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

item LOBO, GABRIEL - Departamento De Ingeniería Hidráulica Y Ambiental, Pontificia Universidad Cato´lica De Chile
item Frankenberger, James - Jim
item Flanagan, Dennis
item BONILLA, CARLOS - Departamento De Ingeniería Hidráulica Y Ambiental, Pontificia Universidad Cato´lica De Chile

Submitted to: Catena
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 1/5/2015
Publication Date: 1/13/2015
Citation: Lobo, G.P., Frankenberger, J.R., Flanagan, D.C., Bonilla, C.A. 2015. Evaluation and improvement of the CLIGEN model for storm and rainfall erosivity generation in Central Chile. Catena. 127:206-213. DOI:10.1016/j.catena.2015.01.002.

Interpretive Summary: Erosion by water is driven by the weather, and especially rainfall amounts and rates. Computer simulation models are often used to estimate how much rainfall, runoff and soil erosion will occur, because it is impractical, difficult and expensive to measure runoff and soil loss in the field on a regular basis. Erosion models use inputs such as the amount of rainfall occurring on a day, the duration of a rain storm, and the rainfall intensity to determine how much soil is detached and transported from some field or other location on a landscape. This study used the CLIGEN (CLImate GENerator) stochastic weather generator (which is used with the Water Erosion Prediction Project soil erosion model) to produce long-term daily weather at 30 locations in the South American country of Chile. Over 18,000 measured rain storm events with 415 cumulative years were analyzed for storm characteristics, and used to test how well CLIGEN worked. We found that CLIGEN did a good job of estimating the number of storms and the rainfall amounts. However, it did not do as well at determining the storm durations and the maximum rainfall intensities. This paper describes a procedure to use the observed data to improve the input parameter to CLIGEN for the average annual thirty minute maximum rainfall depth. With this calibration procedure, the predicted rain storms output by the CLIGEN model were much closer to the input storm distributions, and the erosive power of all of a group of predicted rain storms much more closely matched those of the observed dataset. These results are important for scientists, engineers, natural resource conservationists, and others involved with application of soil erosion models and assessment of land management on runoff, erosion, and sediment losses. Being able to improve the climatic inputs for climate generation programs that drive erosion models will result in better estimates of rain storm events and resulting runoff and erosion.

Technical 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 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, 415 years 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 the 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 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.