Case Studies
Aug 5, 2024

Variability, Attributes, and Drivers of Optimal Forecast-Informed Reservoir Operating Policies for Water Supply and Flood Control in California

Publication: Journal of Water Resources Planning and Management
Volume 150, Issue 10

Abstract

Reservoirs balance multiple conflicting objectives, including flood control and water supply. In California, shifts in seasonal hydrologic patterns under climate change will amplify the difficulties in balancing flood control with water supply. Current flood control policies are based on fixed seasonal rule curves determined by the observed timing and magnitude of floods in the record. These rule curves generally require the release of wet season inflows, reducing the available stored water for use during the dry season. Here we investigate the potential for forecast-informed reservoir operations (FIRO) to increase water supply availability while minimizing additional flood risk at 14 reservoirs in the Sacramento, San Joaquin, and Tulare river basins. We use a differential evolution algorithm to train risk-based reservoir operation policies with an ensemble of historical forecasts over the period 2013–2023. Results show an average 8.1% increase in storage normalized by capacity, though this varies across reservoirs. The forecast-informed policies also reduce the occurrence of high-magnitude releases throughout the system. The accumulation of benefits is sensitive to the timing and magnitude of flood events, and most of the cumulative benefit is obtained during a few years. Under cross-validation, we find that large floods are needed in the training data to avoid overfitting the policy. We further examine the relationship between reservoir properties and FIRO benefits, finding that the ratio of peak inflow magnitude to maximum safe release correlates with increased storage under the FIRO policy, while the ratio of mean inflow to capacity correlates to the reduction of high-magnitude releases. This study highlights how adaptive reservoir management policies can yield water supply benefits without an increase in flood risk, given adequate historical data for policy training. These policies may be a valuable adaptation to climate change but require careful validation and out-of-sample testing.

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Data Availability Statement

All data, models, or code generated or used during the study are available in a repository online in accordance with funder data retention policies: https://github.com/wltaylor/SSJRB-FIRO-Publishing.

Acknowledgments

This work was partially supported by the National Science Foundation Grant 2205239. William Taylor also received support from the US Air Force. All conclusions are those of the authors.

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Go to Journal of Water Resources Planning and Management
Journal of Water Resources Planning and Management
Volume 150Issue 10October 2024

History

Received: Nov 2, 2023
Accepted: May 20, 2024
Published online: Aug 5, 2024
Published in print: Oct 1, 2024
Discussion open until: Jan 5, 2025

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Ph.D. Student, Dept. of Civil and Environmental Engineering, Univ. of California, Davis, CA 95616 (corresponding author). ORCID: https://orcid.org/0009-0000-4033-6615. Email: [email protected]
Zachary P. Brodeur, Ph.D. https://orcid.org/0000-0001-5242-7696
Postdoctoral Researcher, Dept. of Biological and Environmental Engineering, Cornell Univ., Ithaca, NY 14853. ORCID: https://orcid.org/0000-0001-5242-7696
Scott Steinschneider, Ph.D. https://orcid.org/0000-0002-8882-1908
Associate Professor, Dept. of Biological and Environmental Engineering, Cornell Univ., Ithaca, NY 14853. ORCID: https://orcid.org/0000-0002-8882-1908
John Kucharski
Ph.D. Student, Dept. of Land, Air and Water Resources, Univ. of California, Davis, CA 95616; Researcher, Engineer Research and Development Center, US Army Corps of Engineers, Vicksburg, MS.
Jonathan D. Herman, Ph.D. https://orcid.org/0000-0002-4081-3175
Associate Professor, Dept. of Civil and Environmental Engineering, Univ. of California, Davis, CA 95616. ORCID: https://orcid.org/0000-0002-4081-3175

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