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Global sensitivity analysis of the hydraulic parameters of the reservoir colluvial landslides in the Three Gorges Reservoir area, China

  • Yankun Wang
  • Jinsong Huang
  • Huiming TangEmail author
Technical Note


Hydraulic parameters are key data for calculating groundwater level, which is critical for assessing reservoir landslide stability. However, the quantitative understanding the influence of hydraulic parameters on the groundwater level of a reservoir landslide remains limited. In this paper, we apply a novel global sensitivity analysis method, PAWN, to quantify the sensitivity of hydraulic properties. The Shuping landslide, which is a typical reservoir colluvial landslide located in the Three Gorges Reservoir area, China, is used as a study case. The hydraulic parameters are first sampled within their entire feasibility space by the Latin hypercube sampling method. These samples are then used as inputs into a nonintrusive finite element program to automatically compute the corresponding groundwater level outputs. Finally, sensitivity indices are calculated based on the input–output dataset via the PAWN method. The global sensitivity analysis results provide useful guidelines for site investigation and reservoir colluvial landslide model simplification and calibration.


Global sensitivity analysis Reservoir colluvial landslide Hydraulic parameters PAWN Three Gorges Reservoir area 



The authors appreciate the editor and reviewers for valuable suggestions on this paper, and we thank the Dr. Miaomiao Ge at the University of Newcastle, Australia, for her fruitful discussion on the unsaturated soil. The first author thanks the China Scholarship Council for providing the scholarship for the research described in this paper, which was conducted as a joint Ph.D. at the Priority Research Centre for Geotechnical Science and Engineering at the University of Newcastle, Australia.

Funding information

This work was funded by the National Key R&D Program of China (2017YFC1501305), National Natural Science Foundation of China (Grant No. 41702328), Hubei Provincial Natural Science Foundation of China (Grant No. 2019CFB585), Fundamental Research Funds for the Central Universities, China University of Geosciences (Wuhan) (Grant No. CUGL170813 and CUGQYZX1747), and Xi′an Center of Geological Survey, China Geological Survey (Grant No. DD20190714).


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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Faculty of EngineeringChina University of GeosciencesWuhanPeople’s Republic of China
  2. 2.Discipline of Civil, Surveying and Environmental Engineering, Priority Research Centre for Geotechnical Science and EngineeringThe University of NewcastleCallaghanAustralia
  3. 3.Three Gorges Research Center for Geo-hazards of Ministry of EducationChina University of GeosciencesWuhanPeople’s Republic of China

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