Testing the global applicability of ground-motion prediction equations for active shallow crustal regions

Bulletin of the Seismological Society of America

Volumn 102, Issue 2, 2012, Pages 707-721

  Delavaud, Elise ^a   Scherbaum, Frank ^a   Kuehn, Nicolas ^a   Allen, Trevor ^b  

^a UNIVERSITY OF POTSDAM   (Germany)

^b GEOSCIENCE AUSTRALIA   (Australia)

Author keywords

[No Author keywords available]

Indexed keywords

COLLABORATIVE EFFORTS; DATA SETS; DATA SUPPORT; EARTHQUAKE MODELS; GEOGRAPHIC REGIONS; GLOBAL STANDARDS; GROUND MOTIONS; GROUND-MOTION; GROUND-MOTION PREDICTION EQUATIONS; NON-INDIGENOUS; OBSERVATIONAL DATA; RANKING PROCESS; REGIONAL SCALE; RESEARCH INITIATIVES; SEISMIC HAZARDS; STRONG-MOTION; TARGET REGIONS;

DATA PROCESSING;

STATISTICAL TESTS;

CRUSTAL STRUCTURE; DATA SET; EARTHQUAKE PREDICTION; GROUND MOTION; HAZARD ASSESSMENT; NUMERICAL MODEL; SEISMIC DATA; STRONG MOTION; TESTING METHOD;

EID: 84859134402     PISSN: 00371106     EISSN: 19433573     Source Type: Journal    
DOI: 10.1785/0120110113     Document Type: Article

References (52)

1. Abrahamson, N. A., and W. J. Silva (2008). Summary of the Abrahamson & Silva NGA ground motion relations, Earthquake Spectra 24, no. 1, 67-97.
2. Akaike, H. (1973). Information theory and an extension of the maximum likelihood principle, in Petrov, B. N., and F. Csaki (Editors), Second International Symposium on Information Theory, Akademiai Kiado, Budapest, Hungary, 267-281.
3. Akkar, S., and J. J. Bommer (2007). Empirical prediction equations for peak ground velocity derived from strong-motion records from Europe and the Middle East, Bull. Seismol. Soc. Am. 97, no. 2, 511-530.
4. Akkar, S., and J. J. Bommer (2010). Empirical equations for the prediction of PGA, PGV, and spectral accelerations in Europe, the Mediterranean Region, and the Middle East, Seismol. Res. Lett. 81, no. 2, 195-206.
5. Akkar, S., and Z. Çaǧnan (2010). A local ground-motion predictive model for Turkey, and its comparison with other regional and global groundmotion models, Bull. Seismol. Soc. Am. 100, no. 6, 2978-2995.
6. Allen, T. I., and D. J. Wald (2009). Evaluation of ground-motion modeling techniques for use in global ShakeMap: A critique of instrumental ground-motion prediction equations, peak ground motion to macroseismic intensity conversions, and macroseismic intensity predictions in different tectonic settings, U.S. Geol. Surv. Open-File Rept. 2009-1047, 114 pp.
7. Allen, T. I., D. J. Wald, P. S. Earle, K. D. Marano, A. J. Hotovec, K. Lin, and M. G. Hearne (2009). An atlas of ShakeMaps and population exposure catalog for earthquake loss modeling, Bull. Earthquake Eng 7, no. 3, 701-718.
8. Ambraseys, N., and M. Free (1997). Surface-wave magnitude calculation for European region earthquakes, J. Earthquake Eng. 1, no. 1, 1-22.
9. Ambraseys, N. N., J. Douglas, S. K. Sarma, and P. M. Smit (2005). Equation for the estimation of strong ground motions from shallow crustal earthquakes using data from Europe and the Middle East: Horizontal peak ground acceleration and spectral acceleration, Bull. Earthquake Eng. 3, no. 1, 1-53.
10. Atkinson, G. M., and S. I. Kaka (2007). Relationships between felt intensity and instrumental ground motion in the central United States and California, Bull. Seismol. Soc. Am. 97, no. 2, 497-510.
11. Atkinson, G. M., and M. Morrison (2009). Observations on regional variability in ground-motion amplitudes for small-to-moderate earthquakes in North America, Bull. Seismol. Soc. Am. 99 no. 4, 2393-2409.
12. Atkinson, G. M., and E. Sonley (2000). Empirical relationships between modified Mercalli intensity and response spectra, Bull. Seismol. Soc. Am. 90, no. 2, 537-544.
13. Atkinson, G. M., and D. J. Wald (2007). "Did You Feel It?" intensity data: A surprisingly good measure of earthquake ground motion, Seismol. Res. Lett. 78, no. 3, 362-368.
14. Beauval, C., H. Oksuz, A. Laurendeau, E. Delavaud, F. Cotton, Ph. Guéguen, and N. Kühn (2012). On the testing of ground-motion prediction equations against small magnitude data, Bull. Seismol. Soc. Am., in press.
15. Beyer, K., and J. J. Bommer (2006). Relationships between median values and between aleatory variabilities for different definitions of the horizontal component of motion, Bull. Seismol. Soc. Am. 96, no. 4A, 1512-1522.
16. Berge-Thierry, C., F. Cotton, O. Scotti, D. A. Griot-Pommera, and Y. Fukushima (2003). New empirical response spectral attenuation laws for moderate European earthquakes, J. Earthquake Eng. 7, no. 2, 193-222.
17. Bishop, C. M. (2006). Pattern Recognition and Machine Learning, Springer, New York, 304 pp.
18. Bommer, J. J., B. Douglas, F. Scherbaum, F. Cotton, H. Bungum, and D. Fäh (2010). On the selection of ground-motion prediction equations for seismic hazard analysis, Seismol. Res. Lett. 81, no. 5, 783-793.
19. Bommer, J. J., P. J. Stafford, J. E. Alarcon, and S. Akkar (2007). The influence of magnitude range on empirical ground-motion prediction, Bull. Seismol. Soc. Am. 97, no. 6, 2152-2170.
20. Boore, D. M., and G. M. Atkinson (2008). 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, no. 1, 99-138.
21. Boore, D. M., W. B. Joyner, and T. E. Fumal (1997). Equations for estimatng horizontal response spectra and peak acceleration from western North American Earthquakes: A summary of recent work, Seismol. Res. Lett. 68, no. 1, 128-153.
22. Burnham, K. P., and D. R. Anderson (2002). Model Selection and Multimodel Inference: A Practical Information-Theoretic Approach Second Ed., Springer, New York, 488 pp.
23. Campbell, K. W., and Y. Bozorgnia (2007). Campbell-Bozorgnia NGA ground motion relations for the geometric mean horizontal component of peak and spectral ground motion parameters, PEER Report 2007/ 02, Pacific Earthquake Engineering Research, College of Engineering, University of California, Berkeley, California, 240 pp.
24. Campbell, K. W., and Y. Bozorgnia (2008). NGA ground motion model for the geometric mean horizontal component of PGA, PGV, PGD and 5%-damped linear elastic response spectra for periods ranging from 0.01 to 10 s, Earthquake Spectra 24, no. 1, 139-171.
25. Cauzzi, C., and E. Faccioli (2008). Broadband (0.05 to 20 s) prediction of displacement response spectra based on worldwide digital records, J. Seismol. 12, no. 4, 453-475.
26. Chiou, B., R. Darragh, N. Gregor, and W. Silva (2008). NGA project strongmotion database, Earthquake Spectra 24, no. 1, 3-21.
27. Chiou, B., and R. R. Youngs (2008). An NGA model for the average horizontal component of peak ground motion and response spectra, Earthquake Spectra 24, no. 1, 173-215.
28. Chiou, B., R. R. Youngs, N. A. Abrahamson, and K. Addo (2010). Groundmotion attenuation model for small-to-moderate shallow crustal earthquakes in California and its implications on regionalization of groundmotion prediction models, Earthquake Spectra 26, no. 4, 907-926.
29. Cotton, F., G. Pousse, F. Bonilla, and F. Scherbaum (2008). On the discrepancy of recent European ground-motion observations and predictions from empirical models: Analysis of KiK-net accelerometric data and point-sources stochastic simulations, Bull. Seismol. Soc. Am. 98, no. 5, 2244-2261.
30. Cotton, F., F. Scherbaum, J. J. Bommer, and H. Bungum (2006). Criteria for selecting and adjusting ground-motion models for specific target regions: Application to central Europe and rock sites, J. Seismol. 10, no. 2, 137-156.
31. Cua, G., D. J. Wald, T. I. Allen, D. Garcia, C. B. Worden, M. Gerstenberger, K. Lin, and K. Marano (2010). "Best Practices" for using macroseismic intensity and ground motion intensity conversion equations for hazard and loss models in GEM1, GEM Technical Report 2010-4, 67 pp.
32. Delavaud, E., F. Cotton, S. Akkar, F. Scherbaum, L. Danciu, C. Beauval, S. Drouet, J. Douglas, R. Basili, M. A. Sandikkaya, M. Segou, E. Faccioli, and N. Theodoulidis (2012). Toward a ground-motion logic tree for probabilistic seismic hazard assessment in Europe, J. Seismol., in press.
33. Delavaud, E., F. Scherbaum, N. Kühn, and C. Riggelsen (2009). Information-theoretic selection of ground-motion prediction equations for seismic hazard analysis: An applicability study using Californian data, Bull. Seismol. Soc. Am. 99, no. 6, 3248-3263.
34. Dewey, J. W., M. G. Hopper, D. J. Wald, V. Quitoriano, and E. R. Adams (2002). Intensity distribution and isoseismal maps for the Nisqually, Washington, earthquake of 28 February 2001, U.S. Geol. Surv. Openfile Rept. 20020346, 57 pp.
35. Douglas, J. (2007). On the regional dependence of earthquake response spectra, ISET Journal of Earthquake Technology 44, no. 1, 71-99.
36. Douglas, J. (2011). Ground-motion prediction equations 1964-2010, Final Report BRGM/RP-59356-FR, 446 pp.
37. Douglas, J., and R. Mohais (2009). Comparing predicted and observed ground motions from subduction earthquakes in the Lesser Antilles, J. Seismol. 13, no. 4, 577-587.
38. Ekström, G., and A. M. Dziewonski (1988). Evidence of bias in estimations of earthquake size, Nature 332, 319-323.
39. Giardini, D. (1999). The Global Seismic Hazard Assessment Program (GSHAP)-1992/1999, Ann. Geofisc. 42, no. 6, 957-974.
40. Idriss, I. M. (2008). An NGA empirical model for estimating the horizontal spectral values generated by shallow crustal earthquakes, Earthquake Spectra 24, no. 1, 217-242.
41. Kaklamanos, J., and L. G. Baise (2011). Model validation and comparisons of the Next Generation Attenuation of ground motions (NGA-West) project, Bull. Seismol. Soc. Am. 101, no. 1, 160-175.
42. Kanno, T., A. Narita, N. Morikawa, H. Fujirawa, and Y. Fukushima (2006). A new attenuation relation for strong ground motion in Japan based on recorded data, Bull. Seismol. Soc. Am. 96, no. 3, 879-897.
43. Musson, R. M. W. (2009). Ground motion and probabilistic hazard, Bull. Earthquake Eng. 7, 575-589.
44. Perǔs, I., and P. Fajfar (2009). How reliable are the ground-motion prediction equations?, in 20th International Conf. on Structural Mechanics in Reactor Technology, Espoo, Finland, August 9-14, paper 1662.
45. Scasserra, G., J. P. Stewart, P. Bazzurro, G. Lanzo, and F. Mollaioli (2009). A comparison of NGA ground-motion prediction equations to Italian data, Bull. Seismol. Soc. Am. 99, no. 5, 2961-2978.
46. E. Delavaud, F. Scherbaum, N. Kuehn, and T. Allen Scherbaum, F., and N. Kühn (2011). Logic tree branch weights and probabilities: Summing up to one is not enough, Earthquake Spectra 27, 1237-1251.
47. Scherbaum, F., E. Delavaud, and C. Riggelsen (2009). Model selection in seismic hazard analysis: An information-theoretic perspective, Bull. Seismol. Soc. Am. 99, no. 6, 3234-3247.
48. Scherbaum, F., N. Kühn, M. Ohrnberger, and A. Köhler (2010). Exploring the proximity of ground-motion models using high-dimensional visualization techniques, Earthquake Spectra 26, no. 4, 1117-1138.
49. Stafford, P. J., F. O. Strasser, and J. J. Bommer (2008). An evaluation of the applicability of the NGA models to ground-motion prediction in the Euro-Mediterranean region, Bull. Earthquake Eng. 6, no. 2, 149-177.
50. Wald, D. J., and T. I. Allen (2007). Topographic slope as a proxy for seismic site conditions and amplification, Bull. Seismol. Soc. Am. 97, no. 5, 1379-1395.
51. Wells, D. L., and K. J. Coppersmith (1994). New empirical relationships among magnitude, rupture length, rupture width, rupture area, and surface displacement, Bull. Seismol. Soc. Am. 84, no. 4, 974-1002.
52. Zhao, J. X., J. Zhang, A. Asano, Y. Ohno, T. Oouchi, T. Takahashi, H. Ogawa, K. Irikura, H. K. Thio, P. Somerville, Y. Fukushima, and Y. Fukushima (2006). Attenuation relations of strong ground motion in Japan using site classification based on predominant period, Bull. Seismol. Soc. Am. 96, no. 3, 898-913.