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A comparison of simplified conceptual models for rapid web-based flood inundation mapping

Author

Listed:
  • Heather McGrath

    (Natural Resources Canada)

  • Jean-François Bourgon

    (Natural Resources Canada)

  • Jean-Samuel Proulx-Bourque

    (Natural Resources Canada)

  • Miroslav Nastev

    (Natural Resources Canada)

  • Ahmad Abo El Ezz

    (Natural Resources Canada)

Abstract

In many parts of Canada, limited data are available for hydrodynamic model inputs, and the ability to generate quality flood grids through 1D, 2D or 3D methods is nonviable. In this paper, the capability of simplified flood models, which rely solely on digital terrain models (DTMs), was explored to assess the quality and speed of their results. Results were validated against historic floods in two locations. Three non-physics-based simplified conceptual flood models were tested: (1) planar method, (2) inclined plane and (3) height above nearest drainage network (HAND) model. The accuracy and performance were evaluated using three criteria: inundation extent, water depth and computation time. Findings show that the HAND model is the best predictor of inundation extent, with Probability of Detection and Critical Success Index being higher than 0.90 in both study areas. Though the preprocessing time for the HAND model is lengthy, once completed, the time to simulate flooding at a variety of water levels is rapid, making this model the most suitable choice for web-based, on-demand flood inundation mapping. Knowledge of the fit of these flood models and associated uncertainty can be helpful to emergency managers such that they can better understand exposure and vulnerability while preparing flood response plans.

Suggested Citation

  • Heather McGrath & Jean-François Bourgon & Jean-Samuel Proulx-Bourque & Miroslav Nastev & Ahmad Abo El Ezz, 2018. "A comparison of simplified conceptual models for rapid web-based flood inundation mapping," 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. 93(2), pages 905-920, September.
    • Handle: RePEc:spr:nathaz:v:93:y:2018:i:2:d:10.1007_s11069-018-3331-y
    DOI: 10.1007/s11069-018-3331-y
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    References listed on IDEAS

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    1. J. Teng & J. Vaze & D. Dutta & S. Marvanek, 2015. "Rapid Inundation Modelling in Large Floodplains Using LiDAR DEM," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(8), pages 2619-2636, June.
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    Cited by:

    1. Saad Mazhar Khan & Imran Shafi & Wasi Haider Butt & Isabel de la Torre Díez & Miguel Angel López Flores & Juan Castañedo Galvlán & Imran Ashraf, 2023. "Model Driven Approach for Efficient Flood Disaster Management with Meta Model Support," Land, MDPI, vol. 12(8), pages 1-27, August.
    2. Blair William Gerald Scriven & Heather McGrath & Emmanuel Stefanakis, 2021. "GIS derived synthetic rating curves and HAND model to support on-the-fly flood mapping," 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. 109(2), pages 1629-1653, November.
    3. Heather McGrath & Ahmad Abo El Ezz & Miroslav Nastev, 2019. "Probabilistic depth–damage curves for assessment of flood-induced building losses," 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. 97(1), pages 1-14, May.
    4. Zhouyayan Li & Jerry Mount & Ibrahim Demir, 2022. "Accounting for uncertainty in real-time flood inundation mapping using HAND model: Iowa case study," 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(1), pages 977-1004, May.

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