The purpose of a flood control reservoir operation is to prevent flood damage downstream of the reservoir and the safety of the reservoir itself. When a single reservoir cannot provide enough storage capacity for certain flood control points downstream, cascade reservoirs should be operated together to protect these areas from flooding. In this study, for efficient use of the reservoir storage, an optimal flood control operation model of cascade reservoirs for certain flood control points downstream was proposed. In the proposed model, the upstream reservoirs with the optimal operation strategy were considered to reduce the inflow of the reservoir downstream. For a large river basin, the flood routing and time-lag cannot be neglected. So, dynamic programming (DP) combined with the progressive optimality algorithm (POA) method, DP-POA, was proposed. Thus, the innovation of this study is to propose a two-stage optimal reservoir operation model with a DP-POA algorithm to solve the problem of optimal co-operation of cascade reservoirs for multiple flood control points downstream during the flood season. The upper Yangtze River was selected as a case study. Three reservoirs from upstream to downstream, Xiluodu, Xiangjiaba and the Three Gorges reservoirs (TGR) in the upper Yangtze River, were taken into account. Results demonstrate that the two-stage optimization algorithm has a good performance in solving the cascade reservoirs optimization problem, because the inflow of reservoir downstream and the division volumes were largely reduced. After the optimal operation of Xiluodu and Xiangjiaba reservoirs, the average reduction of flood peak for all these 13 typical flood hydrographs (TFHs) is 13.6%. Meanwhile, the cascade reservoirs can also store much more storm water during a flood event, and the maximum volumes stored in those two reservoirs upstream in this study can reach 25.2 billion m3 during a flood event. Comprising the proposed method with the current operation method, results demonstrate that the flood diversion volumes at the flood control points along the river decrease significantly.
During flood control reservoir operation, uncertainties in inflow forecast, the reservoir discharge capacity curve, and the reservoir storage curve significantly impact the reservoir operation processes and cause flood risk. This article proposes an improved stochastic differential equation (SDE) method for flood-risk analysis. The uncertainties mentioned above were quantified, and the mean and variance of the water level at each time step were calculated, then the flood risk was estimated and the impact of these uncertainties on flood control reservoir operation was evaluated. The Three Gorges Reservoir (TGR) was selected as a case study. Results show that the variance of the water level at each time step does not monotonically increase over time. Inflow forecast and flood hydrograph shape work together and have a great influence on the flood risk. The method provides a way for flood-risk assessment for flood control reservoir operation.flood control reservoir operation, flood-risk analysis, stochastic differential equation, Three Gorges Reservoir, uncertainties
Flood disasters are the most frequent and most severe natural disasters in most countries around the world. Reservoir flood operation is an important method to reduce flood losses. When there are multiple reservoirs and flood control points in the basin, it is difficult to use reservoirs separately to fully realize their flood control potential. However, the multi-reservoir joint flood control operation is a multi-objective, multi-constrained, multi-dimensional, nonlinear, and strong-transition feature decision-making problem, and these characteristics make modeling and solving very difficult. Therefore, a large-scale reservoirs flood control operation modeling method is innovatively proposed, and Dynamic Programming (DP) combined with the Progressive Optimality Algorithm (POA) and Particle Swarm Optimization (PSO) methods, DP-POA-PSO, are designed to efficiently solve the optimal operation model. The middle and upper Yangtze River was chosen as a case study. Six key reservoirs in the basin were considered, including Xiluodu (XLD), Xiangjiaba (XJB), Pubugou (PBG), Tingzikou (TZK), Goupitan (GPT), and Three Gorges (TG). Studies have shown that DP-POA-PSO can effectively solve the optimal operation model. Compared with the current operation method, the joint flood control optimal operation makes the flood control point reach the flood control standard, moreover, in the event of the flood with a return period of 1000 years, Jingjiang, the most critical flood control point of the Yangtze River, does not require flood diversion, and the volume of flood diversion in Chenglingji is also greatly reduced.
The risk inevitably exists in the process of flood control operation and decision-making of reservoir group, due to the hydrologic and hydraulic uncertain factors. In this study different stochastic simulation methods were applied to simulate these uncertainties in multi-reservoir flood control operation, and the risk caused by different uncertainties was evaluated from the mean value, extreme value and discrete degree of reservoir occupied storage capacity under uncertain conditions. In order to solve the conflict between risk assessment indexes and evaluate the comprehensive risk of different reservoirs in flood control operation schemes, the subjective weight and objective weight were used to construct the comprehensive risk assessment index, and the improved Mahalanobis distance TOPSIS method was used to select the optimal flood control operation scheme. The proposed method was applied to the flood control operation system in the mainstream and its tributaries of upper reaches of the Yangtze River basin, and 14 cascade reservoirs were selected as a case study. The results indicate that proposed method can evaluate the risk of multi-reservoir flood control operation from all perspectives and provide a new method for multi-criteria decision-making of reservoir flood control operation, and it breaks the limitation of the traditional risk analysis method which only evaluated by risk rate and cannot evaluate the risk of the multi-reservoir flood control operation system.
Multireservoir joint flood control operation is an important nonstructural measure for flood control in some basins. Owing to the existence of uncertainties in flood control operation, various degrees of risk can be shown in flood control operation systems. Examining these uncertainties and the resulting risk of failure in multireservoir operation systems is extremely beneficial and indispensable for basin flood mitigation. In this study, different stochastic simulation methods were employed to generate streamflow series at multiple stations and other uncertainties such as the flood forecast errors, discharge capacity, and reservoir storage. Then, the Monte Carlo framework was established based on the simulation sequence to estimate the risk of a failure of each flood control unit in the flood control system. Furthermore, a comprehensive risk assessment indicator was proposed to consider the failure probability and failure consequences at the same time. The Xiluodu-Xiangjiaba-Three Gorges cascade reservoirs were selected as a case study. Results show that the applied probabilistic simulation methods could simulate various uncertainties in a multireservoir flood control system effectively, and the proposed risk analysis method could comprehensively evaluate the risks of reservoir overtopping, flood flows exceeding a standard, and flood diversion from the perspective of overall watershed security.
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