<p>The effective detection of earthquake precursors is pivotal for mitigating the hazards of earthquakes. However, its feasibility has been controversial for decades and remains unanswered. In general, observation systems must be installed to predict physical phenomena. An ideal observation system has not been established globally for earthquake phenomena. In this context, the Japanese government has developed various earthquake-related observation systems over the past few decades. Among them, the GEONET is an extensive and high-density system deployed throughout Japan using continuous GNSS technology. Using this system, we developed methods for analyzing the spatiotemporal evolution of crustal strains and examining their ability to detect precursors for the recent devastating earthquakes. We focused on the tensor analysis of strains rather than the vector analysis of the observed displacements from GEONET, by using the Finite Element Method to estimate the crustal strain from the displacement. The spatiotemporal evolution of crustal strains due to the 2024 Noto Peninsula Earthquake of Mw7.5 was examined in detail in this study. Through the present analysis of this representative earthquake, we demonstrated that the spatiotemporal evolution of crustal strains showed clear signs of earthquake occurrence.</p>

错误:搜索内容不能为空,请输入英文关键词
错误:关键词超出字数限制,请精简
高级检索

Spatiotemporal evolution of crustal strains preceding destructive earthquakes using GNSS

  • Makoto Kamiyama,
  • Atsushi Mikami,
  • Yasuji Sawada,
  • Hiroshi Akita

摘要

The effective detection of earthquake precursors is pivotal for mitigating the hazards of earthquakes. However, its feasibility has been controversial for decades and remains unanswered. In general, observation systems must be installed to predict physical phenomena. An ideal observation system has not been established globally for earthquake phenomena. In this context, the Japanese government has developed various earthquake-related observation systems over the past few decades. Among them, the GEONET is an extensive and high-density system deployed throughout Japan using continuous GNSS technology. Using this system, we developed methods for analyzing the spatiotemporal evolution of crustal strains and examining their ability to detect precursors for the recent devastating earthquakes. We focused on the tensor analysis of strains rather than the vector analysis of the observed displacements from GEONET, by using the Finite Element Method to estimate the crustal strain from the displacement. The spatiotemporal evolution of crustal strains due to the 2024 Noto Peninsula Earthquake of Mw7.5 was examined in detail in this study. Through the present analysis of this representative earthquake, we demonstrated that the spatiotemporal evolution of crustal strains showed clear signs of earthquake occurrence.