Risk analysis of waterlogging in a big city based on a bow-tie Bayesian network model, using the megacity of Wuhan as an example

Abstract

At present, the global urbanization process is accelerating, with the climate changing constantly and extreme weather increasing. In this background, urban flood disasters caused by rainstorms frequently occur in China. Therefore, a disaster risk analysis model based on a bow-tie Bayesian network was established to analyze the risk of waterlogging disasters. First, the waterlogging accident was analyzed, the intermediate and basic events that caused the accident were identified, and the accident tree was drawn. According to the intuitive nature of the fault tree, it was transformed into a Bayesian network, and in the meantime, a posteriori probability analysis of nodes was performed to further obtain the critical importance of basic events. By analyzing the importance of the basic events of waterlogging disasters, the key basic events that lead to disasters were proposed. Finally, the bow-tie model was used to analyze the importance of the hazards, and a strategy for the prevention and control of accidents was proposed. The results show that the major accident node of urban waterlogging accidents is the unsafe state of the urban environment, and the management and control of the urban environment should be strengthened to improve the prevention and control of urban waterlogging, e.g., pre-disaster prevention.