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ARS Home » Northeast Area » Beltsville, Maryland (BARC) » Beltsville Agricultural Research Center » Hydrology and Remote Sensing Laboratory » Research » Publications at this Location » Publication #365521

Research Project: Integrating Remote Sensing, Measurements and Modeling for Multi-Scale Assessment of Water Availability, Use, and Quality in Agroecosystems

Location: Hydrology and Remote Sensing Laboratory

Title: Comparison of satellite passive microwave with modeled snow water equivalent estimates in the Red River of the North Basin

Author
item SCHROEDER, R. - University Of New Hampshire
item JACOBS, J. - University Of New Hampshire
item CHO, E. - National Weather Service
item OLHEISER, C. - National Weather Service
item DEWEESE, M.M. - National Weather Service
item Cosh, Michael
item JIA, X. - North Dakota State University
item VUYOVICH, C. - Goddard Space Flight Center
item TUTTLE, S. - Mount Holyoke College

Submitted to: IEEE Journal of Selected Topics in Applied Remote Sensing
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 7/15/2019
Publication Date: 7/24/2019
Citation: Schroeder, R., Jacobs, J., Cho, E., Olheiser, C., Deweese, M., Cosh, M.H., Jia, X., Vuyovich, C., Tuttle, S. 2019. Comparison of satellite passive microwave with modeled snow water equivalent estimates in the Red River of the North Basin. IEEE Journal of Selected Topics in Applied Remote Sensing. 12(9):3233-3246. https://doi.org/10.1109/JSTARS.2019.2926058.
DOI: https://doi.org/10.1109/JSTARS.2019.2926058

Interpretive Summary: Snow water equivalent estimates from models are commonly used for flood forecasting applications, but this ignores current capabilities from passive microwave remote sensing. In this study, snow water equivalent estimates from satellites are compared to modeled products for the years 2003 to 2016 and evaluated for accuracy and variability. Observations for peak snow pack were observed to be 40 to 125% higher than the modeled estimates which would have a significant impact on water management and flood forecasting applications in the Red River of the North Basin. Future work includes the application of these observational data in the forecasting system operated by NOAA in this region.

Technical Abstract: The Red River of the North basin (RRB) is vulnerable to spring snowmelt flooding because of its flat terrain, low permeability soils, and the presence of river ice jams resulting from the river’s northward flow direction. The onset and magnitude of major flood events in the RRB have been very difficult to forecast, in part due to limited field observations of snow water equivalent (SWE). Coarse-resolution (25-km) passive microwave observations from satellite instruments are well suited for the monitoring of SWE. Despite routine use in the Earth sciences community to document the impacts of climate change, the use of passive microwave observations in operational flood forecasting is rare. This study compares daily satellite passive microwave SWE observations from SSM/I and SSMIS, AMSR-E, and AMSR2 from 2003 to 2016 to modeled output from the SNODAS and GlobSnow-2 in the RRB to determine the differences between the remotely sensed SWE estimates and the model products currently used in flood forecasting. Results show statistically significant differences between the satellite observations and SNODAS in the northern region of the basin that were not evident in the southern region. Satellite estimates of peak SWE in the forecast sub-basins in the northern region were 40-125% higher than the model results which points to the lack of ground observations used to constrain the model simulations. This study recommends that satellite SWE observations should be considered for improving operational snowmelt forecasting in the RRB.