Seismotectonics and seismogenesis of Kashmir Valley, NW Himalaya, India from a local seismic network

IF 1.3 4区 地球科学 Q3 GEOSCIENCES, MULTIDISCIPLINARY Journal of Earth System Science Pub Date : 2024-03-29 DOI:10.1007/s12040-024-02270-x
Nayeem Ahmad Bhat, Bikram Singh Bali, Sareer Ahmad Mir, Prakash Kumar
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Abstract

The analysis of earthquake data related to low-magnitude events provides vital information on seismotectonics and the seismic processes that generate seismic sequences with strong events. Kashmir Valley in the northwest Himalaya experiences seismic shaking due to near-field and far-field earthquakes. A seismic network consisting of 12 broadband seismic stations was installed in the Kashmir Valley in 2019 to monitor the local seismic activity. Data recorded by this network is analysed continuously 24×7 at 10-sec intervals to monitor earthquake activity in and adjoining regions of the Kashmir Valley. The determined fault plane solutions using local seismic data and centroid moment tensor (CMT) data reveal thrust faulting in and around the Kashmir Valley. The waveform analysis of the acquired data shows the occurrence of seismic events both from local (432 events between 2019 and 2022) and distant/teleseismic sources. The study area is devoid of major earthquakes because most of the crustal motion is accommodated by the basal detachment or Main Himalayan Thrust (MHT) beneath the surface. This results in the accumulation of significant stress within the Earth's crust in the southern region of the valley. However, a local tectonic element (Balapora Thrust) in association with Magam Fault has produced some seismic events of low magnitude. This suggests that Balapora Thrust and other minor fault (Magam Fault) are active in the Kashmir Valley.

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从当地地震台网看印度西北喜马拉雅克什米尔山谷的地震构造和地震发生情况
对与低震级地震相关的地震数据进行分析,可提供有关地震构造和产生强震序列的地震过程的重要信息。位于喜马拉雅山西北部的克什米尔山谷经历着近场和远场地震引起的震荡。2019 年,在克什米尔山谷安装了由 12 个宽带地震台站组成的地震网络,以监测当地的地震活动。该网络记录的数据以 10 秒为间隔进行 24×7 连续分析,以监测克什米尔山谷及其邻近地区的地震活动。利用当地地震数据和中心力矩张量(CMT)数据确定的断层面解决方案揭示了克什米尔山谷及其周边地区的推力断层。对所获数据的波形分析表明,本地(2019 年至 2022 年间发生了 432 次地震)和远距离/远程震源都发生过地震。由于大部分地壳运动被地表下的基底脱离或喜马拉雅主推力(MHT)所容纳,因此研究区域没有发生大地震。这导致山谷南部地区的地壳中积累了大量应力。然而,与马甘断层相关联的当地构造元素(巴拉波拉断层)产生了一些震级较低的地震事件。这表明,巴拉波拉断层和其他小断层(马加姆断层)在克什米尔山谷很活跃。
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来源期刊
Journal of Earth System Science
Journal of Earth System Science Earth and Planetary Sciences-General Earth and Planetary Sciences
CiteScore
3.20
自引率
5.30%
发文量
226
期刊介绍: The Journal of Earth System Science, an International Journal, was earlier a part of the Proceedings of the Indian Academy of Sciences – Section A begun in 1934, and later split in 1978 into theme journals. This journal was published as Proceedings – Earth and Planetary Sciences since 1978, and in 2005 was renamed ‘Journal of Earth System Science’. The journal is highly inter-disciplinary and publishes scholarly research – new data, ideas, and conceptual advances – in Earth System Science. The focus is on the evolution of the Earth as a system: manuscripts describing changes of anthropogenic origin in a limited region are not considered unless they go beyond describing the changes to include an analysis of earth-system processes. The journal''s scope includes the solid earth (geosphere), the atmosphere, the hydrosphere (including cryosphere), and the biosphere; it also addresses related aspects of planetary and space sciences. Contributions pertaining to the Indian sub- continent and the surrounding Indian-Ocean region are particularly welcome. Given that a large number of manuscripts report either observations or model results for a limited domain, manuscripts intended for publication in JESS are expected to fulfill at least one of the following three criteria. The data should be of relevance and should be of statistically significant size and from a region from where such data are sparse. If the data are from a well-sampled region, the data size should be considerable and advance our knowledge of the region. A model study is carried out to explain observations reported either in the same manuscript or in the literature. The analysis, whether of data or with models, is novel and the inferences advance the current knowledge.
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