Research on annual disaster probability risk assessment based on historical disaster big data

The fluctuation of annual disaster losses is significant, and it is crucial to scientifically evaluate the annual disaster risk in order to improve disaster prevention, reduction, and relief efforts. This paper attempts to establish an annual disaster probability risk assessment method based on historical disaster situations. The main conclusions are as follows: 1) Based on the lognormal distribution, Rayleigh distribution, Weibull distribution, exponential distribution, logarithmic logistic distribution, and information diffusion techniques, a comprehensive annual probability risk assessment method integrating optimal distribution fitting, information diffusion, and risk assessment is established. Using data on annual deaths and collapsed houses caused by disasters from 1990 to 2016 as an example, the feasibility and operability of this method are verified. 2) The extreme values of annual data may have some impact on the assessment results, but the impact of extreme values is more significant. In this study, the assessment results of annual probability risk assessment of death population were not ideal when extreme values were involved, while the impact of maximum values in the annual probability risk assessment of collapsed houses was small. The purpose of this study is to provide case studies and method references for conducting annual disaster risk assessment in related research and business practices.