The Impact of Spatial Soil Variability on Simulation of Regional Maize Yield

Abstract

Abstract. The study of climate variability and its impacts on crop production has become a continuous effort for the scientific community over the past two decades. However, the impact of spatial soil variability along with climatic factors on crop yield remains uncertain. The objective of this study was to determine the impact of soil and climatic variability on maize yield. We used Alabama as a case study because the agriculture is predominantly rainfed and there is a large variability in growing season precipitation due to the influence of climate variability signals such as the El Niño Southern Oscillation (ENSO). The cropping system model CERES-Maize of the Decision Support System for Agrotechnology Transfer (DSSAT) was used to simulate growth, development, and grain yield for maize for the top ten maize-producing counties in Alabama under rainfed conditions during dry and wet ENSO years. Maize yield simulations were compared for one prominent agricultural soil in each county, the top three prominent agricultural soils in each county, and spatially distributed SSURGO soils in each county. Simulated yields were then compared with maize yields reported by the National Agricultural Statistical Services (NASS). The simulation results showed that maize yield was impacted by both climate variability and spatial soil variability. Statistical relationships were established between crop yield, yield changes, and soil properties. This simulation study established the clear importance of soil variability in crop-climate impact studies. Keywords: Crop Modeling, DSSAT, Database, Soil properties, Spatial variability.