SWAT Literature Database for Peer-Reviewed Journal Articles

Title:Evaluation of multi-satellite precipitation products for streamflow simulations: A case study for the Han River Basin in the Korean Peninsula, East Asia 
Authors:Vu, T.T., L. Li and K.S. Jun 
Article ID:642 
URL (non-DOI journals): 
Broad Application Category:hydrologic only 
Primary Application Category:climate data effects 
Secondary Application Category:calibration, sensitivity, and/or uncertainty analysis 
Watershed Description:26,219 km^2 Han River, which drains a small portion of southeast North Korea and most of the northern part of South Korea. 
Calibration Summary: 
Validation Summary: 
General Comments: 
Abstract:The accuracy and sufficiency of precipitation data play a key role in environmental research and hydrological models. They have a significant effect on the simulation results of hydrological models; therefore, reliable hydrological simulation in data-scarce areas is a challenging task. Advanced techniques can be utilized to improve the accuracy of satellite-derived rainfall data, which can be used to overcome the problem of data scarcity. Our study aims to (1) assess the accuracy of different satellite precipitation products such as Tropical Rainfall Measuring Mission (TRMM 3B42 V7), Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN), PERSIANN-Climate Data Record (PERSIANN-CDR), and China Meteorological Assimilation Driving Datasets for the SWAT Model (CMADS) by comparing them with gauged rainfall data; and (2) apply them for runoff simulations for the Han River Basin in South Korea using the SWAT model. Based on the statistical measures, that is, the proportion correct (PC), the probability of detection (POD), the frequency bias index (FBI), the index of agreement (IOA), the root-mean-square-error (RMSE), the mean absolute error (MAE), the coefficient of determination (R2), and the bias, the rainfall data of the TRMM and CMADS show a better accuracy than those of PERSIANN and PERSIANN-CDR when compared to rain gauge measurements. The TRMM and CMADS data capture the spatial rainfall patterns in mountainous areas as well. The streamflow simulated by the SWAT model using ground-based rainfall data agrees well with the observed streamflow with an average Nash-Sutcliffe efficiency (NSE) of 0.68. The four satellite rainfall products were used as inputs in the SWAT model for streamflow simulation and the results were compared. The average R2, NSE, and percent bias (PBIAS) show that hydrological models using TRMM (R2 = 0.54, NSE = 0.49, PBIAS = [-52.70–28.30%]) and CMADS (R2 = 0.44, NSE = 0.42, PBIAS = [-29.30–41.80%]) data perform better than those utilizing PERSIANN (R2 = 0.29, NSE = 0.13, PBIAS = [38.10–83.20%]) and PERSIANN-CDR (R2 = 0.25, NSE = 0.16, PBIAS = [12.70–71.20%]) data. Overall, the results of this study are satisfactory, given that rainfall data obtained from TRMM and CMADS can be used to simulate the streamflow of the Han River Basin with acceptable accuracy. Based on these results, TRMM and CMADS rainfall data play important roles in hydrological simulations and water resource management in the Han River Basin and in other regions with similar climate and topographical characteristics. 
Keywords:TRMM; PERSIANN; PERSIANN-CDR; CMADS; satellite-derived rainfall; streamflow simulation; SWAT; Han River