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Enhancing Flood Routing Accuracy: A Fuzzified Approach to Nonlinear Variable-Parameter Muskingum Model

Author

Listed:
  • Amirfarhad Aletaha

    (Shahid Bahonar University of Kerman)

  • Masoud-Reza Hessami-Kermani

    (Shahid Bahonar University of Kerman)

  • Reyhaneh Akbari

    (Shahid Bahonar University of Kerman)

Abstract

Variable-parameter Muskingum models emerge as a highly efficient approach among the prevalent hydrological flood routing methods, owing to their accuracy and robustness. This research introduces a novel partitioning framework aimed at refining outcomes from a nonlinear variable-parameter Muskingum model by introducing fuzzification to the adjacent sub-periods of the inflow hydrograph. The results prove the efficacy of the proposed method in enhancing the accuracy of routed outflow, aligning well with the inherent characteristics of a flooding event. Validation of the newly introduced fuzzified nonlinear variable-parameter Muskingum model was conducted using four distinct case studies from the literature, including Wilson's data, the flood events in Rivers Wye and Wyre, and Viessman and Lewis' data. The evaluation of the proposed framework's effectiveness utilized the Sum of Squared Deviations (SSQ) as the objective function of the model, along with six different supplemental metrics. The results demonstrated a meaningful increase in the accuracy of the nonlinear Muskingum model for the respective cases studied. The findings imply that the proposed partitioning framework is adaptable to the variable-parameter Muskingum models with an intensity-based partitioning technique, thereby advancing the results of this conventional flood routing method.

Suggested Citation

  • Amirfarhad Aletaha & Masoud-Reza Hessami-Kermani & Reyhaneh Akbari, 2024. "Enhancing Flood Routing Accuracy: A Fuzzified Approach to Nonlinear Variable-Parameter Muskingum Model," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 38(10), pages 3913-3935, August.
    • Handle: RePEc:spr:waterr:v:38:y:2024:i:10:d:10.1007_s11269-024-03846-4
    DOI: 10.1007/s11269-024-03846-4
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    References listed on IDEAS

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    1. Reyhaneh Akbari & Masoud-Reza Hessami-Kermani & Saeed Shojaee, 2020. "Flood Routing: Improving Outflow Using a New Non-linear Muskingum Model with Four Variable Parameters Coupled with PSO-GA Algorithm," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(10), pages 3291-3316, August.
    2. Majid Niazkar & Seied Hosein Afzali, 2016. "Application of New Hybrid Optimization Technique for Parameter Estimation of New Improved Version of Muskingum Model," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(13), pages 4713-4730, October.
    3. Ling Kang & Liwei Zhou & Song Zhang, 2017. "Parameter Estimation of Two Improved Nonlinear Muskingum Models Considering the Lateral Flow Using a Hybrid Algorithm," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(14), pages 4449-4467, November.
    4. Mike Spiliotis & Alvaro Sordo-Ward & Luis Garrote, 2021. "Estimation of Fuzzy Parameters in the Linear Muskingum Model with the Aid of Particle Swarm Optimization," Sustainability, MDPI, vol. 13(13), pages 1-26, June.
    5. Wen-chuan Wang & Wei-can Tian & Dong-mei Xu & Kwok-wing Chau & Qiang Ma & Chang-jun Liu, 2023. "Muskingum Models’ Development and their Parameter Estimation: A State-of-the-art Review," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 37(8), pages 3129-3150, June.
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