Earthquake-related Natech risk assessment using a Bayesian belief network model

Natural hazard triggering technological disasters (Natech) events pose risks to industrial facilities and process plants. As these plants handle hazardous materials, they can endanger nearby residential areas and have financial consequences. Thus, proper Natech risk assessment is required for effective prevention, mitigation and emergency response planning at industrial plants and nearby residential areas. The parameters used to quantify Natech risk assessment are subject to uncertainties and their interactions are non-linear. In this study, a Bayesian belief network-based Natech risk assessment model is developed to assess the earthquake-related Natech risk considering different levels of uncertainties. The cause and effect relationships between different parameters are constructed based on published body of knowledge and expert knowledge. The capabilities of the proposed model are demonstrated for the earthquake-related Natech risk assessment of Kobe City, Higashinada Ward, Japan because of the Great Hanshin earthquake in 1995. The proposed model is also capable of performing both predictive analysis and diagnostic analysis.