The Indian Himalayan region has been severely affected by landslides causing an immense loss in terms of human lives and economic loss. The landslides are usually induced by rainfall which can be slow and continuous or heavy downpour. The incidences of landslide events in Indian Himalayas have been further aggravated due to the rapid increase in urbanization and thus its increasing impact on socio-economic aspects. There is a dire need for understanding landslide phenomena, estimating its occurrence potential and formulating strategies to minimize the damage caused by them. One of the most affected area is Kalimpong of Darjeeling Himalayas where significant studies have been conducted on zonation, threshold estimation and other related aspects. However, a comprehensive study in terms of temporal prediction for this region remains unattended. The paper deals with assessing landslide hazard using a rainfall threshold model involving daily and cumulative antecedent rainfall values for landslide events. The threshold values were determined using daily rainfall and antecedent rainfall using precipitation and landslide records for 2010–2016. The results show that 20-day antecedent rainfall provides the best fit for landslide occurrences in the region. The rainfall thresholds were further validated using rainfall and landslide data of 2017, which was not considered for threshold estimation. Finally, the results were used to determine the temporal probability for landslide incidence using a Poisson probability model. The validated results suggest that the model has the potential to be used as a preliminary early warning system.

中文翻译：

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估计大吉岭喜马拉雅山滑坡发生的降雨阈值和时间概率

印度喜马拉雅地区受到山体滑坡的严重影响，造成了巨大的生命和经济损失。滑坡通常是由降雨引起的，降雨可能是缓慢而连续的或倾盆大雨。由于城市化的迅速发展及其对社会经济方面的影响越来越大，印度喜马拉雅山的滑坡事件的发生率进一步加剧。迫切需要了解滑坡现象，估计其发生可能性并制定策略以最大程度地减少滑坡造成的破坏。受灾最严重的地区之一是大吉岭喜马拉雅山的Kal伦堡（Kalimpong），该地区已对分区，阈值估计和其他相关方面进行了重要研究。但是，对该区域的时间预测方面的综合研究仍无人看管。本文使用降雨阈值模型评估滑坡灾害，该模型涉及滑坡事件的每日和累积前降雨值。该阈值是使用2010-2016年的每日降雨量和之前的降雨以及降雨和滑坡记录确定的。结果表明，前20天的降雨最适合该地区发生滑坡。使用2017年的降雨和滑坡数据进一步验证了降雨阈值，未将其用于阈值估计。最后，使用泊松概率模型将结果用于确定滑坡发生的时间概率。验证的结果表明该模型具有用作初步预警系统的潜力。