资源环境科技发展态势分析平台

Short-term weather forecasts have the potential to improve reservoir operations for both flood control and water supply objectives, especially in regions currently relying on fixed seasonal flood pools to mitigate risk. The successful development of forecast-based policies should integrate uncertainty from modern forecast products to create unambiguous rules that can be tested on out-of-sample periods. This study investigates the potential for such operating policies to improve water supply efficiency while maintaining flood protection, combining state-of-the-art weather hindcasts with downstream conjunctive use to transfer surplus flood releases to groundwater storage. Because available weather hindcasts are relatively short (10-20 years), we propose a novel statistical framework to develop synthetic forecasts over longer periods of the historical record. Operating rules are trained with a recently developed policy search framework in which decision rules are structured as binary trees. Policies are developed for a range of scenarios with varying forecast skill and conjunctive use capacity, using Folsom Reservoir, California, as a case study. Results suggest that the combination of conjunctive use and short-term weather forecasts can substantially improve both water supply and flood control objectives by allowing storage to remain high until forecasts trigger a release. Further, increased conjunctive use capacity reduces the importance of forecast skill, since surface storage can be moved to groundwater during the flood season without losing water supply. This analysis serves the development of forecast-based operating policies for large, multipurpose reservoirs in California and other regions with similar flood hydroclimatology.