A comparison of MODIS and NOHRSC snow-cover products for simulating streamflow using the Snowmelt Runoff Model Academic Article uri icon

abstract

  • Remote sensing is an important source of snow-cover extent for input into the Snowmelt Runoff Model (SRM) and other snowmelt models. Since February 2000, daily global snow-cover maps have been produced from data collected by the Moderate Resolution Imaging Spectroradiometer (MODIS). The usefulness of this snow-cover product for streamflow prediction is assessed by comparing SRM simulated streamflow using the MODIS snow-cover product with streamflow simulated using snow maps from the National Operational Hydrologic Remote Sensing Center (NOHRSC). Simulations were conducted for two tributary watersheds of the Upper Rio Grande basin during the 2001 snowmelt season using representative SRM parameter values. Snow depletion curves developed from MODIS and NOHRSC snow maps were generally comparable in both watersheds: satisfactory streamflow simulations were obtained using both snow-cover products in larger watershed (volume difference: MODIS, 2.6%; NOHRSC, 14.0%) and less satisfactory streamflow simulations in smaller watershed (volume difference: MODIS, -33.1%; NOHRSC, -18.6%). The snow water equivalent (SWE) on 1 April in the third zone of each basin was computed using the modified depletion curve produced by the SRM and was compared with in situ SWE measured at Snowpack Telemetry sites located in the third zone of each basin. The SRM-calculated SWEs using both snow products agree with the measured SWEs in both watersheds. Based on these results, the MODIS snow-cover product appears to be of sufficient quality for streamflow prediction using the SRM in the snowmelt-dominated basins. Copyright 2005 John Wiley & Sons, Ltd.

published proceedings

  • HYDROLOGICAL PROCESSES

author list (cited authors)

  • Lee, S. W., Klein, A. G., & Over, T. M.

citation count

  • 88

complete list of authors

  • Lee, SW||Klein, AG||Over, TM

publication date

  • October 2005

publisher