A rapid inundation flood cell model for flood risk analysis

• Main Author: Krupka, Martin
• Other Authors: Pender, Gareth : Wallis, Steve
• Published: Heriot-Watt University 2009
• Subjects: 363.34932
• Online Access: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.507923

Government flooding policy across Europe, and in the UK, has switched from flood defence to flood risk management. The approach requires the evaluation of the consequences of all possible asset failures over a range of flood probabilities. For a typical flood system this necessitates the simulation of thousands of inundation permutations. As a consequence, the speed of simulation is a significant factor in the practical implementation of this approach. This thesis reports on the development and testing of a Rapid Flood Inundation Model (RFIM) designed to satisfy this requirement. The model consists of a precalculation part, and a subsequent rapid flood inundation prediction. Three variations of the rapid inundation routine are presented. The algorithms differ in the way in which the flood depth on the communication links between the cells is calculated. The latter version also permits a spatially limited estimation of flow velocities. The RFIM was applied to the Greenwich and Thamesmead embayments on the River Thames in London. The main objectives of the RFIM testing were: to evaluate the predictive capabilities of the simple volume spreading method used. In order to undertake the task a Monte Carlo analysis was performed and the flood extent maps were compared to predictions produced by the two-dimensional hydrodynamic model, TUFLOW. The overall performance of the model was found to be acceptable, although some inaccuracies in the predictions, as a result of the oversimplification of the hydraulics, were observed. These were discussed and recommendations were given to improve model behaviour. The computational speeds were found to be acceptable and within the required limits. It is therefore suggested that the proposed Rapid Flood Inundation Model can be used for flood predictions in urban areas for the purpose of flood risk management.