Probabilistic modeling of seismically triggered landslides using Monte Carlo simulations

WANG Huai-bing; Kyoji. Sassa

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Probabilistic modeling of seismically triggered landslides using Monte Carlo simulations

更新时间：2026-06-25

- Probabilistic modeling of seismically triggered landslides using Monte Carlo simulations
- Vol. 28, Issue 12, (2007)
- 作者机构：
  
  1. 华中科技大学土木工程与力学学院,武汉,430074
  2. 京都大学防灾研究所日本京都宇治 611－,0011
- 作者简介：
- 基金信息：
- DOI：
  CLC： O242
- Online First：18 October 2013，
  
  Published：2007
- 稿件说明：
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WANG Huai-bing, Kyoji. Sassa. Probabilistic modeling of seismically triggered landslides using Monte Carlo simulations[J]. 2007, 28(12).
DOI：

WANG Huai-bing, Kyoji. Sassa. Probabilistic modeling of seismically triggered landslides using Monte Carlo simulations[J]. 2007, 28(12). DOI：

摘要

2004年10月23日，日本新泻中越地区发生史上最强地震之一，震级达到Mw6.6。这次地震诱发上千个规模大小不一、形式各样的滑坡，造成一定的灾害损失和人员伤亡。因此，为了有效地避免和减轻这方面的灾害，有必要有效地、科学地预测和评价地震诱发滑坡的空间发生规律。为此以一定的地区作为研究对象，提出了蒙特卡罗随机模拟和Newmark滑动体位移分析法在区域地震斜坡失稳概率分析中的应用。该法充分考虑到岩土参数和相关地震参数空间变异性，结合地理信息系统空间分析的优势，以网格模型为基础，分析该区斜坡滑动体位移分布规律，并以2 cm为失稳临界值探讨网格斜坡破坏的概率。实例证明，所提出的模型有效地预测了滑坡发生的空间分布规律。

Abstract

The 2004 Chuetsu earthquakes of Niigata (Japan) triggered numerous landslides

and the most widespread types of landslides were highly disrupted

relatively shallow slides and soil (debris) flows. To avoid and mitigate such seismic landslide hazard

this paper presents a method to evaluate the probability of slope failures using Newmark displacement on a pixel-by-pixel basis in a given area. The proposed method was able to integrate Newmark displacement modeling and Monte Carlo simulations with geographic information systems (GIS). In the modeling

an empirical attenuation relationship was utilized to calculate Arias intensity over this study area; and the variability of geotechnical parameters was taken into account to calculate coseismic displacement. After deriving the displacement from related inputs

the Monte Carlo simulations ran 1 000 times

and generated 1 000 displacement values for each grid cell; and then the displacement mean and standard deviation were calculated and its probabilistic distribution can be obtained. Finally

given 2 cm as a threshold value of displacement

estimated probabilities of displacement exceeding 2 cm were shown as a map of seismic landslide hazard. The resulting map was classified into four categories from very low to high level.

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