ASSESSING SEASONAL CLIMATIC IMPACT ON WATER RESOURCES AND CROP PRODUCTION USING CLIGEN AND WEPP MODELS
Physically based response models are useful tools for assessing climatic impact on water resources and crop 
productivity. Most response models require daily weather, which is often synthesized using stochastic daily weather 
generators. Synthesis of climate scenarios using weather generators provides an effective means for making impact 
assessments. The objectives were to evaluate the ability of the CLIGEN model to generate various climate scenarios and to 
assess further the hydrological and crop productivity responses using the WEPP model. The CLIGEN model was evaluated 
at four Oklahoma weather stations with mean annual precipitation ranging from 420 to 1150 mm and was then used to 
generate typical climate scenarios that represent wet, dry, and average conditions for Chandler, Oklahoma. The WEPP model 
was used to simulate hydrologic and grain yield responses to the generated climate scenarios. Results show that CLIGEN 
simulated daily and monthly precipitation reasonably well. CLIGEN was capable of preserving statistics of monthly 
precipitation as well as reproducing seasonal precipitation patterns for the dry, average, and wet year conditions. Simulated 
surface runoff, deep percolation, and plant transpiration increased as precipitation increased, but the rates of the increase 
varied with initial soil moisture levels and total precipitation. Predicted percent increase of wheat grain yield per 1% increase 
of growing–season precipitation, which was a function of initial soil moisture and total precipitation, ranged from 0.5% to 
0.75%. Overall results indicate that CLIGEN is capable of translating monthly climate forecasts into daily weather series 
while preserving statistics of the forecasts. This study demonstrates that CLIGEN, when used in conjunction with response 
models such as WEPP, provides a useful tool for assessing the impact of seasonal climate variations or forecasts on water 
resources and crop production.