Economic simulation and optimization of irrigation water in humid regions.

摘要

combination of simulation, econometric, and optimization models were used to develop a methodology that can be applied to examine the effect of water scarcity on net farm income. Since both quantity, as well as, timing of irrigation has important bearing on crop yield, a biophysical simulation model, known as Erosion Productivity Impact Calculator (EPIC), was used to simulate the relationship between water, from rainfall and/or various irrigation management practices, and crop yields. The water yield response functions for selected crops were estimated using EPIC simulated data. The estimated parameters of these yield response functions were used to develop a recursive stochastic linear programming model.;In the resulting model, rainfall was treated as a stochastic process, which follows its own historical pattern randomly. This capability to deal with an erratic rainfall process distinguishes the recursive stochastic linear programming model from other multi-period programming models. The optimization model was designed to solve a series of irrigation decisions problem faced by a model farm, which is growing corn, cotton, and peanuts. Different irrigation decision rules were derived for dry and normal weather conditions. Using a preference scale and the flow data of Chattahoochee river measured at Columbus, the residual flow that could be used for crop irrigation was calculated. The results indicated that even if the historical flow could be maintained in the future, it would not be enough to meet the total irrigation demand in many instances.;The aggregate optimal demand for irrigation water in the Middle Chattahoochee Sub-Basin was estimated to be 3.211 million gallons per week. The contribution of this optimal irrigation level to net farm income would be