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

Heather McGrath (), Jean-François Bourgon, Jean-Samuel Proulx-Bourque, Miroslav Nastev and Ahmad Abo El Ezz
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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

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2018, vol. 93, issue 2, No 17, 905-920

Abstract: 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.

Keywords: 0D; Bathtub model; DTM; HAND; LiDAR; Rapid floodplain inundation; Simplified conceptual models (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (4)

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DOI: 10.1007/s11069-018-3331-y

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