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.
Get full access to this article
View all available purchase options and get full access to this article.
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.
References
AMS (American Meteorological Society). 2022. “Atmospheric river.” Accessed October 16, 2023. https://glossary.ametsoc.org/wiki/Atmospheric_river.
Badrinath, A., L. D. Monache, N. Hayatbini, W. Chapman, F. Cannon, and M. Ralph. 2023. “Improving precipitation forecasts with convolutional neural networks.” Weather Forecast. 38 (2): 291–306. https://doi.org/10.1175/WAF-D-22-0002.1.
Brodeur, Z. P., C. Delaney, B. Whitin, and S. Steinschneider. 2024. “Synthetic forecast ensembles for evaluating forecast informed reservoir operations.” Water Resour. Res. 60 (2): e2023WR034898. https://doi.org/10.1029/2023WR034898.
Brodeur, Z. P., J. D. Herman, and S. Steinschneider. 2020. “Bootstrap aggregation and cross-validation methods to reduce overfitting in reservoir control policy search.” Water Resour. Res. 56 (Jun): e2020WR027184. https://doi.org/10.1029/2020WR027184.
Brodeur, Z. P., and S. Steinschneider. 2021. “A multivariate approach to generate synthetic short-to-medium range hydro-meteorological forecasts across locations, variables, and lead times.” Water Resour. Res. 57 (6): e2020WR029453. https://doi.org/10.1029/2020WR029453.
California Department of Water Resources. 2023. California water plan 2023 update. Sacramento, CA: California Department of Water Resources.
Chapman, W. E., A. C. Subramanian, L. Delle Monache, S. P. Xie, and F. M. Ralph. 2019. “Improving atmospheric river forecasts with machine learning.” Geophys. Res. Lett. 46 (17–18): 10627–10635. https://doi.org/10.1029/2019GL083662.
CNRFC (California Nevada River Forecase Center). 2023a. “Heavy precipitation events: California and northern Nevada: January and February 2017.” Accessed August 24, 2023. https://www.cnrfc.noaa.gov/storm_summaries/janfeb2017storms.php.
CNRFC (California Nevada River Forecast Center). 2023b. “Long range daily ensemble CSV file download.” Accessed August 29, 2023. https://www.cnrfc.noaa.gov/ensembleProductCSV.php.
Cohen, J. S., H. B. Zeff, and J. D. Herman. 2020. “Adaptation of multiobjective reservoir operations to snowpack decline in the Western United States.” J. Water Resour. Plann. Manage. 146 (12): 04020091. https://doi.org/10.1061/(ASCE)WR.1943-5452.0001300.
Corringham, T. W., J. McCarthy, T. Shulgina, A. Gershunov, D. R. Cayan, and F. M. Ralph. 2022. “Climate change contributions to future atmospheric river flood damages in the western United States.” Sci. Rep. 12 (1): 13747. https://doi.org/10.1038/s41598-022-15474-2.
Das, T., M. D. Dettinger, D. R. Cayan, and H. G. Hidalgo. 2011. “Potential increase in floods in California’s Sierra Nevada under future climate projections.” Clim. Change 109 (Dec): 71–94. https://doi.org/10.1007/s10584-011-0298-z.
Delaney, C. J., et al. 2020. “Forecast informed reservoir operations using ensemble streamflow predictions for a multipurpose reservoir in Northern California.” Water Resour. Res. 56 (9): e2019WR026604. https://doi.org/10.1029/2019WR026604.
Dettinger, M. D., F. M. Ralph, T. Das, P. J. Neiman, and D. R. Cayan. 2011. “Atmospheric rivers, floods and the water resources of California.” Water 3 (2): 445–478. https://doi.org/10.3390/w3020445.
Doering, K., J. Quinn, P. M. Reed, and S. Steinschneider. 2021. “Diagnosing the time-varying value of forecasts in multiobjective reservoir control.” J. Water Resour. Plann. Manage. 147 (7): 04021031. https://doi.org/10.1061/(ASCE)WR.1943-5452.0001386.
Feng, Z., L. R. Leung, S. Hagos, R. A. Houze, C. D. Burleyson, and K. Balaguru. 2016. “More frequent intense and long-lived storms dominate the springtime trend in central US rainfall.” Nat. Commun. 7 (1): 13429. https://doi.org/10.1038/ncomms13429.
Gupta, R. S., A. L. Hamilton, P. M. Reed, and G. W. Characklis. 2020. “Can modern multi-objective evolutionary algorithms discover high-dimensional financial risk portfolio tradeoffs for snow-dominated water-energy systems?” Adv. Water Resour. 145 (Nov): 103718. https://doi.org/10.1016/j.advwatres.2020.103718.
Hejazi, M. I., X. Cai, and B. L. Ruddell. 2008. “The role of hydrologic information in reservoir operation—Learning from historical releases.” Adv. Water Resour. 31 (12): 1636–1650. https://doi.org/10.1016/j.advwatres.2008.07.013.
Jager, H. I., and B. T. Smith. 2008. “Sustainable reservoir operation: Can we generate hydropower and preserve ecosystem values?” River Res. Appl. 24 (Jun): 340–352. https://doi.org/10.1002/rra.1069.
Jasperse, J., et al. 2020. “Lake Mendocino forecast informed reservoir operations final viability assessment” Accessed October 4, 2023. https://escholarship.org/uc/item/3b63q04n.
Koskinas, A., A. Tegos, P. Tsira, P. Dimitriadis, T. Iliopoulou, P. Papanicolaou, D. Koutsoyiannis, and T. Williamson. 2019. “Insights into the Oroville dam 2017 spillway incident.” Geosciences 9 (Jan): 37. https://doi.org/10.3390/geosciences9010037.
Lamontagne, J. R., and J. R. Stedinger. 2018. “Generating synthetic streamflow forecasts with specified precision.” J. Water Resour. Plann. Manage. 144 (4): 04018007. https://doi.org/10.1061/(ASCE)WR.1943-5452.0000915.
Lavers, D. A., M. J. Rodwell, D. S. Richardson, F. M. Ralph, J. D. Doyle, C. A. Reynolds, V. Tallapragada, and F. Pappenberger. 2018. “The gauging and modeling of rivers in the sky.” Geophys. Res. Lett. 45 (15): 7828–7834. https://doi.org/10.1029/2018GL079019.
McCuen, R. H., Z. Knight, and A. G. Cutter. 2006. “Evaluation of the Nash–Sutcliffe efficiency index.” J. Hydrol. Eng. 11 (6): 597–602. https://doi.org/10.1061/(ASCE)1084-0699(2006)11:6(597).
Nayak, M. A., J. D. Herman, and S. Steinschneider. 2018. “Balancing flood risk and water supply in California: Policy search integrating short-term forecast ensembles with conjunctive use.” Water Resour. Res. 54 (10): 7557–7576. https://doi.org/10.1029/2018WR023177.
Pan, B., K. Hsu, A. AghaKouchak, S. Sorooshian, and W. Higgins. 2019. “Precipitation prediction skill for the West Coast United States: From short to extended range.” J. Clim. 32 (1): 161–182. https://doi.org/10.1175/JCLI-D-18-0355.1.
Pathak, T. B., M. L. Maskey, J. A. Dahlberg, F. Kearns, K. M. Bali, and D. Zaccaria. 2018. “Climate change trends and impacts on California agriculture: A detailed review.” Agronomy 8 (3): 25. https://doi.org/10.3390/agronomy8030025.
Peel, M. C., B. L. Finlayson, and T. A. McMahon. 2007. “Updated world map of the Köppen-Geiger climate classification.” Hydrol. Earth Syst. Sci. 11 (Jun): 1633–1644. https://doi.org/10.5194/hess-11-1633-2007.
Reed, P. M., D. Hadka, J. D. Herman, J. R. Kasprzyk, and J. B. Kollat. 2013. “Evolutionary multiobjective optimization in water resources: The past, present, and future.” Adv. Water Resour. 51 (Jan): 438–456. https://doi.org/10.1016/j.advwatres.2012.01.005.
Semmendinger, K., and S. Steinschneider. 2024. “Influence of subseasonal-to-annual water supply forecasts on many-objective water system robustness under long-term change.” J. Water Resour. Plann. Manage. 150 (5): 04024009. https://doi.org/10.1061/JWRMD5.WRENG-6205.
Steinschneider, S., J. D. Herman, J. Kucharski, M. Abellera, and P. Ruggiero. 2023. “Uncertainty decomposition to understand the influence of water systems model error in climate vulnerability assessments.” Water Resour. Res. 59 (1): e2022WR032349. https://doi.org/10.1029/2022WR032349.
Storn, R., and K. Price. 1997. “Differential evolution—A simple and efficient heuristic for global optimization over continuous spaces.” J. Global Optim. 11 (Dec): 341–359. https://doi.org/10.1023/A:1008202821328.
Swain, D. L., B. Langenbrunner, J. D. Neelin, and A. Hall. 2018. “Increasing precipitation volatility in twenty-first-century California.” Nat. Clim. Change 8 (5): 427–433. https://doi.org/10.1038/s41558-018-0140-y.
Turner, S. W. D., J. C. Bennett, D. E. Robertson, and S. Galelli. 2017. “Complex relationship between seasonal streamflow forecast skill and value in reservoir operations.” Hydrol. Earth Syst. Sci. 21 (Apr): 4841–4859. https://doi.org/10.5194/hess-21-4841-2017.
Tustison, B. 2020. “Geographical trends in central valley flood control reservoirs.” Accessed October 10, 2023. https://blog.mbkapps.com/posts/res-prop/.
US Army Corps of Engineers. 2017. Management of water control systems. Washington, DC: US Army Corps of Engineers.
US Census Bureau. 2023. “QuickFacts: California.” Accessed August 29, 2023. https://www.census.gov/quickfacts/fact/table/CA/PST045222.
USGS. 2023. “California’s Central Valley.” Accessed August 21, 2023. https://ca.water.usgs.gov/projects/central-valley/about-central-valley.html.
Virtanen, P., et al. 2020. “SciPy 1.0: Fundamental algorithms for scientific computing in Python.” Nat. Methods 17 (Jun): 261–272. https://doi.org/10.1038/s41592-019-0686-2.
Warner, M. D., C. F. Mass, and E. P. Salathé. 2015. “Changes in winter atmospheric rivers along the North American West Coast in CMIP5 climate models.” J. Hydrometeorol. 16 (1): 118–128. https://doi.org/10.1175/JHM-D-14-0080.1.
Woodside, G. D., A. S. Hutchinson, F. M. Ralph, C. Talbot, R. Hartman, and C. Delaney. 2022. “Increasing stormwater capture and recharge using forecast informed reservoir operations.” Prado Dam. Groundwater 60 (5): 634–640. https://doi.org/10.1111/gwat.13162.
Yang, G., S. Guo, P. Liu, and P. Block. 2020. “Integration and evaluation of forecast-informed multiobjective reservoir operations.” J. Water Resour. Plann. Manage. 146 (6): 04020038. https://doi.org/10.1061/(ASCE)WR.1943-5452.0001229.
Zatarain Salazar, J., P. M. Reed, J. D. Herman, M. Giuliani, and A. Castelletti. 2016. “A diagnostic assessment of evolutionary algorithms for multi-objective surface water reservoir control.” Adv. Water Resour. 92 (Jun): 172–185. https://doi.org/10.1016/j.advwatres.2016.04.006.
Zeff, H. B., A. L. Hamilton, K. Malek, J. D. Herman, J. S. Cohen, J. Medellin-Azuara, P. M. Reed, and G. W. Characklis. 2021. “California’s food-energy-water system: An open source simulation model of adaptive surface and groundwater management in the Central Valley.” Environ. Modell. Software 141 (Jul): 105052. https://doi.org/10.1016/j.envsoft.2021.105052.
Zimmerman, J. K. H., D. M. Carlisle, J. T. May, K. R. Klausmeyer, T. E. Grantham, L. R. Brown, and J. K. Howard. 2018. “Patterns and magnitude of flow alteration in California, USA.” Freshwater Biol. 63 (Sep): 859–873. https://doi.org/10.1111/fwb.13058.
Information & Authors
Information
Published In
Copyright
© 2024 American Society of Civil Engineers.
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
ASCE Technical Topics:
- Climates
- Continuum mechanics
- Disaster risk management
- Disasters and hazards
- Engineering fundamentals
- Engineering mechanics
- Environmental engineering
- Floods
- Flow (fluid dynamics)
- Fluid dynamics
- Fluid mechanics
- Forecasting
- Hydraulic engineering
- Hydraulic structures
- Hydrologic engineering
- Inflow
- Mathematics
- Natural disasters
- Reservoirs
- River engineering
- Rivers and streams
- Seasonal variations
- Statistics
- Structural engineering
- Structures (by type)
- Water and water resources
- Water management
- Water policy
- Water supply
Authors
Metrics & Citations
Metrics
Citations
Download citation
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.