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TABLE OF CONTENTS EXECUTIVE SUMMARY BACKGROUND AND METHODOLOGY CALCULATIONS AND MODEL RESULTS MODEL FARM ANALYSIS: OPTIMIZED RESULTS CONCLUSIONS BIBLIOGRAPHY EXECUTIVE SUMMARY The future organization of typical San Joaquin Valley farming operations is likely to be affected by a number of differing factors in the future. Among the most important is water availability and cost. In addition, changes in farm programs may alter the balance between cotton, grains, vegetables, alfalfa and other field crops. The typical San Joaquin Valley field crop operator might seem to have an abundant number of crop choices to consider each year. However, a previous research report notes that the vast majority of income flow is derived from fewer than 20 crops. For example, cotton dominates, occupying more than one-half of the total acres in the Westlands irrigation district. Typically, as water use restrictions increase, cotton acres begin to decline. Instead of pushing into vegetable crops, farmers have tended to increase fallow acres. The results of the simulations conducted in the aggregate district model paralleled that which actually occurred during the drought period of the late 1980's and early 1990's.1 This report focuses on the economic and structural organization of a typical general farming operation in the San Joaquin Valley faced with the same sort of constraints as in our aggregate model. We wished to determine if the economic outcome would parallel that which was found in the aggregate model. We also wished to develop a planning mechanism which might be useful to Central California farm managers in the area desiring to look at more sophisticated planning mechanisms. We tested seven management situations, basing the analysis on the assumptions of declining water availability, farm program compliance and forced rotational inclusion of alfalfa into farming operations. The first four alternatives might be viewed characteristic of existing organizations and farm programs. The latter three represent a transition from existing institutions and reliance on farm programs. Farm income varied from a low of about $1.4 million to a high of $2.6 million. The low figure was derived from a situation where compliance with the farm program Acreage Reduction Program (ARP) and alfalfa inclusion was necessary and was combined with a 40-percent reduction in water supplies. The high figure resulted from a simulation in which alfalfa could be eliminated, ARP compliance was not necessary and water necessary to supply all crops would be available. Finally, the program was used to evaluate how this same farm might operate in the future, given the possibility farm programs will be eliminated. We looked at the same water reduction possibilities, but this time in the absence of any institutional mechanisms to provide income support for cotton and wheat. In addition, alfalfa would not be required in the farm crop rotation. Methodology In this analysis, a base linear programming model incorporating "attainable or representative" data of acreage, yields and prices, was first constructed for a 5,100-acre general farming operation. This outcome was compared to successive runs which incorporated varying water, labor and capital constraints. To accomplish this task, we again utilized the Westlands district historic economic picture as a basis for projections of that which might occur with the introduction of bounds in the use of water, labor and capital. Our base model was comprised of eight crop activities, a fallow activity, and a farm program compliance activity. Enterprise costs for each of these 10 activities were incorporated as a basic framework, derived primarily from University of California Cooperative Extension Service budgets. These activities were incorporated in a linear program which systematically tested the profitability of each of these cropping activities, considering important constraints. Details of these constraints are discussed in the report. In this case we were able to look at various sets of economic circumstances with which an individual farmer might be faced and project their likely direct economic effect on the ensuing farm organization. We also evaluated the model farm's structure in the absence of farm programs. Base Model Study Considerations and Constraints The farm model, like the district example, demonstrated the domination of the farm economic activity by cotton. Five field crops and three of the dominant vegetable crops were included. The latter were garlic, onions and cantaloupes. The five field crops were cotton, alfalfa, wheat, safflower, and processing tomatoes. Garlic, onions and processing tomatoes were to be grown under contract. Three soil types were considered on the farm. At a minimum, one-fourth of the acreage under each soil type was devoted to alfalfa production for rotational purposes. The model also included provisions for set aside and ARP under the 1990 Farm Program. These provisions were relaxed in ensuing runs. Variable production costs for each of these crops and non-crop activities were extracted and standardized from UC-Davis Cooperative Extension Service enterprise budgets. Irrigation costs were included for both surface and ground water. Water use factors indicated in the crop budgets were used as a starting basis for constructing water use parameters for each of the crops. In the base model, a blend of 60-percent surface and 40-percent ground water served as the aggregate supply source. Cotton acreage could vary to a maximum of sixty percent of total farm acres under the initial scenario and was tested under various alternatives in ensuing model situations. We wished to establish varying productive capabilities for the farm's soil types. To simulate these characteristic, three soil types were incorporated into the model. Each of the soil types had differing yield and water use characteristics. Land in each of the three soil types could be set aside or fallowed, but cotton and vegetables could not be grown on the poorest soil type. Four alternatives were evaluated under the assumptions of the base model. A norm was established by considering a situation with sufficient water available to meet all crop demands. Succeeding runs considered reductions in water availability of 25 and 40-percent. The final run using base model assumptions suspended the alfalfa acreage requirement. Base Model Results The base model farm income situation was established under the assumption of a normal farm organization in which alfalfa would normally occupy one- fourth of the acres each year for rotational purposes and water, sufficient to meet all crop needs, available. Net income in this situation amounted to about $2.53 million (Table 1). All acres would be farmed, excluding the base ARP requirement and slightly over 300 acres of vegetables would be grown. 
A farm income high of about $2.56 million was established in the base situation in which water sufficient for all crops was available and alfalfa was not required in the rotation (Table 4). Again, all land would be used, excepting Acreage Reduction Program (ARP) requirements, and 337 acres of vegetables would be grown. 
A reduction in water supplies of 25-percent resulted in about 3,700 acres being farmed and a drop in net income to $1.97 million (Table 2). Production remained in field crops and vegetable production was eliminated. 
If a more severe 40-percent reduction in water availability were to occur, farm income would be reduced to $1.46 million. Again, vegetable production would be eliminated and about 2,800 acres would be farmed (Table 3). 
Elimination of ARP and Alfalfa Requirements Ensuing model runs tested the relaxation of alfalfa inclusion for rotational purposes, as well as the requirement for the inclusion of acreage set aside from production for farm program compliance. The 1996 farm program has moved from a concept of deficiency payments to a direct payment schedule, which will be phased out in seven years. Under the 1996 farm program ARP land can be planted to other crops. The same basic cost structure was considered, but the crop mix changed. Managers would likely react to reductions in water supplies by evaluating the most profitable crops in relation to use of this most critical resource. Eliminating the requirement of alfalfa in the rotation is realistic. Alfalfa is a crop requiring a bit of time to be established. Cut back in acres of this crop would likely be gradual, but the model tests the terms on which it would or would not be included. Since it is a relatively high water user, it is eliminated at the $102 per ton price level utilized in the optimizing routine. In the base situation of water availability sufficient to meet all crop needs, farm income amounted to about $2.67 million. The farm was completely utilized for cropping, and 337 acres of vegetables would be grown (Table 5). 
In the event water availability was to be reduced 25-percent, vegetables would occupy 737 acres and net income would fall to $2.45 million. Unlike the base situation, all farm acres were still utilized for field or vegetable crops (Table 6). 
Finally, if water reductions amounted to 40-percent, 4,170 acres would be farmed, with only 32 acres of vegetables in the mix. Farm income would amount to about $2.16 million (Table 7). 
A more detailed analysis of crops will be presented in the narrative. However, it should be noted that safflower played a major role in "filling" available acres in the event water supplies were to be curtailed and alfalfa was not forced into the solution. Cotton remained the most important crop in all cases. Reasons for this will also be discussed in the narrative. In the case of traditional or transitional farming evaluations, major allocation of crop acres to cotton and alfalfa remained relatively unchanged in the event water supplies were unconstrained. This was not to be the case if alfalfa was not forced into the solution and water supply reductions were implemented. Alternatives Considered The first seven alternatives considered were as follows Traditional Farming: Farm Programs and Alfalfa in the Rotation
Model Farm Organization: Crop Alternatives and Acreage Effects A very large number of institutional and political alternatives could be tested in relation to their impact on farm profitability and resulting organization. Those included in this analysis bracket a set of possibilities considering both water reduction, rotational considerations and farm program alternatives. Water Reduction Effects: Crop Alternatives Alfalfa has always been an important crop in San Joaquin Valley agriculture. It is a significant portion of the rotation in a farm situation in which water supplies are sufficient to meet all crop needs. In the event water supplies are curtailed, the model suggests other crop alternatives provide greater farming profits. If alfalfa is not required in the rotation, with reductions in water supplies of 25-percent, the more optimal choice is a combination of cotton, garlic, onions, tomatoes, cants, wheat and safflower. If water reductions move beyond that point, the combination is one of cotton, a few acres of onions, tomatoes, wheat, safflower and over 900 acres of fallow (Table 8). 
Water Reduction Effects: Acreage Effects Field crop acreage was most constrained by the two extreme water reduction scenarios, with alfalfa being forced into the rotation. Fallow acreage varied from 1,036 acres to nearly 2,000 under the most extreme case of a 40- percent reduction in water supplies. If alfalfa could be eliminated from the rotation, all crop land would be utilized in the event of a 25-percent reduction. About 1,100 acres would be fallowed in the event of a 40-percent reduction. Acreage of cotton was only restricted from the maximum allowed in the model in the two situations in which alfalfa was forced into the solution and water supplies were restricted 25-percent and 40-percent respectively (Table 8). Water Reduction Effects: Net Income Alternatives Farm income exceeded $2.5 million for the three alternatives (B, NH and NSA), situations within which full water supplies were assumed to be available. Net income reached nearly $2.7 million in the situation (NSA) which allowed producers planting flexibility within the farm program and the elimination of alfalfa from the rotation (Table 9). 
Farm income amounted to about $2.4 million in the case in which the producer would endure a 25-percent reduction in water availability but could eliminate alfalfa and had planting flexibility within the farm program. In the circumstance of farm program compliance and adherence to the alfalfa rotation mandate, net income amounted to about $2 million (Table 9). Farm income amounted to about $2.1 million in the situation in which the producer would endure a 40-percent reduction in water availability but could eliminate alfalfa and had planting flexibility within the farm program. In the situation of farm program compliance associated with the alfalfa rotation mandate, net income dropped to about $1.5 million (Table 9). Farming Without Farm Programs Since price supports are not scheduled to be phased out until 2003, it may be too early to suggest the final shape of a farm in the absence or ultimate modification of farm programs. It is not too early to evaluate some of the possibilities. A final part of the study was an assessment of this same farm in the absence of price supports, farm payments and ARP provisions. The only constraints would be those applied to various water use alternatives and to contracted crops with processors for tomatoes, garlic and onions. Farm income varies from about $2.47 million with water supplies necessary for all crops to about $2.0 million with a 40-percent water supply reduction. In the latter case, farm income is generated from three crops-- cotton, processing tomatoes and wheat. More than 1,200 acres would be left to fallow. With a more moderate cut of 25-percent, income is derived from four crops--the previous three and from 274 acres of onions. More than 2,000 acres of wheat would be planted and fallowed acres would be absent (Table 10). 
Major highlights of the study point to the following:
BACKGROUND AND METHODOLOGY Background General farming operations in the San Joaquin valley, particularly on the west side, are large and capital intensive. Historically, large cotton acreage portrays the fact that cotton has been and still is the dominant crop in the region. It has tended to account for 30-50 percent of total arable acreage in Westlands Irrigation District over the past two decades. As water supplies have tightened and the agricultural environment has become more competitive, production intensity in fewer crops has become more evident. Presently, about 10 crops of the 50 listed in the district dominate. About 10 more could be considered as having profit potential but market demand limits their expansion to relatively small shares of total acreage. Evaluation of data over time suggests the following mix of crops as being or becoming the foundation of the Westlands growing programs:
In the early years, San Joaquin growers, exemplified by those in Westlands, had sufficient ground and surface water supplies available to provide the possibility of more extensive crop production, but the rising cost of water coupled with spot shortages have resulted in declining acreage of grains, particularly feed grains like corn and barley. Growers currently use water more efficiently than in the past and are growing more intensive crops like vegetables, orchard and nut crops, and grapes, but expansion of acreage of these sorts of crops is limited by institutional constraints or market demand. Growers have been faced with spot water shortages before-a 25-percent allocation in 1977. In 1991 the district received about one half of its allocation. Alfalfa production seems vulnerable because of its high water use requirements and growers must make a complex set of crop choices affected by rotational requirements and potential profitability which in turn is affected by contract constraints of some crops and price sensitivity of specialty crops grown for the market without forward price protection. Problem Statement Typical growers in the San Joaquin use a blend of surface and ground water. Drought is largely beyond the individual manager's control, but drought years have in general caused area growers to become much more efficient in their use of water. Continued spot shortages of water will be a fact of life for the individual manager. Other policies have direct and indirect effects, not only influencing the farmer, but those the manager buys from or to whom he or she sells. The 1996 farm program dictates a gradual phase out of price support programs and the ending of price or income support by the year 2003. Cotton and wheat are crops most directly affected, but the elimination of dairy price supports could affect the demand for alfalfa as well. Individual farm managers need to gain some understanding of the economic impact of particular political actions, like water supply restrictions and farm program elimination, on the ultimate structure and organization of their operations. A cohesive and comprehensive methodology to evaluate these proposed actions and policies could be very useful to the individual and to policy makers attempting to assess future farm and community organization. It is the intent of this analysis to develop such a methodology and apply it to a model San Joaquin valley farming operation. Methodology The technique used, linear programming (LP), is a technique for solving a special set of conditions involving: (1) a means of maximizing profit or minimizing cost, called the objective function, (2) a set of activities or processes within the model which accomplishes this objective and (3) a set of constraints or restrictions which limit the ability to accomplish this objective. The linear programming model used in this analysis might be compared to a sophisticated budgeting procedure, because it can systematically evaluate various economic enterprises available to the business manager. An operator usually analyzes business choices using a trial and error basis, but when linear programming is used, this trial and error approach is replaced by a mathematical process which tests total resource combination needs and insures they do not exceed the resources available. At the same time this resource combination maximizes the total net returns to the business. Problems facing farm managers can be specified within models of varying sophistication. Crops, appropriate for the farm, can be incorporated into models maximizing profits, subject to rotational, institutional, farm program and particular problem constraints, like water availability. Crops grown in the valley and typical to the region can be specified and tested for profitability, subject to acreage and farm program constraints. The program chooses that combination of crops according to net profitability and the aforementioned constraints. It then maximizes total district profitability subject to these constraints and specified activities. A properly constructed model does no more than predict the likely longer term organization of any business as it adjusts to economic or market forces. While the results may be counter to intuition, they can provide an accurate predilection of that which is to occur over time. Change may be gradual, but the detection of the most important forces influencing change and their magnitude are invaluable to those involved in longer term financial planning. The optimizing model was used to evaluate various sets of economic and institutional circumstances or external forces with which a typical San Joaquin Valley general row crop farm might be faced. The results measure the likely direct economic effect on the farm and its future organization. Analytic Software The software used for the analysis was developed with an optimizing program contained within Quattro Pro for Windows® (QPW). There are several advantages in the use of this particular procedure. QPW has both a linear and non-linear capability. Since QPW is a highly sophisticated multiple page spread sheet, the analytic capacity of the system is limited only by individual program characteristics. This multiple page capability also allows the separation of the LP from the supporting data. QPW Version 7 for Windows 95 will also read and write multiple page programs from other spread sheets, assuring a high level of compatibility. Thus, the model is also easily adapted to the Microsoft Excel format and others having an optimization package. The entries on any of these pages can easily be modified according to assumptions made about costs, yields, prices, acreage water and/or irrigation costs and many of the other essential ingredients of the LP mix. The optimizing program can be executed with any MS-DOS based personal PC with Windows® Version 3.1 or Windows 95® At least sixteen megabytes of memory is preferable if Windows 95® is to be used. The model used for this analysis is adaptable to an examination of labor and capital utilization, harvest time constraints and a myriad of other problems with which the farm manager is faced. Model Composition Our base model consisted of five field crop, three vegetable crops and two non-crop activities for a total of 10 crop and non-crop activities. The eight crops are those described below. The three non-crop activities included set aside (ARP), and fallow, which represented an alternative in the event of water use restrictions. Each of the crop and non-crop activities was supported by underlying data regarding variable cost of production, water supply. Associated irrigation costs and price, acreage and yield data were also integrated into the model. Each of the non-cropping activities was supported by associated costs.
Crops by Soil Types Crops and activities were grouped according to production on three main soil types.
Program Constraints Crop rotation constraints were applied to cotton so that it could not occupy more than 60-percent of total crop acres. Wheat acres were limited in the base situations in order to simulate farm program compliance. It was not constrained in the simulation of farm program elimination. Garlic, processing tomatoes and onions are generally grown under contract so a production base for each was applied (Table 11). Cantaloupe, safflower and fallow acres were not restrained. The usual non-negativity constraints were included. Labor, water and capital use were all calculated, but water was the only variable of the three constrained. 
Farm Acreage by Soil Type As indicated, the model farm was segmented by soil classification. Budget data for each of the three soil types were compiled (Table 12). The base model dictated at least one-fourth of total farm acres be kept in alfalfa. This meant that at least 467, 516 and 292 acres of each soil type be in alfalfa production. Similarly, cotton production could not exceed 1,121 and 1,239 acres of Class I and II acres. Total acres of the three soil types amounted to 1,868, 2,065 and 1,167 acres respectively (Table 12). 
Water Use: Water Base Model While water use per acre for individual crops was not modified in variations from the base model, the total amount of water used in ensuing runs was dictated by optimization which took into account profit per acre, constrained by each of the individual crops' use requirements and the total water supply available. The total supply of water under unconstrained conditions would be that amount necessary to grow the farm's crops without restriction based on aggregate crop requirements. This amount was calculated to be 16,701 acre-feet, the amount aggregated from the total number of acres grown for each crop (Table 8). The composition of this supply was based on a normal rotation followed by the farm within which alfalfa hay would comprise at least one-fourth of each soil type classification's total (Table 13). 
Aggregate supplies under the varying scenario were adjusted from this initial base, depending on reductions made. The optimizing program then chose the most profitable use of the supply based on crop requirements and the relative profitability of each crop. Basic Farm Model Operating Characteristic Assumptions
Individual enterprise costs utilized in the optimizing routine were developed by localizing UC-Cooperative Extension Service budgets to approximate conditions believed to represent the model farm situation. Cost of production included cash pre-harvest, harvest and post-harvest segments. Irrigation costs were also localized and were aggregated independently from other costs so that they could be dynamic, based upon water use (Table 14). The basic water supply mix used in the analyses was 60-percent surface and 40-percent ground water. Estimates of water costs were developed through engineering synthesis, thus the results dynamically reflect limited water supplies' effects on crop choice and resulting irrigation costs. 
Cost synthesis is an engineering-economics technique by which each process, procedure or application is evaluated both in terms of their relevant cost and the rate or amount of each input used. Cost synthesis techniques represent that which is representative of a particular situation rather than any actual individual operation. In this manner a standardized framework for all budgets is constructed. This standardized set of assumptions eliminates aberrations which can occur from farm to farm, or between enterprise, in regard to prices, use of inputs and the like. CALCULATIONS AND MODEL RESULTS Overview Although production and net income may be curtailed with rising water prices, a farm's economic damage is not likely to be as significant in the short run as those resulting from outright reductions in the total water supply. As water prices rise, we would expect shifts in the production and types of crops to occur. Reductions in the supply of water brought about by periods of dry weather will produce some of the same effects, but institutional constraints in the supply of water will be much more immediate, depending on the amount of the reduction considered. In order to determine these effects, several simulations of operating possibilities are incorporated into this analysis. Sets of data regarding the basis from which change was to be measured were prepared. These data sets normalized farm yields, prices and acres by soil type. Realistically, any analysis involves a recognition that external forces can considerably affect a projection's accuracy. Many means are used to attempt to anticipate these forces. Over the long term, the most dynamic is the weather, but institutional decisions can affect water supplies immediately. Demand for products can change over time as can government policies and programs. Our model does not attempt to make econometric predictions of changes in these forces. MODEL FARM ANALYSIS: OPTIMIZED RESULTS Overview The model farm analysis offers a view of some likely structural changes occurring on a San Joaquin valley general farming operation within which the manager faces water supply restrictions. It is important for the farm planner to be able to anticipate some of the changes which might occur as a result of disparate agricultural and economic policies. In order to accomplish this task, 10 differing operating conditions were formulated and processed with our linear programming model. For purposes of brevity in the tabular formats, they are noted by abbreviated codes when referred to as variations from the base. The base and nine differing situations optimized were as follows:
The basic farm model was comprised of the eight crop activities, a fallow and a set aside activity. Enterprise costs for each of these 10 activities were adapted from University of California Cooperative Extension Service budgets and modified by soil type. These activities were incorporated into the linear program. The routine systematically tested the profitability of each of these cropping activities, considering constraints also contained in the model. Productivity varies within a farm according to soil type. In order to simulate soil and accompanying yield variability, three soil types were included in the model. Yields were successively lowered from the top soil type, class I. Some soil types cannot support intensive field crop production, like cotton and vegetables. This was association was included in the model as soil type III (Table 14). The first four options consisted of the base model of a traditional farming operation operating within the 1990 farm program and variations from this base due to water supply reductions. Option 4 in this series also tested the model without the alfalfa requirement. Options 5 through 7 might be regarded as transitional in that set aside requirements were lifted in order to look at farm organization as it might exist until 2003. Options 8-10 could be considered free market evaluations. They do not include any farm program payments, acreage restrictions or set aside requirements. Optimized Acreage: Four Farm Program Options The base model establishes basic parameters for crop acres, income and water use and serves as a barometer from which all other results were varied. The most notable aspect of the model is the reliance on alfalfa, cotton and tomatoes as the primary sources of income. While 337 acres of onions are grown, they contribute only $128,000 or 5 percent of farm net income. In an overall sense, the model seems to verify that which is mirrored in traditional San Joaquin Valley Farms under the program. In addition, soil type III is used for 430 acres of set aside to satisfy farm program requirements (Table 15). 
Model 1(B)Results: Acreage and Income by Soil Type Cotton and alfalfa are dominant crops, occupying about 4,800 acres of the farm. Cotton acres expand to the maximum allowed in the program and alfalfa acreage is about 200 acres over the minimum required by rotation with most of the overage on soil type I. Onions are grown on soil types I and II and tomatoes are grown on types II and III (Table 15).
Model 2 (25)Results: Acreage and Income by Soil Type When water supplies are reduced 25-percent and alfalfa forced into the rotation, production is concentrated in alfalfa, cotton and tomatoes. Wheat replaces onions in the rotation and 1,036 acres are idled. Net income declines from about $2.5 million in the base model to about $1.98 million (Table 16). 
Alfalfa acres decline to the minimum required for each soil type. Cotton acres remain at the maximum on soil type I, but are reduced about 700 acres on soil type II. Set aside moves from soil type III to soil type II (Table 16). Fallow acres amount to more than 1,000 and more than 1,450 acres are idled, including set aside. Model 3 (40)Results: Acreage and Income by Soil Type Water supply reductions of 40-percent drop net income more than $1 million from the base situation. Cotton declines to 1,121 acres and slightly over $900 thousand in net revenue. Tomato acres decline to less than 100 and more than 2,200 acres are idled (Table 17). 
Alfalfa, cotton, tomatoes and wheat become the four staples of the farm and wheat acres are split between soil types I and II. Cotton is only grown on soil type I. Model 4 (NH)Results: Acreage and Income by Soil Type A final run relaxed the alfalfa requirement. In this case total alfalfa acres were slightly below the 1,275 acre minimum. In all other respects the model mirrored the base model (Table 18). With sufficient water supplies for all crops, slightly less alfalfa would be produced than in (B), about the same tomato acreage would be harvested and onion acreage would increase slightly. Wheat would be added and net income would increase about $20 thousand from the base (B). 
Optimized Results: Farm Program Transition The base model and its variations represent that which might be viewed as traditional farm organizations, based on the requirements imposed by the 1990 farm program. The next three sets of simulations evaluate some of the possibilities occurring from 1996 to 2003. In the interim, direct payments are made to participants, but set aside acres may be planted to other crops. In this sense, the set aside requirement was removed from the model. In addition, we continue with the relaxed alfalfa requirement. Model 5 (NSA)Results: Acreage and Income by Soil Type With the relaxation of the set aside requirement, alfalfa acres increased to 1,566 acres. This was more than 400 acres greater the model in which minimums were set for the three soil types, but with a set aside required. Most of the set aside acres were diverted to alfalfa production and a very slight increase in onion production occurred. This arrangement produced the highest net income of all contingencies tested (Table 19). This might be termed the "best of all worlds' possibility, since it included direct payments, no ARP and water supplies adequate to irrigate all crops (Table 19). 
Model 6 (NSA25) Results: Acreage and Income by Soil Type The second of the transitional simulations was about the same as previous, excepting a reduction of water supply of 25-percent was introduced, This simulation, like all of the water supply reduction alternatives in this series, eliminated alfalfa. With the set aside restriction removed and more limited water supplies available, the program resulted in the most diverse crop mix of all simulations with onions, garlic and cantaloupes all being produced. The resulting income was the highest of the two 25-percent water supply reduction alternatives tested, down about four percent from the bench mark (B) alternative (Table 20). 
It should be noted that all farm resources would be utilized. The other 25- percent water supply reduction tested resulted in more than 1,000 acres being idled. Fallow acres were absent since the absence of alfalfa made the production of the vegetable crops possible (Table 20). Model 7 (NSA40) Results: Acreage and Income by Soil Type The last transitional situation involved another 40-percent reduction in water supplies, but this time the manager has the option of reducing alfalfa acres and eliminating set aside. Again, alfalfa was eliminated, but as in the 25-percent reduction alternative, some vegetables were produced as alternatives to the lost alfalfa production (Table 21). 
Resulting income of $2.14 million is more than $600,000 higher than an analogous 40-percent water supply reduction alternative which embodied an alfalfa requirement. Optimized Results: Farming Without the Farm Program All farm programs are to be phased out by the year 2003. The last set of alternatives provide insight as to the nature of the model farm's organization after 2003, as well as to the nature and magnitude of income flows from the various enterprises. Three alternatives were considered. A base model similar to (B) used as the base model in the first seven simulations was constructed. All direct payments were eliminated as was the set aside requirement. Acreage restrictions on grains were removed but the 60- percent limitation on cotton acreage was retained. The first model used the full water supply assumption. The following two runs considered 25-percent and 40-percent water supply reductions respectively. Model 8 (NPRG) Results: Acreage and Income by Soil Type If full water supplies are available, the farm becomes a four crop enterprise, with nearly 1,900 acres of alfalfa produced. Cotton is again produced to the limit permitted. Onions and processing tomatoes comprise the balance of the rotation. Net income exceeds $2.46 million (Table 22). This total is about $100 thousand less than the base (B) result of $2.54 million. 
Model 9 (N25) Results: Acreage and Income by Soil Type A 25-percent water reduction again results in the elimination of alfalfa from the rotation. Tomato and onion acres are reduced and a very large increase in wheat acreage is introduced. Cotton is produced at the maximum level allowed by the program and the land resource of the operation is fully utilized (Table 23). 
Model 10 (N40) Results: Acreage and Income by Soil Type The final example evaluated a "free market" situation, coupled with a 40- percent water supply reduction. Cotton production to the maximum allowed by the program resulted. Tomato acres were the same as in the previous situation and more than 1,100 acres were fallowed. Net income was about $500,000 higher than the traditional 40-percent model, but about $120,000 less than the transitional model with a 40- percent water supply reduction (Table 24). 
Total Water Use: Alternatives Four situations were analyzed within which water supplies would be considered sufficient to irrigate all crops. The total amount of water used was functionally related to the type and magnitude of acres for each selected by the routine. The base (B) or traditional model resulted in about 16,700 acre feet of water being used. If alfalfa (NH) was not considered to be necessary for rotational purposes, this amount would decline to 15,627 acre feet. The transitional situation (NSA) in which set aside land could be used for production purposes resulted in the use of 15,627 acre feet of water. The greatest water use resulted from the "free market" alternative. This model resulted in 18,773 acre feet of water used on the farm (Table 25). Total water use under the remaining alternatives were dictated by the constraints introduced into the program. 
Crop Selection and Price Sensitivity Crop selection is usually dictated by a combination of available resources, institutional prices and producers' expectations concerning prices. This analysis has focused on the issue of resource allocation. Prices of most commodities included in this analysis move cyclically, with little evidence of upward trend. Onions and cantaloupes traditionally evidence substantial price variation. In evaluating this question of price sensitivity two issues are important. The first issue involves the actual magnitude of the price change necessary to bring the crop into the optimal solution. The second involves the issue of how frequently annual prices may exceed or fall below these threshold or entry prices. Cantaloupes. Cantaloupes were priced at $5.10 per carton in the model. According to the Westlands data, the probability of prices frequently (better than 50 percent of the time) exceeding these levels is not high. Onions. Onions are even more sensitive to price changes than cantaloupes. Onions were priced at $70 per ton in the model and were included in seven of the ten model situations at this level. According to Westlands data, a reasonable probability exists for prices frequently (better than 50 percent) of the time) exceeding these levels. Cotton. The case for cotton is quite interesting. Growers, using either the futures markets, basis contracts or forward contracts have "beaten" the price level chosen for this analysis and will likely do so in the future. Premium for California quality cotton is one factor. Production uncertainty in competing countries, particularly the former Soviet Union and China, is likely to continue. Although not included in the model results, price sensitivity for cotton was tested to $.70 and the optimal acreage mix was not altered. Obviously, overall profitability would be affected. CONCLUSIONS Our evaluation of the operating possibilities of this 5,100 acre model farm by no means exhausts all possibilities available for analysis. The study considers a series of alternatives ranging from moderate water supply contractions to those which could be considered fairly extreme. Major highlights of the study point to the following:
BIBLIOGRAPHY ____. Federal agriculture improvement and reform act of 1996; Title I: agricultural market transition program. Library of Congress, Washington, DC, (1996). California Agricultural Statistics Service. California field crop statistics. California Agricultural Statistics Service. 1980-94. Cothern, J.H. and Nef, D. Economics of crop production with surface water reduction alternatives: westlands water district, Center for Agricultural Business Publication 950201, Fresno, February:1995. Cothern, J.H. and Nef, D. Economic impact of surface water reduction alternatives: westlands water district and fresno county, Center for Agricultural Business Publication 950702, Fresno, July:1995. Cothern, J.H., Nef, D. and Hornor, J. The economic impact of 1990-91 surface water reductions: westlands water district and fresno county, Center for Agricultural Business Publication, Fresno, July:1994. Dorfman, R., Samuelson, P.A. and Solow, R.M. Linear programming and economic analysis, New York: Dover Publications, 1987. Kolb, Robert W., Understanding futures markets. 4th ed. Miami, Fla., Kolb Pub. Co., [1994]. Kolman, B. and Beck, R.E. Elementary linear programming with applications, 2nd Ed. San Diego: Academic Press, 1995. Ortmann, G.F., Patrick, G.F., Musser, W.N., Doster, D.H. Information sources, computer use, and risk management; evidence from leading commercial cornbelt farmers. Purdue University Agricultural Experiment Station Bulletin 638. (June:1992). Young, C.E. and Shields, D.A. Special provisions of the 1996 farm bill. Agricultural Outlook, Economic Research Service, Washington, DC, (April:1996). Young, C.E. and Westcott, P.C. The 1996 U.S. farm act increases market orientation. Agricultural Information Bulletin 726, Economic Research Service, Washington, DC, (August:1996). Westlands Water District. Water conservation and management handbook, Fresno. 1 James H. Cothern and Dennis L. Nef, Economics of Crop Production With Surface Water Reduction Alternatives: Westlands Water District, CATI Publication #950201, Center for Agricultural Business, February,1995 { page top } |
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