On the Ground Motions Spatial Correlation for Vrancea Intermediate-Depth Earthquakes

  • Ionut Craciun
  • Radu Vacareanu
  • Florin Pavel
  • Veronica Coliba
Conference paper
First Online:
Part of the Springer Natural Hazards book series (SPRINGERNAT)

Abstract

The spatial correlation of ground motions is a subject extensively analysed in the literature, with many studies obtaining spatial correlation models for different datasets, using multiple ground motion prediction equations for various ground motion parameters, being a necessary tool in assessing the seismic risk of building portfolios or spatially distributed systems. A subject tackled mostly for shallow earthquakes datasets, in recent months, two studies considering a database consisting of strong ground motions generated by earthquakes originating from Vrancea intermediate-depth seismic source have been developed. The differences between the two studies consist of the approach in obtaining the correlation model, directly evaluating the correlation coefficients and using the semivariogram approach. A comparison of the two studies is made, resulting in different decay ratios for the same ground motion parameter, the main reasons being the restrains encountered in the first methodology and the subtraction of some ground motion records in the second study. An investigation regarding the influence of the dataset is performed by developing a correlation model for an adjusted dataset using the direct approach. Comparisons with other available models are performed, revealing higher correlation values and more gradual decays for the two studies discussed here, which is mainly caused by the different seismo-tectonic context of the Vrancea intermediate-depth source.

Keyword

Correlation coefficient Models Semivariogram Comparison 
This is a preview of subscription content, log in to check access

Notes

Acknowledgements

The results are obtained within the CoBPEE (Community Based Performance Earthquake Engineering) research project, financed by the Romanian National Authority for Scientific Research and Innovation, CNCS—UEFISCDI, project number PN-II-RU-TE-2014-4-0697. This support is gratefully acknowledged.

References

  1. Boore D, Gibbs J, Joyner W, Tinsley J, Ponti D (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(6):2737–2751CrossRefGoogle Scholar
  2. CEN (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
  3. Cimellaro GP, Stefano A, Reinhorn AM (2011) Intra-event spatial correlation of ground motion using L’Aquila earthquake ground motion data. In: 3rd ECCOMAS thematic conference on computational methods in structural dynamics and earthquake engineering, Corfu, Greece, pp 3091–3108Google Scholar
  4. Clark I, Harper W (2000) Practical geostatistics. Ecosse North America, Columbus, OhioGoogle Scholar
  5. Cornell CA (1968) Engineering seismic risk analysis. Bull Seismol Soc Am 58:1583–1606Google Scholar
  6. Esposito E, Iervolino I, d’Onofrio A, Santo A (2014) Simulation-based seismic risk assessment of gas distribution networks. Comput Aided Civil Infrastruct Eng 00:1–16Google Scholar
  7. Esposito S, Iervolino I (2011) PGA and PGV spatial correlation models based on European multievent datasets. Bull Seismol Soc Am 101(5):2532–2541CrossRefGoogle Scholar
  8. Esposito S, Iervolino I (2012) Spatial correlation of spectral acceleration in European data. Bull Seismol Soc Am 102(6):2781–2788CrossRefGoogle Scholar
  9. Foulser-Piggott R, Goda K (2015) Ground-motion prediction models for arias intensity and cumulative absolute velocity for Japanese earthquakes considering single-station sigma and within-event spatial correlation. Bull Seismol Soc Am 105(4):1903–1918CrossRefGoogle Scholar
  10. Goda K, Atkinson G (2009) Probabilistic characterization of spatially correlated response spectra for earthquakes in Japan. Bull Seismol Soc Am 99(5):3003–3020CrossRefGoogle Scholar
  11. Goda K, Atkinson G (2010) Intraevent spatial correlation of ground-motion parameters using SK-net data. Bull Seismol Soc Am 100(6):3055–3067CrossRefGoogle Scholar
  12. Goda K, Hong HP (2008a) Estimation of seismic loss for spatially distributed buildings. Earthq Spectra 24(4):889–910CrossRefGoogle Scholar
  13. Goda K, Hong HP (2008b) Spatial correlation of peak ground motions and response spectra. Bull Seismol Soc Am 98(1):354–365CrossRefGoogle Scholar
  14. Hong HP, Zhang Y, Goda K (2009) Effect of spatial correlation on estimated ground-motion prediction equations. Bull Seismol Soc Am 99(2A):928–934CrossRefGoogle Scholar
  15. Jayaram N, Baker JW (2009) Correlation model for spatially distributed ground-motion intensities. Earthq Eng Struct Dyn 38(15):1687–1708Google Scholar
  16. Kawakami H, Sharma S (1999) Statistical study of spatial variation of response spectrum using free field records of dense strong motion arrays. Earthq Eng Struct Dynam 28:1273–1294CrossRefGoogle Scholar
  17. Pavel F, Vacareanu R (2017) Spatial correlation of ground motions from Vrancea (Romania) intermediate-depth earthquakes. Bulletin of the Seismological Society of America 107(1),  https://doi.org/10.1785/0120160095
  18. Sokolov V, Wenzel F (2011a) Influence of spatial correlation of strong ground motion on uncertainty in earthquake loss estimation. Earthq Eng Struct Dynam 40(9):993–1009CrossRefGoogle Scholar
  19. 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):1339–1360CrossRefGoogle Scholar
  20. Sokolov V, Wenzel F (2013) 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):1909–1926CrossRefGoogle Scholar
  21. Sokolov V, Wenzel F, Jean WY, Wen KL (2010) Uncertainty and spatial correlation of earthquake ground motion in Taiwan. Terr Atmos Oceanic Sci (TAO) 21(6):905–921Google Scholar
  22. Vacareanu R, Pavel F, Craciun I, Aldea A, Calotescu I (2017) Correlation models for strong ground motions from Vrancea intermediate-depth seismic source. In: 16th World Conference on Earthquake Engineering, Santiago, Chile, January 9th to 13th 2017. Paper no. 2026Google Scholar
  23. Vacareanu R, Radulian M, Iancovici M, Pavel F, Neagu C (2015) Fore-arc and back-arc ground motion prediction model for Vrancea intermediate depth seismic source. J Earthq Eng 19:535–562CrossRefGoogle Scholar
  24. Wagener T, Goda K, Erdik M, Daniell J, Wenzel F (2016) A spatial correlation model of peak ground acceleration and response spectra based on data of the Istanbul earthquake rapid response and early warning system. Soil Dyn Earthq Eng 85:166–178CrossRefGoogle Scholar
  25. Wang M, Takada T (2005) Macrospatial correlation model of seismic ground motions. Earthq Spectra 21(4):1137–1156CrossRefGoogle Scholar
  26. Wesson RL, Perkins DM (2001) Spatial correlation of probabilistic earthquake ground motion and loss. Bull Seismol Soc Am 91(6):1498–1515Google Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Ionut Craciun
    • 1
  • Radu Vacareanu
    • 1
  • Florin Pavel
    • 1
  • Veronica Coliba
    • 1
  1. 1.Seismic Risk Assessment Research Center, Technical University of Civil Engineering of BucharestBucharestRomania

Personalised recommendations