Case-based risk analysis model for rainstorm inundation in metro systems based on a bayesian network

The intensities and frequencies of extreme rainstorms are increasing, which may result in severe inundation of urban metro systems. Although there is some risk assessment research on regional metro systems based on spatiotemporal data, the characteristics of specific metro stations and shortcomings in the emergency response process need more consideration. In this paper, a risk analysis model for rainstorm inundation in metro systems based on a Bayesian network and a practical case study are proposed. First, the risk factors are obtained by integrating general mechanism analysis and the case study. Second, an event evolution diagram is established to represent the comprehensive evolution process of a potential event. Third, the risk analysis model is established using a Bayesian network model considering the quantitative causal relationships between risk factors. This model is used to analyze the risk of supporting emergency management, including emergency preparation based on critical risk factor sensitivity identification, prewarning response strategy development based on risk analysis as rainstorms occur, and rescue strategy development based on risk analysis as rainstorm water flows into metro tunnels. Furthermore, this model can be flexibly improved as natural hazards and metro systems change and as new problems are exposed in practical cases.