Japan Geoscience Union Meeting 2015

Presentation information


Symbol S (Solid Earth Sciences) » S-SS Seismology

[S-SS32] Seismicity

Tue. May 26, 2015 6:15 PM - 7:30 PM Convention Hall (2F)

Convener:*Yoshinari Hayashi(Faculty of safety Science, Kansai University)

6:15 PM - 7:30 PM

[SSS32-P13] Precursory seismicity change of the 2013 Nantou, Taiwan earthquake sequence revealed by ETAS, PI, and Z-value methods

*Masashi KAWAMURA1, Chien-chih CHEN2, Yih-min WU3 (1.Dep. of Earth Sciences, National Taiwan Normal Univ., 2.Dep. of Earth Sciences, National Central Univ., Taiwan, 3.Dep. of Geosciences, National Taiwan Univ.)

Keywords:Seismic quiescence, The Nantou earthquake, Stress accumulation, ETAS model, Pattern informatics, ZMAP

ML6.2 and ML6.3 earthquakes occurred in the Nantou area of central Taiwan on Mar. 27, 2013 and June 2, 2013, respectively. Because their epicenters are close to one another, we regard the March ML6.2 and June ML6.3 earthquakes as an event sequence. To investigate precursory seismicity change of the Nantou earthquake sequence (or the March ML6.2 earthquake), we applied the Epidemic-Type Aftershock-Sequences model (ETAS model) to the earthquake catalog data of the Central Weather Bureau (CWB) covering broader Taiwan region. Application of more than one model to an earthquake catalog would be informative in elucidating the relationships between seismicity precursors and the preparatory processes of large earthquakes. Based on this motivation, we further applied two different approaches: the pattern informatics (PI) method and the ZMAP method, which is a gridding technique based on the standard deviate (Z-value) test to the same earthquake catalog data of CWB. As a result, we found that the epicenter of the 2013 ML6.2 Nantou earthquake was surrounded by three main seismic quiescence regions prior to its occurrence. The assumption that this is due to precursory slip (stress drop) on fault plane or its deeper extent of the ML6.2 Nantou earthquake is supported by previous researches based on seismicity data, geodedic data, and numerical simulations using rate- and state-dependent friction laws (Kawamura and Chen, 2013).