Skip to main content
ARS Home » Plains Area » Las Cruces, New Mexico » Range Management Research » Research » Publications at this Location » Publication #259916

Title: Infrastructure improvements for snowmelt runoff forecasting and assessments of climate change impacts on water supplies in the Rio Grande Basin

Author
item Rango, Albert
item STEELE, CAITI - New Mexico State University
item DEMOUCHE, LEANN - New Mexico State University

Submitted to: American Geophysical Union
Publication Type: Abstract Only
Publication Acceptance Date: 11/1/2009
Publication Date: 12/14/2009
Citation: Rango, A., Steele, C.S., Demouche, L. 2009. Infrastructure improvements for snowmelt runoff forecasting and assessments of climate change impacts on water supplies in the Rio Grande Basin [abstract]. 2009 American Geophysical Union meetings, December 14-18, 2009, San Francisco, California. U13B-0072.

Interpretive Summary:

Technical Abstract: n the Southwest US, the southern Rocky Mountains provide a significant orographic barrier to prevailing moisture-laden Westerly winds, which results in snow accumulation and melt, both vitally important to the region’s water resources. The inherent variability of meteorological conditions in the Southwest, during both snowpack buildup and depletion, requires improved spatially-distributed data. The population of ground-based networks (SNOTEL, SCAN, and weather stations) is sparse and does not satisfactorily represent the variability of snow accumulation and melt. Remote sensing can be used to supplement data from ground networks, but the most frequently available remotely sensed product with the highest temporal and spatial resolution, namely snow cover, only provides areal data and not snow volume. Fortunately, the Snowmelt Runoff Model(SRM), which was developed in mountainous regions of the world, including the Rio Grande basin, accepts snow covered area as one of its major input variables along with temperature and precipitation. With the growing awareness of atmospheric warming and the southerly location of Southwest watersheds, it has become apparent that the effects of climate change will be especially important for Southwestern water users. The NSF-funded EPSCoR project “Climate Change Impacts on New Mexico’s Mountain Sources of Water” (started in 2009) has focused on improving hydrometeorological measurements, developing basin-wide and sub-basin snow cover mapping methods, generating snowmelt runoff simulations, forecasts, and long-term climate change assessments, and informing the public of the results through outreach and educational activities. Five new SNOTEL and four new SCAN sites are being installed in 2009-2010 and 12 existing basic SNOTEL sites are being upgraded. In addition, 30 automated precipitation gages are being added to New Mexico measurement networks. The first phase of snow mapping and modeling has focused on four sub basins, namely, the Rio Grande near Del Norte, CO and the Rio Hondo, Rio Chama, and Castillo Creek in NM, all tributaries of the Rio Grande basin. An additional 21 sub basins will be added as the development and testing of methods progresses. High spatial resolution Landsat TM data (30 m) are being used to evaluate estimates of snow cover maps from moderate spatial resolution data from Terra MODIS (250m and 500 m). Currently MODIS provides optimal temporal sampling (daily data) but the most effective MODIS-based snow cover mapping method has yet to be determined. We aim to identify the best MODIS snow-mapping algorithm for the Rio Grande area. For the snowmelt modeling, we are using an updated revision of SRM which directly accepts remote sensing snow cover inputs but can also automatically assess the climate change effects of future scenarios. The methods under development are intended for operational use by interested water resources agencies. With this end in mind, we will be developing an ArcGIS Toolbox (ESRI) and manual that will incorporate all the tools and instructions necessary for data download, re-projection and formatting, modeling and streamflow estimation.