Abstract

Understandings of reinforcement mechanisms of landslide-stabilizing pile system are important for long-term safety of reservoir landslides installed piles. The paper proposes a framework to study deformation response and identify triggering factors for landslide–pile system by using geographic detector technology and uncertainty of monitoring data. Majiagou landslide, a representative reservoir landslide installed stabilizing and test piles, is selected as the case study. Firstly, monitoring data of monthly rainfall, variations of reservoir water level, deformation of landslide surface and piles’ head were preprocessed. The random deformation data were generated considering uncertainty of deformation monitoring data. Meanwhile, the deformation response of landslide–pile system is analyzed through studying the monitoring deformation data and random deformation data using the clustering algorithm. Finally, geographic detector technique was used to identify main triggering factors of landslide surface deformation and explore interaction types of any two factors. The uncertainty of monitoring data was used to identify the most important triggering factor. Influences of different error and uncertainty of monitoring data on the influence degrees of each factor were further discussed. The comparison with improved Apriori algorithm shows that the presented framework can intuitively measure influence degrees of each factor and analyze interaction types of any two factors. The main conclusions by studying Majiagou landslide indicate that the anti-slide performance and action range of piles gradually decrease with the increase of hydraulic cycle; the deterioration of geomaterials’ properties are the most important triggering factor leading to the deformation of landslide–pile system and the degradation of piles’ performance, supported by most random deformation groups.

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