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Calculation of Water Depth during Flood in Rivers using Linear Muskingum Method and Particle Swarm Optimization (PSO) Algorithm

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Listed:
  • Hadi Norouzi

    (University of Zanjan)

  • Jalal Bazargan

    (University of Zanjan)

Abstract

To estimate the damage caused by flooding rivers, it is critical to analyze unsteady flow and determine downstream water depth. Hydraulic methods for examining unsteady river flow require cross-sectional specifications of the river at a close distance with optimal accuracy. Obtaining these specifications is often time-consuming and expensive. In contrast, hydrologic routing methods, such as the linear Muskingum method, are more beneficial for the analysis of unsteady flow. In flood routing, the linear Muskingum method has only been utilized to calculate the outflow hydrograph (downstream). However, in practical problems regarding flood analysis, such as economic analysis, damage assessment, and flood management and engineering, downstream water depth is needed. By employing kinematic wave relations, the linear Muskingum method, and the Particle Swarm Optimization (PSO) algorithm, the present study estimates water depth, with respect to time, of a downstream section of the Karun River, between the Mollasani (upstream) and Ahwaz (downstream) hydrometric stations. The proposed approach is simpler and less expensive and more accurate than hydraulic methods. The current work estimated the values of the Mean Relative Error (MRE) to the total flood and the Mean Relative Error (MRE) to the peak section of input depth along with the absolute value of the peak deviations of the observed and routed depth (DPO) as 1.29, 0.24, and 1.16 percent, respectively.

Suggested Citation

  • Hadi Norouzi & Jalal Bazargan, 2022. "Calculation of Water Depth during Flood in Rivers using Linear Muskingum Method and Particle Swarm Optimization (PSO) Algorithm," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(11), pages 4343-4361, September.
  • Handle: RePEc:spr:waterr:v:36:y:2022:i:11:d:10.1007_s11269-022-03257-3
    DOI: 10.1007/s11269-022-03257-3
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    References listed on IDEAS

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    1. Davor Kvočka & Roger Falconer & Michaela Bray, 2015. "Appropriate model use for predicting elevations and inundation extent for extreme flood events," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 79(3), pages 1791-1808, December.
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    3. H. Moel & J. Aerts, 2011. "Effect of uncertainty in land use, damage models and inundation depth on flood damage estimates," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 58(1), pages 407-425, July.
    4. Jalal Bazargan & Hadi Norouzi, 2018. "Investigation the Effect of Using Variable Values for the Parameters of the Linear Muskingum Method Using the Particle Swarm Algorithm (PSO)," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(14), pages 4763-4777, November.
    5. Meyer, Volker & Messner, Frank, 2005. "National flood damage evaluation methods: A review of applied methods in England, the Netherlands, the Czech Republik and Germany," UFZ Discussion Papers 21/2005, Helmholtz Centre for Environmental Research (UFZ), Division of Social Sciences (ÖKUS).
    6. Abbas Afshar & Hamideh Kazemi & Motahareh Saadatpour, 2011. "Particle Swarm Optimization for Automatic Calibration of Large Scale Water Quality Model (CE-QUAL-W2): Application to Karkheh Reservoir, Iran," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 25(10), pages 2613-2632, August.
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    Cited by:

    1. 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.
    2. Kazem Shahverdi & Hossein Talebmorad, 2023. "Automating HEC-RAS and Linking with Particle Swarm Optimizer to Calibrate Manning’s Roughness Coefficient," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 37(2), pages 975-993, January.

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