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Beluga Whale Optimization Algorithm for Estimating Nonlinear Muskingum Model in Flood Routing

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Abstract

Using hydraulic and hydrological routing approaches, the transient flow is examined. The Muskingum model (MM), a hydrological routing methodology, is a reasonably accurate and useful technique for the calculation of the output hydrograph from a river reach. The storage and continuity equations serve as the foundation for the comparatively straightforward process of flood routing using the Muskingum method. The type and manner of solving determine how accurate the Muskingum method is. In order to solve the routing problem utilizing the Muskingum method, a new meta-heuristic algorithm known as the Beluga whale optimization algorithm (BWO) is used in this study. By taking into account the nonlinear lateral flow, the MM type in this article is the nonlinear 6th-type Muskingum model. In this work, four case studies are looked into. It is demonstrated that the BWO algorithm performs well in approximating the relevant MM parameters. For the first through fourth case studies in this study, the goal values that are determined by minimizing the sum of square errors are acquired to be 2.1, 50.6, 11.82, and 61.4 (m3/s)2, respectively.

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Authors and Affiliations

  1. Department of Water Engineering, Kermanshah Branch, Islamic Azad University, Kermanshah, Iran

    Ehsan Moradi, Behrouz Yaghoubi & Saeid Shabanlou

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  1. Ehsan Moradi
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  2. Behrouz Yaghoubi
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  3. Saeid Shabanlou
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Correspondence to Behrouz Yaghoubi.

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Moradi, E., Yaghoubi, B. & Shabanlou, S. Beluga Whale Optimization Algorithm for Estimating Nonlinear Muskingum Model in Flood Routing. Iran J Sci Technol Trans Civ Eng 48, 1227–1243 (2024). https://doi.org/10.1007/s40996-023-01252-1

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  • DOI: https://doi.org/10.1007/s40996-023-01252-1

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