HR: 0830h
AN: H41A-04    [Abstracts]
TI: Improved Forecasting of Spring Snowmelt Runoff in the Ob River Basin Using Satellite-Derived Snow Volumes
AU: * Stoll, J
EM: Jeremy.Stoll@gsfc.nasa.gov
AF: Science Systems and Applications, Inc., 10210 Greenbelt Road Suite 600, Lanham, MD 20706 United States
AU: Jasinski, M
AF: Goddard Space Flight Center, NASA/GSFC Mail Code 614.3, Greenbelt, MD 20771 United States
AU: Perica, S
AF: University of Utah, University of Utah Dept. of Civil and Environmental Eng. 122 South Central Campus Drive, Salt Lake City, UT 84112 United States
AU: Brubaker, K
AF: University of Maryland, College Park, EGR 1173 University of Maryland, College Park, MD 20742 United States
AB: In high latitude river basins like the Ob in central Siberia, snowmelt runoff can contribute 75 percent of the annual streamflow. As is the case with many remote basins, in-situ snow data for the Ob basin are sparse, and therefore satellite data must be relied upon for accurate modeling. This current study seeks to improve forecasts of the spring snowmelt runoff through the incorporation of winter satellite derived snow water equivalent into a precipitation runoff model. The snow product used is Scanning Multichannel Microwave Radiometer (SMMR) snow depth imagery with a 0.25 degree resolution for the period 1980-1987. Spatial and temporal biases of the SMMR images are corrected through the development of a set of correction factors using 10-day NSIDC snow depth measurements. The satellite data are used in conjunction with local meteorological forcing and an enhanced version of the original USGS Precipitation Runoff Model to estimate runoff. Results indicate the use of the satellite imagery for both calibration and forcing purposes improves the annual spring snowmelt forecast.
DE: 1836 Hydrologic budget (1655)
DE: 1860 Runoff and streamflow
DE: 3360 Remote sensing
SC: Hydrology [H]
MN: 2005 Joint Assembly