Regional yield estimation using a crop simulation model: Concepts, methods, and validation

Abstract

Crop simulation models are increasingly being used in the analysis of regional agricultural production systems. The purpose of this study was to develop and test an approach to estimate regional crop yields using a crop simulation model. Potential average annual maize ( Zea mays L.) yields for the period 1960–1989 in the Eastern crop reporting district of Illinois were estimated using a maize simulation model. Historical climate data were used, and representative soil series, crop varieties, and planting times for this region were considered in the simulations. The simulated potential yield was adjusted for economically efficient nitrogen use, disease, insect, and harvest losses to derive a final regional simulated yield. The simulated yield for each year of the study was compared to the historical average yield levels obtained by farmers in the region. To assess the value of incorporating varying levels of soil and planting date information in the model, four scenarios were considered: (1) one soil, one planting date; (2) three soils, one planting date; (3) one soil, seven planting dates, and (4) three soils, seven planting dates. The most detailed scenarios, (3) and (4), provided the best estimation of maize yields.