An integrated framework for high-resolution urban flood modelling considering multiple information sources and urban features. (September 2018) - Wang, Yuntao; Chen, Albert S.; Fu, Guangtao; Djordjević, Slobodan; Zhang, Chi; Savić, Dragan A.
Abstract: High accuracy models are required for informed decision making in urban flood management. This paper develops a new holistic framework for using information collected from multiple sources for setting parameters of a 2D flood model. This illustrates the importance of identifying key urban features from the terrain data for capturing high resolution flood processes. A Cellular Automata based model CADDIES was used to simulate surface water flood inundation. Existing reports and flood photos obtained via social media were used to set model parameters and investigate different approaches for representing infiltration and drainage system capacity in urban flood modelling. The results of different approaches to processing terrain datasets indicate that the representation of urban micro-features is critical to the accuracy of modelling results. The constant infiltration approach is better than the rainfall reduction approach in representing soil infiltration and drainage capacity, as it describes the flood recession process better. This study provides an in-depth insight into high resolution flood modelling. Highlights: New holistic framework is developed to handle multi-source data and urban features. Flood data from social media are a useful source for setting the model parameters. Urban micro-features can significantly influence simulated inundation extent and depth. Constant infiltration can better represent drainage capacity than the rainfall reduction approach in the study. This study provides an in-depth insight into high resolution urban flood modelling.