Evaluation and improvement of the CLIGEN model for storm and rainfall erosivity generation in Central Chile

Abstract

CLIGEN (CLImate GENerator) is a stochastic weather generator that produces daily estimates of precipitation and individual storm parameters, including time to peak, peak intensity and storm duration. These parameters are typically used as inputs for other models, such as the Water Erosion Prediction Project (WEPP) model. Although CLIGEN has been proven to be effective for predicting daily estimates, some discrepancies have been observed when generating storm parameters, such as the storm duration. Therefore, a study was conducted to evaluate and improve CLIGEN for storm generation. Individual rainfall events were identified from 1-h pluviograph records that were collected from 30 sites in Central Chile. In this study, 415years of data were used; 18,012 storms were analyzed. In addition, rainfall erosivity was computed for all storms using the prescribed method to compare the energy provided by the measured and generated rainfall events. Using measured rainfall data, a procedure was developed to improve the CLIGEN estimates by calibrating the input parameter that controls the storm durations. This procedure in turn improved the rainfall intensities and erosivities. The model was tested before and after calibration with the measured rainfall data from the 30 sites in both the wet and dry seasons. Based on a monthly rainfall analysis, the results demonstrated that the number of storms and rainfall amounts, which are not affected by the calibration process, were accurately estimated with CLIGEN. However, before the calibration, especially in the wet season, the storm durations and maximum intensities were consistently overestimated and underestimated, respectively, at most of the sites and for most months. Therefore, the annual rainfall erosivities were underestimated with CLIGEN at 19 of the 30 sites. After performing the calibration, the R2 value for the CLIGEN-generated storm durations increased from 0.41 to 0.65. The maximum intensities also exhibited an improvement; the R2 value increased from 0.31 to 0.60. Consequently, annual rainfall erosivities were generated with an R2 value of 0.89; these erosivities were accurately estimated at 29 of the 30 sites. Therefore, this calibration procedure proved to be an effective alternative for generating more reliable storm patterns. This paper explains the procedure in detail and analyzes the parameters related to the individual storm generation process.