Simulating Winter Wheat Productivity under Various Climate Scenarios! (A03-zhang641286-oral)
Authors:
J. Zhang* - USDA-ARS
Abstract:
Hydrologic and crop models are useful tools for assessing the impacts of climate variation on natural resources. Most response models require daily weather input, which is often generated using stochastic daily weather generators. The objectives of this work are to evaluate the ability of the CLIGEN model to generate daily weather and to assess further the hydrologic and crop responses to generated climate scenarios at a field scale using the WEPP model. Four Oklahoma weather stations were used to evaluate the ability of the CLIGEN model to generate daily weather. The validated CLIGEN model was then used to generate typical climate scenarios that mimic wet-, dry-, and average-year conditions or to reproduce seasonal climate forecasts. The calibrated WEPP model was used to simulate grain yield of a winter wheat for the generated climate scenarios. The CLIGEN model is suitable to generate daily weather series of climate scenarios of particular interest. It provides a useful tool for downscaling monthly climate forecasts to daily values for input into crop models. Results also indicated that for 1%
increase in growing-season precipitation in central Oklahoma, wheat grain yield increased by 0.5 to 0.8%, depending on initial soil moisture conditions. This study shows that CLIGEN when used with crop models such as WEPP provides an effective means for assessing the impacts of seasonal climate variations or a particular forecast on wheat productivity.
Speaker Information: John Zhang, USDA-ARS, Grazinglands Res Lab 7207 W. Cheyenne St., El Reno, OK 73036; Phone: 405 262-5291; E-mail: [email protected]
Session Information: Wednesday, November 5, 2003, 2:10 PM-4:00 PM Presentation Start: 3:30 PM
