Real-Time Irrigation Decision Analysis Using Simulation

AMETHODOLOGY is developed in which a dynamic crop simulation model is used to evaluate the expected profit and yield benefits for irrigating on any day of the season. The algorithm uses current season weather prior to the decision date and several years of historical weather data for the rest of the season. The user interacts with the computer, if necessary to update crop, soil, and economic information. Direct comparisons of expected net profit, water use, yield, and energy use are made for two options of the decision to (a) irrigate today or (b) wait one or more days to re-evaluate the need to irrigate. A soybean crop growth model (SOYGRO) was used to demonstrate this concept for soybean growing in sandy soil in a humid region. The model was first used to determine an optimal strategy based on 17 years of historical weather data. The sequential use of the real-time decision model during the 1978 growing season was shown to improve this long term strategy by about 5%. This algorithm allows users to input current product prices, fuel costs, and wather conditions to provide within-season adjustments to irrigation schedules that were formulated using long-term weather conditions and out-dated economic data.