Parameters Estimation of the Nonlinear Muskingum Flood-Routing Model Using Wolf Search Algorithm (WSA) (Case Study: Kardeh River)

Akbarifard, Saeid

doi:10.22092/aridse.2017.109605

Document Type : Original Article

Author

Saeid Akbarifard

https://doi.org/10.22092/aridse.2017.109605

Abstract

Flood routing is one of the most complex problems that is investigated in open channel hydraulics and river engineering. Among the different flood routing methods, the Muskingum model, as the most common hydrologic method of flood routing, has been widely used with high accuracy in river flood studies. The parameters estimation of the nonlinear Muskingum flood-routing model has been considered by different researchers and several methods have been utilized to this purpose. In this paper, the wolf search algorithm (WSA) was used to this end. To assess the optimum values of Muskingum parameters, the objective function was defined as the minimizing of the sum of square residuals between the observed and routed outflows. To investigate the desirability of research findings, the results of the WSA were compared with other heuristic algorithms including genetic algorithm (GA), particle swarm optimization (PSO), harmony search (HS), and imperialist competitive algorithm (ICA). Six benchmark functions with different dimensions were used to evaluate the capability of algorithms. The results showed that the WSA is capable to provide satisfactory estimates of nonlinear Muskingum parameters, so that, the values of R2 and RMSE were obtained 0.99261 and 2.419886 for Kardeh river and 0.778425 and 0.712358 for Wilson river, respectively.

Keywords

References

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Irrigation and Drainage Structures Engineering Research

Parameters Estimation of the Nonlinear Muskingum Flood-Routing Model Using Wolf Search Algorithm (WSA) (Case Study: Kardeh River)

References

References

Volume 17, Issue 67
March 2017
Pages 95-112

Parameters Estimation of the Nonlinear Muskingum Flood-Routing Model Using Wolf Search Algorithm (WSA) (Case Study: Kardeh River)

References

References

Volume 17, Issue 67March 2017Pages 95-112

Volume 17, Issue 67
March 2017
Pages 95-112