HPCCprojects:Combining a MODIS-based snow water equivalent product and statistical interpolation methods to estimate snowpack and streamflow conditions in the Colorado headwaters
Combining a MODIS-based snow water equivalent product and statistical interpolation methods to estimate snowpack and streamflow conditions in the Colorado headwaters
Project description
We are seeking to develop a SWE monitoring technique that can leverage both point scale measurements and spatially explicit patterns of SWE from remote sensing in near real-time. Current estimates of SWE distribution are frequently interpolated from point measurements based on physiographics with a observations of SCA occasionally used to constrain modeled values. Statistical models relating physiography and 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 goal of this project is to combine a statistical interpolation model with remote-sensing based reconstructed SWE to augment resources available to water managers.
Objectives
List the main objectives of your project
Time-line
4-5 years. This is part of my PhD work so I hope to wrap up in 2015.
Models in use
I primarily use MATLAB to derive independent variables from a DEM and condition the SNOTEL data for use in statistical models. MATLAB and now R are used for statistical analyses. SNODIS, our SWE reconstruction model, is run in IDL and was written by Bin Guan at the NASA Jet Propulsion Laboratory.
Results
Users
Dominik Schneider Noah P. Molotch
Funding
NOAA
Publications and presentations
Schneider, D., N.P. Molotch. (2013) "A regression-based approach for combining ground-based observations, distributed models, and remotely sensed data for real-time SWE estimates." Western Snow Conference, Jackson, WY. Poster.
Schneider, D., N.P. Molotch. (2012) "A regression-based approach for blending remotely-sensed and in-situ snow water equivalent estimates in the Colorado River Basin". AGU Fall Meeting, San Francisco, CA. Poster.
