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Natural Hazards and Earth System Sciences An interactive open-access journal of the European Geosciences Union
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Discussion papers
https://doi.org/10.5194/nhess-2019-167
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/nhess-2019-167
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: research article 23 Jul 2019

Submitted as: research article | 23 Jul 2019

Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Natural Hazards and Earth System Sciences (NHESS).

Real-time probabilistic seismic hazard assessment based on seismicity anomaly

Yu-Sheng Sun1, Hsien-Chi Li1, Ling-Yun Chang1, Zheng-Kai Ye1, and Chien-Chih Chen1,2 Yu-Sheng Sun et al.
  • 1Department of Earth Sciences, National Central University, Taoyuan City 32001, Taiwan, R.O.C.
  • 2Earthquake-Disaster and Risk Evaluation and Management Center, National Central University, Taoyuan City 32001, Taiwan, R.O.C.

Abstract. The real-time Probabilistic Seismic Hazard Assessment (PSHA) is developed for considering the practicability for daily life and the rate of seismic activity with time. The real-time PSHA follows the traditional PSHA framework, but the statistic occurrence rate is substituted by time-dependent seismic source probability. Pattern Informatics method (PI) is a proper time-dependent probability model of seismic source, which have been developed over a decade. Therefore, in this research, we chose the PI method as the function of time-dependent seismic source probability and selected two big earthquakes in Taiwan, the 2016/02/05, Meinong earthquake (ML 6.6) and the 2018/02/06, Hualien earthquake (ML 6.2), as examples for the real-time PSHA. The forecasting seismic intensity maps produced by the real-time PSHA present the maximum seismic intensity for the next 90 days. Compared to real ground motion data from the P-alert network, these forecasting seismic intensity maps have considerable effectiveness in forecasting. It indicates that the real-time PSHA is practicable and can provide a useful information for the prevention of earthquake disasters.

Yu-Sheng Sun et al.
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Short summary
This study presents how the real-time seismic hazard assessment can be achieved by replacing the static seismic rate with the time-dependent seismic source probability. We take the 2016 Meinong (ML 6.6) and the 2018 Hualien (ML 6.2) earthquakes in Taiwan as examples. The forecasting seismic intensity maps from the real-time PSHA have significant performances, which demonstrates that the real-time PSHA is doable and can be realized by the time-dependent seismic source probability.
This study presents how the real-time seismic hazard assessment can be achieved by replacing the...
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