Estimation of Shallow Landslide Susceptibility Incorporating the Impacts of Vegetation on Slope Stability

Hu Jiang; Qiang Zou; Bin Zhou; Yao Jiang; Junfang Cui; Hongkun Yao; Wentao Zhou

doi:10.1007/s13753-023-00507-9

Volume 14 Issue 4

Sep. 2023

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Hu Jiang, Qiang Zou, Bin Zhou, Yao Jiang, Junfang Cui, Hongkun Yao, Wentao Zhou. Estimation of Shallow Landslide Susceptibility Incorporating the Impacts of Vegetation on Slope Stability[J]. International Journal of Disaster Risk Science, 2023, 14(4): 618-635. doi: 10.1007/s13753-023-00507-9

Citation:

Hu Jiang, Qiang Zou, Bin Zhou, Yao Jiang, Junfang Cui, Hongkun Yao, Wentao Zhou. Estimation of Shallow Landslide Susceptibility Incorporating the Impacts of Vegetation on Slope Stability[J]. International Journal of Disaster Risk Science, 2023, 14(4): 618-635. doi: 10.1007/s13753-023-00507-9

Citation:

Hu Jiang, Qiang Zou, Bin Zhou, Yao Jiang, Junfang Cui, Hongkun Yao, Wentao Zhou. Estimation of Shallow Landslide Susceptibility Incorporating the Impacts of Vegetation on Slope Stability[J]. International Journal of Disaster Risk Science, 2023, 14(4): 618-635. doi: 10.1007/s13753-023-00507-9

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Estimation of Shallow Landslide Susceptibility Incorporating the Impacts of Vegetation on Slope Stability

doi: 10.1007/s13753-023-00507-9

Hu Jiang^1,3,
Qiang Zou^{1,2
,
,},
Bin Zhou^1,3,
Yao Jiang¹,
Junfang Cui¹,
Hongkun Yao^1,3,
Wentao Zhou^1,3

1. Key Laboratory of Mountain Hazards and Earth Surface Process, Institute of Mountain Hazards and Environment(IMHE), Chinese Academy of Sciences(CAS), Chengdu, 610041, China;
2. China-Pakistan Joint Research Center on Earth Sciences, Islamabad, 45320, Pakistan;
3. University of Chinese Academy of Sciences, Beijing, 100049, China

Funds:

This research was supported by the Strategic Priority Research Program of the Chinese Academy of Sciences (Grant No. XDA23090303), the National Natural Science Foundation of China (Grant No. 42171085), the Light of West China Program of the Chinese Academy of Sciences (Grant No. xbzg-zdsys-202104), and the Key R&D Project of Sichuan Provincial Department of Science and Technology (Grant No. 2023YFS0434).

Accepted Date: 2023-08-20
Publish Date: 2023-09-07

Abstract

Abstract

This study aimed to develop a physical-based approach for predicting the spatial likelihood of shallow landslides at the regional scale in a transition zone with extreme topography. Shallow landslide susceptibility study in an area with diverse vegetation types as well as distinctive geographic factors (such as steep terrain, fractured rocks, and joints) that dominate the occurrence of shallow landslides is challenging. This article presents a novel methodology for comprehensively assessing shallow landslide susceptibility, taking into account both the positive and negative impacts of plants. This includes considering the positive effects of vegetation canopy interception and plant root reinforcement, as well as the negative effects of plant gravity loading and preferential flow of root systems. This approach was applied to simulate the regional-scale shallow landslide susceptibility in the Dadu River Basin, a transition zone with rapidly changing terrain, uplifting from the Sichuan Plain to the Qinghai–Tibet Plateau. The research findings suggest that: (1) The proposed methodology is effective and capable of assessing shallow landslide susceptibility in the study area; (2) the proposed model performs better than the traditional pseudo-static analysis method (TPSA) model, with 9.93% higher accuracy and 5.59% higher area under the curve; and (3) when the ratio of vegetation weight loads to unstable soil mass weight is high, an increase in vegetation biomass tends to be advantageous for slope stability. The study also mapped the spatial distribution of shallow landslide susceptibility in the study area, which can be used in disaster prevention, mitigation, and risk management.
- Physical-based model,
- Qinghai-Tibet Plateau,
- Shallow landslide,
- Susceptibility analysis,
- Vegetation effect

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References(85)

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