SWAT Literature Database for Peer-Reviewed Journal Articles

Title:Assessing the uncertainties of four precipitation products for SWAT modeling in Mekong River Basin 
Authors:Tang, X., J. Zhang, C. Gao, G.B. Ruben and G. Wang 
Journal:Remote Sensing 
Volume (Issue):11(3) 
Article ID:304 
URL (non-DOI journals): 
Broad Application Category:hydrologic only 
Primary Application Category:climate data effects 
Secondary Application Category:hydrologic assessment 
Watershed Description:795,000 km^2 Mekong River System, which drains parts of southwest China, eastern Myanmar, eastern Thailand, western Vietnam and much of Laos PDR and Cambodia. 
Calibration Summary: 
Validation Summary: 
General Comments: 
Abstract:Using hydrological simulation to evaluate the accuracy of satellite-based and reanalysis precipitation products always suffer from a large uncertainty. This study evaluates four widely used global precipitation products with high spatial and temporal resolutions [i.e., AgMERRA (AgMIP modern-Era Retrospective Analysis for Research and Applications), MSWEP (Multi-Source Weighted-Ensemble Precipitation), PERSIANN-CDR (Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Climate Data Record), and TMPA (Tropical Rainfall Measuring Mission 3B42 Version7)] against gauge observations with six statistical metrics over Mekong River Basin (MRB). Furthermore, the Soil and Water Assessment Tool (SWAT), a widely used semi-distributed hydrological model, is calibrated using different precipitation inputs. Both model performance and uncertainties of parameters and prediction have been quantified. The following findings were obtained: (1) The MSWEP and TMPA precipitation products have good accuracy with higher CC, POD, and lower ME and RMSE, and the AgMERRA precipitation estimates perform better than PERSIANN-CDR in this rank; and (2) out of the six different climate regions of MRB, all six metrics are worse than that in the whole MRB. The AgMERRA can better reproduce the occurrence and contributions at different precipitation densities, and the MSWEP has the best performance in Cwb, Cwa, Aw, and Am regions that belong to the low latitudes. (3) Daily streamflow predictions obtained using MSWEP precipitation estimates are better than those simulated by other three products in term of both the model performance and parameter uncertainties; and (4) although MSWEP better captures the precipitation at different intensities in different climatic regions, the performance can still be improved, especially in the regions with higher altitude. 
Keywords:SWAT model, AgMERRA, MSWEP, PERSIANN-CDR, TMPA, Uncertainty analysis, Mekong River Basin