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Rapid Inundation Modelling in Large Floodplains Using LiDAR DEM

J. Teng, J. Vaze, D. Dutta () and S. Marvanek

Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), 2015, vol. 29, issue 8, 2619-2636

Abstract: Rapid and accurate inundation modelling in large floodplains is critical for emergency response and environmental management. This paper describes the development and implementation of a floodplain inundation model that can be used for rapid assessment of inundation in very large floodplains. The model uses high resolution DEM (such as LiDAR DEM) to derive floodplain storages and connectivity between them at different river stages. We tested the performance of the model across several large floodplains in southeast Australia for estimating floodplain inundation extent, volume, and water depth for a few recent flood events. The results are in good agreement with those obtained from high resolution satellite imageries and MIKE 21 two-dimensional hydrodynamic model. The model performed particularly well in the reaches that have confined channels with above 85 % agreement with the flood maps derived from Landsat TM imagery in cell-to-cell comparison. While the model did not performance as well in the flat and complex floodplains, the overall level of agreement of the modelled inundation maps with the satellite flood maps was still satisfactory (60–75 %). The key advantage of this model is demonstrated by its capability to simulate inundation in large floodplains (over 2000 km 2 ) at a very high resolution of 5-m with more than 81 million cells at a reasonably low computational cost. The model is suitable for practical floodplain inundation simulation and scenario modelling under current and future climate conditions. Copyright Springer Science+Business Media Dordrecht 2015

Keywords: Rapid inundation modelling; LiDAR DEM; Floodplain; TVD model; Hydrodynamic modelling; Flood emergency response (search for similar items in EconPapers)
Date: 2015
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Citations: View citations in EconPapers (11)

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DOI: 10.1007/s11269-015-0960-8

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