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Capability of passive microwave and SNODAS SWE estimates for hydrologic predictions in selected U.S. watersheds. Missouri Basin River Forecaster’s Meeting 28-29 January 2014 Carrie M. Vuyovich, PE ERDC/CRREL. Overview. Background Distributed snow data available in the U.S.
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Capability of passive microwave and SNODAS SWE estimates for hydrologic predictions in selected U.S. watersheds Missouri Basin River Forecaster’s Meeting 28-29 January 2014 Carrie M. Vuyovich, PE ERDC/CRREL
Overview • Background • Distributed snow data available in the U.S. • Previous study to evaluate Snow Water Equivalent (SWE) data • Motivation for current study • Water Budget Analysis • Snowmelt Timing Comparison • Conclusions • 2011 Flood Demonstration
Distributed Snow Data in the U.S. NOAA National Operational Hydrologic Remote Sensing Center (NOHRSC) SNODAS • SWE estimates based on multi-sensor snow observations combined with energy balance snow model • Hourly/Daily gridded SWE product for conterminous U.S. • 1 km2 resolution • POR: October 2003 – Present • Sources of Error: • Uncertainty in forcing and observation data • Gaps in available observation data Snow Water Equivalent 21 Feb 2006 (Cline 2008) NOHRSC Flight Lines (http://www.nohrsc.noaa.gov/)
Distributed Snow Data in the U.S. Passive Microwave SWE • SSM/I • POR: July 1987 – Present • Algorithm: SWE = C(TB,19 – TB,37) • AMSR-E • POR: June 2002 – July 2011 • Algorithm accounts for forest cover, shallow/deep snow • Sources of Error • Wet snow • Vegetation • Saturation depth • Topography • Snow metamorphosis • 25x25 km resolution
Comparison of passive microwave and SNODAS SWE by HUC8 • Conclusion: Best comparison in areas with < 20% forest cover with an average annual maximum SWE < 200 mm Vuyovich et al, (in press), Water Resources Research SNODAS - AMSR-E SNODAS - SSM/I R2
Comparison of passive microwave and SNODAS SWE by HUC8 • Nash-Sutcliffe Efficiency measure: SNODAS - AMSR-E SNODAS - SSM/I
Great Plains SWE estimates • Objective: Evaluate SWE estimates from the 3 datasets (SNODAS, AMSR-E and SSM/I) by comparison to water budget components in selected Great Plains basins. • Sheyenne River near Cooperstown, ND • Cannonball River at Breien, ND • Moreau River near Whitehorse, SD • Bad River near Ft. Pierre, SD • Cheyenne River at Spencer, WY • White River near Interior, SD • White River near Oacoma, SD • Ponca Creek near Verdel, NE • South Loup River at St. Michael, NE
Methods • Where the SWE was the max annual value • R, P and ET are the total volume measured through the spring melt period, typically March – June • GW is the loss to deep groundwater • ΔSM is the change in soil moisture from the beginning to end of the period Water Budget data • Discharge: USGS daily streamflow records at basin outlet • Precipitation: NOAA CPC model output, NCDC stations • Evapotranspiration: NOAA CPC model output, NCDC stations • Soil Moisture: NOAA CPC model output for soil moisture
Example Results Sheyenne River at Cooperstown, ND Ponca Creek at Verdel, NE
Timing of snowmelt Winter snowpack and spring runoff for the 2008-09 water year in the Moreau River basin, SD. Timing of Spring runoff: typically corresponds to onset of snowmelt. Method: calculated timing difference between start of spring runoff and peak SWE
Conclusion • Passive microwave estimates of SWE are well-correlated to water budget components in the Great Plains region of the US. • Potential use for satellite SWE estimates in water resource applications in the Plains.
2011 Missouri River Flood 1Feb 1Mar 1Jan 1May 1Apr US Army Corps of Engineers, 2011