The Influence of Road Network Topology on Street Flooding in New York City—A Social Media Data Approach

Road network is important in urban planning because it not only shapes the spatial structure of an urban area but also serves as a critical stormwater infrastructure. Existing literature on urban flooding focused on flood risk assessment, traffic disruption, and congestion analysis at large river basin scales under high-magnitude and high-intensity flooding events. However, the relationship between road network topology and urban flooding remains unclear. Additionally, smaller, and more frequent street flooding events, which cause higher cumulative costs, are often less studied. The common use of physicallybased hydrological models with strict data requirements further limits the scope of previous flooding studies. To address these gaps, this study utilized statistic models to investigated the influence of urban road network topology on street flooding risks in 557 sewer catchments across New York City (NYC) with a social media big data approach. We used 11 road network topology metrics and 11,042 street flooding complaints recorded on the NYC 311 Sewer Complaints platform from 2010 to 2022. We performed generalized linear mixed models to investigate the relationship between road network topology metrics and street flooding risks. The control variables included sewer drainage type, rainfall intensity, land use, impervious density, human and nature factors. We found that road network connectivity significantly affected the risk of street flooding, while the influence of impervious was not significant. Our findings suggested that increasing road network connections, average road width, and number of intersections while decreasing the total road length, total number of roads, and sewer catchment area would reduce the risk of street flooding. Therefore, optimizing road network connectivity is a key consideration for flooding mitigation in urban planning.Master of Landscape Architecture (MLA)Master of Science (MS)School for Environment and SustainabilityUniversity of Michiganhttp://deepblue.lib.umich.edu/bitstream/2027.42/176148/1/Zuo, Chen_Thesis.pd