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Estimation of Shallow Landslide Susceptibility Incorporating the Impacts of Vegetation on Slope Stability
International Journal of Disaster Risk Science ( IF 4 ) Pub Date : 2023-09-07 , DOI: 10.1007/s13753-023-00507-9
Hu Jiang , Qiang Zou , Bin Zhou , Yao Jiang , Junfang Cui , Hongkun Yao , Wentao Zhou

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.



中文翻译:

考虑植被对边坡稳定性影响的浅层滑坡敏感性估计

本研究旨在开发一种基于物理的方法来预测极端地形过渡区区域尺度浅层滑坡的空间可能性。在植被类型多样以及主导浅层滑坡发生的独特地理因素(如陡峭地形、裂隙岩石和节理)的地区进行浅层滑坡敏感性研究具有挑战性。本文提出了一种综合评估浅层滑坡敏感性的新方法,同时考虑了植物的积极和消极影响。这包括考虑植被冠层拦截和植物根系加固的积极影响,以及植物重力载荷和根系优先流动的消极影响。该方法用于模拟大渡河流域的区域尺度浅层滑坡敏感性,大渡河流域是一个地形快速变化的过渡带,从四川平原隆起到青藏高原。研究结果表明:(1)所提出的方法是有效的,能够评估研究区浅层滑坡的敏感性;(2)所提出的模型比传统的伪静态分析方法(TPSA)模型表现更好,精度提高了9.93%,曲线下面积提高了5.59%;(3)当植被重量荷载与不稳定土体重量之比较高时,植被生物量的增加往往有利于边坡的稳定。该研究还绘制了研究区浅层滑坡敏感性的空间分布,

更新日期:2023-09-08
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