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

• Exploring unlocked landslide displacement mechanisms: A multidimensional perspective. • Assessing influencing factors with diverse analytical methods. • Analyzing smoothed and denoised data with SSA filtering technology. • Understanding simulated and monitored displacement with PSO-GSA-SVR model. 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.

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Publication Details

Journal
Geoscience Frontiers
Published
2024-10-31
DOI
https://doi.org/10.1016/j.gsf.2024.101959
Citations
9
Primary Topic
Landslides and related hazards
Type
article
Field-Weighted Citation Impact
6.39

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article

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

Jiafeng Xiao, Xuekun Xiang, Hongyue Yin, Xiongfeng Wang et al.
9 citations
Geoscience Frontiers
Landslides and related hazards
6.39
article

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

Jiafeng Xiao, Xuekun Xiang, Hongyue Yin, Xiongfeng Wang, Haijia Wen, Junhao Huang
article en
9 citations

Abstract

• Exploring unlocked landslide displacement mechanisms: A multidimensional perspective. • Assessing influencing factors with diverse analytical methods. • Analyzing smoothed and denoised data with SSA filtering technology. • Understanding simulated and monitored displacement with PSO-GSA-SVR model. 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.

Geoscience FrontiersVol. 16(1)
Chongqing Normal University (CN), Chongqing University (CN), Ministry of Natural Resources (CN), Chongqing Institute of Geology and Mineral Resources (CN), Shanghai Harbour Engineering Design & Research Institute (CN)
Ministry of Science and Technology of the People's Republic of China, National Key Research and Development Program of China
Climate action
Openalex Percentile: Top 4%
Landslides and related hazards
6.39
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