except short staple cotton, vegetables, and specialty crops go out
of production due to rising water costs. In the HAR and RAN water situations, sorghum, safflower, and alfalfa largely disappear for the same
reasons. However, barley and wheat continue to be grown as long as they
can pay the variable pumping cost for winter water made available by
replacing wells to meet summer water demands for cotton. The production
of grains during the winter months doesn't persist into later time periods in the MAR situation because of the large acreages of vegetables
which compete with barley and wheat for water. Like the CRK situation,
farmers in the MAR water situation had largely discontinued growing all
crops except cotton, vegetables, and specialty crops by 1967 due to high
water costs. The same is true of the ADAM water situation.
Pumping Lifts and Water Costs
Table 33 presents the amounts by which water tables are expected
to decline (or pumping lifts to increase) during each projection period
and over the entire time horizon of the analysis. These projected declines are based upon the projected annual water use shown in Tables 31
and 32 and the annual rates of decline per 1,000 acre-feet of water withdrawn from the aquifers which were presented in Chapter IV.
Total declines between 1967 and 2015 range from two to four
times as great in Area B as in Area A water situations. The difference
130
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in water table declines occurs in spite of the fact that water use
levels
are sustained close to 1967 levels in much of Area A while they decline
substantially in such large water-using situations as MAR and HAR in
Area B as shown in Table 32. This phenomenon simply reflects the many
differences between aquifers in size, yield, and rates of recharge
relative to levels of water use.
Given these decline rates and the 1967 pumping lifts, the projected variable costs of pumping water in the, benchmark projection years
are shown in Table 34. When these water costs are related to the net
returns over variable costs per acre-foot of water shown in Tables 15
and 16, it readily is seen why the cropping patterns shown in Tables
25-27 differed substantially between areas in 1967. Also explained is
why various crops drop out of the enterprise mix in any one water situation between 1967 and 2015. However, this comparison only indicates
when crops would be dropped due to inability to cover the variable costs
of pumping water. Low-value crops are likely to disappear earlier due
to inability to cover both variable costs and the fixed costs of replacing a well determined by the break-even lifts shown in Tables 23
and 24.
Number of Farms and Land Use
Given the projected adjustments in crop enterprise combinations,
substantial amounts of cropland can be expected to be idle or be abandoned in the future. Figures for "idle land" in Tables 25-27 show the
total amount of unused cropland by use period over and above that removed from the models for urban uses. In most cases, less land A is
left idle than land B because cotton utilizes land for the entire year
132
Table 34.
Projected Variable Costs of Water Per Acre-Foot by Water
Situation, Areas A and B.
Area and
Water
Situation
Year
1967
1985
1975
1995
2005
2015
Dollars Per Acre-Foot
Area A
BID & BIDW
2.71
3.19
3.78
4.32
4.94
5.56
RID & RIDW
4.89
5.52
6.32
7.06
7.72
8.36
ARL & ARLW
3.70
4.17
4.76
5.31
5.92
6.54
SRV
2.55
3.02
3.62
4.17
4.78
5.39
ARV a
3.97
4.32
4.77
5.19
5.65
6.12
GB
5.11
5.48
5.92
6.33
6.66
6.97
MARW
10.62
11.89
13.36
14.75
15.94
17.14
ADAM
10.00
11.25
12.75
14.15
15.30
16.50
LMP
9.28
10.54
12.01
13.40
14.59
15.79
AGA
12.03
12.75
13.65
14.55
15.14
15.73
6.54
8.64
10.08
11.39
12.31
13.20
6.48
7.05
7.72
8.40
9.36
10.32
5.22
5.89
6.75
7.44
8.04
8.66
10.89
11.93
13.18
14.40
15.61
16.79
Area B
HAR
a
TON
RAN
CRK
a
natural gas engines
a. Water costs are based upon the use of
per foot
acre-foot
per
Cost
situations.
for pumping water in these
$.02043 for electric
of lift is $.01549 for natural gas engines and
motor-driven pumps (Lamoreaux, 1966).
133
but uses most of its water during the spring and summer months. Therefore, water is available to grow crops such as barley, wheat, safflower,
or early sorghum which utilize land A from December to June. Hence,
"idle land A" in the tables indicates the amount of cropland which can
be considered idle, fallow, or abandoned for the entire year. This is
true of all water situations except ADAM where crop enterprise combinations indicated heavier use of land B.
According to Table 25, close to 100,000 acres of cropland may
be expected to lie idle or abandoned in the groundwater region by the
year 2015. Approximately 70 percent of this will be in Area B where
large acreages of crops will be lost due to increasing water costs.
Within Area B, the areas likely to experience the largest
proportionate increases in idle lands are the Harquahala Valley (HAR)
and the McMullen Valley near Aguila (AGA). The former area experiences
by far the highest rate of decline in water tables in all of Maricopa
County. This decline was estimated to be approximately 17 feet per year
during the peak pumping years of 1962 to 1965 shown in Table 1.
In the Aguila area, water table declines are more modest. However, this area was originally developed in the mid-1950's to grow vegetables. In a few short years market adjustments led to the withdrawal
of most vegetable production from the area. This withdrawal left only a
small amount of cotton acreage and substantial production of feed grains
to support cattle operations. As indicated in Table 27, sorghum is not
even brought into the AGA linear programming models for the 1967 projection. Barley persists until 1995 only because it can cover the
variable costs of pumping surplus water available during the winter
134
months. Long staple cotton cannot justify well replacement in the Aguila
area after the year 2005, given the prices and production practices
assumed in this study.
Not all of the idle land shown in Tables 25-27 will remain as
a part of operating farms. As acreages utilized to grow crops decline,
the unused lands are likely to be abandoned. Due to substantial surplus
pumping capacity relative to crop acreages grown as of 1966 when cotton
acreages were reduced by 35 percent, some lands may be abandoned even
before irrigation wells are completely depreciated. In these situations
the low-value crops may persist for some time because the surplus
pumping capacity only makes it necessary that these crops cover variable
pumping costs and not both variable costs and the fixed cost of
replacing wells.
Tables 35 and 36 show the estimated number of farms, acres of
cropland in active farms, and acres of cropland cropped by benchmark
years through the year 2015 for Areas A and B, respectively. Cropped
acres are obtained by deducting the smallest amount of idle land
(usually land A) shown in Tables 26 and 27 from the total cropland
available to farm models in the water situation. Number of farms and
acres of cropland are determined by the amount of land transferred to
urban uses, transferred between farm size groups within a water situation, or left idle in the farm models.
Only the MAR and LMP water situations are affected by urbanization of farmlands. In all other situations cropland acreage and number
of farms are calculated on the basis of whether the idle land was needed
to maintain crop rotations and whether the relevant farm model could
135
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afford to replace wells to grow marginal crops. If some idle land was
needed for inclusion in crop rotations, allowances were made for this
and number of farms and acres of cropland calculated accordingly.
Lands not needed for rotation purposes stayed in the models
also but were not used due to lack of water when wells were not replaced.
If a small size farm in a water situation could not afford to replace
wells for a marginal crop but larger farms could, land, water, and
crop allotments were transferred to the most efficient sized farm model
as indicated in Chapter IV. In this case, the amount of cropland shown
for a water situation may stay the same but the number of farms will be
reduced as small farms are combined into or absorbed by larger units.
Such transfers of resources and reduction of farm numbers occurred only
in the GB and MARW water situations of Areas A and B, respectively.
This type of transfer is most apparent for the MAR and MARW water situation in Table 36. Between the years 1975 and 1985 cropland acres stay
constant but number of farms decline by two due to transfers of resources
between size groups within the water situation.
Table 35 shows that in Area A only the RIDW and GB water situations experience a decline in farm numbers and cropland between 1967
and 2015. Table 36, however, shows that only the ADAM water situation
might be expected to maintain farm numbers and acres of cropland in
active farms. This is because this water situation produced high-value
crops such as cotton, vegetables, and citrus in 1967. It also produced
grapes which, as explained earlier, are a low-return crop and tending
toward replacement by citrus. All other water situations show declines
in number of farms and acres of cropland between 1967 and 2015.
139
Urbanization of Cropland
A total of 15,855 acres of cropland in the LMP water situation
and 7,670 acres in the MAR and MARW water situations are projected to
be transferred to urban uses by the year 2015. A breakdown of these
acreages by farm size and time period is shown in Table 37. The urbanization of approximately 97,000 acres of cropland in the adjacent
surface water region are also shown by time period.
The water situations subject to urbanization were predetermined
by their location relative to existing urban areas and direction of urban
expansion along transportation routes. Urban expansion has been, and is
expected to continue, occurring along the north and west edges of Phoenix
and along the highway leading northwest toward Wickenburg. This route
goes through the northern part of Maricopa County Municipal Water Conservation District Number One represented by the MAR and MARW water
situations. The bulk of the urban expansion will occur in the LMP water
situation and is likely to include significant expansion of the town of
Litchfield Park near the southwest edge of this area by the latter part
of the projection period.
As shown in Table 5, all five farm size groups found in Area B
are represented in the LMP and MARW water situations. However, urbanization of cropland was limited to those models representing the smallest
and the largest farms in these water situations. The reason for this
limitation was related to both geographic and economic factors. Many
of the smaller farms and at least one of the largest farms in each of
these situations were located in areas expected to be urbanized.
140
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Several of the 1,000 acre farms were also located in these areas.
However, because most of these operations specialized in the production
of vegetables and cotton, and because many of them rented much of their
cropland from other farms in the area, it was reasoned that this group
of farms was not likely to succumb to urbanization. Some of the land
they operated might very well be urbanized. However, in the event this
occurred, it appears likely that the entrepreneur would merely rent or
purchase another small farm outside the expanding perimeter of urbanized
lands.
On the other hand, smaller farm operators who grew some of the
low-value crops in 1967 would in all probability be forced to drop these
crops from their enterprise mix as water costs rose over time. They
would then be forced to seek more high-return alternative enterprises
such as cotton or vegetables, lease or sell the land to others, or face
eventual bankruptcy due to inability to cover the fixed costs of operations containing large amounts of idle land. Since in most cases they
would not be equipped technologically or economically to engage in
vegetable production the most likely alternative seemed to be that these
farms would be absorbed by larger units seeking replacement lands or be
merged into a larger unit capable of handling vegetable production in a
manner competitive with established producers. Hence, urbanization of
cropland was limited to the 130 and 430 acre farm models and to the
6,000 acre models.
Summary
Results of the linear programming models indicate that in the
future the groundwater region of Maricopa County can be expected to
142
experience a decline in cropped acreages, resource use, and income from
their 1967 levels. Table 38 shows that by 2015 cropped acreage and water
use are projected to decline by 21 and 22 percent, respectively. Net
revenue shows a projected decline of 13 percent. Part of these declines
can be accounted for by the loss of over 23,000 acres of cropland to
urban uses. However, net revenue declines less than resource use because the crops that go out of production over the projection period are
the low-return crops which can no longer cover the costs chargeable to
their production. Also over 10,000 acres of short staple cotton allotment are projected to be transferred into the region. This is a highvalue crop which both utilizes idle resources and replaces the
low-return crops.
The effects experienced by the two water resource areas and the
various water supply situations located within the study region are
quite different. Both Area A and Area B experience projected declines
in cropped acreage and water use. However, the percentage change in
water use is over twice as large in Area B as in Area A and the percentage change in cropped acres is over four times as great. Furthermore,
net returns over variable costs for Area B farms are projected to
decline by 23 percent while Area A shows a 7 percent increase.
These differences in movement of resource use and income between
the two water resource areas are explained by a combination of factors.
First, all urbanization of cropland takes place in Area B. Secondly,
water costs and rates of increase in water costs are greater in Area B
because of differences in characteristics of the groundwater aquifers
from which most of the irrigation water is obtained.
143
Table 38. Percent Change in Cropped Acreage, Water Use, Cotton Acreage,
and Net Revenues by Area and Water Situation: 1967-2015.
==========__
Net
Cotton
Water
Cropped
Area and
c
b
Revenue
c
Acreage
Use
Acreage a
Water Situation
Percent
Area A
BID & BIDW
+4
+4
+97
+14
RID & RIDW
- 9
+5
- 8
+ 35
-4
+81
SRV
ARV
+7
-6
+12
GB
-26
0
-31
- 7
-13
+121
+72
+100
+ 64
- 5
+21
+15
+19
+9
+ 7
-24
+5
-22
ARL & ARLW
Total Area A
Area B
MAR & MARW
ADAM
-49
-48
LMP
AGA
HAR
TON
RAN
CRK
Total Area B
-54
+31
-21
Total Region
+13
-48
-38
-68
- 25
0
- 37
+ 1
+33
-7
+33
-30
-6
-33
-30
+ 98
+54
- 1
- 8
-21
-22
+ 18
•n••nn••nnnnn
a. From "Cropped acres," Tables 28 and 29.
b. From Tables 31 and 32.
c. From Tables 25-27.
- 13
+441
- 26
- 9
+ 7
+ 15
- 3
-11
- 13
- 23
144
Thirdly, due to lower water costs, the farm operations in Area A
are better able to purchase and use the surplus cotton allotments released from urbanized lands in both Area B and the adjacent surface
water region. This is reflected in the figures shown in Table 38 for
cotton acreage. While Area B suffers an 8 percent decline in cotton
acreage, Area A experiences a 64 percent increase. Part of this vast
differential in direction and magnitude of cotton acreage movement is
due to the fact that approximately 78 percent of all long staple cotton
acreage is found in Area B in 1967. However, due to the inability of
long staple cotton to cover all variable production costs plus fixed
costs of well replacement in many parts of Area B after 1995, most of
these allotment acreages are transferred to lower water cost water
situations in Area A. In addition, Area A also acquires the bulk of the
short staple allotments released from urbanized lands in the surface
water region of Maricopa County.
Sorghum and safflower are the two crops which yield the lowest
return and go out of production first. These two crops could not
profitably be grown in many parts of Area B in 1967 and cannot be
expected to continue in production in parts of Area A much beyond 1985,
given the prices and conditions of production assumed in this study.
Barley, wheat, and alfalfa are projected to continue in production in Area A at fairly high levels through the year 2015. However,
projections for these crops in Area B show their combined acreages
declining steadily to approximately 65 percent of the 1967 levels by
the year 2015. Sugar beets are projected to continue in production at
1967 levels throughout the projection period. Most of this acreage
145
will be produced in Area A water situations where water costs are low
enough to make them profitable.
Conclusions and Im lications
Data presented in Chapter II indicated that the agricultural
sector of the Maricopa County economy entered a stage of decline about
1960. Results from the linear programming models further indicate that
this decline in crop acreages, incomes, and resource use will continue,
barring some unusual developments in product markets or technology
affecting the cost of producing the crops found in the County.
Given the 1967 conditions assumed for the purpose of making the
projections, it appears that by the year 2015farms in Area A will still
be characterized by diversified cropping patterns. However, much of
Area B will support only high value crops such as short staple cotton,
vegetables, and citrus. As a result, substantial amounts of cropland
will be idle or abandoned.
The decline of agricultural activity in Maricopa County is being
lands at a
accelerated by the expansion of urban areas onto agricultural
lands for crop
point in time when it is still profitable to use these
little
production. In the past, this urbanization of cropland was of
supplies
consequence. So long as there were other lands with adequate
of relatively low-cost water available which could be developed, agri-
1960 most of the
cultural production simply moved to another area. By
supplies of water had been
lands overlying aquifers promising adequate
to changing
developed. Since then, the decline in crop production due
which
government programs have released significant amounts of land
146
could be put to urban uses or accommodate crops displaced by urban
expansion.
However, the decline in crop acreages has occurred in almost all
areas of the County, whereas most of the land subject to urban pressures
is located in the Salt River Project (SRP) service area where water
supplies are abundant, cheap, and of good quality for agricultural crop
production. When lands in this area can no longer accommodate the crops
displaced by urbanization, these crops will have to be transferred to
other areas where it is less profitable to grow them or be dropped from
production entirely. In either case, net incomes to the agricultural
sector of the economy will fall.
If the populace of the County desire to maintain the agricultural sector and its income at the maximum levels possible under existing
conditions, it would seem that a county-wide comprehensive plan backed by
zoning ordinances which prevented urban encroachment on lands with lowcost water supplies available to them might offer one means of accomplishing this goal. This would halt or at least slow the 71 percent
decrease in cropped acreage and 50 percent decrease in net revenues
projected by Mack (1969:99) for the SRP water situation by the year
2020. In effect it would force urban construction to shift directions
onto lands outside the SRP service area where water costs are much
higher and crop acreages will continue to decline even without urban
pressures. By so doing it would likely increase the value of these
lands instead of having some of them depreciate for lack of economically
viable alternatives to the crop enterprises they can no longer support.
147
One serious obstacle to such a zoning plan, of course, is that
the city of Phoenix prefers the better quality, lower cost water available on SRI' lands and competes for it. Also, the use of these waters
for municipal or industrial purposes instead of higher cost groundwater
may produce enough additional returns to offset completely the loss of
income to the agricultural sector of the community. Hence, there may
not be much support for the kind of zoning proposed above.
However, if the value of having a greenbelt in a metropolitan
area and the beneficial effects this has on the quality of life for
urban rssidents is considered also, the decision might shift in favor
of restrictive zoning. The impact of such a proposal cannot be pursued
further here but may be a topic worthy of further research as another
means of dealing with the problems attendant to a declining water table
in Arizona.
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