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SHALSTAB模型在浙南林溪流域滑坡预测中的应用

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孙强, 张泰丽, 伍剑波, 王赫生, 朱延辉, 韩帅. 2021. SHALSTAB模型在浙南林溪流域滑坡预测中的应用. 华东地质, 42(4): 383-389. doi: 10.16788/j.hddz.32-1865/P.2021.04.003
引用本文: 孙强, 张泰丽, 伍剑波, 王赫生, 朱延辉, 韩帅. 2021. SHALSTAB模型在浙南林溪流域滑坡预测中的应用. 华东地质, 42(4): 383-389. doi: 10.16788/j.hddz.32-1865/P.2021.04.003
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SUN Qiang, ZHANG Taili, WU Jianbo, WANG Hesheng, ZHU Yanhui, HAN Shuai. 2021. Application of shallow landslide stability model to landslide prediction in the Linxi River basin of southern Zhejiang. East China Geology, 42(4): 383-389. doi: 10.16788/j.hddz.32-1865/P.2021.04.003
Citation: SUN Qiang, ZHANG Taili, WU Jianbo, WANG Hesheng, ZHU Yanhui, HAN Shuai. 2021. Application of shallow landslide stability model to landslide prediction in the Linxi River basin of southern Zhejiang. East China Geology, 42(4): 383-389. doi: 10.16788/j.hddz.32-1865/P.2021.04.003
shu

SHALSTAB模型在浙南林溪流域滑坡预测中的应用

  • 中国地质调查局南京地质调查中心, 江苏 南京 210016

  • 基金项目:

    中国地质调查局"浙江丽水地区灾害地质调查（编号：DD20190648）"项目资助。

详细信息
    作者简介: 孙强,1983年生,男,高级工程师,硕士,主要从事环境地质调查及地质灾害勘察、防治工作。Email:huiqiangsun@foxmil.com。

  • 中图分类号: P694

Application of shallow landslide stability model to landslide prediction in the Linxi River basin of southern Zhejiang

  • Nanjing Center, China Geological Survey, Nanjing 210016, Jiangsu, China

    摘要
  • 受台风暴雨影响,浙南林溪流域滑坡频发。针对该区域滑坡规模小、长度与厚度比值大的特点,采用浅层滑坡稳定性模型(SHALSTAB)对潜在滑坡进行了预测,以log(降雨量q/土壤的导水系数T)作为划分标准,结果显示随着log(q/T)值的提高,预测的滑坡区域逐渐扩大,预测捕获率升高的同时,误判率也随之上升。以log(q/T)≤-3.1作为预测滑坡的判别标准,模型效果较好,预测捕获率为62.50%,误判率(17.79%)较低。预测结果显示,滑坡潜在区域主要位于斜坡下部、土体厚度大和坡度陡峭的地区,山体顶部、土体厚度薄和地形平坦的区域斜坡稳定。
    Landslides occurred frequently in the Linxi River basin of southern Zhejiang due to typhoon rainstorm. Shallow landslide stability model (SHALSTAB) is used to predict potential landslides according to the landslides characteristics of small scale and large ratio of length to thickness in this area. Log (rainfall q/soil hydraulic conductivity T) is used as the criterion of potential landslide. Quantitative index analysis shows that with the increase of log(q/T) level, the area of landslides predicted by the model expanded gradually, but the model also increased the misjudgment rate. The model has better prediction effect when log(q/T)=-3.1 is applied as criterion to predict landslide. The capture rate of landslides prediction is 62.50%, the misjudgment rate is 17.79%. The simulation results show that bottom of the hillslope, side of the deep valley and the steep hillslope are the landslide-prone regions. Top of the mountain, and the region with shallow soil mass and flat topography have good stability.
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    • 参考文献(22)
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出版历程
收稿日期:  2020-10-29
修回日期:  2021-07-29

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