基于贝叶斯更新的滑坡时间概率预测方法

A Probability Prediction Method for Landslide Time Based on Bayesian Update

滑坡时间预测是滑坡风险管理的重要组成部分,受限于多种不确定性、随机性因素的影响,准确预测滑坡时间非常困难。本研究提出一种基于贝叶斯更新的参数估计方法对滑坡时间进行实时概率预测,并进行多模型集成预测分析。结果表明:两个滑坡案例验证了贝叶斯更新进行滑坡时间概率预测的可行性;实时预测中,早期加速变形阶段的预测不确定性大,只有在临滑阶段才能获取较为可靠的预测结果;多模型集成预测分析可提升实时预测的可靠性,因此建议采用多模型集成进行滑坡时间预测决策。

Landslide time prediction is an important component of landslide risk management,which is limited by various uncertain and random factors,making accurate prediction of landslide time very difficult.A parameter estimation method based on Bayesian update is proposed for real-time probability prediction of landslide time,and multi model ensemble prediction analysis is conducted.The results indicate that:Two landslide cases have verified the feasibility of Bayesian updating for landslide time probability prediction;In real time prediction,the prediction uncertainty in the early acceleration deformation stage is high,and reliable prediction results can only be obtained in the critical slip stage;Multi model ensemble prediction analysis can improve the reliability of real-time prediction,therefore it is recommended to use it for landslide time prediction decision-making.