A real-time operation optimization model for flood management in river-reservoir systems

Malekmohammadi, Bahram; Zahraie, Banafsheh; Kerachian, Reza

doi:10.1007/s11069-009-9442-8

Cited by 53 publications

(26 citation statements)

References 25 publications

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“…In flood damage estimation model, peak flow frequency analysis was conducted. Flood damages were estimated by linking a hydraulic flood routing model with GIS tools for considering land-use information and flood damage functions in the downstream floodplain of the reservoir (Malekmohammadi et al 2010).…”

Section: Methodsmentioning

confidence: 99%

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Application of Harmony Search Algorithm to Reservoir Operation Optimization

Bashiri-Atrabi

Qaderi

Rheinheimer

et al. 2015

Water Resour Manage

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In this study, a meta-heuristic technique called harmony search (HS) algorithm is developed for reservoir operation optimization with respect to flood control. The HS algorithm is used to minimize the water supply deficit and flood damages downstream of a reservoir. The GIS database is used to determine the flood damage functions. The efficacy of HS algorithm is evaluated in comparison with other techniques by using a benchmark problem for a single reservoir operation optimization problem. HS showed promising results in terms of speed of convergence to an optimal objective function value compared with other techniques such as honey-bee mating optimization (HBMO) and a global optimization model (LINGO 8.0 NLP solver). The HS algorithm is then applied to the Narmab reservoir, north of Iran, as a case study. Narmab reservoir serves multiple purposes including irrigation, flood control, and drinking water requirements. The developed model is applied for monthly operation. The results show that the HS algorithm can be effectively used for operation of reservoir for flood management.

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Section: Methodsmentioning

confidence: 99%

“…Applications of metaheuristic techniques to flood problems are described in several studies (Chang and Chen 1998; Karaboga et al 2004;Ngo et al 2007;Kumar et al 2010;Malekmohammadi et al 2010). However, one particularly promising metaheuristic technique, the harmony search (HS) algorithm, described below, has not yet been tested or applied to flood models.…”

mentioning

confidence: 99%

Application of Harmony Search Algorithm to Reservoir Operation Optimization

Bashiri-Atrabi

Qaderi

Rheinheimer

et al. 2015

Water Resour Manage

View full text Add to dashboard Cite

show abstract

“…Chang et al (2010) reported a real-time reservoir operation mode for flood control using artificial intelligent techniques. Malekmohammadi et al (2010) developed a real-time flood management model for riverreservoir systems based upon combining a reservoir operation based upon a genetic algorithm with a hydraulic flood routing simulation for routing reservoir releases in the downstream river. The operation model determines the hourly releases that minimize the flood damages in the downstream river.…”

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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“…To scale the inputs and the targets, the normalized equation, Equation (6), is often used, forcing the data to fall within a specified range.…”

Section: Back Propagation Neural Network (Bpnn)mentioning

confidence: 99%

Enhancing the Predicting Accuracy of the Water Stage Using a Physical-Based Model and an Artificial Neural Network-Genetic Algorithm in a River System

Liu

Chung

2014

Water

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Accurate simulations of river stages during typhoon events are critically important for flood control and are necessary for disaster prevention and water resources management in Taiwan. This study applies two artificial neural network (ANN) models, including the back propagation neural network (BPNN) and genetic algorithm neural network (GANN) techniques, to improve predictions from a one-dimensional flood routing hydrodynamic model regarding the water stages during typhoon events in the Danshuei River system in northern Taiwan. The hydrodynamic model is driven by freshwater discharges at the upstream boundary conditions and by the water levels at the downstream boundary condition. The model provides a sound physical basis for simulating water stages along the river. The simulated results of the hydrodynamic model show that the model cannot reproduce the water stages at different stations during typhoon events for the model calibration and verification phases. The BPNN and GANN models can improve the simulated water stages compared with the performance of the hydrodynamic model. The GANN model satisfactorily predicts water stages during the training and verification phases and exhibits the lowest values of mean absolute error, root-mean-square error and peak error compared with the simulated results at different stations using the hydrodynamic model and the BPNN model. Comparison of the simulated results shows that the GANN OPEN ACCESSWater 2014, 6 1643 model can be successfully applied to predict the water stages of the Danshuei River system during typhoon events.

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A real-time operation optimization model for flood management in river-reservoir systems

Cited by 53 publications

References 25 publications

Application of Harmony Search Algorithm to Reservoir Operation Optimization

Application of Harmony Search Algorithm to Reservoir Operation Optimization

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

Enhancing the Predicting Accuracy of the Water Stage Using a Physical-Based Model and an Artificial Neural Network-Genetic Algorithm in a River System

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