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Hugo A Loaiciga - One of the best experts on this subject based on the ideXlab platform.

  • developing a novel parameter free optimization framework for Flood Routing
    Scientific Reports, 2021
    Co-Authors: Omid Bozorghaddad, Parisa Sarzaeim, Hugo A Loaiciga
    Abstract:

    The Muskingum model is a popular hydrologic Flood Routing technique; however, the accurate estimation of model parameters challenges the effective, precise, and rapid-response operation of Flood Routing. Evolutionary and metaheuristic optimization algorithms (EMOAs) are well suited for parameter estimation task associated with a wide range of complex models including the nonlinear Muskingum model. However, more proficient frameworks requiring less computational effort are substantially advantageous. Among the EMOAs teaching–learning-based optimization (TLBO) is a relatively new, parameter-free, and efficient metaheuristic optimization algorithm, inspired by the teacher-student interactions in a classroom to upgrade the overall knowledge of a topic through a teaching–learning procedure. The novelty of this study originates from (1) coupling TLBO and the nonlinear Muskingum Routing model to estimate the Muskingum parameters by outflow predictability enhancement, and (2) evaluating a parameter-free algorithm’s functionality and accuracy involving complex Muskingum model’s parameter determination. TLBO, unlike previous EMOAs linked to the Muskingum model, is free of algorithmic parameters which makes it ideal for prediction without optimizing EMOAs parameters. The hypothesis herein entertained is that TLBO is effective in estimating the nonlinear Muskingum parameters efficiently and accurately. This hypothesis is evaluated with two popular benchmark examples, the Wilson and Wye River case studies. The results show the excellent performance of the “TLBO-Muskingum” for estimating accurately the Muskingum parameters based on the Nash–Sutcliffe Efficiency (NSE) to evaluate the TLBO’s predictive skill using benchmark problems. The NSE index is calculated 0.99 and 0.94 for the Wilson and Wye River benchmarks, respectively.

  • application of a new hybrid non linear muskingum model to Flood Routing
    Proceedings of the Institution of Civil Engineers - Water Management, 2020
    Co-Authors: Omid Bozorghaddad, Sahar Mohammadazari, Farzan Hamedi, Maryam Pazoki, Hugo A Loaiciga
    Abstract:

    This paper introduces a hybrid non-linear Muskingum model for Flood Routing. The proposed hybrid model has more degrees of freedom for fitting observed data than other non-linear Muskingum models. ...

  • generalized storage equations for Flood Routing with nonlinear muskingum models
    Water Resources Management, 2019
    Co-Authors: Omid Bozorghaddad, Farzan Hamedi, Maryam Pazoki, Mehri Abdidehkordi, Hugo A Loaiciga
    Abstract:

    The nonlinear Muskingum model is a leading method for hydrologic Routing. The efficiency of the nonlinear Muskingum model for Routing of hydrograph outflow has been improved in recent years. This study introduces four Muskingum models with improved, generalized, nonlinear storage equations. The proposed models provide more degrees of freedom in fitting observed hydraulic data than other corresponding nonlinear Muskingum models and they have better predictive skill for river flow than other nonlinear Muskingum models. The accuracy of the proposed Muskingum models is herein demonstrated with examples.

  • a re parameterized and improved nonlinear muskingum model for Flood Routing
    Water Resources Management, 2015
    Co-Authors: Omid Bozorg Haddad, Farzan Hamedi, Maryam Pazoki, Hosein Orouji, Hugo A Loaiciga
    Abstract:

    The nonlinear form of the Muskingum model has been widely applied to river Flood Routing. There are four variants of the nonlinear Muskingum model based on alternative formulations of the nonlinear storage equation. This paper proposes a new Muskingum model with an improved, seven-parameter, nonlinear storage equation. The proposed model provides more degrees of freedom in fitting observed hydraulic data than other nonlinear Muskingum models. The proper estimation of the proposed Muskingum nonlinear model’s parameters is essential to achieve accurate Flood-Routing predictions. This paper introduces a hybrid method for the estimation of Muskingum parameters. The parameter-estimation method combines the shuffled frog leaping algorithm (SFLA) and the Nelder-Mead simplex (NMS). The proposed Muskingum model and parameter estimation method were applied to the Routing of several hydrographs. Our results indicate improved performance of the methodology described in this work when compared with those of other Muskingum models.

  • a re parameterized and improved nonlinear muskingum model for Flood Routing
    Water Resources Management, 2015
    Co-Authors: Omid Bozorg Haddad, Farzan Hamedi, Maryam Pazoki, Hosein Orouji, Hugo A Loaiciga
    Abstract:

    The nonlinear form of the Muskingum model has been widely applied to river Flood Routing. There are four variants of the nonlinear Muskingum model based on alternative formulations of the nonlinear storage equation. This paper proposes a new Muskingum model with an improved, seven-parameter, nonlinear storage equation. The proposed model provides more degrees of freedom in fitting observed hydraulic data than other nonlinear Muskingum models. The proper estimation of the proposed Muskingum nonlinear model’s parameters is essential to achieve accurate Flood-Routing predictions. This paper introduces a hybrid method for the estimation of Muskingum parameters. The parameter-estimation method combines the shuffled frog leaping algorithm (SFLA) and the Nelder-Mead simplex (NMS). The proposed Muskingum model and parameter estimation method were applied to the Routing of several hydrographs. Our results indicate improved performance of the methodology described in this work when compared with those of other Muskingum models. Copyright Springer Science+Business Media Dordrecht 2015

Jun Zhu - One of the best experts on this subject based on the ideXlab platform.

  • Dam-Break Flood Routing Simulation and Scale Effect Analysis Based on Virtual Geographic Environment
    IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2015
    Co-Authors: Jun Zhu, Lingzhi Yin, Jinhong Wang, Heng Zhang, Zhujun Liu
    Abstract:

    Because of the barrier lake affected by highly changing and complex environment, it is always a great challenge that proper actions must be performed within a limited amount of time. Thus, how to scientifically and efficiently analyze the dam-break risk of the barrier lake and its impact area is very important for barrier lake disposal and downstream communities transfer. To improve the efficiency and the accuracy of the dam-break Flood Routing simulation, this paper mainly focuses on the construction of the virtual geographic environment (VGE) system and the scale effect analysis. Unlike most of the current cellular automata (CA)-based Flood simulation systems, the proposed VGE system can offer an intuitive, efficient, and interactive visualization environment through which users can explore complicated spatial information and conduct risk assessment work. Some key technologies including the CA model of dam-break Flood, the VGE system framework, the impact analysis method, and the scale effect analysis method were discussed in detail. A prototype system was developed to support dam-break simulation and risk analysis of the Xiaojiaoqiao barrier lake in Anxian County, Sichuan Province of China. By means of a variety of cell scales effect analysis experiments, the adaptation scope and characteristics of multiscale cells were obtained to implement the simulation analysis of the dam-break Flood Routing better. The proposed VGE system can improve the efficiency of risk assessment and decision-making.

  • a virtual geographic environment for simulation analysis of dam break Flood Routing
    Advanced Materials Research, 2012
    Co-Authors: Jun Zhu
    Abstract:

    Dam-break Flood affected by highly changing and complex environment, has some characteristics including the sudden of occurrence, the rapid of expansion and the urgency of respond. This paper focuses on how to develop a virtual geographic environment (VGE) system to study the dam-break Flood Routing and its impact. Unlike existing work, our methods pay attention to the multidimensional and dynamic analysis methods in virtual geographic environment, which make Flood Routing easily understood to public and officers. Moreover, some GIS spatial analysis and real-time interactive operation with the VGE will also be implemented to support the risk assessment of the dam-break. Finally, a prototype system is developed to construct a virtual geographic environment for impact analysis of dam-break Flood Routing and dynamic interaction. Experimental results prove that the scheme addressed in the paper is effective and feasible.

Farzan Hamedi - One of the best experts on this subject based on the ideXlab platform.

  • application of a new hybrid non linear muskingum model to Flood Routing
    Proceedings of the Institution of Civil Engineers - Water Management, 2020
    Co-Authors: Omid Bozorghaddad, Sahar Mohammadazari, Farzan Hamedi, Maryam Pazoki, Hugo A Loaiciga
    Abstract:

    This paper introduces a hybrid non-linear Muskingum model for Flood Routing. The proposed hybrid model has more degrees of freedom for fitting observed data than other non-linear Muskingum models. ...

  • generalized storage equations for Flood Routing with nonlinear muskingum models
    Water Resources Management, 2019
    Co-Authors: Omid Bozorghaddad, Farzan Hamedi, Maryam Pazoki, Mehri Abdidehkordi, Hugo A Loaiciga
    Abstract:

    The nonlinear Muskingum model is a leading method for hydrologic Routing. The efficiency of the nonlinear Muskingum model for Routing of hydrograph outflow has been improved in recent years. This study introduces four Muskingum models with improved, generalized, nonlinear storage equations. The proposed models provide more degrees of freedom in fitting observed hydraulic data than other corresponding nonlinear Muskingum models and they have better predictive skill for river flow than other nonlinear Muskingum models. The accuracy of the proposed Muskingum models is herein demonstrated with examples.

  • a re parameterized and improved nonlinear muskingum model for Flood Routing
    Water Resources Management, 2015
    Co-Authors: Omid Bozorg Haddad, Farzan Hamedi, Maryam Pazoki, Hosein Orouji, Hugo A Loaiciga
    Abstract:

    The nonlinear form of the Muskingum model has been widely applied to river Flood Routing. There are four variants of the nonlinear Muskingum model based on alternative formulations of the nonlinear storage equation. This paper proposes a new Muskingum model with an improved, seven-parameter, nonlinear storage equation. The proposed model provides more degrees of freedom in fitting observed hydraulic data than other nonlinear Muskingum models. The proper estimation of the proposed Muskingum nonlinear model’s parameters is essential to achieve accurate Flood-Routing predictions. This paper introduces a hybrid method for the estimation of Muskingum parameters. The parameter-estimation method combines the shuffled frog leaping algorithm (SFLA) and the Nelder-Mead simplex (NMS). The proposed Muskingum model and parameter estimation method were applied to the Routing of several hydrographs. Our results indicate improved performance of the methodology described in this work when compared with those of other Muskingum models.

  • a re parameterized and improved nonlinear muskingum model for Flood Routing
    Water Resources Management, 2015
    Co-Authors: Omid Bozorg Haddad, Farzan Hamedi, Maryam Pazoki, Hosein Orouji, Hugo A Loaiciga
    Abstract:

    The nonlinear form of the Muskingum model has been widely applied to river Flood Routing. There are four variants of the nonlinear Muskingum model based on alternative formulations of the nonlinear storage equation. This paper proposes a new Muskingum model with an improved, seven-parameter, nonlinear storage equation. The proposed model provides more degrees of freedom in fitting observed hydraulic data than other nonlinear Muskingum models. The proper estimation of the proposed Muskingum nonlinear model’s parameters is essential to achieve accurate Flood-Routing predictions. This paper introduces a hybrid method for the estimation of Muskingum parameters. The parameter-estimation method combines the shuffled frog leaping algorithm (SFLA) and the Nelder-Mead simplex (NMS). The proposed Muskingum model and parameter estimation method were applied to the Routing of several hydrographs. Our results indicate improved performance of the methodology described in this work when compared with those of other Muskingum models. Copyright Springer Science+Business Media Dordrecht 2015

Maryam Pazoki - One of the best experts on this subject based on the ideXlab platform.

  • application of a new hybrid non linear muskingum model to Flood Routing
    Proceedings of the Institution of Civil Engineers - Water Management, 2020
    Co-Authors: Omid Bozorghaddad, Sahar Mohammadazari, Farzan Hamedi, Maryam Pazoki, Hugo A Loaiciga
    Abstract:

    This paper introduces a hybrid non-linear Muskingum model for Flood Routing. The proposed hybrid model has more degrees of freedom for fitting observed data than other non-linear Muskingum models. ...

  • generalized storage equations for Flood Routing with nonlinear muskingum models
    Water Resources Management, 2019
    Co-Authors: Omid Bozorghaddad, Farzan Hamedi, Maryam Pazoki, Mehri Abdidehkordi, Hugo A Loaiciga
    Abstract:

    The nonlinear Muskingum model is a leading method for hydrologic Routing. The efficiency of the nonlinear Muskingum model for Routing of hydrograph outflow has been improved in recent years. This study introduces four Muskingum models with improved, generalized, nonlinear storage equations. The proposed models provide more degrees of freedom in fitting observed hydraulic data than other corresponding nonlinear Muskingum models and they have better predictive skill for river flow than other nonlinear Muskingum models. The accuracy of the proposed Muskingum models is herein demonstrated with examples.

  • a re parameterized and improved nonlinear muskingum model for Flood Routing
    Water Resources Management, 2015
    Co-Authors: Omid Bozorg Haddad, Farzan Hamedi, Maryam Pazoki, Hosein Orouji, Hugo A Loaiciga
    Abstract:

    The nonlinear form of the Muskingum model has been widely applied to river Flood Routing. There are four variants of the nonlinear Muskingum model based on alternative formulations of the nonlinear storage equation. This paper proposes a new Muskingum model with an improved, seven-parameter, nonlinear storage equation. The proposed model provides more degrees of freedom in fitting observed hydraulic data than other nonlinear Muskingum models. The proper estimation of the proposed Muskingum nonlinear model’s parameters is essential to achieve accurate Flood-Routing predictions. This paper introduces a hybrid method for the estimation of Muskingum parameters. The parameter-estimation method combines the shuffled frog leaping algorithm (SFLA) and the Nelder-Mead simplex (NMS). The proposed Muskingum model and parameter estimation method were applied to the Routing of several hydrographs. Our results indicate improved performance of the methodology described in this work when compared with those of other Muskingum models.

  • a re parameterized and improved nonlinear muskingum model for Flood Routing
    Water Resources Management, 2015
    Co-Authors: Omid Bozorg Haddad, Farzan Hamedi, Maryam Pazoki, Hosein Orouji, Hugo A Loaiciga
    Abstract:

    The nonlinear form of the Muskingum model has been widely applied to river Flood Routing. There are four variants of the nonlinear Muskingum model based on alternative formulations of the nonlinear storage equation. This paper proposes a new Muskingum model with an improved, seven-parameter, nonlinear storage equation. The proposed model provides more degrees of freedom in fitting observed hydraulic data than other nonlinear Muskingum models. The proper estimation of the proposed Muskingum nonlinear model’s parameters is essential to achieve accurate Flood-Routing predictions. This paper introduces a hybrid method for the estimation of Muskingum parameters. The parameter-estimation method combines the shuffled frog leaping algorithm (SFLA) and the Nelder-Mead simplex (NMS). The proposed Muskingum model and parameter estimation method were applied to the Routing of several hydrographs. Our results indicate improved performance of the methodology described in this work when compared with those of other Muskingum models. Copyright Springer Science+Business Media Dordrecht 2015

Roger Moussa - One of the best experts on this subject based on the ideXlab platform.

  • Approximation zones of the Saint-Venant equations f Flood Routing with overbank flow
    Hydrology and Earth System Sciences Discussions, 2000
    Co-Authors: Roger Moussa, C. Bocquillon
    Abstract:

    The classification of river waves as gravity, diffusion or kinematic waves, corresponds to different forms of the momentum equation in the Saint-Venant system. This paper aims to define approximation zones of the Saint-Venant equations for Flood Routing in natural channels with overbank flow in the Flooded area. Using linear perturbation theory, the different terms in the Saint-equations were analysed as a function of the balance between friction and inertia. Then, using non-dimensionalised variables, Flood waves were expressed as a function of three parameters: the Froude number of the steady uniform flow, a dimensionless wave, number of the unsteady component of the motion and the ratio between the Flooded area zone width and the main channel width. Finally, different theoretical cases, corresponding to different Flooded area zone widths were analysed and compared. Results show that, when the width of the Flooded area increases, the domain of application of the diffusive wave and the inematic wave models is restricted. Keywords: Saint-Venant equations; river waves; overbank flow

  • criteria for the choice of Flood Routing methods in natural channels
    Journal of Hydrology, 1996
    Co-Authors: Roger Moussa, Claude Bocquillon
    Abstract:

    Abstract The Saint-Venant equations are used to describe river waves. Generally, for Flood Routing in rivers, the Saint-Venant system is reduced to the diffusive wave equation which can be resolved using finite-difference algorithms. The choice of a numerical method, and of the space and time steps to be retained, depends essentially on the form of Flood hydrographs and the hydraulic properties of the river. This paper investigates these areas; two sets of criteria are propossed, the first to define parameter ranges representing each wave type and then, in the particular case of the diffusive wave model, to define criteria for the choice of numerical algorithm and appropriate space and time steps. The first analysis was based on the concept that river wave behaviour is determined by the balance between friction and inertia. The conclusions relate to the magnitude of temporal characteristics of Flood waves, expressed as a function of the Froude number of the steady uniform flow and a dimensionless wave number of the unsteady component of the motion. The second part discussed questions related to the diffusive wave problem and to numerical instabilities. A technique is proposed to guide the user in the choice of the computational algorithm and specifies the error introduced by numerical methods. The technique was applied to Flood-Routing simulation for the Loire river in France. In this case, two finite-difference algorithms were compared to the exact solution given by the analytical method. Comparisons between results show the efficiency of the technique to optimise the choice of the finite-difference method and the adequate space and time steps.

  • analytical hayami solution for the diffusive wave Flood Routing problem with lateral inflow
    Hydrological Processes, 1996
    Co-Authors: Roger Moussa
    Abstract:

    The diffusive wave equation is generally used in Flood Routing in rivers. The two parameters of the equation, celerity and diffusivity, are usually taken as functions of the discharge. If these two parameters can be assumed to be constant without lateral inflow, the diffusive wave equation may have an analytical solution: the Hayami model. A general analytical method, based on ‘Hayami’s hypothesis, is developed here which resolves the diffusive wave Flood Routing equation with lateral inflow or outflow uniformly distributed over a channel reach. Flood Routing parameters are then identified using observed inflow and outflow and the Hayami model used to simulate outflow. Two examples are discussed. Firstly, the prediction of the hydrograph at a downstream section on the basis of a knowledge of the hydrograph at an upstream section and the lateral inflow. The second example concerns lateral inflow identification between an upstream and a downstream section on the basis of a knowledge of hydrographs at the upstream and downstream sections. The new general Hayami model was applied to Flood Routing simulation and for lateral inflow identification of the River Allier in France. The major advantages of the method relate to computer simulation, real-time forecasting and control applications in examples where numerical instabilities, in the solution of the partial differential equations must be avoided.