Model Modification of Verhulst Inverse-Function Forecasting Model and Probabilistic Forecast for Landslide Failure Time
Chen Mingxi
Tao Peijie
Zhou Chuangbing
Jiang Qinghui
Abstract：Landslide time-of-failure forecast is an essential part of landslide disaster prevention and control.However,due to the uncertainty of the landslide evolution process,it is challenging to forecast the occurrence time of landslide events accurately.The Verhulst inverse-function model is a common landslide time-of-failure forecasting model,but the model suffers from the problems of poor fitting quality and low forecasting accuracy of displacement monitoring data caused by the improper selection of the calculation starting points.To address this deficiency,an improved Verhulst inverse-function model(MVIF model)is proposed and analyzed for near real-time probabilistic forecast.The results show that(1)the MVIF model addresses the problem of harsh selection of the calculation starting points in the original model;(2)the MVIF model has high forecasting accuracy and can make reliable forecasts after the landslide enters the medium accelerating deformation phase;(3)the combination of predicted landslide time and failure probability provides a new forecasting criterion.This study can provide valuable reference for early warning and forecast of creeping landslides.
Keywords：landslideslandslide time-of-failure forecastVerhulst inverse-function modelmodel modificationprobabilistic analysisforecasting decisionhazards
Publication Date：2024-05-15
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：14( 1692-1705 )