The colorado basin river forecast center (cbrfc) has successfully utilized modis-based snow cover fraction and snow radiative forcing data for over a decade to enhance water supply forecasts in the…

The University of Colorado has received a $750,000 cooperative agreement from the Bureau of Reclamation under the SECURE Water Act – Research Agreements program (CFDA 15.560) to transition water supply forecasting operations from aging MODIS (Moderate Resolution Imaging Spectroradiometer) sensors to the newer VIIRS (Visible Infrared Imaging Radiometer Suite) sensor technology. The award, effective July 18, 2025, with completion targeted for June 30, 2028, will deliver an intercalibrated 28-year snow cover and albedo data record across 17 western U.S. states using advanced spectral mixture analysis methods. The university will develop near real-time operational implementations of these datasets for deployment by the Colorado Basin River Forecast Center and collaborating partners including the Natural Resources Conservation Service, producing research publications that support evidence-based water management decision-making.

This research directly addresses the Colorado Basin River Forecast Center's decade-long operational reliance on MODIS-based snow cover data while providing enhanced forecasting accuracy through superior sensor capabilities and analytical methods. Deliverables include the comprehensive intercalibrated historical dataset, operational near real-time data systems, and peer-reviewed findings that bridge complex climate science and actionable water resource management insights for western water managers and stakeholders.

The colorado basin river forecast center (cbrfc) has successfully utilized modis-based snow cover fraction and snow radiative forcing data for over a decade to enhance water supply forecasts in the upper colorado river basin. However, as modis sensors degrade due to limitations in repositioning fuel, there is an urgent need for high-quality data to improve forecasting accuracy. This project aims to transition to the newer viirs sensor, which will extend the modis record, leveraging superior spectral mixture analysis (SMA) methods for estimating snow surface properties, including snow cover and albedo. Our objectives are to develop an intercalibrated 28-year data record encompassing diverse hydroclimatic conditions across 17 western U.S. States, create near real-time implementations for operational use, and publish research findings that enhance understanding and applications in water supply forecasting. By collaborating with partners such as the nrcs and cbrfc, we seek to bridge the GAP between complex climate data and actionable insights for water management decision-makers and the public.