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

Page: 
1-12
|
DOI: 
https://doi.org/10.2495/SAFE-V9-N1-1-12
Received: 
N/A
|
Accepted: 
N/A
|
Published: 
24 January 2019
| 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

  References

[1] Kouzes, R.T., Anderson, G.A., Elbert, S.T., Gorton, I. & Gracio, D.K., The changing paradigm of data-intensive computing. Computer, 42(1), pp. 26–34, 2009. https://doi.org/10.1109/mc.2009.26

[2] Ma, Y., Wang, L., Liu, P. & Ranjan, R., Towards building a data-intensive index for big data computing – A case study of Remote Sensing data processing. Information Sciences, 319, pp. 171–188, 2015. https://doi.org/10.1016/j.ins.2014.10.006

[3] Moore, R., Prince, T.A. & Ellisman, M., Data-intensive computing and digital libraries, Communications of the ACM, 41(11), pp. 56–62, 1998. https://doi.org/10.1145/287831.287840

[4] Miller, S.D., Kleese van Dam, K. & Li, D., Challenges in Data Intensive Analysis at Scientific Experimental User Facilities. Springer: Berlin, pp. 249–284, 2011.

[5] McAfee, A. & Brynjolfsson, E., Big data: The management revolution. Harvard Business Review, 2012.

[6] Hu, H., Wen, Y., Chua, T.-S. & Li, X., Toward scalable systems for big data analytics: a technology tutorial. IEEE Access, 2, pp. 652–687, 2014. https://doi.org/10.1109/access.2014.2332453

[7] U.S. Department of Energy, The Office of Science data-management challenge, Technical Report 1–2, 2004.

[8] U.S. Department of Energy, Synergistic challenges in data-intensive science and exascale computing, Summary Report of the Advanced Scientific Computing Advisory Committee (ASCAC) Subcommittee, 2013.

[9] Dilling, L. & Lemos, M.C., Creating usable science: opportunities and constraints for climate knowledge use and their implications for science policy. Global Environmental Change, 21, pp. 680–689, 2011. https://doi.org/10.1016/j.gloenvcha.2010.11.006

[10] IBM, IBM Knowledge Center available at http://www-01.ibm.com/support/knowledgecenter, 2014.

[11] Kropivnitskaya, Y., Qin, J., Tiampo, K.F. & Bauer, M.A., A pipelining implementation for high resolution seismic hazard maps production. Procedia Computer Science; 51, pp. 1473–1482, 2015. https://doi.org/10.1016/j.procs.2015.05.337

[12] Bauer, M.A., Biem, A., McIntyre, S. & Xie, Y., A pipelining implementation for parsing X-ray diffraction source data and removing the background noise. Journal of Physics: Conference Series, 256, p. 012017, 2010. https://doi.org/10.1088/1742-6596/256/1/012017

[13] Cornell, C.A., Engineering seismic risk analysis. Bulletin of the Seismological Society of America, 58(5), pp. 1583–1606, 1968.

[14] McGuire, R., Seismic hazard and risk analysis. Earthquake Engineering Research Institute, Oakland, California, 2004.

[15] McGuire, R., Probabilistic seismic hazard analysis: early history. Earthquake Engineering & Structural Dynamics, 37, pp. 329–338, 2008. https://doi.org/10.1002/eqe.765

[16] Musson, R.M.W. & Henni, P.H.O., Methodological considerations of probabilistic seismic hazard mapping. Soil Dynamics and Earthquake Engineering, 21, pp. 385–403, 2001. https://doi.org/10.1016/s0267-7261(01)00020-3

[17] Assatourians, K. & Atkinson, G.M., EqHaz: An open-source probabilistic seismichazard code based on the Monte Carlo simulation approach. Seismological Research Letters, 84, pp. 516–524, 2013. https://doi.org/10.1785/0220120102

[18] Musson, R.M.W., Determination of design earthquakes in seismic hazard analysis through Monte Carlo simulation. Journal of Earthquake Engineering, 3, pp. 463–474, 1999. https://doi.org/10.1080/13632469909350355

[19] Adams, J. & Halchuk, S., Fourth generation seismic hazard maps of Canada: Values for over 650 Canadian localities intended for the 2005 National Building Code of Canada. Geological Survey of Canada Open File 4459, 2003.

[20] Adams, J. & Halchuk S., Fourth-generation seismic hazard maps for the 2005 national building code of Canada. Proceedings of the 13th World Conference on Earthquake Engineering, Vancouver, Canada. Paper 2502 on CD-ROM, 2004.

[21] Halchuk, S. & Adams, J., Fourth generation seismic hazard maps of Canada: maps and grid values to be used with the 2005 National Building Code of Canada, Geological Survey of Canada Open File 5813, 2008.

[22] UNSD Demographic Statistics, UnData, available at http://data.un.org/, 2011.

[23] National Building Code of Canada, Associate Committee on the National Building Code, National Research Council of Canada, Ottawa, ON, 2016.

[24] AIR Worldwide, Study of impact and the insurance and economic cost of a major earthquake in British Columbia and Ontario/Québec, IBC of Canada, 2013.

[25] Adams, J. & Basham, P.W., The seismicity and seismotectonics of eastern Canada. Neotectonics of North America, ed. D.B. Slemmons, E.R. Engdahl, M.D. Zoback, D.D. Blackwell, Geological Society of America, Boulder, CO, 1991.

[26] Atkinson, G. & Goda K., Effects of seismicity models and new ground motion prediction equations on seismic hazard assessment for four Canadian cities. Bulletin of the Seismological Society of America, 101, pp. 176–189, 2011. https://doi.org/10.1785/0120100093

[27] Rosset, P., Bour-Belvaux, M. & Chouinard, L., Microzonation models for Montréal with respect to VS30. Bulletin of Earthquake Engineering, 13(8), pp. 2225–2239, 2015. https://doi.org/10.1007/s10518-014-9716-8

[28] Hong, H.P. & Goda, K., A comparison of seismic-hazard and risk deaggregation. Bulletin of the Seismological Society of America, 96(6), pp. 2021–2039, 2006. https://doi.org/10.1785/0120050238

[29] Boore, D.M. & Atkinson, G.M., Ground-motion prediction equations for the average horizontal component of PGA, PGV, and 5%-damped PSA at spectral periods between 0.01 s and 10.0 s. Earthquake Spectra, 24(1), pp. 99–138, 2008. https://doi.org/10.1193/1.2830434

[30] Halchuk, S., Allen, T.I., Adams, J. & Rogers, G.C., Fifth generation seismic hazard model input files as proposed to produce values for the 2015 National Building Code of Canada. Geological Survey of Canada, Open File 7576, 2014.

[31] Pezeshk, S., Zandieh, A. & Tavakoli, B., Hybrid empirical ground-motion prediction equations for eastern North America using NGA models and updated seismological parameters. Bulletin of the Seismological Society of America, 101(4), pp. 1859–1870, 2011. https://doi.org/10.1785/0120100144