ABSTRACT
Risk analysis has been widely used in climate adaptation practice. However, traditional probabilistic risk analysis methods are not capable of tackling the unavailability or incompleteness of climate risk data. To deal with such challenges, this paper further applies an advanced Fuzzy Bayesian Reasoning (FBR) model for climate risk analysis of railways system in the UK. Its novelty lies in the realisation of climate risk ranking under high uncertainty in data and its practical contribution on the risk perception of stakeholders in the UK railway systems. To test the feasibility of the developed model in the transport industry, a large scale of surveys are conducted to collect data, regarding the timeframe of climate hazards, likelihood of occurrence, severity of consequences, and infrastructure resilience for the analysis of climate risks threatening British rail systems. The findings will provide transport planners with useful insights on the identification of climate hazards of high risks to facilitate the development of cost-effective climate adaptation strategies.
