Development of an Integrated Urban Flood Model and Its Application in a Concave-Down Overpass Area

• Published in: Remote sensing (Basel, Switzerland) Switzerland), 2024-05, Vol.16 (10), p.1650
• Main Authors: Yan, Yuna, Zhang, Han, Zhang, Na, Feng, Chuhan
• Format: Article
• Language: English
• Subjects: Accuracy; Case studies; Cellular automata; China; Decision making; Disaster management; Drainage; Drainage patterns; Extreme weather; flood depth; Flood management; flood range; flood volume; Flood, Mike; Flooding; Floods; Hydrologic cycle; Hydrologic models; Hydrology; Land cover; landscapes; Modules; Overflow; overflow expansion; pipe convergence; Rain; Rainstorms; Robots; Runoff; Simulation; Simulation methods; Stormwater; Stormwater management; Surface properties; Surface runoff; Temporal variations; Terrain; Topography; Urban areas; Urban runoff; Vegetation; Water; Water management
• ISSN: 2072-4292; 2072-4292
• DOI: 10.3390/rs16101650

Urban floods caused by extreme rainstorm events have increased in recent decades, particularly in concave-down bridge zones. To simulate urban flooding processes accurately, an integrated urban flood model (IUFM) was constructed by coupling a distributed urban surface runoff model based on the cellular automata framework (CA-DUSRM), a widely used pipe convergence module in the storm water management model (SWMM), with an inundation module that describes the overflow expansion process associated with terrain and land-cover. The IUFM was used in a case study of the Anhua Bridge (a typical concave-down overpass) study area in Beijing, China. The spatial-temporal variations in flood depth modeled by the IUFM were verified to be reliable by comparison with actual measurements and other simulations. The validated IUFM was used to obtain temporal variations in flood range, depth, and volume under four rainstorm scenarios (return periods of 3-year, 10-year, 50-year, and 100-year). The results showed that the surface runoff process, overflow from drainage networks, and overflow expansion process could affect the flooding status by changing the composition and spatial configuration of pervious or impervious patches, drainage capacity, and underlying surface characteristics (such as terrain and land-cover). Overall, although the simulation results from the IUFM contain uncertainties from the model structures and inputs, the IUFM is an effective tool that can provide accurate and timely information to prevent and control urban flood disasters and provide decision-making support for long-term storm water management and sponge city construction.