Major Progress on Reactivation Mechanism and Early Identification of Ancient Landslides on the Eastern Tibetan Plateau
Abstract
There are a vast number of large-scale ancient landslides in the east Tibetan plateau. However, these landslides have experienced reactivation in recent years and resulted in increasingly serious casualties and economic losses. To study the reactivation mechanism and early identification of ancient landslides on the eastern margin of the Tibetan Plateau, high-resolution remote-sensing interpretation, field survey, interferometric synthetic aperture radar (InSAR) monitoring, laboratory and in situ geotechnical tests, physical modeling tests, and numerical simulations were used, and the main results obtained are as follows. The development and distribution of ancient landslides on the eastern margin of the Tibetan Plateau were clarified, and an efficient identification method was proposed. Reactivation characteristics, triggering factors, and typical genesis patterns were analyzed. Second, the macroscopic mechanical properties of gravelly slip-zone soil and their strength evolution mechanisms at the mesoscale were revealed, and then the strength criterion of gravelly slip-zone soil is improved. Third, combined with typical cases, the reactivation mechanism of ancient landslides under different conditions is simulated and analyzed, and a multistage dynamic evolution model for the reactivation of ancient landslides is established by considering key factors such as geomorphic evolution, coupled endogenic and exogenic geological processes. Finally, an early identification method for ancient landslide reactivation was proposed, enabling rapid determination of the evolutionary stage of ancient landslide reactivation. These findings provide new theoretical and technical support for effectively preventing the risk of reactivation disasters of ancient landslides on the Tibetan Plateau.
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Data Availability Statement
Some or all data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request.
Acknowledgments
This research was supported by the National Natural Science Foundation of China (Nos. 41731287, 42307229, and 41941017) and the China Geological Survey Projects (No. DD20221816). The authors express their gratitude to Professor Guo Changbao and Professor Yao Xin for their help in field investigations, experiments, and data processing. The figures were prepared using ArcGIS 10.7 and CorelDRAW X7 software.
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Natural Hazards Review
Volume 25 • Issue 4 • November 2024
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© 2024 American Society of Civil Engineers.
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Received: Jan 15, 2024
Accepted: May 28, 2024
Published online: Jul 30, 2024
Published in print: Nov 1, 2024
Discussion open until: Dec 30, 2024
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