This project estimates snowpack and streamflow conditions in the Colorado headwaters. The overall goal is to develop a Snow Water Equivalent (SWE) monitoring technique that can leverage both point scale measurements and a spatially explicit patterns of SWE from remote sensing in near real-time. Please reference our Real-Time SWE Reports that are accessible to download.
CWEST Participants: Noah Molotch and Graduate Student Dominik Schneider
Ingestion of MODIS-based snow water equivalent (SWE) estimates into water supply forecast models
Downloading snow depth measurements on Niwot Ridge along an elevational transect that monitor snow accumulation and ablation patterns. Winter 2012. Photo credit: Dominik Schneider.
Current estimates of SWE distribution are frequently interpolated from point measurements based on physiographics with an observation of SCA occasionally used to constrain modeled values. Statistical models relating physiography and Snow Telemetry (SNOTEL) SWE only explain up to ~15% of the observed variability and thus these techniques provide limited credibility for water resource applications. Recent improvements in SWE estimates have been obtained using SWE reconstruction models whereby satellite data of SCA are coupled with fully distributed energy balance modeling to reconstruct peak snow mass. The first goal of this project is to combine a statistical interpolation model with remote-sensing based spatially distributed reconstructed SWE to augment resources available to water managers.
For more information please visit the USDA NRSC SNOTEL website and the NASA’s MODIS website.