LAPSE:2023.34467
Published Article
LAPSE:2023.34467
Stage Division of Landslide Deformation and Prediction of Critical Sliding Based on Inverse Logistic Function
Liulei Bao, Guangcheng Zhang, Xinli Hu, Shuangshuang Wu, Xiangdong Liu
April 27, 2023
The cumulative displacement-time curve is the most common and direct method used to predict the deformation trends of landslides and divide the deformation stages. A new method based on the inverse logistic function considering inverse distance weighting (IDW) is proposed to predict the displacement of landslides, and the quantitative standards of dividing the deformation stages and determining the critical sliding time are put forward. The proposed method is applied in some landslide cases according to the displacement monitoring data and shows that the new method is effective. Moreover, long-term displacement predictions are applied in two landslides. Finally, summarized with the application in other landslide cases, the value of displacement acceleration, 0.9 mm/day2, is suggested as the first early warning standard of sliding, and the fitting function of the acceleration rate with the volume or length of landslide can be considered the secondary critical threshold function of landslide failure.
Keywords
critical sliding prediction, displacement-time curve, inverse distance weighted, inverse logistic curve, the deformation stage division
Subject
Suggested Citation
Bao L, Zhang G, Hu X, Wu S, Liu X. Stage Division of Landslide Deformation and Prediction of Critical Sliding Based on Inverse Logistic Function. (2023). LAPSE:2023.34467
Author Affiliations
Bao L: Faculty of Engineering, China University of Geosciences, Wuhan 430074, China
Zhang G: Faculty of Engineering, China University of Geosciences, Wuhan 430074, China [ORCID]
Hu X: Faculty of Engineering, China University of Geosciences, Wuhan 430074, China
Wu S: Faculty of Engineering, China University of Geosciences, Wuhan 430074, China [ORCID]
Liu X: Faculty of Engineering, China University of Geosciences, Wuhan 430074, China
Journal Name
Energies
Volume
14
Issue
4
First Page
1091
Year
2021
Publication Date
2021-02-19
Published Version
ISSN
1996-1073
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PII: en14041091, Publication Type: Journal Article
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LAPSE:2023.34467
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doi:10.3390/en14041091
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