Advertisement

Bulletin of Earthquake Engineering

, Volume 13, Issue 5, pp 1281–1301 | Cite as

On the relation between point-wise and multiple-location probabilistic seismic hazard assessments

  • Vladimir SokolovEmail author
  • Friedemann Wenzel
Original Research Paper

Abstract

The results of classical probabilistic seismic hazard analysis (PSHA) contain no information about simultaneous ground motions at different sites during a particular earthquake. Seismic risk analysis for distributed critical structures requires estimates of the level of earthquake shaking that are likely to occur concurrently at multiple locations: whether the vulnerable elements of a lifeline system are likely to be simultaneously affected by shaking of sufficient strength to disable them and whether the shaking at any one of critical points may be sufficient to cause failure of the whole system. While the analysis of lifeline performance requires multiple-location estimations, the sparsely located elements of a network or critical facilities are designed on the basis of point-wise PSHA. In this paper we study specific features of multiple-location PSHA, as compared with the classical point-wise PSHA, using Monte Carlo simulations. We analyze the level of ground motion (PGA) that will be exceeded at any site inside a particular area or at several sites simultaneously with reference annual probability. The analysis has been performed for regions of Western and South-Western Germany, Northern and Eastern Taiwan, which represent different levels of seismicity (low, moderate and high, respectively). The relationship between the multiple-location and point-wise estimations are analyzed and quantified. Results of the study may be used to decide whether it may be possible to utilize the procedure of point-wise PSHA in particular cases of multiple-location PSHA, i.e. for assessment of maximum level of ground motion among several sites, or for estimation a reasonable lower safety level when considering simultaneous exceedances.

Keywords

Multiple-location probabilistic seismic hazard Ground-motion correlation Importance factor 

Notes

Acknowledgments

We would like to thank Wen-Yu Jean, Gottfried Grünthal and Dietrich Stromeyer for providing necessary data used in this study, valuable comments and suggestions. The constructive comments from anonymous reviewers are gratefully acknowledged. This work was sponsored by Deutsche Forschungsgemeinschaft (DFG), Germany, project WE 1394/20-1.

References

  1. Akkar S, Bommer JJ (2007) Prediction of elastic displacement response spectra in Europe and the Middle East. Earthq Eng Struct Dyn 36(10):1275–1301CrossRefGoogle Scholar
  2. Assatourians K, Atkinson GM (2013) EqHaz: an open-source probabilistic seismic-hazard code based on the Monte Carlo simulation approach. Seismol Res Lett 84:516–524CrossRefGoogle Scholar
  3. Baker JW, Jayaram N (2008) Effects of spatial correlation of ground motion parameters for multi-site seismic risk assessment: collaborative research with Stanford University and AIR. Final Technical Report. Report for U.S. Geological Survey National Earthquake Hazards Reduction Program (NEHRP) External Research Program Award 07HQGR0031Google Scholar
  4. Bommer JJ, Crowley H (2006) The influence of ground-motion variability in earthquake loss modelling. Bull Earthq Eng 4(3):231–248. doi: 10.1007/s10518-006-9008-z CrossRefGoogle Scholar
  5. Bommer JJ, Douglas J, Strasser FO (2003) Style-of-faulting in ground motion-prediction equations. Bull Earthq Eng 1:171–203. doi: 10.1023/A:1026323123154 CrossRefGoogle Scholar
  6. Boore DM, Gibbs JF, Joyner WB, Tinsley JC, Ponti DJ (2003) Estimated ground motion from the 1994 Northridge, California, Earthquake at the site of the Interstate 10 and La Cienega Boulevard Bridge collapse. West Los Angeles, California. Bull Seismol Soc Am 93:2737–2751. doi: 10.1785/0120020197 CrossRefGoogle Scholar
  7. Burkhard M, Grünthal G (2009) Seismic source zone characterization for the seismic hazard assessment project PEGASOS by the expert Group 2 (EG 1b). Swiss J Geosci 102:149–188CrossRefGoogle Scholar
  8. CEN (European Committee for Standardization) (2004) Eurocode 8: design of structures for earthquake resistance, part 1: general rules, seismic actions and rules for buildings. EN 1998–1:2004. Brussels, BelgiumGoogle Scholar
  9. Cornell CA (1968) Engineering seismic risk analysis. Bull Seismol Soc Am 58:1583–1606Google Scholar
  10. Crowley H, Bommer JJ (2006) Modelling seismic hazard in earthquake loss models with spatially distributed exposure. Bull Earthq Eng 4:249–273. doi: 10.1007/s10518-006-9011-4
  11. Du W, Wang W (2013) Intra-event spatial correlations for cumulative absolute velocity, Arias intensity, and spectral accelerations based on regional site conditions. Bull Seismol Soc Am 103:1117–1129. doi: 10.1785/0120120185 CrossRefGoogle Scholar
  12. Ebel JE, Kafka AL (1999) A Monte Carlo approach to seismic hazard analysis. Bull Seismol Soc Am 89:854–866Google Scholar
  13. Federal Emergency Management Agency (FEMA) (2008) FEMA 366: HAZUS estimated earthquake losses for the United States. Federal Emergency Management Agency. Washington DCGoogle Scholar
  14. Goda K, Atkinson GM (2009) Probabilistic characterization of spatially correlated response spectra for earthquakes in Japan. Bull Seismol Soc Am 99:3003–3020. doi: 10.1785/0120090007 CrossRefGoogle Scholar
  15. Goda K, Hong HP (2008) Spatial correlation of peak ground motions and response spectra. Bull Seismol Soc Am 98:354–365. doi: 10.1785/0120070078 CrossRefGoogle Scholar
  16. Grünthal G, Arvidsson R, Bosse Ch (2010) Earthquake Model for the European-Mediterranean Region for the Purpose of GEM1. Scientific Technical Report STR10/04, p. 35 http://www.globalquakemodel.org/media/publication/GEM-TechnicalReport_2010-E2.pdf
  17. Jayaram N, Baker JW (2009) Correlation models for spatially distributed ground motion intensities. Earthq Eng Struct Dyn 38:1687–1708. doi: 10.1002/eqe.922 CrossRefGoogle Scholar
  18. Loh CH, Jean WY (1997) Seismic zoning on ground motion in Taiwan area. In: Proceedings of 14th international conference on soil mechanics and foundation engineering, Germany, 6–12 September, 1997, pp 71–79Google Scholar
  19. Malhotra PK (2008) Seismic design loads from site-specific and aggregate hazard analyses. Bull Seismol Soc A 98:1849–1862. doi: 10.1785/0120070241 CrossRefGoogle Scholar
  20. McGuire RK (2001) Deterministic vs. probabilistic earthquake hazard and risks. Soil Dyn Earthq Eng 21:377–384CrossRefGoogle Scholar
  21. McGuire RK (2004) Seismic hazard and risk analysis. Earthquake Engineering Research Institute, Oakland 240 pGoogle Scholar
  22. McVerry GH, Rhoades DA, Smith WD (2004) Joint hazard of earthquake shaking at multiple locations. In: Proceedings of the 13th world conference on earthquake engineering, Vancouver, Canada, August 1–6, 2004. Paper 646Google Scholar
  23. Musson RMW (1999) Determination of design earthquakes in seismic hazard analysis through Monte Carlo simulation. J Earthq Eng 3(4):463–474Google Scholar
  24. Musson RMW (2012) PSHA validated by quazi observational means. Seismol Res Lett 83:130–134CrossRefGoogle Scholar
  25. NEHRP Recommended Provisions for Seismic Regulations for New Buildings and Other Structures (2004) FEMA 450, 2003 Edition, Part 1: Provisions. Chapter 14. Nonbuilding Structure Design Requirements Building Seismic Safety Council, Washington, DC, pp 233–260Google Scholar
  26. NFP06-013 (1995) Regles de construction parasismique aux batiments, dites regles PS92, norme francaise, AFNORGoogle Scholar
  27. Rhoades DA, McVerry GH (2001) Joint hazard of earthquake shaking at two or more locations. Earthq Spectra 17(4):697–710CrossRefGoogle Scholar
  28. Park J, Bazzurro P, Baker JW (2007) Modeling spatial correlation of ground motion intensity measures for regional seismic hazard and portfolio loss estimations. In: Kanda J, Takada T, Furuta H (eds) Applications of statistics and probability in civil engineering. Taylor & Francis Group, London, pp 1–8Google Scholar
  29. Seismic Force Requirements for Buildings in Taiwan Extracted from: 2005 Seismic Design Code for Buildings in Taiwan (2005) Translated by: National Center for Research on Earthquake Engineering. http://iisee.kenken.go.jp/worldlist/51_Taiwan/51_Taiwan_Code.pdf
  30. Sokolov V, Wenzel F (2011a) Influence of spatial correlation of strong ground-motion on uncertainty in earthquake loss estimation. Earthq Eng Struct Dyn 40:993–1009. doi: 10.1002/eqe.1074 CrossRefGoogle Scholar
  31. Sokolov V, Wenzel F (2011b) Influence of ground-motion correlation on probabilistic assessments of seismic hazard and loss: sensitivity analysis. Bull Earthq Eng 9(5):1339–1360. doi: 10.1007/s10518-011-9264-4 CrossRefGoogle Scholar
  32. Sokolov V, Wenzel F (2013a) Spatial correlation of ground-motions in estimating seismic hazard to civil infrastructure. In: Tesfamariam S, Goda K (eds) Seismic risk analysis and management of civil infrastructure systems. Woodhead Publishing Ltd, Cambridge, pp 57–78. doi: 10.1533/9780857098986.1.57
  33. Sokolov V, Wenzel F (2013b) Further analysis of the influence of site conditions and earthquake magnitude on ground-motion within-earthquake correlation: analysis of PGA and PGV data from the K-NET and the KiK-net (Japan) networks. Bull Earthq Eng 11(6):1909–1926. doi: 10.1007/s10518-013-9493-9 CrossRefGoogle Scholar
  34. Sokolov V, Wenzel F, Jean WY, Wen KL (2010) Uncertainty and spatial correlation of earthquake ground motion in Taiwan. Terr Atmos Ocean Sci (TAO) 21:905–921. doi: 10.3319/TAO.2010.05.03.01(T)
  35. Sokolov V, Wenzel F, Wen KL, Jean WY (2012) On the influence of site conditions and earthquake magnitude on ground-motion within-earthquake correlation: analysis of PGA data from TSMIP (Taiwan) network. Bull Earthq Eng 10(5):1401–1429. doi: 10.1007/s10518-012-9368-5 CrossRefGoogle Scholar
  36. Wang M, Takada T (2005) Macrospatial correlation model of seismic ground motions. Earthq Spectra 21(4):1137–1156. doi: 10.1193/1.2083887 CrossRefGoogle Scholar
  37. Wesson RL, Perkins DM (2001) Spatial correlation of probabilistic earthquake ground motion and loss. Bull Seism Soc Am 91:1498–1515CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2014

Authors and Affiliations

  1. 1.Geophysical InstituteKarlsruhe Institute of Technology (KIT)KarlsruheGermany

Personalised recommendations