Derivation of Stability Equation and Early Warning Value of Landslides on Gentle Piedmont Slopes in the Ningzhen Area of China
Abstract
There are a series of gentle Piedmont slopes with a unique special stratigraphic structure in Ningzhen area of China, which manifest as clay on the surface and the underlying being primarily gravel, exhibiting a binary structure similar to fluvial facies. The number of landslides has increased significantly on gentle Piedmont slopes in this area in recent years due to an increase in extreme rainfall events. Medium to large creeping landslides are dominant, and the sliding surface is between the clay and gravel layers. The main reason is the formation of a water cushion effect due to the unique stratigraphic structure. In this paper, based on previous research, we conducted a model test to verify the influence of the water cushion effect on gentle Piedmont slopes. Meanwhile, we derived a stability equation based on the static equilibrium for gentle Piedmont slopes under three conditions and proposed two methods to derive an early warning value of the pressure head. The rationality of the early warning value was verified by comparing it with measurements. The research results provide important theoretical and technical guidance for early warning and prediction of landslides on gentle Piedmont slopes.
Practical Applications
The stability equation of landslides is crucial in adequately mitigating hazards, which can provide guidelines for landslide prone areas to avoid hazards in the future. Therefore, landslide warning and prediction is of the utmost significance to ensure the safety of human life, mitigate the negative impacts on the economy, and prevent landslide hazards in gentle Piedmont slopes. Government agencies, policymakers, local authorities, and urban planners can use stability equations and early warning values to plan effective landslide monitoring and prevention measures, and make wise decisions on land-use zoning and development. By identifying areas with high landslide susceptibility through early warning values, constructing buildings and engaging in human activities in hazardous zones can be avoided, reducing the risk of damage and loss during potential landslide events. In addition, landslide warning and prediction play a crucial role in disaster risk management of landslides in gentle Piedmont slopes. Authorities can use these warning values to prioritize areas for early measures. Residents can benefit from the results by being made aware of landslide-prone areas on their property. Consequently, this study is a scientific basis and technical support for the early warning and prediction of landslides on gentle Piedmont slopes in the Ningzhen area, China.
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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. Data generated in this study include the physical, mechanical properties, and landslide strength with each landslide points; onsite monitoring data of pore pressure with each landslide points; monitoring data for model test, including pore pressure and vertical displacement; and all derivation data of landslide early warning value.
Acknowledgments
Fieldwork was supported by the Jiangsu Geological Engineering Survey Institute. The authors acknowledge the help of the graduate students in the field survey, including Chengliang Li, Zhuangzhuang Hou, Chao Li, Conghui Dong, Chaolin Peng, and Xiao Zhang. This study was supported by the National Natural Science Foundation of China (No. 42077232), the Intelligent Monitoring Research Center of Geological Environment Engineering in Jiangsu Province (No. 2021-ZNJKJJ-05), and the Science and Technology Planning Project of Anhui Provincial Department of Housing and Urban-Rural Development (No. 2022-YF017).
Author contributions: Liangchen Yu: Writing–original draft preparation, Writing–review and editing, Methodology. Shulan Guo: Writing–original draft preparation, Methodology. Changhong Yan: Writing–original draft preparation. Yang Liu: Writing–review and editing, Data collection and analysis. Jingzhong Tan: Investigation. Chenghua Xu: Investigation. Pengbin Wang: Data collection and analysis. Jiabao Li: Data collection and analysis.
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Published In
Natural Hazards Review
Volume 25 • Issue 3 • August 2024
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© 2024 American Society of Civil Engineers.
History
Received: Sep 4, 2023
Accepted: Jan 4, 2024
Published online: Mar 25, 2024
Published in print: Aug 1, 2024
Discussion open until: Aug 25, 2024
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