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<p>On 8 February 2025, a catastrophic landslide occurred in Junlian County, Sichuan Province, southwestern China, resulting in 10 fatalities, 19 missing persons, and severe damage to houses and farmland. This event offers a rare opportunity to investigate the full dynamics of a high-speed, long-runout landslide from direct observations. Previous studies relied mainly on geological and remote-sensing analyses of pre- and post-failure data, but the lack of direct observations during failure has limited understanding of its dynamic evolution. In this study, we integrate broadband seismic records capturing the complete failure process from the Sichuan regional network with high-resolution airborne LiDAR data to reconstruct the complete dynamics of the Junlian landslide. The seismic signals reveal two major failure episodes (LS01 and LS02), initiated at 11:50:54.855 and 11:53:38.615 (UTC+8), respectively. Detailed analysis of LS01 identifies four kinematic stages and two discrete sliding masses, whose volume ratio ranges from 0.296 to 0.304, as validated by spectral and 3D geometric analyses. These results provide a comprehensive reconstruction of the temporal evolution of the landslide and demonstrate the potential of seismic observations to quantitatively resolve the dynamics of catastrophic landslides in near-real time.</p>

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The catastrophic 2025 Junlian landslide in Sichuan, China: insights revealed by seismic signals

  • 期刊论文

  • 发表日期：

    2026年2月11日

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  • Feng Pu,
  • Qiang Xu,
  • Chuanhao Pu,
  • Xiujun Dong,
  • Jinrong Su,
  • Xing Zhu,
  • Pengyu Guo,
  • Zhigang Li,
  • Bo Deng

摘要

On 8 February 2025, a catastrophic landslide occurred in Junlian County, Sichuan Province, southwestern China, resulting in 10 fatalities, 19 missing persons, and severe damage to houses and farmland. This event offers a rare opportunity to investigate the full dynamics of a high-speed, long-runout landslide from direct observations. Previous studies relied mainly on geological and remote-sensing analyses of pre- and post-failure data, but the lack of direct observations during failure has limited understanding of its dynamic evolution. In this study, we integrate broadband seismic records capturing the complete failure process from the Sichuan regional network with high-resolution airborne LiDAR data to reconstruct the complete dynamics of the Junlian landslide. The seismic signals reveal two major failure episodes (LS01 and LS02), initiated at 11:50:54.855 and 11:53:38.615 (UTC+8), respectively. Detailed analysis of LS01 identifies four kinematic stages and two discrete sliding masses, whose volume ratio ranges from 0.296 to 0.304, as validated by spectral and 3D geometric analyses. These results provide a comprehensive reconstruction of the temporal evolution of the landslide and demonstrate the potential of seismic observations to quantitatively resolve the dynamics of catastrophic landslides in near-real time.