R-factor prediction for Australian and the U.S. sites using weather generators.

Abstract

CLIGEN is a stochastic weather generator to produce daily variables to drive process-based runoff and erosion prediction models such as WEPP. Algorithms were developed to compute the R-factor, its monthly distribution, and 10-year storm erosion index (EI) needed to apply the revised Universal Soil Loss Equation (RUSLE) using stochastically generated weather variables. Measured R-factor and 10-year storm EI for 43 sites in Australia and 75 sites in the United States were used to test whether CLIGEN can be used to produce necessary climate inputs for RUSLE. It was found that R-factor calculated using CLIGENgenerated weather sequences is well related to the measured R-factor for these sites (r2 = 0.94, n = 118). In addition, CLIGEN-generated precipitation data can be used to predict 10-year storm EI (r2 = 0.82), and monthly distribution of rainfall erosivity for a wide range of climate environments (average discrepancy about 1.9%). CLIGEN can be used to generate a range of climate inputs for runoff and soil erosion predictions. This represents considerable improvement over existing methods to estimate climate inputs for RUSLE.