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On the Use of NLDAS2 Weather Data for Hydrologic Modeling in the Upper Mississippi River Basin

by Junyu Qi 1,*, Qianfeng Wang 2,* and Xuesong Zhang 1,3
1
Earth System Science Interdisciplinary Center, University of Maryland, College Park, MD 20740, USA
2
College of Environment and Resources, Fuzhou University, Fuzhou, Fujian 350116, China
3
Joint Global Change Research Institute, Pacific Northwest National Laboratory and University of Maryland, College Park, MD 20740, USA
*
Authors to whom correspondence should be addressed.
Water 2019, 11(5), 960; https://doi.org/10.3390/w11050960
Received: 10 February 2019 / Revised: 5 May 2019 / Accepted: 6 May 2019 / Published: 8 May 2019
(This article belongs to the Section Hydrology)
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. View Full-Text
Keywords: SWAT; reanalysis climate data; stream flow; watershed modeling SWAT; reanalysis climate data; stream flow; watershed modeling
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Qi, J.; Wang, Q.; Zhang, X. On the Use of NLDAS2 Weather Data for Hydrologic Modeling in the Upper Mississippi River Basin. Water 2019, 11, 960.

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