Risk assessment of dammed lakes in China based on Bayesian network

Abstract

Scientific risk assessment of dammed lakes is vitally important for emergency response planning. In this study, based on the evolution process of the disaster chain, the logic topology structure of dammed lake risk was developed. Then, a quantitative risk assessment model of dammed lake using Bayesian network is developed, which includes three modules of dammed lake hazard evaluation, outburst flood routing simulation, and loss assessment. In the model, the network nodes of each module were quantified using statistical data, empirical model, logical inference, and Monte Carlo method. The failure probability of a dammed lake, and the losses of life and property were calculated. This can be multiplied to assess the risk a dammed lake imposes after the uniformization of each loss type. Based on the socio-economic development and longevity statistics of dammed lakes, a risk-level classification method for dammed lakes is proposed. The Baige dammed lake, which emerged in China in 2018, was chosen as a case study and a risk assessment was conducted. The obtained results showed that the comprehensive risk index of Baige dammed lake is 0.7339 under the condition without manual intervention, identifying it as the extra-high level according to the classification. These results are in accordance with the actual condition, which corroborates the reasonability of the proposed model. The model can quickly and quantitatively evaluate the overall risk of a dammed lake and provide a reference for decision-making in a rapid emergency response scenario.