Insights into Seismic Hazard from Big Data Analysis of Ground Motion Simulations

Insights into Seismic Hazard from Big Data Analysis of Ground Motion Simulations

Kristy F. Tiampo Javad Kazemian Hadi Ghofrani Yelena Kropivnitskaya Gero Michel 

Department of Geological Sciences and Cooperative Institute for Research in Environmental Sciences, University of Colorado Boulder, USA

Department of Earth Sciences, Western University, Canada

Chaucer Copenhagen, Denmark

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1-12
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DOI: 
https://doi.org/10.2495/SAFE-V9-N1-1-12
Received: 
N/A
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Revised: 
N/A
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Accepted: 
N/A
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Available online: 
N/A
| Citation

OPEN ACCESS

Abstract: 

Despite the fact that most seismic activity occurs along plate boundaries, large earthquakes do occur within the plates and result in significant human and economic losses. Unlike seismicity along the plate boundaries, this intraplate seismicity is distributed unevenly, is generally rare, and often poorly understood. For example, the most seismically active region in eastern canada is located in a stable continental region within the North American plate. While it has a relatively low rate of earthquake activity, this largely urban region has experienced six earthquakes of approximately magnitude six since 1663, with large earthquakes concentrated in regions of crustal weakness. montréal, located in the seismically active region of the western Quebec seismic zone, is one the largest and most populated cities in the eastern canada. Here we present the results of a high-performance computing application for ground motion simulations for montréal. The simulations are performed based on the pipelining implementation of the Eqhaz program suite. These high-resolution scenario shakemaps produces estimates of ground shaking that are not tied to particular scenario earthquakes, but are probabilistic in nature, and that can be combined with exposure values to estimate most likely risk and loss scenarios. These results can be used not only to estimate potential losses but to mitigate against risks and losses due to large events through better estimation of stability and damage and the directed implementation of earthquake resistant construction standards.

Keywords: 

big data, earthquake ground motions, seismic hazard, seismic risk

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