Gaps Between Western U.S. Reservoir Inflows and Headwater Precipitation Timing, Amount, and Phase

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Snowmelt from mountain headwater basins supplies approximately 80% of the runoff to reservoirs in the western United States (WUS), and is therefore a key component of western hydropower. Yet predicting runoff from hydrometeorological data in complex terrain (and its sensitivity to disturbances and extremes) remains highly uncertain. Basic science uncertainties include how inflows to reservoirs respond to shifts in precipitation timing, amount, phase (rain versus snow), the impacts of evolving forest/land cover due to disturbances, and the often overlooked role of groundwater in the mountain hydrologic cycle. Challenges to address these questions arise in validating and downscaling climate data for use in physics-based or AI-driven watershed models, assessing biases and process fidelity in these models, and scaling process understanding from plot/hillslope/intensive field campaigns to watershed and hydropower-relevant scales. Further, water management restrictions and policies drive reservoir operation guidelines such as stationary rule curves, with the potential to inhibit energy production and water supply.

Citation Formats

TY - DATA AB - Snowmelt from mountain headwater basins supplies approximately 80% of the runoff to reservoirs in the western United States (WUS), and is therefore a key component of western hydropower. Yet predicting runoff from hydrometeorological data in complex terrain (and its sensitivity to disturbances and extremes) remains highly uncertain. Basic science uncertainties include how inflows to reservoirs respond to shifts in precipitation timing, amount, phase (rain versus snow), the impacts of evolving forest/land cover due to disturbances, and the often overlooked role of groundwater in the mountain hydrologic cycle. Challenges to address these questions arise in validating and downscaling climate data for use in physics-based or AI-driven watershed models, assessing biases and process fidelity in these models, and scaling process understanding from plot/hillslope/intensive field campaigns to watershed and hydropower-relevant scales. Further, water management restrictions and policies drive reservoir operation guidelines such as stationary rule curves, with the potential to inhibit energy production and water supply. AU - Rudisill, William A2 - Siirila-Woodburn, Erica A3 - Feldman, Dan DB - Energy-Water Resilience DP - Open EI | National Laboratory of the Rockies DO - KW - large hydropower KW - headwater KW - precipitation KW - timing KW - phase KW - runoff KW - snowmelt KW - mountain headwater KW - hydropower KW - inflows KW - hydrologic cycle KW - climate KW - data KW - physics-based KW - AI KW - watershed LA - English DA - 2026/01/15 PY - 2026 PB - LBNL T1 - Gaps Between Western U.S. Reservoir Inflows and Headwater Precipitation Timing, Amount, and Phase UR - https://ewr.openei.org/submissions/104 ER -
Export Citation to RIS
Rudisill, William, et al. Gaps Between Western U.S. Reservoir Inflows and Headwater Precipitation Timing, Amount, and Phase. LBNL, 15 January, 2026, Energy-Water Resilience. https://ewr.openei.org/submissions/104.
Rudisill, W., Siirila-Woodburn, E., & Feldman, D. (2026). Gaps Between Western U.S. Reservoir Inflows and Headwater Precipitation Timing, Amount, and Phase. [Data set]. Energy-Water Resilience. LBNL. https://ewr.openei.org/submissions/104
Rudisill, William, Erica Siirila-Woodburn, and Dan Feldman. Gaps Between Western U.S. Reservoir Inflows and Headwater Precipitation Timing, Amount, and Phase. LBNL, January, 15, 2026. Distributed by Energy-Water Resilience. https://ewr.openei.org/submissions/104
@misc{EWR_Dataset_104, title = {Gaps Between Western U.S. Reservoir Inflows and Headwater Precipitation Timing, Amount, and Phase}, author = {Rudisill, William and Siirila-Woodburn, Erica and Feldman, Dan}, abstractNote = {Snowmelt from mountain headwater basins supplies approximately 80\% of the runoff to reservoirs in the western United States (WUS), and is therefore a key component of western hydropower. Yet predicting runoff from hydrometeorological data in complex terrain (and its sensitivity to disturbances and extremes) remains highly uncertain. Basic science uncertainties include how inflows to reservoirs respond to shifts in precipitation timing, amount, phase (rain versus snow), the impacts of evolving forest/land cover due to disturbances, and the often overlooked role of groundwater in the mountain hydrologic cycle. Challenges to address these questions arise in validating and downscaling climate data for use in physics-based or AI-driven watershed models, assessing biases and process fidelity in these models, and scaling process understanding from plot/hillslope/intensive field campaigns to watershed and hydropower-relevant scales. Further, water management restrictions and policies drive reservoir operation guidelines such as stationary rule curves, with the potential to inhibit energy production and water supply. }, url = {https://ewr.openei.org/submissions/104}, year = {2026}, howpublished = {Energy-Water Resilience, LBNL, https://ewr.openei.org/submissions/104}, note = {Accessed: 2026-06-17} }

Details

Data from Jan 15, 2026

Last updated Jan 15, 2026

Submitted Jan 15, 2026

Contact

Dan Feldman

Authors

William Rudisill

LBNL

Erica Siirila-Woodburn

LBNL

Dan Feldman

LBNL

DOE Project Details

Project Name White Papers on Ideas to Advance Energy-Water Resilience

Project Lead

Project Number WP-104

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