Physically based hydrological and plant growth models are useful tools for assessing impacts of climate variations. Most response models require daily weather, which is often synthesized using stochastic daily weather generators. The objectives are to evaluate the ability of the CLImate GENerator (CLIGEN) model to generate various climate scenarios and to assess further the hydrological and crop productivity responses using the Water Erosion Prediction Project (WEPP) model. The 99 years of National Weather Service data of the Chandler station was used in the evaluation. The WEPP model was calibrated using field data collected from the Water Resource and Erosion watershed at El Reno, OK. Results showed that CLIGEN was capable of preserving statistics of monthly precipitation and reproducing seasonal precipitation patterns for the three year categories on the Chandler site. Predicted percent increase of wheat grain yield per 1% increase of precipitation, which was a function of initial soil moisture storage and total precipitation, ranged from 0.5 to 0.75%. This study demonstrated that CLIGEN, when used in conjunction with response models such as WEPP, could provide a useful tool for assessing the impact of seasonal and interannual climate variations derived from probabilistic type of climate forecast. More importantly, CLIGEN has the potential of downscaling monthly climate forecasts to daily weather series while preserving the statistics of the forecasts.