Abstract
In the U.S., a dedicated system of snow measurement stations and snowpack modeling products is available to estimate the snow water equivalent (SWE) throughout the winter season. In other regions of the world that depend on snowmelt for water resources, snow data can be scarce, and these regions are vulnerable to drought or flood conditions. Even in the U.S., water resource management is hampered by limited snow data in certain regions, as evident by the 2011 Missouri Basin flooding due in large part to the significant Plains snowpack. Satellite data could potentially provide important information in under‐sampled areas. This study compared the daily AMSR‐E and SSM/I SWE products over nine winter seasons to spatially distributed, modeled output SNODAS summed over 2100 watersheds in the conterminous U.S. Results show large areas where the passive microwave retrievals are highly correlated to the SNODAS data, particularly in the northern Great Plains and southern Rocky Mountain regions. However, the passive microwave SWE is significantly lower than SNODAS in heavily forested areas, and regions that typically receive a deep snowpack. The best correlations are associated with basins in which maximum annual SWE is less than 200 mm, and forest fraction is less than 20%. Even in many watersheds with poor correlations between the passive microwave data and SNODAS maximum annual SWE values, the overall pattern of accumulation and ablation did show good agreement and therefore may provide useful hydrologic information on melt timing and season length.
Department
Earth Systems Research Center
Publication Date
10-27-2014
Journal Title
Water Resources Research
Publisher
American Geophysical Union (AGU)
Digital Object Identifier (DOI)
Document Type
Article
Recommended Citation
Vuyovich*, C.M., J.M Jacobs and S.F. Daly. 2014. Comparison of passive microwave and SNODAS estimates of total watershed SWE in the continental U.S. Water Resources Research. doi: 10.1002/2013WR014734.
Rights
© 2014. American Geophysical Union. All Rights Reserved.
Comments
This is an article published by AGU in Water Resources Research in 2014, available online: https://dx.doi.org/10.1002/2013WR014734