Can I read Deformation Response and Triggering Factors of the Reservoir Landslide–pile System Based Upon Geographic Detector Technology and Uncertainty of Monitoring Data on EtoBox?
Deformation Response and Triggering Factors of the Reservoir Landslide–pile System Based Upon Geographic Detector Technology and Uncertainty of Monitoring Data by Haikuan Zhang; Changdong Li; Xinli Hu; Zhiyong Fu; Wenqiang Chen; Wenmin Yao; Yunpeng Zhang; Xihui Jiang is a Environmental Science article available to read on EtoBox.
What is Deformation Response and Triggering Factors of the Reservoir Landslide–pile System Based Upon Geographic Detector Technology and Uncertainty of Monitoring Data about?
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
Who reads Deformation Response and Triggering Factors of the Reservoir Landslide–pile System Based Upon Geographic Detector Technology and Uncertainty of Monitoring Data?
It is typically read by researchers, students, and practitioners in Environmental Science.
- Author
- Haikuan Zhang; Changdong Li; Xinli Hu; Zhiyong Fu; Wenqiang Chen; Wenmin Yao; Yunpeng Zhang; Xihui Jiang
- Publisher
- Springer Science and Business Media LLC
- Published
- 2020
- Language
- EN
- Field
- Environmental Science (Physical Sciences)