Risk analysis of rainfall-induced disasters along the Shuozhou-Huanghua Railway

The risk analysis of rainfall-induced disasters along the Shuozhou-Huanghua Railway can provide reference for precise flood control for railway departments. Based on the daily precipitation data from 1951 to 2022, Pearson III distribution, Gumbel distribution and Logarithmic normal distribution were used to fit the return period of annual maximum daily precipitation of rainfall process over the years along the railway respectively, the chi square test was used to screen the optimal fitting distribution model in different regions, the distribution characteristics of the maximum daily precipitation for different return periods in each region along the Shuozhou-Huanghua Railway were obtained. Then based on the hourly precipitation data from 2004 to 2023 of the national meteorological stations and the data from 2018 to 2023 of the meteorological stations along the Shuozhou-Huanghua Railway set by the railway department, the rainfall process and precipitation factors along the railway were counted, the 12 factors of rainfall process, including the annual average frequency of process precipitation, maximum hourly precipitation and maximum 24-hour precipitation that reaching the thresholds for patrol, speed limit and blockade warning respectively, and the extreme value of precipitation were selected to construct the risk assessment index of rainfall-induced along Shuozhou-Huanghua Railway, the AHP and entropy weight method was used to calculate the index weight coefficient of each evaluation index factor, finally the hazard level of rainfall along Shuozhou-Huanghua Railway was obtained. The results show: The sections from Xibaipo Station to Sanji Station and Boye Station to Lixian Station along the Shuozhou-Huanghua Railway are the highest risk level of rainfall, while the sections from South of Shenchi Station to Dongye Station are the lowest risk level of rainfall, the assessment results are basically consistent with the distribution of maximum daily precipitation in different return periods.