Synergistic evolution of hydrological and movement characteristics of Majiagou landslide and identification of key triggering factors through interpretable machine learning

被引：1

作者：

Yao, Wenmin ^{[1
]}

Zhang, Xin ^{[1
]}

Li, Changdong ^{[2
,3
]}

Lv, Yiming ^{[1
]}

Fu, Yu ^{[1
]}

Criss, Robert E. ^{[4
]}

Zhan, Hongbin ^{[5
]}

Yan, Changbin ^{[1
]}

机构：

[1] Zhengzhou Univ, Sch Civil Engn, Zhengzhou 450001, Peoples R China

[2] China Univ Geosci, Fac Engn, Wuhan 430074, Peoples R China

[3] China Univ Geosci, Badong Natl Observat & Res Stn Geohazards, Wuhan 430074, Peoples R China

[4] Washington Univ, Dept Earth & Planetary Sci, St Louis, MO 63130 USA

[5] Texas A&M Univ, Dept Geol & Geophys, College Stn, TX 77843 USA

来源：

BULLETIN OF ENGINEERING GEOLOGY AND THE ENVIRONMENT | 2025年 / 84卷 / 02期

基金：

中国国家自然科学基金;

关键词：

Reservoir landslide; Stabilizing piles; Deformation characteristics; Triggering factor; Interpretable machine learning; 3 GORGES RESERVOIR; FILLING-DRAWDOWN CYCLES; STEP-LIKE LANDSLIDE; DEFORMATION CHARACTERISTICS; DISPLACEMENT PREDICTION; BAIJIABAO LANDSLIDE; NETWORK; MODEL; AREA;

D O I：

10.1007/s10064-025-04116-2

中图分类号：

X [环境科学、安全科学];

学科分类号：

08 ; 0830 ;

摘要：

Variations in reservoir water level and seasonal precipitation have reactivated or accelerated numerous reservoir landslides in the Three Gorges Reservoir (TGR) area in China since its impoundment in 2003. Majiagou landslide, a typical reservoir landslide with stabilizing piles, is affected by the coupling effect of rainfall and reservoir level fluctuations. Monitoring data of nearly 11 years show continuous movement of Majiagou landslide, in contrast to the step-like movements of many landslides in this region. Displacements of the landslide surface and sliding zone are accelerated in rainy seasons accompanied by rapid fluctuations in reservoir water level. A SHAP-XGBoost-based interpretable machine learning method was proposed to identify the key triggering factors of the deformation of Majiagou landslide. The crucial triggering factors vary among different monitoring sites, monitoring periods (e.g., before and after the replacement of monitoring sites), and monitoring intervals. Rainfall makes the most prominent contribution to the displacements of the landslide surface and slip zone. From the front to the rear of Majiagou landslide, the response period of surface deformation to reservoir water level fluctuation gradually lengthens, and the middle and rear parts are more sensitive to the average reservoir water level in the short term. The proposed SHAP-XGBoost method will facilitate deformation prediction, stability evaluation, and the calibration of early warning systems for reservoir landslides.

引用

页数：19