Urban road waterlogging risk assessment based on the source–pathway–receptor concept in Shenzhen, China

Abstract Urban roads are especially vulnerable to waterlogging during rainfall events. Assessments of urban road waterlogging risk are critical for disaster prevention and mitigation. This paper presents a rapid and practical approach for assessing the risk of urban road waterlogging based on a source–pathway–receptor concept and a digital elevation model (DEM). Waterlogging sources are identified by neighborhood analysis, overland flow pathways are extracted using a DEM, and the properties of cross‐nodes between pathways and roads are used to assess the waterlogging risk of roads. Futian District in Shenzhen, China, is selected as the study area. The risk results show that the waterlogging risk sources are clustered in residential land parcels and low‐lying road sections, while most road intersections and overpasses in the central area are at higher risks. The results also found that the waterlogging risk decreases as the road grade increases. Actual telephonic flooding records and reported waterlogging areas were used to validate the method, with the risk results displaying good agreement with the actual conditions. The prospects for generalizing this framework and its usage are discussed. The proposed approach provides support for pluvial flooding risk assessment and urban road waterlogging prevention.