基于贝叶斯公式修正的降雨型滑坡灾害概率研究OA

To improve the spatiotemporal probability algorithm for rainfall-induced landslide disasters and im-prove early warning accuracy,the dataset of rainfall and landslide events in Shanxi,China form 2001 to 2020 was reconstructed by removing samples from the freeze-thaw period and landslides not clearly rainfall-induced.A di-saster probability model was developed using logistic regression based on accumulated effective rainfall and rain-fall duration.Shanxi Province was divided into five subregions according to the spatial distributions of underly-ing surface factors;the probability model was corrected using a Bayesian formula to obtain a spatial probability model.The receiver operating characteristic curve(ROC)was applied to determine the critical value of landslide disasters,and the models were validated with data from 2021 to 2023.Finally,interpolation was used to derive the disaster threshold curves for different subregions.The conclusions are as follows:(1)The freeze-thaw period ends in early May in southern Shanxi Province but lasts until mid-June in the north.(2)The ROC curve shows that both the logistic regression and Bayesian formula correction models predict accurately,with the latter per-forming better;critical probabilities are 61.51%and 60.37%,respectively.(3)The accuracies of the logistic re-gression and Bayesian formula correction models are 86.44%and 93.22%,respectively,indicating significant im-provements with the Bayesian formula correction.(4)Threshold curves across subregions of Shanxi Province de-crease with rainfall duration increases.Spatially,landslide thresholds decrease from southwest to northeast across Shanxi Province.