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

Author:

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

Abstract

AbstractThis 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.

Publisher

Springer Science and Business Media LLC

Subject

Management, Monitoring, Policy and Law,Safety Research,Geography, Planning and Development,Global and Planetary Change

Reference85 articles.

1. Aksoy, B., and M. Ercanoglu. 2012. Landslide identification and classification by object-based image analysis and fuzzy logic: An example from the Azdavay region (Kastamonu, Turkey). Computers and GeoSciences 38: 87–98.

2. Allen, R.G., L. Pereira, and D. Raes. 1998. Crop evapotranspiration: Guidelines for computing crop water requirements. FAO irrigation and drainage paper No. 56. Rome: Food and Agriculture Organization (FAO).

3. Araújo, J.R., A.M. Ramos, P.M.M. Soares, R. Melo, S.C. Oliveira, and R.M. Trigo. 2022. Impact of extreme rainfall events on landslide activity in Portugal under climate change scenarios. Landslides 19: 2279–2293.

4. Arnone, E., D. Caracciolo, L.V. Noto, F. Preti, and R.L. Bras. 2016. Modeling the hydrological and mechanical effect of roots on shallow landslides. Water Resources Research 52: 8590–8612.

5. Ba, R.J., L. Wang, W.M. Zhen, Z.L. Li, M.H. Li, Y.J. Liu, H.Y. Ni, and R.G. Xu. 2011. Characteristics and distribution of the geology disasters of the Dadu River in Sichuan, China. Journal of Chengdu University of Technology (Science & Technology Edition) 38: 529–537.

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3