Probabilistic back analysis of rainfall-induced slope failure considering slope survival records from past rainfall events
Research output: Journal Publications and Reviews (RGC: 21, 22, 62) › 21_Publication in refereed journal › peer-review
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Detail(s)
Original language | English |
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Article number | 105436 |
Journal / Publication | Computers and Geotechnics |
Volume | 159 |
Online published | 6 Apr 2023 |
Publication status | Published - Jul 2023 |
Link(s)
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.
Research Area(s)
- Back analysis, Rainfall-induced landslide, Probabilistic methods, Slope stability
Citation Format(s)
Probabilistic back analysis of rainfall-induced slope failure considering slope survival records from past rainfall events. / Liu, Xin; Wang, Yu; Leung, Anthony Kwan.
In: Computers and Geotechnics, Vol. 159, 105436, 07.2023.
In: Computers and Geotechnics, Vol. 159, 105436, 07.2023.
Research output: Journal Publications and Reviews (RGC: 21, 22, 62) › 21_Publication in refereed journal › peer-review