Submitted to: Transactions of the ASAE
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: May 1, 2004
Publication Date: July 1, 2004
Citation: Zhang, X.J. 2004. Calibration, refinement, and application of the WEPP model for simulating climatic impact on wheat production. Transactions of the American Society of Agricultural Engineers. 47(4):1075-1085. Interpretive Summary: Crop simulation computer models are the most effective tools for evaluating crop responses to climate variations. The objectives of this work were to evaluate the ability of a computer program called Water Erosion Prediction Project (WEPP), to simulate hydrological and winter wheat responses to climate variations, and to illustrate the use of WEPP to assess the potential impact of generated climate scenarios on winter wheat production. Precipitation, surface runoff, soil moisture, and wheat biomass collected mainly between 1980 and 1995 at four 1.6-ha watersheds near El Reno, Oklahoma were used to evaluate or validate the WEPP model. Wet and dry climate scenarios were generated for El Reno using a climate generator (CLIGEN) to assess the potential climatic impact on wheat production. The WEPP model simulated seasonal soil moisture changes in the top 0.5-m soil layer reasonably well. However, it tended to over-predict soil moisture changes for the soil layers below the 0.5-m depth, indicating that WEPP-simulated wheat would be less susceptible to drought stress. The relationship between biomass production and total soil water consumption by wheat was well represented by the model. Model simulations under the generated dry and wet climate scenarios showed that simulated wheat grain yields were sensitive to initial soil moisture at El Reno. For a 1% increase in growing-season precipitation, wheat grain yields increased 0.7 and 0.5% for the 40 and 70% initial soil moisture conditions, respectively. This work demonstrates that the WEPP model, if calibrated rigorously, is capable of generating information needed by farmers and extension professionals for making informed management decisions with respect to a particular climate scenario or forecast.
Technical Abstract: Physically based response models are the best available tools for evaluating hydrological and crop responses to climate variations. The objectives here were to (i) evaluate or validate the water balance and crop components of the Water Erosion Prediction Project (WEPP) model, and (ii) further simulate hydrological and crop responses to generated climate scenarios. Precipitation, surface runoff, soil moisture, and wheat biomass collected mainly between 1980 and 1995 at four 1.6-ha watersheds near El Reno, Oklahoma were used. Wet and dry scenarios, generated for the location using a climate generator (CLIGEN), were used to run WEPP for impact assessment. The WEPP model simulated soil moisture fluctuations well in the top 0.5-m soil layer, but overpredicted the fluctuations in the deeper layers, indicating that WEPP-simulated wheat would be less susceptible to water stress. WEPP closely approximated the observed relationship between above ground biomass and growing-season ET, but the model tended to underpredict the year-to-year variability of above ground biomass due to its simplifying representation of reality. Such reduction in variability needs to be considered when utilizing simulated crop data in risk-based decision making. Simulated wheat grain yields were sensitive to initial soil moisture. For a 1% increase in growing-season precipitation, grain yields increased 0.7 and 0.5% for the 40 and 70% initial soil moisture conditions, respectively. Simulating crop yields for a particular climate scenario with yearly resetting of initial soil moisture, as was done in this study, allows yield forecasts to be focused primarily on the mean and the interquartile range of the simulated yield distribution. This approach has the potential of circumventing the inability of many climate generators including CLIGEN to reproduce annual precipitation extremes or low frequency variation. This work demonstrates that WEPP, in conjunction with CLIGEN, is capable of providing reliable information for making optimal management decisions with respect to a particular climate scenario or forecast.