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台风-非台风降雨型滑坡的多时段临界雨量值预测模型

栗倩倩 史绪山 柴波 王伟

栗倩倩, 史绪山, 柴波, 王伟. 台风-非台风降雨型滑坡的多时段临界雨量值预测模型[J]. 地质科技通报, 2022, 41(2): 267-273. doi: 10.19509/j.cnki.dzkq.2021.0076
引用本文: 栗倩倩, 史绪山, 柴波, 王伟. 台风-非台风降雨型滑坡的多时段临界雨量值预测模型[J]. 地质科技通报, 2022, 41(2): 267-273. doi: 10.19509/j.cnki.dzkq.2021.0076
Li Qianqian, Shi Xushan, Chai Bo, Wang Wei. Multiduration critical rainfall prediction model for typhoons and non-typhoon rainfall landslides[J]. Bulletin of Geological Science and Technology, 2022, 41(2): 267-273. doi: 10.19509/j.cnki.dzkq.2021.0076
Citation: Li Qianqian, Shi Xushan, Chai Bo, Wang Wei. Multiduration critical rainfall prediction model for typhoons and non-typhoon rainfall landslides[J]. Bulletin of Geological Science and Technology, 2022, 41(2): 267-273. doi: 10.19509/j.cnki.dzkq.2021.0076

台风-非台风降雨型滑坡的多时段临界雨量值预测模型

doi: 10.19509/j.cnki.dzkq.2021.0076
基金项目: 

国家自然科学基金项目 41702304

国家自然科学基金项目 41877253

详细信息
    作者简介:

    栗倩倩(1998-), 女, 现正攻读环境科学与工程专业硕士学位, 主要从事岩土-水文-生态耦合过程及作用机制研究工作。E-mail: qianli@cug.edu.cn

    通讯作者:

    柴波(1981-), 男, 教授, 博士生导师, 主要从事岩土工程和环境地质方面的教学与研究工作。E-mail: chaibo@cug.edu.cn

  • 中图分类号: P642.22

Multiduration critical rainfall prediction model for typhoons and non-typhoon rainfall landslides

  • 摘要: 统计确定临界降雨量是滑坡早期预警常用的方法。东南沿海地区台风暴雨不同于一般降雨, 常引发滑坡灾害, 从而威胁沿海地区人民生命财产安全。为了建立台风和非台风降雨型滑坡临界降雨量预测模型, 以浙江丽水市为例, 基于2010-2020年台风暴雨、非台风降雨诱发滑坡与降雨量的统计, 构建了丽水市滑坡发生概率和有效降雨量的关系, 提出了多时长临界降雨量预测模型, 并开展了台风和非台风降雨型滑坡预测模型结果的对比分析。结果表明, 非台风降雨与台风暴雨之间雨型和雨量差异是导致丽水市内2类降雨滑坡预测模型差异的主要原因; 以多时长预测模型确定的临界雨量值法和有效降雨天数更加符合丽水市降雨型滑坡的预测预报, 且预测精度相比于传统相关性分析法更高。研究成果对于开发区域降雨型滑坡预测模型具有理论意义, 对我国东南沿海地区汛期滑坡早期预警具有重要实际意义。

     

  • 图 1  相邻天数临界降雨线间距Hi(图中物理量的含义见正文)

    Figure 1.  Critical rain line spacing Hi

    图 2  丽水市2015-2020年滑坡灾害分布图

    Figure 2.  Distribution of landslide locations in Lishui City from 2015 to 2020

    图 3  两次典型台风过境丽水市日均雨量柱状图

    Figure 3.  Histogram of average daily rainfall of typical typhoons passing through Lishui City

    图 4  2015-2020年降雨型滑坡发生前8 d日均雨量

    Figure 4.  Average daily rainfall in the 8 days before rainfall-induced landslides from 2015 to 2020

    图 5  多时长非台风降雨型滑坡临界降雨量

    Figure 5.  Multi-duration critical rainfall for normal rainfall-induced landslides

    图 6  多时长台风降雨型滑坡临界降雨量

    Figure 6.  Multiduration critical rainfall for typhoon rainfall-induced landslides

    图 7  临界雨值线间距Hi的变化

    Figure 7.  Change in the distance of the critical rainfall line spacing Hi

    图 8  降雨型滑坡事件的累积降雨量变化

    Figure 8.  Change in the cumulative rainfall for rainfall-induced landslide events

    表  1  2010-2020年部分非台风降雨型滑坡事件的降雨数据

    Table  1.   Rainfall data of some normal rainfall-induced landslide events in 2010-2020

    日期 R0/mm R1/mm R2/mm R3/mm R4/mm R5/mm R6/mm R7/mm R8/mm 是否发生
    2012-05-05 63.10 23.40 8.90 5.50 0 0 0.10 10.90 0
    2014-06-24 57.20 88.50 66.70 0.70 9.10 0.30 20.70 3 0
    2015-08-09 46.47 63.51 14.09 0.37 0 0 0 0 0
    2016-05-08 16.17 14.35 23.82 24.54 20.13 0 37.18 13.01 0
    2020-07-18 0.03 0.10 11.00 4.78 0.11 0.12 0.04 0.60 23.38
    下载: 导出CSV

    表  2  2015-2020年部分台风降雨型滑坡事件的降雨数据

    Table  2.   Rainfall data of some typhoon rainfall-induced landslide events from 2015 to 2020

    日期 R0/mm R1/mm R2/mm R3/mm R4/mm R5/mm R6/mm R7/mm R8/mm 是否发生
    2015-08-09 38.71 62.84 14.18 0.07 0 0 0 0 0
    2016-09-15 76.94 17.91 8.18 2.74 36.25 10.45 1.56 0.91 3.36
    2019-08-10 28.79 38.57 4.31 0.07 0.86 0.08 1.14 3.90 0.01
    2020-08-04 75.54 7.23 0.14 0 0 0.45 0.20 0.07 2.06
    下载: 导出CSV

    表  3  累积降雨量与降雨型滑坡发生相关性

    Table  3.   Correlation between accumulated rainfall and rainfall-induced landslides

    累计降雨因子 Q0 Q1 Q2 Q3 Q4 Q5 Q6 Q7 Q8
    非台风降雨型滑坡 Pearson相关 0.450** 0.453** 0.485** 0.479** 0.443** 0.441** 0.440** 0.424** 0.415**
    台风型滑坡 Pearson相关 0.507** 0.532** 0.482** 0.487** 0.534** 0.470** 0.485** 0.485** 0.481**
    注:**表示在0.01显著性水平下,相关性显著
    下载: 导出CSV

    表  4  模型预测分类

    Table  4.   Classification of model prediction

    实际统计值 非台风降雨型滑坡 模型预测值 非台风降雨型滑坡
    不发生 发生 正确百分比/% 不发生 发生 正确百分比/%
    不发生20 19 1 95.0 不发生6 6 0 100.0
    发生26 3 23 88.5 发生7 1 6 85.7
    综合 91.3 92.3
    注:分界值为0.500
    下载: 导出CSV
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