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Summary of Proposal HYD0363

TitleUsing TerraSAR-X data for improved urban flood model validation
Investigator Mason, David - University of Reading, Environmental Systems Science Centre
Team Member
Professor Bates, Paul - University of Bristol, School of Geographical Sciences
Dr Neal, Jeffrey - University of Bristol, School of Geographical Sciences
Dr. Schumann, Guy - University of Bristol, School of Geographical Sciences
SummaryFlooding is a major hazard in both rural and urban areas worldwide, but it is in urban areas that the risks to people and the economic impacts are most severe. Urban flood modelling is still at an early stage, and to date most models have been applied in rural areas. Flood modelling in urban areas is more complicated partly because flows interact with the built environment, necessitating at least a 2D treatment of the surface flow hydraulics. Urban flood models need considerable data for their parameterisation, including high resolution LiDAR data, estimates of channel and floodplain friction factors, and estimates of building coverage in each model grid cell. In rural areas, 2D flood models have been successfully calibrated using flood extents determined from SAR data (typically ERS and ASAR) in order to estimate channel and floodplain friction factors. SAR data are used because of their all-weather day-night capability. While ERS-2 and ASAR have too low a resolution for use in urban areas, TerraSAR-X should be good for urban flood detection because of its high resolution in stripmap/spotlight modes. Due to the side-looking nature of SAR, substantial areas of ground surface would not be visible due to shadowing and layover caused by buildings. The proposal involves using a SAR simulator in conjunction with LiDAR data to identify regions of water in areas not affected by buildings. Various sources of information would be exploited in the classification of flooded urban areas. These would include digital map data of roads, man-made surfaces and buildings, as well as LiDAR heights. A classification procedure employing a region-growing approach would be used to extract water regions. The method would be tested on a TerraSAR-X image of a 1-in-100 year flood on the Severn, UK, in 2007 for which near-simultaneous aerial photography exists. The degree to which the TerraSAR-X image could detect water regions in the urban areas would be assessed, as would the degree to which the detected regions could constrain the parameterisation of an example 2D urban flood model.

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