A Time-Dependent Probabilistic Seismic-Hazard Model for California

2000 ◽  
Vol 90 (1) ◽  
pp. 1-21 ◽  
Author(s):  
C. H. Cramer
2016 ◽  
Vol 87 (6) ◽  
pp. 1311-1318 ◽  
Author(s):  
Matthew C. Gerstenberger ◽  
David A. Rhoades ◽  
Graeme H. McVerry

Author(s):  
Mark Stirling ◽  
Matthew Gerstenberger ◽  
Nicola Litchfield ◽  
Graeme McVerry ◽  
Warwick Smith ◽  
...  

We present a new probabilistic seismic hazard model for the Canterbury region, the model superseding the earlier model of Stirling et al. (1999, 2001). The updated model incorporates new onshore and offshore fault data, new seismicity data, new methods for the earthquake source parameterisation of both datasets, and new methods for estimation of the expected levels of Modified Mercalli Intensity (MMI) across the region. While the overall regional pattern of estimated hazard has not changed since the earlier seismic hazard model, there have been slight reductions in hazard in some areas (western Canterbury Plains and eastern Southern Alps), coupled with significant increases in hazard in one area (immediately northeast of Kaikoura). The changes to estimated acceleration for the new versus older model serve to show the extent that major changes to a multidisciplinary source model may impact the final estimates of hazard, while the new MMI estimates show the added impact of a new methodology for calculating MMI hazard.


2016 ◽  
Vol 21 (7) ◽  
pp. 1113-1157 ◽  
Author(s):  
Soumya K. Maiti ◽  
Sankar K. Nath ◽  
Manik D. Adhikari ◽  
Nishtha Srivastava ◽  
Probal Sengupta ◽  
...  

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.


2020 ◽  
Vol 13 (13) ◽  
Author(s):  
Ahmed Deif ◽  
Issa El-Hussain ◽  
Yousuf Alshijbi ◽  
Adel Mohamed El-Shahat Mohamed

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