City-scale dynamic assessment of pedestrian travel risk in urban subway systems during flood events

Urban flooding is intensifying due to climate change and rapid urbanization, yet the flood risk faced by subway travellers remains inadequately understood. Taking the Beijing subway system as a representative megacity case, this study develops a city-scale framework for dynamically assessing travel-related flood risk, integrating flood hazard, pedestrian travel exposure, and pedestrians’ physical vulnerability to floodwater environments. The effects of key factors under future climate scenarios, including global climate models (GCMs), emission pathways, precipitation return periods, land-use patterns, and weekday–weekend differences, on both aggregated and hourly travel flood risk are systematically examined for a typical workday. The results identify four spatially clustered high-risk regions across the Beijing subway network, involving multiple critical lines and stations where pedestrian travel is subject to severe flood threats. Both the spatial coverage of high-risk areas and the number of vulnerable stations increase under higher emission pathways and longer precipitation return periods, with notable regional disparities across different GCMs. In contrast, travel flood risk exhibits limited sensitivity to land-use variations and only minor weekday–weekend differences. Despite pronounced morning (07:00–09:00) and evening (17:00–19:00) travel peaks, the highest travel flood risk occurs during late-night hours (22:00–24:00), primarily due to a temporal mismatch between hourly precipitation intensity and pedestrian travel exposure. These findings underscore the importance of incorporating dynamic human mobility into urban flood risk assessments and offer actionable insights for climate-adaptive planning and flood-resilient management of subway systems.