Submitted to: Remote Sensing and Modeling Applications for Natural Resource Management
Publication Type: Abstract Only
Publication Acceptance Date: 3/13/2002
Publication Date: N/A
Technical Abstract: Crop yield is affected by many factors, primarily encompassing soil and weather conditions, and agronomic management practices. Crop modeling can be used to help understand how multiple factors interact and impact yield. The objectives of this study were to evaluate the performance of the CERES-Maize and CROPGRO-Soybean models for simulating site-specific crop growth, soil water content, and grain yield on claypan soils. Data were obtained during low and average rainfall conditions from two sites over three years in central Missouri. Plant (e.g., yield, leaf area, root length density) and soil (e.g., topsoil thickness, moisture, texture) measurements were collected for calibrating and validating the models. Results indicated that simulated soil water contents in the 15-90 cm soil profile agreed well with measured values, with the exception of sites located in lower elevation areas of the field where topsoil thickness was over a 100 cm. The shallow topsoil thickness areas on eroded sideslopes potentially contributed to subsurface flow during days following major rainfall events, in addition to surface runoff during the rainfall events. Simulated leaf area index and grain yield also agreed well with measured values during average precipitation years, but were under-estimated during extremely dry years. Within-season precipitation and claypan soil topsoil thickness were shown to have greatest influence on simulated yield. Although we hypothesized it to be otherwise, field measurements in 1997 showed that the claypan (with much greater clay content and less soil structure than topsoil above it) did not negatively affect soybean root penetration.