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The influence of road network topology on street flooding in New York City—A social media data approach

CSS Publication Number
Full Publication Date
June 16, 2024

Urban road network is crucial stormwater infrastructure as city roads serve as paths for stormwater runoff and urban flooding. However, it remains unclear how different road networks influence urban flooding. While past studies have examined high-magnitude and high-intensity flooding events at the large river basin scale, they neglected smaller and more frequent street flooding events (SFEs) which could have a higher cumulative cost. Hence, this study used urban road network topology (RNT) factors and social media big data related to street flooding to investigate their associations with data-driven methods for 557 sewer catchments across New York City (NYC). 11,042 SFEs were taken from raw street flooding complaints (SFCs) recorded on the NYC 311 sewer complaints platform between January 1, 2010, and April 28, 2022. We then used generalized linear mixed models to identify the relationship between RNT factors and street flooding risk (SFR) and found that the characteristics of SFR periodically changed with spatial–temporal heterogeneity. While impervious factor was previously found important, RNT emerged as a new significant factor influencing SFR, with the effects being larger in combined sewer systems and heavy precipitation events. We discerned that planning a dendric road network pattern, increasing RNT connectivity in downstream areas, and having wider roads with more intersections could reduce SFR. Decreasing RNT connectivity in upstream areas, road length, the number of roads, and sewer catchment area also mitigated SFR. Our analysis provided informed street flooding mitigation and adaptation strategies to promote a more resilient, healthy, and sustainable urban environment.

Chen ZUO
Runzi Wang
Yi Hong
Yuhan Zhou
Yiyi He
Research Areas
Mobility Systems

Urban flooding; Road connectivity; Mixed effect model; NYC 311; Flooding complaints

Publication Type
Journal Article
Full Citation

Zuo, C., Wang, R., Hong, Y., Zhou, Y., He, Y., & Gronewold, A. D. (2024). The influence of road network topology on street flooding in New York City—A social media data approach. Journal of Hydrology, 131471.