Improving Hydrological Snowpack Forecasting for Hydropower Generation Using Intelligent Information Systems
Optimizing hydropower operations with improved forecasts.
The Regents of the University of California on behalf of the Berkeley campus
Recipient
Berkeley, CA
Recipient Location
7th
Senate District
14th
Assembly District
$944,195
Amount Spent
Completed
Project Status
Project Result
Project was successfully completed in 2019. The research team installed hardware and collected hydrologic data for water years 2016, 2017, 2018 from four project sites: Grizzly Ridge, Kettle Rock, Buck's Lake, and Humbug. Data from in-situ snowpack measurements helped to improve Snowpack Water Equivalent (SWE) maps by 55%. The project team worked closely with hydrologists from PG&E and updated their working model of the Precipitation Runoff Modeling System (PRMS) from version 2 to version 4, which features updated topographical, climate, and vegetation data. Project results were published in the California 4th Climate Change Assessment Report. In addition, the project team published two peer-reviewed papers.
The Issue
Next-generation hydrographic data networks are needed to better measure and predict critical snowpack levels that can help hydropower operators adjust to increased variability and the impacts of climate change on precipitation.
Project Innovation
The project will advance hydrologic modeling and improve the Precipitation-Runoff Modeling System (PRMS) used by PG&E, allowing for more effective management of hydropower resources. The project features an innovative smart wireless sensor network made up of small sensor stations mounted on poles linked by low-power radio, which produces real-time hydrologic data. These data, blended with satellite and Light Detection And Ranging (LiDAR) remote sensing data, have the potential to greatly improve hydrologic forecasting for the Sierra Nevada and other areas in California.
Project Benefits
The project provides improved predictive planning and scheduling tools to manage hydroelectric resources that are needed to adapt to increasing vulnerabilities and uncertainties of a changing climate. This project specifically targets powerhouses operated by PG&E.
Affordability
The tools developed and enhanced by this project increase the ability of hydropower to respond to fluctuations in water supplies, helping lower the cost of energy production.
Environmental Sustainability
Better, more-detailed, real-time predictions for water basin-runoffs will enable improved water management and adaptation to climate change.
Reliability
The quality of hydrologic data collected using installed remote sensing network and Snowpack Water Equivalent (SWE) maps derived from bi-weekly Light Detection and Ranging (LiDAR) scans show a marked improvement compared to the p
Key Project Members
Steven Glaser
Subrecipients
The Regents of the University of California, Merced
Match Partners
The Regents of the University of California, Merced
California Department of Water Resources
