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Estimating return period of landslide triggering by Monte Carlo simulation

机译:通过蒙特卡洛模拟估算滑坡触发的返回周期

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摘要

Assessment of landslide hazard is a crucial step for landslide mitigation planning. Estimation of the return period of slope instability represents a quantitative method to map landslide triggering hazard on a catchment. The most common approach to estimate return periods consists in coupling a triggering threshold equation, derived from an hydrological and slope stability process-based model, with a rainfall intensity-duration-frequency (IDF) curve. Such a traditional approach generally neglects the effect of rainfall intensity variability within events, as well as the variability of initial conditions, which depend on antecedent rainfall. We propose a Monte Carlo approach for estimating the return period of shallow landslide triggering which enables to account for both variabilities. Synthetic hourly rainfall-landslide data generated by Monte Carlo simulations are analysed to compute return periods as the mean interarrival time of a factor of safety less than one. Applications are first conducted to map landslide triggering hazard in the Loco catchment, located in highly landslide-prone area of the Peloritani Mountains, Sicily, Italy. Then a set of additional simulations are performed in order to evaluate the traditional IDF-based method by comparison with the Monte Carlo one. Results show that return period is affected significantly by variability of both rainfall intensity within events and of initial conditions, and that the traditional IDF-based approach may lead to an overestimation of the return period of landslide triggering, or, in other words, a non-conservative assessment of landslide hazard. (C) 2016 Elsevier B.V. All rights reserved.
机译:评估滑坡灾害是减缓滑坡规划的关键步骤。边坡失稳返回期的估算代表了一种定量方法,可绘制出流域引发滑坡的危险图。估算返回期的最常用方法是将触发阈值方程式与降雨强度-持续时间-频率(IDF)曲线耦合,该触发阈值方程式是从基于水文和边坡稳定过程的模型得出的。这种传统方法通常会忽略事件中降雨强度变化的影响以及初始条件的变化,而初始条件取决于先前的降雨。我们提出了一种蒙特卡洛方法来估算浅层滑坡触发的返回周期,该方法能够解决这两种变化。对通过蒙特卡洛模拟生成的每小时合成降雨-滑坡数据进行分析,以计算返回周期,因为平均到达间隔时间小于一个安全系数。首先在意大利西西里岛Peloritani山高滑坡易发地区的Loco流域绘制滑坡触发危险的地图。然后执行一组附加仿真,以便通过与Monte Carlo方法进行比较来评估传统的基于IDF的方法。结果表明,返回期受事件内和初始条件下降雨强度变化的影响很大,并且基于IDF的传统方法可能导致对滑坡触发的返回期的高估,或者换句话说,没有滑坡灾害的保守评估。 (C)2016 Elsevier B.V.保留所有权利。

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