Reliability analysis of an existing slope at a specific site considering rainfall triggering mechanism and its past performance records
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review
Author(s)
Related Research Unit(s)
Detail(s)
Original language | English |
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Article number | 106144 |
Journal / Publication | Engineering Geology |
Volume | 288 |
Online published | 21 Apr 2021 |
Publication status | Published - Jul 2021 |
Link(s)
Abstract
Accurate estimation of landslide probability or slope failure probability when there is a rainstorm event is crucial for assessment and mitigation of rainfall-induced landslide risk. Slope reliability methods provide a rigorous way of estimating landslide probability based on slope failure mechanism and probability theory. However, it is well recognized in literature that the landslide probability estimated from existing slope reliability analysis methods are often much larger than the observed landslide frequency. To improve accuracy of the slope failure probability, this study proposes a slope reliability analysis method for an existing slope at a specific site, which considers both rainfall triggering mechanism and the slope's performance records during previous rainfall events. It was found that the fact that the slope survived from previous rainfall events could be utilized to effectively reduce uncertainties in soil parameters and might reduce the estimated landslide probability by one to two orders of magnitudes. In addition, the proposed method provides a real-time slope failure probability for a given rainfall event, and the estimated slope failure probability varies as the considered rainfall event evolves with time.
Research Area(s)
- Slope reliability, Rainfall, Uncertainties, Bayesian updating, Digital twin
Citation Format(s)
Reliability analysis of an existing slope at a specific site considering rainfall triggering mechanism and its past performance records. / Liu, Xin; Wang, Yu.
In: Engineering Geology, Vol. 288, 106144, 07.2021.
In: Engineering Geology, Vol. 288, 106144, 07.2021.
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review