The U.S. Bureau of Reclamation (USBR) has announced it is providing $2.5 million for 12 projects to advance snow measurement technology with the goal of improving water-supply forecasts. Four projects include partner contributions of $720,000.
USBR Chief Engineer Dr. David Raff noted how this fits in with the agency’s work to improve water-supply forecasts: "With the changing climate and droughts occurring in the west, it is becoming increasingly apparent that the processes and methods used to forecast snow water runoff need improvement."
To this end, Reclamation’s newly-funded research and technology applications include a focus on the remote sensing of snowpack and integrating these data into snowpack models to improve runoff forecasts. The funding will enable new lidar-based snow surveys in the western U.S. to be done using Airborne Snow Observatories Inc., a spin-off of NASA’s Airborne Snow Observatory airborne mission. NASA launched the Airborne Snow Observatory in 2013 to collect data on the snowmelt flowing out of major water basins in the western U.S., and the technology was transferred from NASA to the private sector in 2019.
The new projects will:
- Expand Airborne Snow Observatory (ASO) snow surveys in various regions (details below).
- Assess the use of new satellites to advance state-of-the-art snow and water-supply forecasting in river basins. New work will demonstrate and test capabilities to measure snow water equivalent (SWE) in high-elevation mountain watersheds using InSAR data from NASA’s upcoming NISAR satellite mission, as well as integrated satellite-based altimetry data techniques (photogrammetry from commercial sub-meter stereo imagery).
- Develop an integrated remote-sensing and physical-modeling approach to deliver high-resolution, modeled SWE in near real-time.The focus will be on small to medium basins where snowmelt is the primary driver of spring and summer reservoir inputs.
Planned expansion of ASO surveys:
- Enhancement of San Joaquin snow monitoring program: Operations for California’s Millerton Lake (Friant Dam) have used ASO data for five consecutive years, pairing this remote sensing with snowpack modeling, improvements to ground-based stations, and an innovative approach to synthesizing data that is like Forecasted-Informed Reservoir Operations (FIRO). New funding will augment planned ASO surveys for winter/spring 2021, yielding information critical to operations at Millerton Reservoir and the San Joaquin River Settlement when water is needed early in the runoff season to support salmon restoration.
- Baseline ASO flights for sub-basins with poor existing coverage: ASO flights will be cataloged, identified and funded for sub-basins in snow-melt driven watersheds within all Reclamation Regions that have no or infrequent ASO dataset coverage. Basins will be identified based on considerations such as poor existing terrestrial snow data coverage associated with lack of SNOTEL stations due to wilderness classification.
- New technologies to extend ASO’s temporal and spatial coverage: This work will build on previous efforts to garner information on spatial snow distribution from dozens of ASO flights in the Tuolumne River Basin. The analysis in the Tuolumne will be extended to evaluate the potential benefits of adding stereo-optical snow depth data and spatial patterns from the Sierra Nevada Snow Reanalysis product. An additional component of this proposal will expand the knowledge gathered in the Tuolumne to available ASO SWE and stereo-optical depth data in Colorado.
- Comparing ASO data to current river forecasts in the Truckee-Carlson Basins: The Truckee-Carson Basins need forecasts that provide reliable information, no matter if conditions are wet, dry or average. The USBR’s Lahontan Basin Area Office proposes using ASO to complete two snow-on lidar flights and snow dynamic modeling to deliver high-precision streamflow forecasts.
- Quantitative and economic evaluation of emergent snow products using statistical and AI-based operational water-supply forecast systems: This project will examine ways to integrate emergent snow-measurement technologies (e.g. ASO lidar surveys) into data-driven water-supply forecast (WSF) systems, which are the most widespread WSF approach in the western U.S. Potential WSF skill improvement will be analyzed quantitatively. In addition, WSF improvements will be evaluated from an economic perspective to quantify benefits and identify potential trade-offs and synergies between technologies.