A Two-Stage Bayesian Network Approach to Inland Waterway Navigation Risk Assessment Considering the Characteristics of Different River Segments: A Case of the Yangtze River

Identifying the main sources of risk for different types of waterways helps to develop targeted risk control strategies for different river segments. To improve the level of risk management in inland waterways for sustainable development, a two-stage risk evaluation model is proposed in this study by integrating a fuzzy rule base and Bayesian networks. The model evaluates risk sources from the following four dimensions: probability of occurrence, visibility, probability of causing accidents, and consequences. Typical river sections in the upper, middle, and lower reaches of the Yangtze River were selected as cases, and 19 risk sources were identified and comparatively analyzed from the perspectives of humans, ships, the environment, and management. The fuzzy rule base is employed to compare expert opinions, yielding three key risk sources for each section based on their risk values. The findings reveal certain commonalities in the principal risk sources across sections. For example, natural disasters (landslides, earthquakes, and extreme hydrological conditions) are present in both the middle and lower reaches, and an insufficient channel width is common in the upper and middle reaches. However, the key risk sources differ among the sections. The upper reaches are primarily threatened by the improper management of affiliated vessels and adverse weather, while the middle reaches suffer from insufficient channel width surplus, and the lower reaches are mainly threatened by high vessel traffic density and low-quality crews. The results of the study show that the key risk sources in each section of the Yangtze River have obvious differences and need to be assessed according to the characteristics of different sections. This study can provide a reference for decision-making in inland waterway risk management by maritime safety authorities.