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<p>On 7 January 2025, an Mw 7.1 normal-faulting earthquake struck the Dingri region in southwestern Xizang (Tibet), located within the extensional domain of the plateau - one of the most seismically active intraplate regions on Earth. Investigating the preparatory phase of such events in remote areas is particularly challenging due to limited station coverage. We analysed continuous records from IO.EVN, the only permanent seismic station within approximately 90&#xa0;km of the epicentre that freely provides available data. Using an AI-based approach that integrates phase detection, polarisation analysis and template matching, we reconstructed an earthquake catalogue for the two years preceding the mainshock. Our results reveal a marked increase in event rate and clustering beginning about 45 days before the mainshock, coinciding temporally with an M<sub>L</sub> 2.4 event at the Himalayan front. We interpret this evolution as a slow, progressive increase in seismicity, consistent with a late-stage nucleation process modulated by regional tectonics. Our results are therefore compatible with tectonic loading, and suggest that single-station seismic monitoring, when enhanced by AI techniques, can help identify retrospective seismicity patterns prior to rupture, even in data-sparse and tectonically complex regions.</p>

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Precursory seismicity unveiled before the Mw7.1 Dingri earthquake in Tibet

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年5月11日

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  • Franco Pettenati,
  • Alessandro Vuan,
  • Denis Sandron,
  • Giampietro Verza,
  • Matteo Picozzi

摘要

On 7 January 2025, an Mw 7.1 normal-faulting earthquake struck the Dingri region in southwestern Xizang (Tibet), located within the extensional domain of the plateau - one of the most seismically active intraplate regions on Earth. Investigating the preparatory phase of such events in remote areas is particularly challenging due to limited station coverage. We analysed continuous records from IO.EVN, the only permanent seismic station within approximately 90 km of the epicentre that freely provides available data. Using an AI-based approach that integrates phase detection, polarisation analysis and template matching, we reconstructed an earthquake catalogue for the two years preceding the mainshock. Our results reveal a marked increase in event rate and clustering beginning about 45 days before the mainshock, coinciding temporally with an ML 2.4 event at the Himalayan front. We interpret this evolution as a slow, progressive increase in seismicity, consistent with a late-stage nucleation process modulated by regional tectonics. Our results are therefore compatible with tectonic loading, and suggest that single-station seismic monitoring, when enhanced by AI techniques, can help identify retrospective seismicity patterns prior to rupture, even in data-sparse and tectonically complex regions.