Forecast Informed Reservoir Operations Using Ensemble Streamflow Predictions for a Multipurpose Reservoir in Northern California

Abstract

Ensemble Forecast Operations (EFO) is a risk-based approach of reservoir flood control operations that incorporates ensemble streamflow predictions (ESPs) made by the California-Nevada River Forecast Center. Reservoir operations for each member of an ESP are individually modeled to forecast system conditions and calculate risk of reaching critical operational thresholds. Reservoir release decisions are simulated to manage forecasted risk with respect to established risk tolerance levels. EFO was developed for Lake Mendocino, a 111,000 acre-foot reservoir near Ukiah, California, to evaluate its viability to improve reservoir storage reliability without increasing downstream flood risk. Lake Mendocino is a dual use reservoir, owned and operated for flood control by the United States Army Corps of Engineers and operated for water supply by Sonoma Water. EFO was simulated using a 26-year (1985-2010) ESP hindcast generated by the California-Nevada River Forecast Center, which provides 61-member ensembles of 15-day flow forecasts. EFO simulations yield generally higher storage levels during the flood management season while maintaining needed flood storage capacity by strategically prereleasing water in advance of forecasted storms. Model results demonstrate a 33% increase in median storage at the end of the flood management season (10 May) over existing operations without marked changes in flood frequency for locations downstream from Lake Mendocino. EFO may be a viable alternative for managing flood control operations at Lake Mendocino that provides multiple benefits (water supply, flood mitigation, and ecosystems) and provides a management framework that could be adapted and applied to other flood control reservoirs.

Ensemble flood forecasting: Current status and future opportunities

“…This progress has enabled a number of countries to implement operational ensemble flood forecasting systems (Addor et al, 2011;Pappenberger et al, 2016, and references therein;Emerton et al, 2016, and references therein), even if these still generally run in parallel to their legacy deterministic flood forecasting systems. There are by now many clear operational examples of ensemble forecasts that are used to support decision-making, with many examples to choose from, such as the New York City Department of Environmental Protection's Operations Support Tool, a state-of-the-art decision support system for the city's water supply system (NASEM (National Academies of Sciences, Engineering, and Medicine), 2018), in the Sonoma County Water Authority Lake Mendocino system operations (Delaney et al, 2020), for navigation scheduling operations in Germany (Hemri & Klein, 2017;Meißner et al, 2017;Meißner & Klein, 2015), and in many private sector operations, particularly those related to hydropower.…”

Asymmetric Emergence of Low-to-No Snow in the American Cordillera

“…This warrants attention and action as the southern Chilean Andes have the highest global water tower index outside of Asia (Immerzeel et al, 2020), yet the region has significantly less built infrastructure, monitoring networks, and forecasting centers that could instill resilience to these hydrologic cycle alterations. The cross-hemispheric perspective of low-to-no snow emergence also demonstrates shared commonalities across regions and highlights the need for a pro-active exchange of policy interventions (Castilla-Rho et al, 2019), cutting-edge water management strategies (Scanlon et al, 2016;Sterle et al, 2019;Dillon et al, 2019;Delaney et al, 2020) and conceptual frameworks (Szinai et al, 2020;Vicuña et al, 2021). Most importantly, it highlights the need to implement carbon mitigation strategies at scale (Williams et al, 2021) that inhibit the global warming level at which persistent low-to-no snow conditions emerge.…”

Improved Prediction of Atmospheric Rivers That Drive Flood Damages in the Western United States

“…Observed conditions from a network of gages, sensors and weather stations in the watershed are fed into the California Data Exchange Center (CDEC) where they are coupled with reservoir inflow forecasts from the NWS California-Nevada River Forecast Center (CNRFC). The heart of the Russian River FIRO DSS is the Russian River Forecast Coordinated Operations (FCO) tool where model results from the Lake Mendocino Ensemble Forecast Operations (EFO) Model (Delaney et al, 2020) are used by the reservoir operators to make proposed release decisions. Those proposed releases are then run through a USACE Hydrologic Engineering Center (HEC) Reservoir Simulation (ResSim) model to determine downstream impacts to water supply, flood risk and ecologic benefits from the proposed release.…”