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United States Department of Agriculture

Agricultural Research Service

Title: Simulating Winter Wheat Productivity under Various Climate Scenarios.

Author
item Zhang, Xunchang

Submitted to: American Society of Agronomy Abstracts
Publication Type: Abstract Only
Publication Acceptance Date: October 1, 2003
Publication Date: November 1, 2003
Citation: ZHANG, J. SIMULATING WINTER WHEAT PRODUCTIVITY UNDER VARIOUS CLIMATE SCENARIOS. CD-ROM. MADISON, WI: AMERICAN SOCIETY OF AGRONOMY. 2003.

Interpretive Summary: Abstract Only.

Technical Abstract: Physically based 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 were to evaluate the ability of the CLIGEN model to generate daily weather of particular climate scenarios and to assess further the hydrologic and crop responses to generated climate scenarios at a field scale using the Water Erosion Prediction Project (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, and to reproduce NOAA's seasonal climate forecasts. The calibrated WEPP model was used to simulate grain yield of winter wheat for the generated climate scenarios. The CLIGEN model is suitable to generate daily weather series of climate scenarios of particular interest, and is a useful tool for downscaling monthly climate forecasts to daily values for use with crop models. Results also indicated that for a 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 seasonal/climate forecast on crop productivity.

Last Modified: 8/27/2014
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