Optimal Control of Irrigation Scheduling Using a Random Time Frame

Abstract

Abstract A dynamic programming model of irrigation scheduling is developed which accounts for stochastic weather conditions, results in simple irrigation decision rules, and can be operated on current microcomputers. The model employs heat unit intervals instead of chronological time to define the dynamic equations of the crop‐soil system. Procedures are outlined for estimating the transition probabilities of climate within the heat unit intervals. When compared to maximum yield irrigation scheduling, the model increases net returns of corn, sorghum, and cotton by $@@‐@@10.00 to $@@‐@@30.00 per acre.