USING CLIGEN TO GENERATE RUSLE CLIMATE INPUTS

Abstract

CLIGEN is a stochastic weather generator that produces continuous daily variables to drive processbased runoffand erosion prediction models such as WEPP. To test CLIGENs ability to generate precipitationrelated variables, whichare particularly important to runoff and erosion prediction, algorithms were developed to compute the Rfactor, its monthlydistribution, and 10year storm erosion index (EI) needed to apply the Revised Universal Soil Loss Equation (RUSLE).Measured Rfactor and 10year storm EI for 76 sites in the U.S. were used for calibration, and 89 additional sites were usedfor validation. It was found that the generated Rfactor using CLIGEN is highly correlated with the measured Rfactor forthe calibration sites (r2 = 0.96), although the generated Rfactor is systematically larger than the measured Rfactor. Thepredicted Rfactor for validation sites has a model efficiency (Ec) of 0.92 and a root mean squared error of around 600 MJmm ha1 h1 year1, or 24% of the average Rfactor for the 89 sites. In addition, CLIGENgenerated precipitation data canalso be used to predict 10year storm EI (Ec = 0.75) and monthly distribution of rainfall erosivity for a wide range of climateenvironments (average discrepancy = 2.6%). This represents considerable improvement over existing methods to estimateRfactor and 10year storm EI for locations with only monthly precipitation data, although the systematic overestimationof the Rfactor using CLIGENgenerated climate data suggests possible inadequacies in the assumed storm patterns in CLIGEN and WEPP.