SWAT Literature Database for Peer-Reviewed Journal Articles

Title:Evaluation of gridded precipitation data for driving SWAT Model in area upstream of Three Gorges Reservoir 
Authors:Yang, Y., G. Wang, L. Wang, J. Yu and Z. Xu 
Journal:PLOS ONE 
Article ID: 
URL (non-DOI journals):http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0112725 
Broad Application Category:hydrologic only 
Primary Application Category:climate data effects 
Secondary Application Category:hydrologic assessment 
Watershed Description:1,098 km^2 Dong River and 366 km^2 Puli River, located in the upstream portion of the Three Gorges Reservoir region in central China 
Calibration Summary: 
Validation Summary: 
General Comments:As of March 3, 2015 the DOI for this article connects to a messy, unformatted version of the article webpage. However, the URL for the article connects to the correct, formatted webpage for the article. 
Abstract:Gridded precipitation data are becoming an important source for driving hydrologic models to achieve stable and valid simulation results in different regions. Thus, evaluating different sources of precipitation data is important for improving the applicability of gridded data. In this study, we used three gridded rainfall datasets: 1) National Centers for Environmental Prediction - Climate Forecast System Reanalysis (NCEP-CFSR); 2) Asian Precipitation - Highly-Resolved Observational Data Integration Towards Evaluation (APHRODITE); and 3) China trend - surface reanalysis (trend surface) data. These are compared with monitoring precipitation data for driving the Soil and Water Assessment Tool in two basins upstream of Three Gorges Reservoir (TGR) in China. The results of one test basin with significant topographic influence indicates that all the gridded data have poor abilities in reproducing hydrologic processes with the topographic influence on precipitation quantity and distribution. However, in a relatively flat test basin, the APHRODITE and trend surface data can give stable and desirable results. The results of this study suggest that precipitation data for future applications should be considered comprehensively in the TGR area, including the influence of data density and topography.