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Simulation of Flood Inundation Extent by Integration of HEC-HMS, GA-based Rating Curve and Cost Distance Analysis

Author

Listed:
  • Sagar Debbarma

    (North Eastern Regional Institute of Science and Technology)

  • Subhajit Dey

    (IIT Madras)

  • Arnab Bandyopadhyay

    (North Eastern Regional Institute of Science and Technology)

  • Aditi Bhadra

    (North Eastern Regional Institute of Science and Technology)

Abstract

Flood inundation modeling is crucial for analyzing floods and understanding the impact of rainfall on runoff. Traditional hydraulic models require substantial data and technical skill, which creates difficulties in situations with limited data and expertise. To reduce computational cost and data requirements, the study utilizes HEC-HMS, a Genetic Algorithm (GA)-based rating curve, and cost-distance analysis to develop a flood inundation model in Tlawng river basin. The HEC-HMS SMA model was calibrated for daily streamflow from June 2017 to May 2020 and then cross-validated from Nov 2018 to May 2020. The model streamflow predictions were evaluated using statistical parameters such as Root Mean Standard Deviation Ratio (RSR), Percent Bias (PBIAS), Nash–Sutcliffe Efficiency (NSE), Root Mean Squared Logarithmic Error (RMSLE), and Mean Absolute Error (MAE). The values obtained were 0.4 (calibration) and 0.5 (validation) for RSR, 5.78% (calibration) and 9.28% (validation) for PBIAS, 0.85 (calibration) and 0.775 (validation) for NSE, 0.18 (calibration) and 0.21 (validation) for RMSLE, and 9.92 (calibration) and 7.12 (validation) for MAE, respectively. Then, a GA-based rating curve was developed to convert the simulated discharge into depth at basin outlet. Furthermore, cost-distance analysis tool was used to determine flood inundation extent. Modeled flood inundation extents were accurately validated by observed GPS points of flood marks. The horizontal distance between the modeled inundation and the actual flood mark was 9.48 m, while the vertical distance coincided precisely at an elevation of 40 m MSL. The study demonstrates a practical and efficient way to assess flood risks and develop suitable mitigation strategies in the Tlawng river basin.

Suggested Citation

  • Sagar Debbarma & Subhajit Dey & Arnab Bandyopadhyay & Aditi Bhadra, 2024. "Simulation of Flood Inundation Extent by Integration of HEC-HMS, GA-based Rating Curve and Cost Distance Analysis," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 38(4), pages 1397-1417, March.
    • Handle: RePEc:spr:waterr:v:38:y:2024:i:4:d:10.1007_s11269-023-03727-2
    DOI: 10.1007/s11269-023-03727-2
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    References listed on IDEAS

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    1. Vishal Singh & Anil Kumar Lohani & Sanjay Kumar Jain, 2022. "Reconstruction of extreme flood events by performing integrated real-time and probabilistic flood modeling in the Periyar river basin, Southern India," 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. 112(3), pages 2433-2463, July.
    2. Ishfaq Hussain Malik, 2022. "Spatial dimension of impact, relief, and rescue of the 2014 flood in Kashmir Valley," 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. 110(3), pages 1911-1929, February.
    3. Sheng-Chi Yang & Tsun-Hua Yang & Ya-Chi Chang & Cheng-Hsin Chen & Mei-Ying Lin & Jui-Yi Ho & Kwan Tun Lee, 2020. "Development of a Hydrological Ensemble Prediction System to Assist with Decision-Making for Floods during Typhoons," Sustainability, MDPI, vol. 12(10), pages 1-20, May.
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