4.4 Article

Probabilistic Fault Displacement Hazards along the Milun Fault

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SEISMOLOGICAL SOC AMER
DOI: 10.1785/0120210312

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  1. Ministry of Science and Technology in Taiwan [MOST 109-2116M-008 -029 -MY3, MOST 110-2124-M-002 -008, MOST 1102634-F-008-008]
  2. Earthquake Disaster AMP
  3. Risk Evaluation and Management Center (E-DREaM) from the Featured Areas Research Center Program

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Coseismic surface displacements can cause damage to structures, and probabilistic fault displacement hazard analysis (PFDHA) is proposed to estimate expected displacement. A field investigation of the surface ruptures caused by the Hualien earthquake in Taiwan provided crucial information for PFDHA. Comparing the observations to predictions, most were within one standard deviation, supporting the application of PFDHA.
Coseismic surface displacements can result in significant damage to structures located on or near a fault. To address this particular hazard, probabilistic fault displacement hazard analysis (PFDHA) has been proposed to estimate expected displacement on a fault and in its vicinity. To construct PFDHA, any new observed surface ruptures can be included. In 2018, an Mw 6.4 earthquake hit the city of Hualien, Taiwan, and caused surface ruptures along the Milun fault. Immediately after the earthquake, field investigations were car-ried out to investigate the surface ruptures, which provided crucial information for PFDHA. Based on our analysis of the surface displacement data in the Hualien event, we compared existing fault displacement prediction equations, and found that 86% and 65% of the observations from the free field and manmade structures, respectively, were within one standard deviation of the predictions. Based on our fault displacement model and its uncertainties, we analyze the fault displacement hazard in the Hualien region by incorporating epistemic uncertainties through a logic tree approach. Comparing with the occurrence probability of distributed surface faulting, most obser-vations are within one standard deviation of the predictions, suggesting the applications of derived PFDHA.

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