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首页> 外文期刊>Geosciences >Determination of Rainfall Thresholds for Landslide Prediction Using an Algorithm-Based Approach: Case Study in the Darjeeling Himalayas, India
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Determination of Rainfall Thresholds for Landslide Prediction Using an Algorithm-Based Approach: Case Study in the Darjeeling Himalayas, India

机译：使用基于算法的方法确定滑坡预测的降雨阈值：以印度大吉岭喜马拉雅山为例

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摘要

Landslides are one of the most devastating and commonly recurring natural hazards in the Indian Himalayas. They contribute to infrastructure damage, land loss and human casualties. Most of the landslides are primarily rainfall-induced and the relationship has been well very well-established, having been commonly defined using empirical-based models which use statistical approaches to determine the parameters of a power-law equation. One of the main drawbacks using the traditional empirical methods is that it fails to reduce the uncertainties associated with threshold calculation. The present study overcomes these limitations by identifying the precipitation condition responsible for landslide occurrence using an algorithm-based model. The methodology involves the use of an automated tool which determines cumulated event rainfall–rainfall duration thresholds at various exceedance probabilities and the associated uncertainties. The analysis has been carried out for the Kalimpong Region of the Darjeeling Himalayas using rainfall and landslide data for the period 2010–2016. The results signify that a rainfall event of 48 hours with a cumulated event rainfall of 36.7 mm can cause landslides in the study area. Such a study is the first to be conducted for the Indian Himalayas and can be considered as a first step in determining more reliable thresholds which can be used as part of an operational early-warning system.
机译：滑坡是印度喜马拉雅山最具破坏性和最经常发生的自然灾害之一。它们造成基础设施损坏，土地损失和人员伤亡。大多数滑坡主要是降雨引起的，并且这种关系已经很好地建立，通常使用基于经验的模型进行定义，该模型使用统计方法确定幂律方程的参数。使用传统经验方法的主要缺点之一是它无法减少与阈值计算相关的不确定性。本研究通过使用基于算法的模型识别导致滑坡发生的降水条件，克服了这些限制。该方法论涉及使用自动工具，该工具可确定各种超出概率和相关不确定性下的累积事件降雨-降雨持续时间阈值。已使用2010-2016年期间的降雨和滑坡数据对大吉岭喜马拉雅山的Kal伦堡地区进行了分析。结果表明，降雨48小时，累积降雨36.7 mm，可能在研究区域内引起滑坡。这项研究是首次针对印度喜马拉雅山进行的研究，可以被认为是确定更可靠的阈值的第一步，该阈值可以用作运行中的预警系统的一部分。

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