Improving flood resilience through optimal reservoir operation

Reservoir operation is an effective measure for flood disaster reduction. Previous studies focused on minimizing flood risk to reduce potential flood damage, however, failure and recovery processes are not considered. To address this shortcoming, this study introduces the concept of resilience to measure the ability of flood control systems to maintain or return to the original states after an extreme flood. The quantitative expression of resilience, resilience metric, is proposed based on the system performance and defined as the summation of system functionality loss throughout the entire flood process. Based on the proposed resilience metric, a multiobjective optimization model with flood risk represented by maximum reservoir water level and downstream peak flow, and flood resilience as objectives, is established. Nierji Reservoir, located in Northeast China is taken as a case study. Results show that the proposed method can improve resilience without increasing flood risks (i. e., maximum reservoir water level and downstream peak flow) compared with the traditional model. Pareto optimates of the optimization model show that there exist tradeoffs between risk and resilience, improving resilience inevitably reducing risk. The resilience improvement is large when the flood risk of the reservoir or downstream is medium and is limited when the flood risk is high. Moreover, the resilience improvement is higher for a smaller flood. The improvement is achieved through pre-releasing at the early stage of the flood and releasing slowly at the recession stage of the flood. Six typical schemes, selected referring to the existing scheme are comprehensively compared, and an operation rule for flood control with the highest resilience but without reducing risks is recommended. This study provides a new way for flood control management.