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Hydrological Processes, Vol. 24, No. 11, pp. 1404-1420, 2010.
Ryota Tsubaki 1, Ichiro Fujita 2
1 Department of Civil and Environmental Engineering, Hiroshima University, Kagamiyama 1-4-1, Higashi-Hiroshima 739-8527, Japan
2 Department of Civil Engineering, Kobe University, Rokkodai, Nada-Ku, Kobe 657-8501, Japan
email: Ryota Tsubaki (rtsubaki@hiroshima-u.ac.jp)
Abstract
Inundation disasters, caused by sudden water level rise or rapid flow, occur frequently in various parts of the world. Such catastrophes strike not only in thinly populated flood plains or farmland but also in highly populated villages or urban areas. Inundation of the populated areas causes severe damage to the economy, injury, and loss of life; therefore, a proper management scheme for the disaster has to be developed. To predict and manage such adversity, an understanding of the dynamic processes of inundation flow is necessary because risk estimation is performed based on inundation flow information. In this study, we developed a comprehensive method to conduct detailed inundation flow simulations for a populated area with quite complex topographical features using LiDAR (Light Detection and Ranging) data. Detailed geospatial information including the location and shape of each building was extracted from the LiDAR data and used for the grid generation. The developed approach can distinguish buildings from vegetation and treat them differently in the flow model. With this method, a fine unstructured grid can be generated representing the complicated urban land features precisely without exhausting labour for data preparation. The accuracy of the generated grid with different grid spacing and grid type is discussed and the optimal range of grid spacing for direct representation of urban topography is investigated. The developed method is applied to the estimation of inundation flows, which occurred in the basin of the Shin-minato River. A detailed inundation flow structure is represented by the flow model, and the flow characteristics with respect to topographic features are discussed.
Keywords
inundation • LiDAR • unstructured grid • grid size • shallow water
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