SWAT Literature Database for Peer-Reviewed Journal Articles

Title:Evaluation of multiple satellite precipitation products and use in hydrological modelling over the Luanhe River Basin, China 
Authors:Ren, P., J. Li, P. Feng, Y. Guo and Q. Ma 
Volume (Issue):10(6) 
Article ID:677 
URL (non-DOI journals): 
Broad Application Category:hydrologic only 
Primary Application Category:climate data effects 
Secondary Application Category:hydrologic assessment 
Watershed Description:33,700 km^2 portion of the Luanhe River, which drains to the Panjiakou Reservoir in northeast China. 
Calibration Summary: 
Validation Summary: 
General Comments: 
Abstract:Satellite precipitation products are unique sources of precipitation measurement that overcome spatial and temporal limitations, but their precision differs in specific catchments and climate zones. The purpose of this study is to evaluate the precipitation data derived from the Tropical Rainfall Measuring Mission (TRMM) 3B42RT, TRMM 3B42, and Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN) products over the Luanhe River basin, North China, from 2001 to 2012. Subsequently, we further explore the performances of these products in hydrological models using the Soil and Water Assessment Tool (SWAT) model with parameter and prediction uncertainty analyses. The results show that 3B42 and 3B42RT overestimate precipitation, with BIAs values of 20.17% and 62.80%, respectively, while PERSIANN underestimates precipitation with a BIAs of -6.38%. Overall, 3B42 has the smallest RMSE and MAE and the highest CC values on both daily and monthly scales and performs better than PERSIANN, followed by 3B42RT. The results of the hydrological evaluation suggest that precipitation is a critical source of uncertainty in the SWAT model, and different precipitation values result in parameter uncertainty, which propagates to prediction and water resource management uncertainties. The 3B42 product shows the best hydrological performance, while PERSIANN shows unsatisfactory hydrological performance. Therefore, 3B42 performs better than the other two satellite precipitation products over the study area. 
Keywords:TRMM 3B42RT; TRMM 3B42; PERSIANN; precipitation evaluation; SWAT model; uncertainty analysis