Using Crop Models for Management: Impact of Weather Characteristics on Irrigation Decisions in Soybeans

CROP simulation models that respond to daily weather data are being developed to assist within-season decision making. In this study, a soybean crop model was implemented to evaluate real-time irrigation decisions. The sensitivities of these decisions and of resulting profit to current season weather data, short-term weather forecasts, and assumptions about future weather were investigated for three separate seasons. The analysis indicated that actual rainfall data prior to each decision date were essential. There were increases in net profit of 2 to 3% when actual potential evapotranspiration data were used prior to each decision date instead of historical averages. The use of average temperature and radiation decreased profit by only 1 to 2%. These results suggest that savings in real-time weather data collection may be realized for practical applications of crop models for scheduling irrigations in Florida. Future weather and management conditions had a large impact on the irrigation schedules and the net profit simulated by the model. Therefore, reliable short-term precipitation forecasts coupled with location-specific precipitation probability distributions for the remainder of the season were needed for applying the soybean crop model to make real-time irrigation decisions.