| 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 (Issue): | 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 |