Ven Te Chow Faculty Scholar in Water Resources University of Illinois, Urbana-Champaign
Flooding control and water conservation are two major objectives of many reservoirs; however, they often end with conflict, for example, water shortage during the post-flood season. Effective use of weather and hydrological forecasts is essential in addressing this challenge. Although the integration of forecasts into reservoir operation has been a long-term effort in research, practical applications have been limited. US Army Corps of Engineers (USACE) and other national agencies recently initiated forecast-informed reservoir operation (FIRO) through several pilot programs. This study aims to propose an enhanced FIRO framework that combines analytical and empirical approaches. We will employ a two-stage multi-objective model developed by our previous work to optimize initial release decisions that account for hedging policies. Simultaneously, we will incorporate the empirical work conducted by a USACE polit project to assess flood risk within the forecast horizon, which may enable some adjustments to the initial release decisions. A day-to-day rolling window procedure is adopted to assimilate daily updated forecasts and provide daily hedging release decisions within this framework. We will test the proposed FIRO framework using Lake Mendocino in California as a case study, and the performance using both ensemble streamflow predictions (ESPs) and individual targeted forecasts trusted by stakeholders will be evaluated. This framework will enable us to assess the effectiveness of hedging policies considering the trade-offs between flood mitigation and water scarcity, forecast uncertainty, and stakeholders' risk tolerance. The framework is proposed to support decision making considering both flooding risk reduction and post-flooding season water conservation.
