SWAT Literature Database for Peer-Reviewed Journal Articles

Title:On the use of NLDAS2 weather data for hydrologic modeling in the Upper Mississippi River Basin 
Authors:Qi, J., Q. Wang and X. Zhang 
Year:2019 
Journal:Water 
Volume:11(5) 
Pages: 
Article ID:960 
DOI:10.3390/w11050960 
URL (non-DOI journals): 
Model:SWAT 
Broad Application Category:hydrologic only 
Primary Application Category:climate data effects 
Secondary Application Category:hydrologic assessment 
Watershed Description:431,000 km^2 Upper Mississippi River Basin, which drains large parts of the states of Illinois, Iowa, Minnesota, Missouri, and Wisconsin and smaller portions of Indiana, Michigan, and South Dakota in the north central U.S. 
Calibration Summary: 
Validation Summary: 
General Comments: 
Abstract:Weather data are the key forces that drive hydrological processes so that their accuracy in watershed modeling is fundamentally important. For large-scale watershed modeling, weather data are either generated by using interpolation methods or derived from assimilated datasets. In the present study, we compared model performances of the Soil and Water Assessment Tool (SWAT), as driven by interpolation weather data, and NASA North American Land Data Assimilation System Phase Two (NLDAS2) weather dataset in the Upper Mississippi River Basin (UMRB). The SWAT model fed with different weather datasets were used to simulate monthly stream flow at 11 United States Geological Survey (USGS) monitoring stations in the UMRB. Model performances were evaluated based on three metrics: coefficient of determination (R2), Nash–Sutcliffe coefficient (NS), and percent bias (Pbias). The results show that, after calibration, the SWAT model compared well at all monitoring stations for monthly stream flow using different weather datasets indicating that the SWAT model can adequately produce long-term water yield in UMRB. The results also show that using NLDAS2 weather dataset can improve SWAT prediction of monthly stream flow with less prediction uncertainty in the UMRB. We concluded that NLDAS2 dataset could be used by the SWAT model for large-scale watersheds like UMRB as a surrogate of the interpolation weather data. Further analyses results show that NLDAS2 daily solar radiation data was about 2.5 MJ m-2 higher than the interpolation data. As such, the SWAT model driven by NLDAS2 dataset tended to underestimate stream flow in the UMRB due to the overestimation in evapotranspiration in uncalibrated conditions. Thus, the implication of overestimated solar radiation by NLDAS2 dataset should be considered before using NLDAS2 dataset to drive the hydrological model. 
Language:English 
Keywords:SWAT; reanalysis climate data; stream flow; watershed modeling