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Probabilistic back analysis of rainfall-induced slope failure considering slope survival records from past rainfall events

  • Xin Liu
  • , Yu Wang*
  • , Anthony Kwan Leung
  • *Corresponding author for this work

Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review

29 Downloads (CityUHK Scholars)

Abstract

Many rainfall-induced landslides occur on slopes that have limited, or even no, site investigation data before failure. Probabilistic back analysis of slope failure provides an effective tool to back analyze possible pre-failure soil parameters, thus gaining insights into the mechanism of slope failure. For a slope failure induced by rainfall, the actual factor of safety (FS) is time-variant when time-variant rainfall and infiltration are explicitly modeled. This study proposes a novel probabilistic back analysis method that models explicitly the rainfall triggering mechanism for a rainfall-induced slope failure. Unlike existing methods that are based on a constant FS = 1, the proposed method utilizes FS inequality information for probabilistic back analysis, including slope failure record with FS < 1 and slope survival records from past rainfall events with FS > 1. The proposed method is suitable for high-dimensional problems when soil hydraulic properties are also back analyzed. The proposed method converges to the conventional methods with FS = 1 when the time span of slope failure is narrowed down to a few hours and slope survival records are ignored. Incorporating both slope failure and survival records effectively reduces uncertainties in soil strength and hydraulic parameters. © 2023 Elsevier Ltd. All rights reserved.
Original languageEnglish
Article number105436
JournalComputers and Geotechnics
Volume159
Online published6 Apr 2023
DOIs
Publication statusPublished - Jul 2023

Funding

The work described in this paper was supported by a grant from the Research Grant 19 Council of Hong Kong Special Administrative Region (Project no. C6006-20G) and a grant 20 from Shenzhen Science and Technology Innovation Commission (Shenzhen-Hong Kong21 Macau Science and Technology Project (Category C) No: SGDX20210823104002020), China. 22 The financial support is gratefully acknowledged.

Research Keywords

  • Back analysis
  • Rainfall-induced landslide
  • Probabilistic methods
  • Slope stability

Publisher's Copyright Statement

  • COPYRIGHT TERMS OF DEPOSITED POSTPRINT FILE: © 2023. This manuscript version is made available under the CC-BY-NC-ND 4.0 license https://creativecommons.org/licenses/by-nc-nd/4.0/.

RGC Funding Information

  • RGC-funded

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