Deriving optimal operating rules for flood control considering pre-release based on forecast information

Abstract

Pre-releasing before a flood can increase reservoir flood control storage capacity to effectively improve the flood disaster prevention and mitigation effects, but also might bring water shortage risk due to the uncertain forecasts. This paper proposes a framework to determine the optimal operating rules for flood control considering pre-release based on uncertain forecasts. The framework includes three models: a pre-release model at the early stage of the flood to enlarge the flood control storage capacity; a multi-objective optimization model with resilience and risk as objectives at the flood regulating stage to optimize the flood control operating rules; a fuzzy optimum selecting model to determine the satisfied operating rule considering forecast uncertainty and decision-maker's preferences. In the framework, forecast uncertainty has been considered from the perspective of the forecast error distribution. Nierji Reservoir in Northeast China is taken as a case study. Results show that compared with the existing operating rule, the recommended operating rule considering pre-release releases water more evenly and can not only decrease the peak flow at the downstream protection point but also improve the downstream flood resilience without increasing reservoir risk. The proposed framework that considers forecast error distribution provides higher superiority degrees of the rules than the traditional framework that considers the maximum and minimum forecast errors in the real-time operation of the 1969 and 2013 flood hydrographs.