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Abstract Accurately delineating both pluvial and fluvial flood risk is critical to protecting vulnerable populations in urban environments. Although there are currently models and frameworks to estimate stormwater runoff and predict urban flooding, there are often minimal observations to validate results due to the quick retreat of floodwaters from affected areas. In this research, we compare and contrast different methodologies for capturing flood extent in order to highlight the challenges inherent in current methods for urban flooding delineation. This research focuses on two Philadelphia neighborhoods, Manayunk and Eastwick, that face frequent flooding. Overall, Philadelphia, PA is a city with a large proportion of vulnerable populations and is plagued by flooding, with expectations that flood risk will increase as climate change progresses. An array of data, including remotely sensed satellite imagery after major flooding events, Federal Emergency Management Agency’s Special Flood Hazard Areas, First Street Foundation’s Flood Factor, road closures, National Flood Insurance Program claims, and community surveys, were compared for the study areas. Here we show how stakeholder surveys can illuminate the weight of firsthand and communal knowledge on local understandings of stormwater and flood risk. These surveys highlighted different impacts of flooding, depending on the most persistent flood type, pluvial or fluvial, in each area, not present in large datasets. Given the complexity of flooding, there is no single method to fully encompass the impacts on both human well-being and the environment. Through the co-creation of flood risk knowledge, community members are empowered and play a critical role in fostering resilience in their neighborhoods. Community stormwater knowledge is a powerful tool that can be used as a complement to hydrologic flood delineation techniques to overcome common limitations in urban landscapes.
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This content will become publicly available on December 1, 2025
How urban form impacts flooding
Urbanization and climate change are contributing to severe flooding globally, damaging infrastructure, disrupting economies, and undermining human well-being. Approaches to make cities more resilient to floods are emerging, notably with the design of flood-resilient structures, but relatively little is known about the role of urban form and its complexity in the concentration of flooding. We leverage statistical mechanics to reduce the complexity of urban flooding and develop a mean-flow theory that relates flood hazards to urban form characterized by the ground slope, urban porosity, and the Mermin order parameter which measures symmetry in building arrangements. The mean-flow theory presents a dimensionless flood depth that scales linearly with the urban porosity and the order parameter, with different scaling for disordered square- and hexagon-like forms. A universal scaling is obtained by introducing an effective mean chord length representative of the unobstructed downslope travel distance for flood water, yielding an analytical model for neighborhood-scale flood hazards globally. The proposed mean-flow theory is applied to probe city-to-city variations in flood hazards, and shows promising results linking recorded flood losses to urban form and observed rainfall extremes.
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- PAR ID:
- 10566292
- Publisher / Repository:
- Nature Communications
- Date Published:
- Journal Name:
- Nature Communications
- Volume:
- 15
- Issue:
- 1
- ISSN:
- 2041-1723
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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