A new approach to temporal modelling for landslide hazard assessment using an extreme rainfall induced-landslide index
A new approach to temporal modelling for landslide hazard assessment using an extreme rainfall induced-landslide index
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DOI：
10.1016/j.enggeo.2016.10.006
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发表时间：
2016-12
影响因子：
7.4
通讯作者：
Nikhil Nedumpallile Vasu;Seung-Rae Lee;A. Pradhan;Yun-Tae Kim;Sinhang Kang;Deuk-Hwan Lee
中科院分区：
文献类型：
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作者：
Nikhil Nedumpallile Vasu;Seung-Rae Lee;A. Pradhan;Yun-Tae Kim;Sinhang Kang;Deuk-Hwan Lee
由于气候变化，韩国的极端降雨事件日益增多，导致占国土面积70%的山区出现浅层滑坡和浅层滑坡引发的泥石流。这些灾难性的、由重力驱动的过程每年给政府造成数十亿韩元的损失和随之而来的死亡。观测到的最常见的滑坡类型是发生在1-3 m深度的浅层滑坡，它可能动员成灾难性的泥石流。采用基于不同尺度阶段的滑坡预警系统对两种滑坡类型的潜在区域进行预测。目前的研究主要集中在区域或中等尺度的滑坡危害评价，需要基于实时降雨，对这两种类型的滑坡进行空间演化的滑坡危害图的绘制。然而，由于缺乏完整的滑坡清查数据，促使了作为滑坡灾害独立组成部分的时空模型的发展。大多数现有的时间评价方案传统上基于递归概念，没有考虑土壤因素，由于不能考虑实时降雨，因此不适合纳入滑坡预警系统。这推动了一种新的概率时间模型的发展，称为极端降雨诱发滑坡指数。在江原道通过使用四个因素的逻辑回归开发了概率指数；即连续降雨量、前20天降雨量、饱和水力导率、库容。该模型的训练曲线和验证曲线的AUC值分别为82%和91%，具有良好的统计指标性能。此外，利用逻辑回归分析，以江原道德jeok-ri Creek为例，建立了一个高性能敏感性模型（训练和验证AUC值分别为96%和94%）。在假定危害成分相互独立的前提下，通过两种模型的联合概率建立动态危害指数（DHI）。利用DHI研究了2006年7月德积里河极端降雨诱发滑坡事件的滑坡危险性演变。
An ever-increasing trend of extreme rainfall events in South Korea due to climate change is causing shallow landslides and shallow landslide induced debris flows in the mountains that cover 70% of the total land area of the nation. These catastrophic, gravity-driven processes cost the government several billion won in losses, and attendant fatalities, every year. The most common type of landslide observed is the shallow landslide occurring at 1–3 m depth, which may mobilize into a catastrophic debris flow. A landslide early warning system encompassing different scale-based stages is used to predict potential areas for both the landslide types. Current study focusing on the first stage landslide hazard assessment at regional or medium scale requires the development of spatially evolving landslide hazard maps for both types of landslides based on the real-time rainfall. However, lack of complete landslide inventory data motivates the development of temporal and spatial models as independent components of the landslide hazard. Most of the existing temporal assessment schemes traditionally rooted in recurrence-based concepts does not consider soil factors and are not suitable to be incorporated in to the landslide early warning system since real-time rainfall cannot be considered. This motivated the development of a new probabilistic temporal model termed the extreme rainfall-induced landslide index. The probabilistic index was developed in Gangwon Province through a logistic regression using four factors; namely, continuous rainfall, 20-days antecedent rainfall, saturated hydraulic conductivity, and storage capacity. The developed model exhibited high area under the curve (AUC) values of 82% and 91% obtained for the training and validation curves, exhibiting good performance of the statistical index. Also, a high performance susceptibility model (training and validation AUC values of 96% and 94%, respectively) was developed using a logistic regression analysis, for Deokjeok-ri Creek, located in Gangwon province. Assuming the independence of the hazard components, a dynamic hazard index (DHI) was established through a joint probability of both the well validated models. The DHI was used to study the evolution of landslide hazard for the July 2006 extreme rainfall-induced landslide events in Deokjeok-ri Creek.