高泽民, 丁明涛, 杨国辉, 等. 2021. 川藏铁路孜热-波密段泥石流灾害危险性评价[J]. 工程地质学报, 29(2): 478-485. doi: 10.13544/j.cnki.jeg.2021-0160.
    引用本文: 高泽民, 丁明涛, 杨国辉, 等. 2021. 川藏铁路孜热-波密段泥石流灾害危险性评价[J]. 工程地质学报, 29(2): 478-485. doi: 10.13544/j.cnki.jeg.2021-0160.
    Gao Zemin, Ding Mingtao, Yang Guohui, et al. 2021. Hazard assessment of debris flow along Zire-Bomi section of Sichuan-Tibet Railway[J]. Journal of Engineering Geology, 29(2): 478-485. doi: 10.13544/j.cnki.jeg.2021-0160.
    Citation: Gao Zemin, Ding Mingtao, Yang Guohui, et al. 2021. Hazard assessment of debris flow along Zire-Bomi section of Sichuan-Tibet Railway[J]. Journal of Engineering Geology, 29(2): 478-485. doi: 10.13544/j.cnki.jeg.2021-0160.

    川藏铁路孜热—波密段泥石流灾害危险性评价

    HAZARD ASSESSMENT OF DEBRIS FLOW ALONG ZIRE-BOMI SECTION OF SICHUAN-TIBET RAILWAY

    • 摘要: 泥石流灾害是青藏高原地区最为发育的灾害类型之一,因其暴发突然、运动过程剧烈和破坏性强的特点而对川藏铁路工程建设和生命财产安全构成一定的威胁。地质灾害危险性评估是防灾减灾管理和防治环节中的有效措施之一,为合理量化线路沿程泥石流灾害危险性空间分布特征,研究以林芝市波密县境内的川藏铁路孜热—波密段为试验区,应用基于贝叶斯优化算法的随机森林和梯度提升树模型对该线路段的泥石流危险性进行定量化计算和危险性区划的判定。模型的输入信息包括172个历史泥石流点和11个特征参数,输出信息为每个预测单元泥石流暴发的危险性概率。最后,利用ROC-AUC方法对两种预测模型进行评估结果的检验。计算结果显示,在TBOR与TBOG模型中,川藏铁路孜然—波密线路段总体的泥石流危险性水平较高,两种模型在较高-高危险性区间内的危险分区比例分别达56.439%和66.580%,对应的灾害点密度分别为最高的12.577处/(102 km2)和12.940处/(102km2)。相比于TBOG模型的ROC-AUC值,TBOR模型的计算结果为0.89,高于TBOR的0.83。因此,TBOR模型具有更好的预测精度。本文的研究成果可为川藏铁路沿线防灾减灾防护工程建设和其他线路段危险性评价提供必要的参考。

       

      Abstract: Debris flow is one of the most developed disaster types in the Tibetan Plateau, and poses a certain threat to the construction of Sichuan-Tibet Railway and the safety of life and property due to its sudden outbreak, violent movement process, and strong destructive characteristics. Geological hazard assessment is part of the effective measures in the management and prevention of disaster prevention and mitigation. For reasonably quantifying the spatial distribution characteristics of debris flow hazard along the railway line, the paper takes the Zire-Bomi section of the Sichuan-Tibet Railway within Linzhi City as the experimental area. We apply the Bayesian optimization algorithm based random forest(TBOR) and gradient boosting tree model(TBOG)to quantify the debris flow hazard values of the route section and identify the hazard levels. The input information of the two models includes 172 historical hazard points and 11 feature parameters. The output information is the outbreak probability of debris flow for each prediction unit. Lastly, the ROC-AUC method is employed to test the evaluation outcomes of the two prediction algorithms. The findings reveal that in the TBOR and TBOG models, the overall debris flow hazard level of the Zire-Bomi line section of the Sichuan-Tibet Railway is relatively high. The proportion of hazard zones inside the high-higher hazard interval of the two models reaches 56.439% and 66.580% respectively, corresponding to the highest hazard point densities of 12.577/(102km2) and 12.940/(102km2)respectively. Compared to the ROC-AUC values derived from the TBOG model, the TBOR model computes 0.89, which is higher than that of TBOR at 0.83. Therefore, the TBOR model has better prediction accuracy. The research findings can provide necessary reference for the construction of disaster prevention and mitigation protection projects along Sichuan-Tibet Railway and the hazard evaluation of other line sections.

       

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