Reliability analysis for a large and complex landslide in the three gorges reservoir area (China) based on incomplete information

Abstract

The soil parameters for large, complex landslides are typically derived from incomplete information based on a small sample set due to budgetary constraints. This informational incompleteness results in large statistical uncertainty in landslide reliability analyses. In this article, the bootstrap technique is proposed to quantify the statistical uncertainties associated with a small sample set, and a practice-oriented reliability analysis is performed. The results suggest that the obtained reliability indices are characterized by a long tail, in which the worst-case scenario has a local extreme value and a small population. The statistical uncertainties are quantified and characterized by a confidence interval at a specified confidence level. The confidence interval of the reliability index and identification of the worst-case scenario enable engineers to make more informed decisions.

Keywords

• large complex landslides
• reliability index
• incomplete information
• statistical uncertainty
• bootstrap