scholarly journals Time-dependent probabilistic seismic hazard assessment and its application to Hualien City, Taiwan

2013 ◽  
Vol 13 (5) ◽  
pp. 1143-1158 ◽  
Author(s):  
C.-H. Chan ◽  
Y.-M. Wu ◽  
C.-T. Cheng ◽  
P.-S. Lin ◽  
Y.-C. Wu

Abstract. Here, we propose a time-dependent probabilistic seismic hazard assessment and apply it to Hualien City, Taiwan. A declustering catalog from 1940 to 2005 was used to build up a long-term seismicity rate model using a smoothing Kernel function. We also evaluated short-term seismicity rate perturbations according to the rate-and-state friction model, and the Coulomb stress changes imparted by earthquakes from 2006 to 2010. We assessed both long-term and short-term probabilistic seismic hazards by considering ground motion prediction equations for crustal and subduction earthquakes. The long-term seismic hazard in Hualien City gave a PGA (peak ground acceleration) of 0.46 g for the 2.1‰ annual exceedance probability. The result is similar to the levels determined in previous studies. Seismic hazards were significantly elevated following the 2007 ML =5.8 earthquake that occurred approximately 10 km from Hualien City. This work presents an assessment of a suitable mechanism for time-dependent probabilistic seismic hazard determinations using an updated earthquake catalog. Using minor model assumptions, our approach provides a suitable basis for rapid re-evaluations and will benefit decision-makers and public officials regarding seismic hazard mitigation.

2020 ◽  
Vol 20 (3) ◽  
pp. 743-753
Author(s):  
Yu-Sheng Sun ◽  
Hsien-Chi Li ◽  
Ling-Yun Chang ◽  
Zheng-Kai Ye ◽  
Chien-Chih Chen

Abstract. Real-time probabilistic seismic hazard assessment (PSHA) was developed in this study in consideration of its practicability for daily life and the rate of seismic activity with time. Real-time PSHA follows the traditional PSHA framework, but the statistic occurrence rate is substituted by time-dependent seismic source probability. Over the last decade, the pattern informatics (PI) method has been developed as a time-dependent probability model of seismic source. We employed this method as a function of time-dependent seismic source probability, and we selected two major earthquakes in Taiwan as examples to explore real-time PSHA. These are the Meinong earthquake (ML 6.6) of 5 February 2016 and the Hualien earthquake (ML 6.2) of 6 February 2018. The seismic intensity maps produced by the real-time PSHA method facilitated the forecast of the maximum expected seismic intensity for the following 90 d. Compared with real ground motion data from the P-alert network, our seismic intensity forecasting maps showed considerable effectiveness. This result indicated that real-time PSHA is practicable and provides useful information that could be employed in the prevention of earthquake disasters.


2019 ◽  
Author(s):  
Yu-Sheng Sun ◽  
Hsien-Chi Li ◽  
Ling-Yun Chang ◽  
Zheng-Kai Ye ◽  
Chien-Chih Chen

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.


2020 ◽  
Vol 79 (10) ◽  
pp. 5079-5094
Author(s):  
Seyed Hadi Dehghan-Manshadi ◽  
Noorbakhsh Mirzaei ◽  
Morteza Eskandari-Ghadi ◽  
Elham Shabani ◽  
Seyed Hasan Mousavi-Bafrouei

2021 ◽  
Vol 14 (9) ◽  
Author(s):  
Etoundi Delair Dieudonné Ndibi ◽  
Eddy Ferdinand Mbossi ◽  
Nguet Pauline Wokwenmendam ◽  
Bekoa Ateba ◽  
Théophile Ndougsa-Mbarga

2014 ◽  
Vol 85 (6) ◽  
pp. 1316-1327 ◽  
Author(s):  
C. Beauval ◽  
H. Yepes ◽  
L. Audin ◽  
A. Alvarado ◽  
J.-M. Nocquet ◽  
...  

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