Himalayan earthquakes have deep societal and economic impact. In this article, we implement a surrogate method of nowcasting (Rundle et al., 2016) to determine the current state of seismic hazard from large earthquakes in a dozen populous cities from India and Pakistan that belong to the west‐northwest part of Himalayan orogeny. For this, we (1) perform statistical inference of natural times, intersperse counts of small‐magnitude events between pairs of succeeding large events, based on a set of eight probability distributions; (2) compute earthquake potential score (EPS) of 14 cities from the best‐fit cumulative distribution of natural times; and (3) carry out a sensitivity testing of parameters—threshold magnitude and area of city region. Formulation of natural time (Varostos et al., 2005) based on frequency–magnitude power‐law statistics essentially avoids the daunting need of seismicity declustering in hazard estimation. A retrospective analysis of natural time counts corresponding to M≥6 events for the Indian cities provides an EPS (%) as New Delhi (56), Chandigarh (86), Dehradun (83), Jammu (99), Ludhiana (89), Moradabad (84), and Shimla (87), whereas the cities in Pakistan observe an EPS (%) as Islamabad (99), Faisalabad (88), Gujranwala (99), Lahore (89), Multan (98), Peshawar (38), and Rawalpindi (99). The estimated nowcast values that range from 38% to as high as 99% lead to a rapid yet useful ranking of cities in terms of their present progression to the regional earthquake cycle of magnitude ≥6.0 events. The analysis inevitably encourages scientists and engineers from governments and industry to join hands for better policymaking toward land‐use planning, insurance, and disaster preparation in the west‐northwest part of active Himalayan belt.

中文翻译：

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喜马拉雅山西北部的当代地震危险：自然时期的统计视角

喜马拉雅地震对社会和经济产生深远影响。在本文中，我们实施了一种临近预报的替代方法（Rundle等人，2016），以确定喜马拉雅造山带的西北偏西地区十几个来自印度和巴基斯坦的人口众多城市的大地震造成的地震灾害的现状。 。为此，我们（1）基于一组八种概率分布，对自然时间进行统计推断，在连续的大事件对之间散布小数量事件的计数；（2）从最合适的自然时间累积分布中计算出14个城市的地震潜力得分（EPS）；（3）对城市阈值大小和面积等参数进行敏感性测试。制定自然时间（Varostos等，（2005年）基于频率-幅度幂律统计，从根本上避免了在危险性评估中降低地震活动性的艰巨需求。对印度城市与M≥6事件对应的自然时间计数进行回顾性分析，得出的EPS（％）为新德里（56），昌迪加（86），德拉敦（83），查mu（99），卢迪亚纳（89），莫拉达巴德（84）和西姆拉（87），而巴基斯坦城市的EPS（％）为伊斯兰堡（99），费萨拉巴德（88），古吉兰瓦拉（99），拉合尔（89），木尔坦（98），白沙瓦（ 38）和拉瓦尔品第（99）。估计的临近预报值从38％到高达99％不等，可根据城市到区域地震周期≥6.0级的当前进展，对城市进行快速而有用的排名。