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<br />[1]*. This model simulates the decisions which a rational farmer would make <br />in planning agricultural production in such a way as to optimize his net <br />returns. It takes into consideration the interrelationships between the <br />basic factors of production (water, land, labor, capital equipment and pro- <br />duction inputs such as seed, pesticide, fuel, and fertilizer) and crop out- <br />put. The model also includes significant factors which constrain cropping <br />decisions such as crop rotation and risk diversification. When crop prices <br />and input levels and prices are specified, the LP model then determines the <br />mix of crops which will maximize a specified objective--the farmer's <br />"profit", defined as the total returns to land and to the farm owner's <br />management efforts (Returns to Land and Management, or RLM). The model <br />calculates the total amount of each crop which will be produced, and the <br />amount of each input required. One or more inputs can be constrained in the <br />model either in the total quantity available or in the amount used per acre. <br />Thus the model will use no more than the available number of arable acres or <br />a restricted amount of water per acre. Each of the six participating states <br />built upon previous research in linear-programming farm enterprise models to <br />construct models for the High Plains Study to reflect the particular con- <br />ditions in different portions of the Study Region. Relationships between the <br />various factors of production in the models were changed over the forty-year <br />plus study period to reflect anticipated changes in agricultural and irriga- <br />tion technology. <br /> <br />Input to the LP farm enterprise models came from a variety of sources. <br />Ground water experts in each state developed estimates of the depth to ground <br />water and remaining water in storage in the Ogallala Aquifer using state <br />hydrology models [2]*. Depth to water and total dynamic head are used to <br />determine the amount of energy required to pump an acre-foot of water in a <br />particular subregion of the Ogallala. When combined with energy prices, this <br />produces an estimate of the water input costs for use in the LP models. When <br />resulting crop production is determined by the LP model, the amount of water <br />drawn from the Aquifer can be calculated, and the depth to water and the well <br />yield of remaining water reserves are reestimated. This iterative process <br />provides the key measure of remaining ground water supplies for each <br /> <br />* Numbers in brackets refer to the corresponding numbered models or <br />activities in Figure 1. <br /> <br />A-6 <br />