Subway travel risk evaluation during flood events based on smart card data

Abstract

The intensity and frequency of extreme weather is increasing in major metropolitan areas around the world, which results in unprecedented urban floods. However, subway systems lack consideration of flood risk, and few studies have assessed risk during flood events from the view of subway travel. In this study, subway travel risk was evaluated by flood hazard, subway travel exposure and population vulnerability under three groups of rainfall scenarios. The degree of spatial exposure was calculated based on smart card data and a census, and the vulnerability of the population was assessed based on human stability in floodwaters. The results in the study area indicate that subway travel risk grows with an increase in the rainfall return period, and the highest subway travel risk occurs in the morning peak period. The return periods of rainfall, time-to-peak, and duration have an impact on the spatiotemporal trajectory of subway travel risk. Furthermore, the traditional census tends to underestimate subway transportation exposure due to subway travel. Subway travel risk increases significantly under the extreme rainfall scenario and requires further research. This study provides risk maps for making travel decisions before departures and support for subway operators to develop risk warnings.

Keywords

• Subway travel
• urban flood simulation
• population exposure
• risk modelling