4.6 Article

Identification of movement characteristics and causal factors of the Shuping landslide based on monitored displacements

Journal

BULLETIN OF ENGINEERING GEOLOGY AND THE ENVIRONMENT
Volume 78, Issue 3, Pages 2093-2106

Publisher

SPRINGER HEIDELBERG
DOI: 10.1007/s10064-018-1237-2

Keywords

Shuping landslide; Monitored displacement; Reservoir water level drawdown; Rainfall

Funding

  1. National Key R&D Program of China [2017YFC1501301]
  2. National Natural Science Foundation [41572278]

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Data from in situ monitoring of displacement is of fundamental importance, not only in hazard assessments, but also for understanding the deformation mechanisms of landslides. However, acquiring reliable and continuous displacement data from complex landslides is often a problem because of the high cost of instruments and maintenance. Among more than 250 dangerous landslides monitored in the Chinese Three Gorges reservoir area, the most systematic and complete monitoring data have been obtained from the Shuping landslide. A ten-year record of GPS displacements measured in eight different locations, plus rainfall and reservoir level data, are utilised to identify the movement characteristics and causal factors of the Shuping landslide. The cumulative displacement curves show a series of abrupt increases that occur every year and are separated by periods of steady, slower deformations. The maximum cumulative displacement that occurred during the ten-year monitoring period was 4.7m at site SP-2. The maximum displacement rate was 35mm/day, which was observed on June 13, 2012 at site ZG86. Causal factors of the Shuping landslide are identified through qualitative comparisons of the monitoring data and cross-examined by grey correlation degree analysis. The results show that reservoir water level drawdown is the main factor accelerating the movement of the Shuping landslide, with heavy rainfall playing a subordinate role. The proposed use of field data and analytical methods has the potential for providing procedures and solutions for the interpretation of landslide monitoring data.

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