Triggering factors and threshold analysis of baishuihe landslide based on the data mining methods
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Triggering factors and threshold analysis of baishuihe landslide based on the data mining methods Fasheng Miao1 · Yiping Wu1 · Linwei Li1 · Kang Liao1 · Yang Xue1 Received: 3 July 2020 / Accepted: 5 November 2020 © Springer Nature B.V. 2020
Abstract The analysis of landslide monitoring data is important to the study and prediction of landslide deformation but is very challenging. In this research, a data mining method combining two-step clustering, Apriori algorithm and decision tree C5.0 model are proposed, and the Baishuihe Landslide in the Three Gorges Reservoir area is taken as the study case. 6 hydrologic factors related to rainfall and reservoir water level are chosen to carry out the data mining analysis. First, 6 hydrologic triggering factors and the deformation rate of the landslide are clustered by the two-step clustering. Then, the Apriori algorithm is used to mine the association rules between triggering factors and deformation rate. A total of 173 association rules are generated based on the data mining, and 20 rules are selected to be analyzed. At last, the decision tree C5.0 model is built to carry out threshold analysis of hydrologic triggering factors. The results show that monthly cumulative rainfall plays an important role in controlling landslide deformation, and 73.9 mm can be regarded as its threshold. Monthly average water level is the second factor to control landslide deformation. While the monthly maximum daily rainfall has no direct control over the acceleration stage of landslide deformation. The data mining method proposed in this paper has a high accuracy in the study of Baishuihe landslide, which could provide a significant basis for the data analysis and prediction of the accumulative landslide in the Three Gorges Reservoir area. Keywords Baishuihe landslide · Three gorges reservoir · Data mining · Two-step clustering · Apriori algorithm · Decision tree C5.0
* Yiping Wu [email protected] Fasheng Miao [email protected] Linwei Li [email protected] Kang Liao [email protected] Yang Xue [email protected] 1
Faculty of Engineering, China University of Geosciences, Wuhan 430074, China
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Natural Hazards
1 Introduction Landslides are one of the worst types of natural disasters, which occur frequently around the world, particularly in mountainous regions (Sassa et al. 2010; Juang et al. 2019). The Three Gorges Reservoir area is in the middle and upper reaches of the Yangtze river. Since the impoundment of water in 2003, the reservoir bank has suffered periodic fluctuation of reservoir water level for a long time, which makes the rock and soil of the slope at the reservoir bank undergo the change of dynamic osmotic pressure repeatedly, thus causing great impact on the surrounding regional geological environment, resulting in the deformation and destruction of the original stable reservoir bank, and leading the reactivation and deformation of many ancient landslides (Tang et al. 2015, 2019). The political, economic, and social status of a large hydropower hu
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