Analyzing failure mechanisms and predicting step-like displacement:Rainfall and RWL dynamics in lock-unlock landslides  

作　　者：Xuekun Xiang Haijia Wen Jiafeng Xiao Xiongfeng Wang Hongyue Yin Junhao Huang 

机构地区：[1]National Joint Engineering Research Center of Geohazards Prevention in the Reservoir Areas,Key Laboratory of New Technology for Construction of Cities in Mountain Area,Ministry of Education Chongqing,School of Civil Engineering,Chongqing University,Chongqing 400045,China [2]Technology Innovation Center of Geohazards Automatic Monitoring,Ministry of Natural Resources,Chongqing Institute of Geology and Mineral Resources,Chongqing 401120,China [3]China Harbor Engineering Co.,Ltd,Beijing 100027,China [4]The Key Laboratory of GIS Application Research,Chongqing Normal University,Chongqing 401331,China

出　　处：《Geoscience Frontiers》2025年第1期155-174,共20页地学前缘(英文版)

基　　金：support from National Key Research and Development Program of China(2023YFC3007203).

摘　　要：Lock-unlock landslides have thick sliding zones that store a lot of energy.This makes them start quickly,happen suddenly,and have serious consequences.Therefore,it becomes urgent to study the deformation and failure mechanisms of such landslides and develop rational predictive models.Taking the Jiuxianping landslide as an example,this study investigates the regularity of landslide displacement changes using multi-source data,focusing on the abrupt displacement patterns in the unlock phase.Furthermore,employing Transient Release and Inhalation Method tests combined with Geo-Studio’s SEEP/W and SIGMA/W modules for fluid-solid coupled simulation calculations,the evolution process of landslide failure mechanisms and deformation characteristics is analyzed and discussed.Lastly,utilizing data mining analysis of multi-source data,a hybrid optimized machine learning predictive model is established for model prediction comparison.The study reveals that:(1)The rise in infiltration line elevates pore water pressure,affecting the stability of the sliding zone,leading to“unlock effects”and step-like displacement deformation;(2)Simulation shows that YY208 is closer to the actual situation,located at the far bank position,while YY210 is greatly influenced by the“buoyancy effect”,resulting in a slowdown in deformation velocity;(3)After data preprocessing,overall actual displacement prediction performs better than simulation displacement prediction in terms of Mean Absolute Error,Mean Squared Error and Correlation Coefficient,but noise reduction processing can improve the periodic prediction effect of simulation displacement.

关 键 词：Lock-unlock TRIM test Geo-Studio Hybrid optimization Machine learning 

分 类 号：P64[天文地球—地质矿产勘探]