- Spring 1995 "Update" Newsletter Article -

Program projects crop alternatives

From CATI Publication #950401
Copyright © 1995. All rights reserved.



Following a winter of heavy rains and flooding in California, restrictions on the use irrigation water may be the least of the concerns of San Joaquin Valley farm producers for the 1995 growing season.

Nevertheless, water shortages have been and will likely continue to be a recurring problem as annual weather seasons vary and the state's population continues to grow.

To help address that anticipated problem, a CSU, Fresno agribusiness researcher has used a high-powered software package to project profitable production scenarios in response to irrigation water shortages in the western San Joaquin Valley.

Agricultural economics professor James Cothern has included the production scenarios in a recently-produced publication entitled "Economics of Crop production with Surface Water Reduction Alternatives: Westlands Water District."

The report considers scenarios in which water deliveries to Westlands Water District from the federal Central Valley Project are reduced by eight amounts ranging from 25 to 50 percent. Cothern uses records of recent crop production levels and prices to determine which crop combinations would be most profitable under different irrigation water reduction scenarios.

Certain considerations, such as water use by different crops and possible price changes due size of yield, make the issue of profitability extremely complex, especially since there are 19 crops traditionally grown on the 500,000 acres comprising the Westlands Water District area, Cothern notes. That's where computer software becomes very useful.

"A properly constructed linear program has the ability to evaluate a very large number of alternative enterprise combinations and find those that yield the greatest possible net return," he said.

The software used for the analysis was developed with an optimizing program contained within Quattro Pro for Windows ver. 5.0® (QPW).

In order to obtain the most accurate profit projections possible, Cothern constructed a "normal" base model incorporating four-year moving averages of acreage, yields, and prices. "We systematically looked at the district historic economic picture as compared to projections of that which would occur with reductions in the future water supplies," he said.

The technique used to make the projections, linear programming, was formulated to solve a special set of conditions:
    1) a desire to maximize profit or minimize costs, 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.

Specific results from the projections include a wide range of crop combinations outlined in various tables in the report. Some general conclusions drawn from the software include the following:
    1) Cotton is the dominant crop in the district and few alternatives exist as substitutes for the current acreage devoted to its cultivation.
    2) Alfalfa and grain production are the most vulnerable to a combination of water supply diminishment and/or cost increases.
    3) Fruit, nut and vegetable production are the least vulnerable to changes in water costs, but demand considerations limit expansion of these crops as replacements for reductions in cotton acreage.
    4) High-risk vegetable crops, like cantaloupes, exhibit extreme price variability, limiting their ability to displace institutionally stable crops like cotton, sugar beets, tomatoes and onions.
    5) Expansion in grain production offers an acreage expansion possibility in the event cotton production is curtailed, but substantial declines in district net receipt would still occur.

Copies of the report are available from the California Agricultural Technology Institute. For ordering information, see the Publications Available form on Page 7.

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CALIFORNIA AGRICULTURAL TECHNOLOGY INSTITUTE - CATI
College of Agricultural Sciences and Technology
California State University, Fresno