PRISM vs. CFSR Precipitation Data Effects on Calibration and Validation of SWAT Models

详细信息    查看全文

• 作者：D.E. Radcliffe and R. Mukundan
• 刊名：JAWRA Journal of the American Water Resources Association
• 出版年：2017
• 出版时间：February 2017
• 年：2017
• 卷：53
• 期：1
• 页码：89-100
• 全文大小：1267K
• ISSN：1752-1688

文摘

Precipitation is one of the most important drivers in watershed models. Our objective was to compare two sources of interpolated precipitation data in terms of their effect on calibration and validation of two Soil and Water Assessment Tool (SWAT) models. One model was a suburban watershed in metropolitan Atlanta, Georgia. The precipitation sources were Parameter-elevation Relationships on Independent Slopes Model (PRISM) data on a 4-km grid and climate forecast system reanalysis (CFSR) data on a 38-km grid. The PRISM data resulted in a better fit to the calibration data (Nash Sutcliffe efficiency [NSE] = 0.64, Kling-Gupta efficiency [KGE] = 0.74, p-factor = 0.84, and r-factor = 0.43) than the CFSR data (NSE = 0.47, KGE = 0.53, p-factor = 0.67, and r-factor = 0.39). Validation results were similar. Sensitive parameters were similar in both the PRISM and CFSR models, but fitted values indicated more rapid groundwater flow to the streams with the PRISM data. The same comparison was made in the Big Creek watershed located approximately 1,000 km away, in central Louisiana. Results were similar with a more responsive groundwater system indicating PRISM data may produce better predictions of streamflow because of a more accurate estimate of rainfall within a watershed or because of a denser grid. Our study implies PRISM is providing a better estimate than CFSR of precipitation within a watershed when rain gauge data are not available, resulting in more accurate simulations of streamflows at the watershed outlet. Editor's note: This paper is part of the featured series on SWAT Applications for Emerging Hydrologic and Water Quality Challenges. See the February 2017 issue for the introduction and background to the series.