Application of CSM-CERES-Wheat Model for Irrigation Management of Winter Wheat in the Texas High Plains.

Climate change and recurring drought events in many areas of the world are expected to bring challenges to crop production and food security. Crop growth models, following calibration and validation, offer the opportunity to test response of crop plants to a large number of treatments across long term weather datasets. The CERES-Wheat (DSSAT) model simulates wheat response to environmental factors such as weather, soils, and management on a daily basis. Objectives of this study were i) to investigate the response of winter wheat to various irrigation treatments in the Texas High Plains and ii) to determine the best irrigation strategy that increases water use efficiency and optimizes the yield. Data from field experiments conducted in the Texas High Plains in 1992, 1997, and 1998 were used to calibrate and validate the model. These studies investigated wheat grain yield response to different irrigation treatments. After validation, the model was used to simulate wheat yield response to various irrigation treatments using historical weather dataset from the Texas High Plains (1980-2012). Results from these simulation experiments will be presented.