EVALUATION OF RAILWAY LINK VULNERABILITY DUE TO FLOOD EVENTS

Abstract

Rail transportation is a vital part of both social infrastructure and economic systems, yet it faces growing challenges from natural disasters, especially flooding, which are becoming more frequent and severe due to climate change. This study analyses the vulnerability of railway networks to flood-related disruptions by applying graph theory and Monte Carlo simulations. A passenger flow-based network model is developed to simulate flood-induced link failures and identify the most critical railway segments whose failure would result in substantial disruption to passenger movement. In contrast to traditional methods that consider only single-link failures, this study introduces an approach by simulating the cascading effects of flooding, enabling both a primary link and its adjacent links to fail based on their spatial proximity and associated flood probabilities. This approach more accurately reflects real-world scenarios where flood impacts are not isolated but spread through interconnected infrastructure. The simulation incorporates weighted probabilities and a Poisson distribution to determine how many neighbouring links might fail, enhancing the realism of the model. Results reveal high-risk edges that, if disrupted, would have a major impact on the network’s performance, providing valuable insight for infrastructure managers and policymakers. These findings can support targeted investment in flood prevention and adaptation strategies, such as elevating tracks, improving drainage systems, and implementing real-time monitoring technologies. Furthermore, the insights can guide the development of robust emergency response plans aimed at maintaining service continuity. Overall, the study offers a practical framework for improving the resilience and reliability of railway systems under increasing climate-related risks.