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基于LSTM_TCN模型的降雨型滑坡时间概率预测及气象预警建模

赵玉 陈丽霞 梁梦姣

赵玉, 陈丽霞, 梁梦姣. 基于LSTM_TCN模型的降雨型滑坡时间概率预测及气象预警建模[J]. 地质科技通报, 2024, 43(2): 201-214. doi: 10.19509/j.cnki.dzkq.tb20220657
引用本文: 赵玉, 陈丽霞, 梁梦姣. 基于LSTM_TCN模型的降雨型滑坡时间概率预测及气象预警建模[J]. 地质科技通报, 2024, 43(2): 201-214. doi: 10.19509/j.cnki.dzkq.tb20220657
ZHAO Yu, CHEN Lixia, LIANG Mengjiao. Temporal probability prediction and meteorological early warning modeling of rainfall-induced landslide based on LSTM_TCN model[J]. Bulletin of Geological Science and Technology, 2024, 43(2): 201-214. doi: 10.19509/j.cnki.dzkq.tb20220657
Citation: ZHAO Yu, CHEN Lixia, LIANG Mengjiao. Temporal probability prediction and meteorological early warning modeling of rainfall-induced landslide based on LSTM_TCN model[J]. Bulletin of Geological Science and Technology, 2024, 43(2): 201-214. doi: 10.19509/j.cnki.dzkq.tb20220657

基于LSTM_TCN模型的降雨型滑坡时间概率预测及气象预警建模

doi: 10.19509/j.cnki.dzkq.tb20220657
基金项目: 

国家自然科学基金项目 41877525

详细信息
    作者简介:

    赵玉, E-mail: cugzhaoyu@cug.edu.cn

    通讯作者:

    陈丽霞, E-mail: lixiachen@cug.edu.cn

  • 中图分类号: P642.22

Temporal probability prediction and meteorological early warning modeling of rainfall-induced landslide based on LSTM_TCN model

More Information
  • 摘要:

    如果滑坡发生时间信息不完备则会导致滑坡与降雨时序关系错误, 以至于降雨阈值模型精度偏低。以重庆市万州区1995-2015年所发生的降雨型滑坡为研究对象, 将区内严重缺失历史滑坡时间信息的恒合乡作为验证区, 提出了一种基于长短时记忆网络(LSTM)融合时域卷积网络(TCN)的模型方法。该方法通过模拟降雨型滑坡发生时间与降雨量间的非线性关系, 重建降雨型滑坡事件在某日发生的时间概率。将重建时间信息后的滑坡事件进行了验证与筛选, 应用于累积有效降雨量-降雨历时曲线的合理划分, 构建了滑坡气象预警模型。结果表明, 本方法所预测滑坡时间概率平均值达到90.33%, 高于人工神经网络(ANN)(71.17%)、LSTM(72.75%)和TCN(86.91%)的概率。利用预测概率高于90%的滑坡, 将验证区18个时间信息扩充至201个。基于扩充时间信息后的滑坡数据所构建的气象预警模型比仅利用历史滑坡事件具有更合理的预警分级, 在严重警告级别上有效预警率提升了42.86%。结果说明该方法可弥补野外调查中灾害数据时间信息不足的问题, 为降雨型滑坡气象预警工作提供数据支撑, 由此提高气象预警准确率。

     

  • 图 1  基于深度学习模型构建降雨型滑坡气象预警模型的流程图

    Figure 1.  Flow chart of the deep learning model for predicting the meteorological early warning modeling in landslide

    图 2  LSTM_TCN模型的网络结构

    Figure 2.  Structure of the LSTM_TCN model

    图 3  研究区概况及地质灾害分布图

    Figure 3.  Overview of the study area and geological hazards

    图 4  1995-2015年万州区的当日降雨量和灾害发生日

    Figure 4.  Daily rainfall and geological hazard occurrence dates in Wanzhou District, 1995 to 2015

    图 5  LSTM_TCN模型在不同训练集上损失值和预测准确率的变化曲线

    Figure 5.  Variation curves of loss values and predicted accuracy of the LSTM_TCN model on different training datasets

    图 6  4种模型预测灾害事件的ROC曲线

    Figure 6.  ROC curves of four models predicting geological hazard events

    图 7  2012年1月-2020年8月恒合乡日降雨量和LSTM_TCN模型预测的滑坡在某日发生的时间概率

    Figure 7.  Daily rainfall and the geological hazard probability predicted by the LSTM_TCN model of Henghe Township from January 2012 to August 2020

    图 8  LSTM_TCN模型预测灾害事件的频率直方图(a)和筛选图(b)

    Figure 8.  LSTM_TCN model for predicting geological hazard events: Histogram (a) and filter diagram (b)

    图 9  降雨阈值曲线图

    a.基于万州区历史滑坡事件; b.基于恒合乡历史滑坡事件; c.基于有效扩充后的滑坡事件

    Figure 9.  Rainfall threshold curve

    图 10  气象预警模型有效率混淆矩阵对比

    a.基于历史滑坡事件划分的预警等级; b.基于扩充滑坡事件划分的预警等级。$ \frac{1}{14.3 \%}$.1代表滑坡灾害个数;14.3%代表有效预警率

    Figure 10.  Comparison of the efficient confusion matrix of meteorological early warning model

    表  1  验证区恒合乡降雨型灾害调查汇总

    Table  1.   Summary of rainfall-induced geological hazard in Henghe Township

    编号 灾害名称 发生时间 编号 灾害名称 发生时间 编号 灾害名称 发生时间
    1 向东村崩塌 2012/07/12 15 李子树崩塌 2019/06/29
    2020/07/05
    29 县道拐角大滑坡 2020/07/09
    2 王爷庙桥崩塌 2013/07/19 16 恒一村崩塌 2020/07/07 30 县道拐角泥滑坡 2020/07/14
    3 关家坪崩塌 2015/03/20 17 崩塌 2020/07/07 31 入城要道切坡滑坡 2020/07/13
    4 黄显村2号崩塌 2015/04/19 18 崩塌 2020/07/09 32 乡道泥滑坡 2020/07/13
    5 张氏沟崩塌 2015/05/29 19 马家坪滑坡 2020/7/7 33 乡道崩坡积滑坡 2020/06/22
    6 黄显村1号崩塌 2015/06/17 20 李家坎滑坡 2020/7/7 34 要道宽滑坡 2020/07/09
    7 汪家岭Ⅰ号崩塌 2015/06/17 21 下石坝滑坡 2020/7/17 35 三拐口滑坡 2020/07/13
    8 大河坪崩塌 2015/06/17 22 黄草坪滑坡 2020/07/07 36 北岩质滑坡 2020/07/14
    9 双河口-黄岭庄Ⅰ号 2015/07/15 23 三组滑坡1 2020/07/02 37 石桶寨滑坡 2020/07/13
    10 先锋村 2020/07/04 24 三组滑坡2 2020/07/02 38 石桶寨岩质滑坡 2020/07/9
    11 深沟子崩塌 2020/07/05 25 谯家坪滑坡 2020/07/05 39 先锋村滑坡 2020/06/22
    12 崩塌 2020/07/05 26 玉都村滑坡 2020/07/02 40 先锋东滑坡 2020/07/05
    13 危岩段 2020/07/05 27 杉木冲滑坡 2020/07/06 41 衫木冲滑坡 2020/07/05
    14 崩塌 2020/07/05 28 县道滑坡 2020/07/05 42 道路滑坡 2020/07/05
    下载: 导出CSV

    表  2  不同降雨系数和累积有效降雨量与滑坡的相关性

    Table  2.   Correlation of different rainfall intensity factors and cumulative effective rainfall with landslides

    a R0 E1 E2 E3 E4 E5 E6 E7 E8 E9
    相关系数
    0.4 0.620 0.674 0.659 0.636 0.626 0.622 0.621 0.620 0.620 0.620
    0.5 0.620 0.676 0.676 0.653 0.635 0.627 0.623 0.621 0.620 0.620
    0.6 0.620 0.675 0.687 0.675 0.653 0.639 0.631 0.626 0.624 0.622
    0.7 0.620 0.673 0.688 0.697 0.681 0.661 0.648 0.640 0.634 0.629
    0.8 0.620 0.668 0.679 0.706 0.711 0.696 0.681 0.669 0.659 0.651
    0.9 0.620 0.663 0.659 0.684 0.709 0.710 0.710 0.710 0.706 0.700
    1.0 0.620 0.656 0.632 0.635 0.637 0.600 0.565 0.535 0.514 0.496
    注:a.有效降雨系数;R0.当日降雨量;E1~E9.前1~9 d累积有效降雨量
    下载: 导出CSV

    表  3  4种模型预测结果的对比

    Table  3.   Comparison of prediction results of four models

    模型名称 ACC/% MAE RMSE
    ANN模型 84.63 0.125 0.106
    LSTM模型 90.29 0.065 0.056
    TCN模型 90.85 0.047 0.042
    LSTM_TCN模型 92.37 0.025 0.019
    ACC.准确率;MAE.平均绝对误差; RMSE.均方根误差
    下载: 导出CSV

    表  4  4种模型预测滑坡在某日发生的时间概率对比

    Table  4.   Comparison of the probability of landslide occurrence on a certain day predicted by the four models

    发生时间 灾害个数 ANN LSTM TCN LSTM_TCN
    2012/07/12 1 0.904 1 0.898 3 0.975 4 0.939 6
    2015/06/17 3 0.878 1 0.886 5 0.900 4 0.931 6
    2020/06/22 2 0.869 3 0.866 5 0.899 9 0.918 2
    2020/07/04 1 0.936 9 0.856 6 0.925 8 0.949 8
    2020/07/05 10 0.916 8 0.918 6 0.947 0 0.955 7
    2020/07/06 1 0.923 6 0.801 8 0.941 2 0.968 9
    2020/07/07 5 0.892 3 0.911 0 0.925 6 0.977 5
    2020/07/09 3 0.907 6 0.890 7 0.925 6 0.988 7
    平均值 0.711 7 0.727 5 0.869 1 0.903 3
    下载: 导出CSV

    表  5  基于不同数据划分的降雨阈值方程

    Table  5.   Rainfall threshold equation based on different data

    阈值线 万州区滑坡 恒合乡滑坡 恒合乡扩充滑坡
    20%阈值 E=17.13D0.136 8 E=28.74D0.264 6 E=32.35D0.181 5
    40%阈值 E=24.65D0.136 8 E=34.61D0.264 6 E=37.97D0.181 5
    60%阈值 E=34.43D0.136 8 E=44.53D0.264 6 E=44.56D0.181 5
    80%阈值 E=47.45D0.136 8 E=52.62D0.264 6 E=53.82D0.181 5
    注:D为降雨历时, d; E为累计有效降雨量, mm
    下载: 导出CSV

    表  6  降雨阈值模型的预警等级和恒合乡历史灾害实际风险等级对比

    Table  6.   Comparison between the warning levels of the rainfall threshold model and the actual risk levels of historical hazards in Henghe Township

    历史灾害事件 实际风险等级 实际所处预警等级 基于恒合乡历史灾害阈值模型预警等级 基于扩充后恒合乡灾害阈值模型预警等级
    发生时间 滑坡灾害个数
    2012/07/12 1 极高 严重警告 严重警告 严重警告
    2015/06/17 3 警告 特别注意 警告
    2020/06/22 2 极高 严重警告 警告 严重警告
    2020/07/04 1 极高 严重警告 警告 严重警告
    2020/07/05 10 极高 严重警告 严重警告 严重警告
    2020/07/06 1 极高 严重警告 警告 严重警告
    2020/07/07 5 极高 严重警告 严重警告 严重警告
    2020/07/09 3 极高 严重警告 特别注意 警告
    下载: 导出CSV

    表  7  滑坡气象预警各等级有效预警率对比

    Table  7.   Comparison of effective warning rates for different levels of landslide meteorological warning systems

    滑坡预警等级 注意 特别注意 警告 严重警告
    阈值线 20%阈值 40%阈值 60%阈值 80%阈值
    滑坡风险等级 极高
    历史有效预警率/% 33.33 50 0 42.86
    扩充后有效预警率/% 50 100 100 85.71
    下载: 导出CSV
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  • 收稿日期:  2022-11-24
  • 录用日期:  2023-01-13
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