Determining the optimal timing of irrigations over a season in an uncertain environment is a significant problem in operating and planning irrigation schemes. In the absence of suitable experimental results, a plant growth-soil moisture simulation model is incorporated into a two state variable stochastic dynamic programing model to determine the optimal intraseasonal allocation pattern for irrigation water in a variable environment. Historical traces of climatic data are used, although these data could be synthesized. Given the initial assumptions within the model, the results suggest that an irrigator should maintain available soil moisture in the root zone at a high level, even if it means exhausting the water supply early in the season. However, optimal irrigation strategies are sensitive to changes in the biologic assumptions within the model and thus indicate the importance of good experimental data on which to base these assumptions.
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