Assessment of vulnerability to waterlogging in subway stations using integrated EWM-TOPSIS

Abstract

Waterlogging in subway stations has a devastating impact on normal operation of important urban facilities and can cause harm to passengers and property. It is difficult to assess the vulnerability of metro stations to waterlogging because many complex factors are involved. This study proposes a hybrid model to assess the vulnerability of subway stations to waterlogging by integrating the entropy weight method (EWM) with a technique for order preference based on similarity to the ideal solution (TOPSIS) (the EWM-TOPSIS method). The model is based on analysis of factors influencing the vulnerability of subway stations to waterlogging. The proposed method was applied to a field case (Jinshahu station in Hangzhou, found to be vulnerable to waterlogging at level IV). The results from EWM-TOPSIS, EWM, and TOPSIS were compared. The results using the EWM-TOPSIS method were more accurate and reliable than those using EWM and TOPSIS. However, the reliability of EWM-TOPSIS was determined based on historical data, which cannot capture rapidly changing factors. Based on the assessment results, recommendations were made to promote the overall health and development of urban areas to satisfy the United Nations Sustainable Development Goal 11 (SDG11).