Subway station flood risk management level analysis

In recent years, the frequency of extreme rainfall events has increased due to climate change, resulting in a higher risk of flooding in urban underground spaces, particularly subway systems. Although effective equipment and technologies have emerged to mitigate flood risks in subway stations, there is still a lack of comprehensive flood risk management strategies. Therefore, it is crucial to assess the flood risk management level of subway stations as a first step toward devising effective flood prevention and control plans. This study takes the Beijing subway network as an example and uses complex network theory to establish a weighted undirected subway network model to determine the relative importance of each subway station. Passenger flow statistics are then conducted for each route, and the passenger exposure of each route is analyzed under flooding circumstances. Ultimately, the flood risk index for different subway stations is determined based on the flood risk map. The technique for order preference by similarity to ideal solution (TOPSIS), network weighting method, and analytic hierarchy process (AHP) are employed to analyze the flood risk management level of subway stations. The findings indicate that the flood risk management level of Pinganli, Xizhimen, and Hujialou subway stations of Beijing is relatively high, making these subway stations particularly vulnerable to comprehensive disasters, including operational disruptions and passenger exposure, in the event of flooding. This study has significant academic value in the field of flood risk management in subway systems by applying complex network theory to assess the importance and passenger exposure of subway stations in urban operation, effectively capturing the flood risk associated with subway stations, and providing a comprehensive understanding of the functionality of subways as a public transportation mode.