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This paper describes an improved building treatment approach (IBTA) for use in urban inundation modeling. In this approach, the ground surface elevation was raised by the threshold (h) of the building entrance height to account for both the blockage and storage effect of areas with dense building coverage. A higher roughness coefficient was assigned to the areas where buildings were located to compensate for the resistance effects caused by the inner wall of the structure. The campus of Huazhong University of Science and Technology (HUST) in Wuhan City, China, was used as a case study. Comparison between IBTA and several traditional building treatment approaches suggested that the model results were sensitive to the building treatment method and the threshold used for terrain preprocessing in dense building regions. Furthermore, as the interaction between the surface water flow and dense buildings were adequately represented by using a new terrain preprocessing approach, the proposed IBTA provided better performance in terms of maximum inundation depth and the peak depth time than the traditional approaches in areas with dense building coverage, such as that of the campus.

This paper proposes a new rapid simplified inundation model (NRSIM) for flood inundation caused by rainstorms in an urban setting that can simulate the urban rainstorm inundation extent and depth in a data-scarce area. Drainage basins delineated from a floodplain map according to the distribution of the inundation sources serve as the calculation cells of NRSIM. To reduce data requirements and computational costs of the model, the internal topography of each calculation cell is simplified to a circular cone, and a mass conservation equation based on a volume spreading algorithm is established to simulate the interior water filling process. Moreover, an improved D8 algorithm is outlined for the simulation of water spilling between different cells. The performance of NRSIM is evaluated by comparing the simulated results with those from a traditional rapid flood spreading model (TRFSM) for various resolutions of digital elevation model (DEM) data. The results are as follows: (1) given high-resolution DEM data input, the TRFSM model has better performance in terms of precision than NRSIM; (2) the results from TRFSM are seriously affected by the decrease in DEM data resolution, whereas those from NRSIM are not; and (3) NRSIM always requires less computational time than TRFSM. Apparently, compared with the complex hydrodynamic or traditional rapid flood spreading model, NRSIM has much better applicability and cost-efficiency in real-time urban inundation forecasting for data-sparse areas.

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