Skip to main content
ARS Home » Plains Area » Las Cruces, New Mexico » Range Management Research » Research » Publications at this Location » Publication #159668
Title: INTEGRATING TWO REMOTE-SENSING-BASED HYDROLOGICAL MODELS AND MODIS DATA TO IMPROVE WATER SUPPLY FORECASTS IN THE RIO GRANDE BASIN

Author
item Rango, Albert
item GOMEZ-LANDESA, ENRIQUE - NEW MEXICO STATE UNIV
item BLEIWEISS, MAX - NEW MEXICO STATE UNIV
item DEWALLE, DAVID - PENNSYLVANIA STATE UNIV
item KITE, GEOFF - HYDROLOGICAL SOLUTIONS
item MARTINEC, JAROSLAV - HYDROLOGICAL CONSULTANT
item Havstad, Kris

Submitted to: Meeting Proceedings
Publication Type: Proceedings
Publication Acceptance Date: 7/11/2004
Publication Date: 7/11/2004
Citation: Rango, A., Gomez-Landesa, E., Bleiweiss, M., Dewalle, D., Kite, G., Martinec, J., Havstad, K.M. 2004. Integrating two remote-sensing-based hydrological models and MODIS data to improve water supply forecasts in the Rio Grande Basin. In: Proceedings of the British Hydrological Society International Conference on Hydrology: Science and Practice for the 21st Century, July 12-16, 2004, Imperial College, London, UK. 1:451-457.

Interpretive Summary: Interpretive summary not required.

Technical Abstract: Remotely sensed data can be used with modern hydrological models to provide effective water supply forecasts and to evaluate water resource management options. MODIS, on both NASA TERRA and AQUA satellites, is the likely optimum sensor for snow mapping because it has a best resolution of 250 m (two bands), it passes over daily, it is free for downloading, and it provides a logical transition from 1-km NOAA-AVHRR data. Its worth for snow mapping has been proven both in the Rocky Mountains of the U.S. and the Pyrenees of Spain. Still, research to solve automation and operational problems is ongoing, including corrections for the 'bow-tie' effect, mapping in shaded and heavily vegetated areas, and using bidirectional reflectance distribution functions to retrieve snow albedo. As the remote sensing improvements are made, the data are used in the upper Rio Grande basin for improvement of the snowmelt forecasting system. Remote snow water equivalent site data is acquired through the Natural Resources Conservation Service SNOTEL system employing meteor-burst relay. These data can be used for early season (November-December-January), volumetric forecasts that increase water management flexibility. The MODIS-derived snow cover data are input to the Snowmelt Runoff Model (SRM) for generating daily streamflow forecasts over the entire melt season. Because snowmelt runoff is not significant throughout the entire basin, SRM outflow from snowmelt basins is linked to the Semi-Distributed, Land-Use-Based Runoff Process (SLURP) model as an input. SLURP is a comprehensive, distributed model now operating on the entire basin to assist in water management decision making today and to evaluate future scenarios for improving long-range planning. SLURP is also used for remote sensing inputs to establish current land cover throughout the basin and to derive the Leaf Area Index for use in evapotranspiration algorithms. Examples of forecasts for 2001-2004 in the upper Rio Grande basin are presented.