ABSTRACT Physics‐based flood hydrodynamic models are widely used for predicting inundation in urban basins with complex building layouts. While the treatment of urban buildings in these models has been extensively discussed, over‐assumptions can introduce inaccuracies, uncertainties, and excessive computational effort, particularly under data‐scarce conditions. This study proposes a simple yet effective method, the Building Coverage Ratio (BCR) scheme, to account for building effects in city‐scale urban inundation modeling. The BCR scheme quantifies water abstraction to generate surface runoffs in densely built‐up areas by dynamically adjusting drainage and infiltration volumes based on the proportion of building footprint in each grid cell. This approach improves the accuracy of urban flood predictions when high‐resolution data is unavailable. Validated against a historical rainstorm event in Zhuhai, China, the BCR scheme demonstrated its capability to efficiently and accurately reproduce spatiotemporal inundation patterns. The method significantly improved street‐level flooding simulations, which are often underestimated in traditional approaches that neglect building effects. Results show that simulation accuracy increases from 33% without treatment to over 85% when the BCR scheme was applied to 30 m‐resolution Digital Elevation Model (DEM). As the method relies entirely on open‐source datasets, it offers a practical and transferable solution for urban flood prediction in data‐scarce regions.
Li et al. (Mon,) studied this question.