Prediction of river damming susceptibility by landslides based on a logistic regression model and InSAR techniques: A case study of the Bailong River Basin, China
Prediction of river damming susceptibility by landslides based on a logistic regression model and InSAR techniques: A case study of the Bailong River Basin, China
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DOI：
10.1016/j.enggeo.2022.106562
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发表时间：
2022-02
影响因子：
7.4
通讯作者：
Jiacheng Jin;Guan Chen;Xing-min Meng;Yi Zhang;W. Shi;Yuanxi Li;Yunpeng Yang;Wanyu Jiang
中科院分区：
文献类型：
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作者：
Jiacheng Jin;Guan Chen;Xing-min Meng;Yi Zhang;W. Shi;Yuanxi Li;Yunpeng Yang;Wanyu Jiang
滑坡坝的空间成坝概率评价是滑坡坝风险管理的重要组成部分，也是一个具有挑战性的问题。在这项研究中，我们开发了一种新的方法来评估河流筑坝敏感性的活动滑坡和不稳定的斜坡（ALUSs），它结合了逻辑回归模型与时间序列干涉合成孔径雷达（干涉合成孔径雷达）技术。该方法应用于白龙江流域，在青藏高原，中国东部边缘。利用历史筑坝和非筑坝滑坡数据，建立了基于Logistic回归模型的滑坡风险评价模型。刀切分析表明，最显着的因素控制河流筑坝的敏感性是山谷宽度，滑坡体积，内部救济和河流流量，从显着性降序。利用干涉合成孔径雷达技术对70个ALUS进行了探测，并利用体积-面积经验幂律关系对ALUS的体积进行了预测。对这些不稳定性进行了筑坝敏感性评价，结果表明，其中18个不稳定性具有较高或极高的筑坝可能性。4个体积> 107 m3的活动滑坡被发现容易形成完全阻塞条件，如通过形态阻塞指数（MOI）所识别的。最后，以近期两个拦河工程为例，验证了该方法的预测能力，预测结果与实际情况吻合较好。该方法可为白龙江流域及类似高寒地区滑坡筑坝的早期识别和危险性评价提供参考。
Although a fundamental part of landslide dam risk management, the evaluation of the spatial probability of dam formation is a challenging problem. In this study, we developed a new method for evaluating the river damming susceptibility of active landslides and unstable slopes (ALUSs), which combines a logistic regression model with time series Interferometry Synthetic Aperture Radar (InSAR) techniques. The approach is applied in the Bailong River Basin, on the eastern edge of the Qinghai-Tibet Plateau, China. We established a primary assessment model using historical damming and non-damming landslide data based on a logistic regression model. Jack-knife analysis showed that the most significant factors controlling river damming susceptibility were valley width, landslide volume, internal relief, and river discharge, in order of decreasing significance. Seventy ALUSs were detected by the InSAR technique and their volumes were predicted using a Volume–Area empirical power-law relationship. The river damming susceptibility of these instabilities was assessed and the results show that 18 of them have a high or very high probability of river damming. Four active landslides with volumes >107m3were found to be prone to forming complete blockage conditions, as identified by the Morphological Obstruction Index (MOI). The predictive ability of the methodology was tested using two recent river damming cases and the prediction results were in good agreement with reality. Our approach can potentially help in the early identification and hazard assessment of landslide damming in the Bailong River Basin and similar alpine areas.