Simulation of Hail and Soil Type Effects on Crop Yield Losses in Kansas, USA

Abstract

Computer simulation was used for predictive analysis of the effects of weather and soil type on crop yield in the U.S. crop insurance program. The Environmental Policy Integrated Climate (EPIC) model was modified to include hail weather events, which completed the modifications necessary to simulate the four most frequent causes of crop yield loss (hail, excessive wet, excessive cold, and excessive dry) associated with soil type in Kansas, USA. At the region level, per hectare yields were simulated for corn, wheat, soybean, and sorghum. We concluded that it was possible to predict crop yields through computer simulation with greater than 93% accuracy. The hail damage model test indicated EPIC could predict hail-soil-induced yield losses reasonably well ( R 2 > 0.6). The investigation of soil type influence on dryland sorghum and wheat production indicated that Wymore silty clay loam soil and Kenoma silt loam produced the highest sorghum yields statistically; Kuma silt loam, Roxbury silt loam, Crete silty clay loam, and Woodson silt soils produced the second highest sorghum yields statistically; and Richfiled silt loam, Wells loam, and Canadian sandy loam produced the lowest sorghum yields. By contrast, wheat production showed less sensitivity to soil type variation. The less sensitive response of wheat yields to the soil type could be largely due to the unconsidered small-scale variability of soil features.