Reconnaissance and learning after the February 6, 2018, earthquake in Hualien, Taiwan

Jui Liang Lin, Chun Hsiang Kuo, Yu Wen Chang, Shu Hsien Chao, Yi An Li, Wen Cheng Shen, Chung Han Yu, Cho Yen Yang, Fan Ru Lin, Hsiao Hui Hung, Chun Chung Chen, Chin Kuo Su, Shang Yi Hsu, Chih Chieh Lu, Lap Loi Chung, Shyh Jiann Hwang

Research output: Contribution to journalArticlepeer-review

11 Scopus citations


An earthquake with an epicenter offshore of Hualien City in eastern Taiwan occurred at midnight on February 6, 2018. The Richter magnitude (ML) of the earthquake was 6.26 and the seismic intensity ranged up to level VII, the strongest seismic intensity level regulated in Taiwan. Almost all the major damage resulting from this seismic event was occurred near both sides of the Milun Fault, where records from nearby strong motion stations displayed the characteristics of near-fault ground motions. The main seismic damage was the collapse of four buildings with soft bottom stories, one of which resulted in fourteen of the seventeen total fatalities. Comparing the acceleration response spectra with the design response spectra sheds light on the effects of near-fault ground motions on the collapsed buildings. Based on the eventual forms of collapsed buildings, building collapses that have generally led to major casualties in past seismic events around the world can be classified into sit-down, knee-down and lie-down types. In addition to the four collapsed buildings, seismic reconnaissance on other buildings, bridges, ports, and non-structural components have also been conducted. This study explores the issues and challenges arising from the reconnaissance results and thereby enhances learning from the seismic event.

Original languageEnglish
Pages (from-to)4725-4754
Number of pages30
JournalBulletin of Earthquake Engineering
Issue number10
StatePublished - 1 Aug 2020


  • 0206 Hualien earthquake
  • Bridge
  • Building collapse
  • Liquefaction
  • Milun fault
  • Near-fault ground motion
  • Non-structural component
  • Seismic reconnaissance


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