Landslide Analysis Subject to Geological Uncertainty Using Monte Carlo Simulation (A Study Case in Taiwan)

Joni Fitra, Wen Chao Huang, Yusep Muslih Purwana

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

Landslide is the primary driver of the denudational process and sediment source dominantly onsite. Landslides are one of the most disastrous effects in Taiwan; groundwater or flood erosion is highly attributed to the landslide. Water induced to the slope increases driving force and decrease resisting force causing a slope landslide. This condition is generally affecting slope stability. In this study, we attempt to consider the uncertainty of the dip angle in slope stability analysis. In this research, the Monte Carlo simulation was used to quantify the effect of the geological uncertainty. Various sources of dip angles (with mean and standard deviation) were employed to generate 100,000 dip angle samples. All of the dip angles employed in this study were based on Highway no. 3 sliding events in Taiwan. Four different measurement sources, i.e., Central Geological Survey (CGS, Taiwan), Compass measurement before the sliding event, Surface measurement after the event, and LiDAR-derived data, were employed in this study. Further, the measured dip angles were converted to the projected dip angle based on the plane's strike. Simulation results show LiDAR Measurement Source provides the lowest failure probability of 16.9%, and Central Geological Survey (CGS, Taiwan) Measurement provides the highest failure probability of 78%. Therefore, based on the engineering design concept, if the design performed using the CGS data, the engineering design must be very conservative compared to the design using the LiDAR data.

Original languageEnglish
Title of host publicationProceedings of the 5th International Conference on Rehabilitation and Maintenance in Civil Engineering - ICRMCE 2021
EditorsStefanus Adi Kristiawan, Buntara S. Gan, Mohamed Shahin, Akanshu Sharma
PublisherSpringer Science and Business Media Deutschland GmbH
Pages437-447
Number of pages11
ISBN (Print)9789811693472
DOIs
StatePublished - 2023
Event5th International Conference on Rehabilitation and Maintenance in Civil Engineering, ICRMCE 2021 - Virtual, Online
Duration: 8 Jul 20219 Jul 2021

Publication series

NameLecture Notes in Civil Engineering
Volume225
ISSN (Print)2366-2557
ISSN (Electronic)2366-2565

Conference

Conference5th International Conference on Rehabilitation and Maintenance in Civil Engineering, ICRMCE 2021
CityVirtual, Online
Period8/07/219/07/21

Keywords

  • Geological uncertainty
  • Landslide
  • Monte Carlo simulation

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