Submitted to: Transactions of the ASAE
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: November 1, 2002
Publication Date: November 1, 2002
Citation: Zhang, X.C., Garbrecht, J.D. Evaluation of CLIGEN precipitation parameters and their implication on WEPP runoff and soil loss prediction. Transactions of the American Society of Agricultural Engineers. 2003. v. 46(2). p. 311-320. Interpretive Summary: Daily precipitation data are needed for driving many hydrological and natural resource management models. Since measured daily precipitation data are only available from a limited number of weather stations, climate generators (computer models) are often used to generate daily weather. The quality of generated daily weather directly affects the output of those response models. This work evaluated the ability of a widely used climate generator (CLIGEN) in generating daily, monthly, and annual precipitation amounts, and storm patterns (i.e. storm duration, peak rainfall intensity, and time to peak rainfall), and to study further the impact of generated storm patterns on soil erosion and runoff prediction using a computer model (WEPP). Historic daily precipitation data from four Oklahoma stations and eight other sites dispersed across the U.S. were used in the study. Results indicate that CLIGEN satisfactorily generated daily, monthly, and annual precipitation amounts. However, the generated storm duration was too long for small storms and too short for large storms. Inadequate storm duration led to over-prediction of surface water runoff and soil loss. Overall, this work shows that the CLIGEN model is a useful tool for generating daily precipitation series, which can be used by scientists and extension specialists to evaluate natural resource responses to climate variations. However, storm duration generation should be reevaluated to improve future runoff and erosion predictions.
Technical Abstract: The quality of synthesized daily weather directly affects the output of hydrological and agricultural response models. The objectives of this study are to evaluate the ability of the CLIGEN model to reproduce daily, monthly, and annual precipitation amounts, extremes, and storm patterns (i.e. storm duration, relative peak intensity, and time to peak), and to assess further the impact of generated storm patterns on WEPP runoff and erosion prediction. Four Oklahoma stations with more than 50 years of daily precipitation data, and eight other sites across the U.S. with an average record of 10 years of measured storm patterns were used. Average absolute errors for simulating daily, monthly, and annual precipitations across the 4 Oklahoma stations were 4.7, 1.7, and 1.5% for the means and 3.7, 6.7, and 15% for the standard deviations, respectively. Mean absolute errors for the all-time maxima of daily, monthly, and yearly precipitation were 17.7, 8.9, and 6.5%, respectively. Storm pattern generation, especially storm duration, needs improvement for better prediction of runoff and soil erosion. The CLIGEN-generated durations were generally too long for small storms and too short for large storms. Inaccurate storm pattern generation led to WEPP prediction errors as high as 35% for average annual runoff and 47% for annual sediment yield on the test sites. To improve WEPP runoff and erosion prediction, storm duration generation should be reevaluated, and a distribution free type approach may be used to induce proper correlations between the input storm variables.