Formal Integration of Synthetic Ensemble Forecasts Into the Engineering Design of Forecast Informed Reservoir Operations (FIRO): Lake Sonoma, CA Case Study

Abstract Submission: Synthetic forecasts offer tremendous potential for testing the robustness of forecast-informed reservoir operations (FIRO). These forecasts are statistically generated to mimic hindcasts derived from operational forecasting systems, but they can be created for time periods when hindcast data are unavailable, allowing for a more comprehensive evaluation of FIRO policies. Recently developed synthetic ensemble forecasting algorithms can emulate both the skill and uncertainty characteristics of operational ensemble forecasting systems. When used in operational simulations with current FIRO policy formulations (e.g. the Ensemble Forecast Operations model), these synthetic ensemble forecasts produce operational outcomes that are statistically indistinguishable from the actual forecast outcomes, while illuminating crucial policy vulnerabilities due to forecast uncertainty. These results suggest that synthetic ensemble forecasts have the capability to support robustness analyses in real-world FIRO engineering and design efforts. However, several challenges remain in integrating synthetic ensemble forecasting techniques with these efforts, including the need for synthetic forecasting at hourly scales and the need for reliable synthetic forecasting approaches for scaled events. Here, we address these challenges (and many others) through integration of synthetic ensemble forecasting at the earliest stages of the formal Viability Assessment and Water Control Manual (WCM) update process at Lake Sonoma, CA, which includes coordinated engineering efforts across an interdisciplinary team drawn from federal, state, and local agencies. Through this integration, we advance the operational utility of synthetic forecasts via a Research and Operations Partnership (RAOP) effort that has shown tremendous success in other FIRO domains. In addition, we explore the potential for synthetic forecasts to elucidate FIRO policy performance under climate change and provide a roadmap for developing climate adaptive policy formulations. This work paves the way for the integration of synthetic forecasting into the broad suite of planned and future FIRO implementation efforts.

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