Multireservoir real-time operations for flood control using balanced water level index method

Wei, Chih-Chiang; Hsu, Nien‐Sheng

doi:10.1016/j.jenvman.2007.08.004

Cited by 63 publications

(19 citation statements)

References 15 publications

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“…This model had the objective of minimizing the peak flow at downstream control points along with maximizing the reservoir storage at the end of the flood. A real-time model using optimization-simulation was developed by Wei and Hsu (2008) for determining reservoir releases at each time during a flood. This model included two models a hydrological forecasting model and a reservoir operation model.…”

Section: Previous Optimization/simulation Modelsmentioning

confidence: 99%

Development of an Optimization/Simulation Model for Real-Time Flood-Control Operation of River-Reservoirs Systems

Che

Mays

2015

Water Resour Manage

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Real-time optimal operation models for river-reservoir systems, unfortunately, are not widely available. Such models are still in their infancy perhaps due to the complexity of the application. This paper presents the development and testing of a methodology for determining reservoir release schedules before, during, and after an extreme flood event in real time. The problem is formulated as a real-time optimal control problem in which reservoir releases represent the decision variables. The model consists of five major components: (1) the U.S. Army Corps of Engineers (USACE) Hydrologic Engineering Center -Hydrologic Modeling System (HEC-HMS), which simulates rainfall-runoff processes of watershed systems; (2) the U.S. Army Corps of Engineers Hydrologic Engineering Center -River Analysis System (HEC-RAS) for one-dimensional unsteady flow routing; (3) a reservoir release operation model; (4) a short-term rainfall forecasting model to project rainfall over the next few hours during a rainfall event; and (5) a genetic algorithm (GA) optimizer interfaced with the other components that determine the real time operation of a river-reservoir systems. An example application is used to test the development of the modeling framework, also illustrating the use of such a model. Each model component and its interface in the modeling framework was tested for quality assurance.

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Section: Previous Optimization/simulation Modelsmentioning

confidence: 99%

Development of an Optimization/Simulation Model for Real-Time Flood-Control Operation of River-Reservoirs Systems

Che

Mays

2015

Water Resour Manage

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“…In this study, the operation rule is the concept of water level index balance that the water system reaching the highest levels at the current time has a priority for supply at the next time [27,28]. The FIS follows the following rule; that is, the abundant water system supplies more and the scarce water system supplies less water.…”

Section: Fuzzy Inference System (Fis)mentioning

confidence: 99%

“…where SH is the shortage in demand at the th time step, SH =̂− ∑ , ; , means the supply from node in demand at time step ; and is the demand node set; in the study, = 1. is the difference between water level index (WLI) of the reservoirs and at the th time step [27,28] and is the reservoir storage node set; if = , then = 0 otherwise. is the ratio of residual volume to the capacity in reservoir at the th time step: ( max − )/ max ; 1 , 2 , and 3 are the weight coefficients applied to the shortage, surfacewater level index difference, and residual reservoir volume ratio, respectively ( 1 = 1, 2 = 10, and 3 = 1).…”

Section: Surface Water Submodelmentioning

confidence: 99%

A Fuzzy Inference System for the Conjunctive Use of Surface and Subsurface Water

Chang

Chu

Chen

2013

Advances in Fuzzy Systems

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This study develops the water resources management model for conjunctive use of surface and subsurface water using a fuzzy inference system (FIS). The study applies the FIS to allocate the demands of surface and subsurface water. Subsequently, water allocations in the surface water system are simulated by using linear programming techniques, and the responses of subsurface water system with respect to pumping are forecasted by using artificial neural networks. The operating rule for the water systems is that the more abundant water system supplies more water. By using the fuzzy rule, the FIS conjunctive use model easily incorporates expert knowledge and operational polices into water resources management. The result indicates that the FIS model is more effective and efficient when compared with the decoupled conjunctive use and simulation-optimization models. Furthermore, the FIS model is an alternative way to obtain the conjunctive use policies between surface and subsurface water.

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“…For planning purposes, a management model is usually built for either short-term planning, such as flood control during storms [1][2][3][4][5][6][7], or long-term planning, such as water flow distribution optimization [8][9][10][11] and reservoir operation rule optimization [12][13][14][15][16][17]. Those studies developed complete formulations and algorithms for managing the abovementioned planning topics.…”

Section: Introductionmentioning

confidence: 99%

Risk Analysis of Reservoir Operations Considering Short-Term Flood Control and Long-Term Water Supply: A Case Study for the Da-Han Creek Basin in Taiwan

Cheng¹,

Huang

Wei

2017

Water

Self Cite

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Abstract:This study applies an integrated methodology to assess short-term over-levee risk and long-term water shortage risk in the Da-Han Creek basin, which is the most important flood control and water storage system in northern Taiwan. An optimization model for reservoir flood control and water supply is adopted, to determine reservoir releases based on synthetic inflow hydrographs during typhoons, which are generated by Monte Carlo simulations. The release is then used to calculate the water level at a downstream control point using a novel developed back-propagation neural network-based model, to reduce computational complexity and achieve automatic-efficient risk evaluation. The calculated downstream water levels and final reservoir water levels after a typhoon event are used to evaluate the mapped over-levee risk and water shortage risk, respectively. The results showed that the different upper limit settings for the reservoir have a significant influence on the variation of 1.19 × 10 −5 % to 75.6% of the water shortage risk. This occurs because of the insufficient inflow and narrow storage capacity of the Shih-Men Reservoir during drought periods. However, the upper limit settings have a minor influence (with a variation of only 0.149% to 0.157%) on the over-levee risk in typhoon periods, because of the high protection standards for the downstream embankment.

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Multireservoir real-time operations for flood control using balanced water level index method

Cited by 63 publications

References 15 publications

Development of an Optimization/Simulation Model for Real-Time Flood-Control Operation of River-Reservoirs Systems

Development of an Optimization/Simulation Model for Real-Time Flood-Control Operation of River-Reservoirs Systems

A Fuzzy Inference System for the Conjunctive Use of Surface and Subsurface Water

Risk Analysis of Reservoir Operations Considering Short-Term Flood Control and Long-Term Water Supply: A Case Study for the Da-Han Creek Basin in Taiwan

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