Journal of Seismology

, Volume 16, Issue 3, pp 409–433 | Cite as

Intensity attenuation for active crustal regions

  • Trevor I. Allen
  • David J. Wald
  • C. Bruce Worden
Original Article


We develop globally applicable macroseismic intensity prediction equations (IPEs) for earthquakes of moment magnitude M W 5.0–7.9 and intensities of degree II and greater for distances less than 300 km for active crustal regions. The IPEs are developed for two distance metrics: closest distance to rupture (R rup) and hypocentral distance (R hyp). The key objective for developing the model based on hypocentral distance—in addition to more rigorous and standard measure R rup—is to provide an IPE which can be used in near real-time earthquake response systems for earthquakes anywhere in the world, where information regarding the rupture dimensions of a fault may not be known in the immediate aftermath of the event. We observe that our models, particularly the model for the R rup distance metric, generally have low median residuals with magnitude and distance. In particular, we address whether the direct use of IPEs leads to a reduction in overall uncertainties when compared with methods which use a combination of ground-motion prediction equations and ground motion to intensity conversion equations. Finally, using topographic gradient as a proxy and median model predictions, we derive intensity-based site amplification factors. These factors lead to a small reduction of residuals at shallow gradients at strong shaking levels. However, the overall effect on total median residuals is relatively small. This is in part due to the observation that the median site condition for intensity observations used to develop these IPEs is approximately near the National Earthquake Hazard Reduction Program CD site-class boundary.


Macroseismic intensity attenuation Ground-motion to intensity conversion Site response 



Discussion of preliminary results with Daniel Garcia, Georgia Cua, and Paul Earle were very valuable throughout this study in addition to their thoughtful reviews of this manuscript. Nick Horspool and Clive Collins are thanked for their additional reviews that helped improve this manuscript. We also thank Dino Bindi and an anonymous reviewer for their constructive feedback. Generic Mapping Tools (Wessel and Smith 1991) was used to generate all maps within the manuscript. Trevor Allen publishes with the permission of the Chief Executive Officer of Geoscience Australia.


  1. Abrahamson N, Atkinson G, Boore D, Bozorgnia Y, Campbell K, Chiou B, Idriss IM, Silva W, Youngs R (2008) Comparisons of the NGA ground-motion relations. Earthq Spectra 24(1):45–66CrossRefGoogle Scholar
  2. Akkar S, Bommer JJ (2007) Prediction of elastic displacement response spectra in Europe and the Middle East. Earthq Eng Struct Dyn 36:1275–1301CrossRefGoogle Scholar
  3. Akkar S, Bommer JJ (2010) Empirical equations for the prediction of PGA, PGV, and spectral accelerations in Europe, the Mediterranean region, and the Middle East. Seism Res Lett 81(2):195–206CrossRefGoogle Scholar
  4. Allen TI, Marano KD, Earle PS, Wald DJ (2009a) PAGER-CAT: a composite earthquake catalog for calibrating global fatality models. Seism Res Lett 80(1):57–62CrossRefGoogle Scholar
  5. Allen TI, Wald DJ (2009a) 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. Open-File Report 2009-1047. U.S. Geological Survey, Golden. 114 pGoogle Scholar
  6. Allen TI, Wald DJ (2009b) On the use of high-resolution topographic data as a proxy for seismic site conditions (V S 30). Bull Seism Soc Am 99(2A):935–943CrossRefGoogle Scholar
  7. Allen TI, Wald DJ, Earle PS, Marano KD, Hotovec AJ, Lin K, Hearne M (2009b) An Atlas of ShakeMaps and population exposure catalog for earthquake loss modeling. Bull Earthq Eng 7(3):701–718. doi: 10.1007/s10518-10009-19120-y CrossRefGoogle Scholar
  8. Allen TI, Wald DJ, Hotovec AJ, Lin K, Earle PS, Marano KD (2008) An Atlas of ShakeMaps for selected global earthquakes. Open-File Report 2008-1236. U.S. Geological Survey, Golden. 47 pGoogle Scholar
  9. Archuleta RJ (1982) Analysis of near-source static and dynamic measurements from the 1979 Imperial Valley earthquake. Bull Seism Soc Am 72(6A):1927–1956Google Scholar
  10. Atkinson GM, Kaka SI (2007) Relationships between felt intensity and instrumental ground motion. Bull Seism Soc Am 97(2):497–510CrossRefGoogle Scholar
  11. Atkinson GM, Wald DJ (2007) "Did You Feel It?" intensity data: a surprisingly good measure of earthquake ground motion. Seism Res Lett 78(3):362–368CrossRefGoogle Scholar
  12. Bakun WH, Scotti O (2006) Regional intensity attenuation models for France and the estimation of magnitude and location of historical earthquakes. Geophys J Int 164:596–610CrossRefGoogle Scholar
  13. Bommer JJ, Akkar S (2012) Consistent source-to-site distance metrics in ground-motion prediction equations and seismic source models for PSHA. Earthq Spectra 28(1). doi: 10.1193/1.3672994
  14. Bommer JJ, Stafford PJ, Alarcón JE, Akkar S (2007) The influence of magnitude range on empirical ground-motion prediction. Bull Seism Soc Am 97(6):2152–2170CrossRefGoogle Scholar
  15. Boore DM, Atkinson GM (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. Earthq Spectra 24(1):99–138CrossRefGoogle Scholar
  16. Boore DM, Joyner WB, Fumal TE (1997) Equations for estimating horizontal response spectra and peak acceleration from Western North American earthquakes: a summary of recent work. Seism Res Lett 68(1):128–153CrossRefGoogle Scholar
  17. Borcherdt RD (1970) Effects of local geology on ground motion near San Francisco Bay. Bull Seism Soc Am 60(1):29–61Google Scholar
  18. Borcherdt RD (1994) Estimates of site-dependent response spectra for design (methodology and justification). Earthq Spectra 10(4):617–653CrossRefGoogle Scholar
  19. Building Seismic Safety Council (2004) NEHRP recommended provisions for seismic regulations for new buildings and other structures, 2003 edition. Federal Emergency Management Agency 450, Washington, D.C, 338 pGoogle Scholar
  20. Campbell KW, Bozorgnia Y (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. Earthq Spectra 24(1):139–171CrossRefGoogle Scholar
  21. Castellaro S, Mulargia F, Rossi PL (2008) Vs30: proxy for seismic amplification? Seism Res Lett 79(4):540–543CrossRefGoogle Scholar
  22. Chiou B, Darragh R, Gregor N, Silva W (2008) NGA project strong-motion database. Earthq Spectra 24(1):23–44CrossRefGoogle Scholar
  23. Chiou BS-J, Youngs RR (2008) An NGA model for the average horizontal component of peak ground motion and response spectra. Earthq Spectra 24(1):173–215CrossRefGoogle Scholar
  24. Cua G, Wald DJ, Allen TI, Garcia D, Worden CB, Lin K, Marano K (2010) “Best practices” for using macroseismic intensity and ground motion-intensity conversion equations for hazard and loss models in GEM1. GEM Technical Report n. 6. GEM Foundation, Pavia, Italy, p 57Google Scholar
  25. Dengler LA, Dewey JW (1998) An intensity survey of households affected by the Northridge, California, earthquake of 17 January, 1994. Bull Seism Soc Am 88(2):441–462Google Scholar
  26. Dobry R, Borcherdt RD, Crouse CB, Idriss IM, Joyner WB, Martin GR, Power MS, Rinne EE, Seed RB (2000) New site coefficients and site classification system used in recent Building Seismic Code provisions. Earthquake Spectra 16(1):41–67CrossRefGoogle Scholar
  27. Douglas J (2004) An investigation of analysis of variance as a tool for exploring regional differences in strong ground motions. J Seismology 8:485–496CrossRefGoogle Scholar
  28. Douglas J (2007) On the regional dependence of earthquake response spectra. ISET J Earthq Tech 44(1):471–499, Paper no. 477Google Scholar
  29. Dowrick DJ, Rhoades DA (2005) Revised models for attenuation of Modified Mercalli Intensity in New Zealand earthquakes. NZ Soc Earthq Eng 38(4):185–214Google Scholar
  30. Earle PS, Wald DJ, Jaiswal KS, Allen TI, Hearne MG, Marano KD, Hotovec AJ, Fee JM (2009) Prompt Assessment of Global Earthquakes for Response (PAGER): a system for rapidly determining the impact of earthquakes worldwide. Open-File Report 2009-1131. U.S. Geological Survey, Golden. 15 pGoogle Scholar
  31. Edwards MR, Robinson D, McAneney KJ, Schneider J (2004) Vulnerability of residential structures in Australia. In: 13th World Conf. Earthq. Eng., Vancouver, Canada, August 1–6, 2004. vol 2985. Paper 2985Google Scholar
  32. Eguchi RT, Goltz JD, Seligson HA, Flores PJ, Blais NC, Heaton TH, Bortugno E (1997) Real-time loss estimation as an emergency response decision support system: the early post-earthquake damage assessment tool (EPEDAT). Earthq Spectra 13(4):815–832CrossRefGoogle Scholar
  33. Electric Power Research Institute (2003) CEUS ground motion project: model development and desults. Electric Power Research Institute Report 1008910. Palo Alto, CA. 105 pGoogle Scholar
  34. Engdahl ER, Villaseñor A (2002) Global seismicity: 1900–1999. In: Lee WK, Kanamori H, Jennings PC, Kisslinger C (eds) International handbook of earthquake engineering and seismology, vol 81A. Academic, Amsterdam, pp 665–690CrossRefGoogle Scholar
  35. Farr TG, Kobrick M (2000) Shuttle radar topography mission produces a wealth of data. EOS Trans 81:583–585CrossRefGoogle Scholar
  36. Harmandar E, Oye V, Lindholm C, Bungum H (2007) Soil condition maps based on topographic slope. NERIES JRA3 Report. Network of Earthquake Research Institutes for Earthquake Seismology (NERIES) JRA3 Report: 20 pGoogle Scholar
  37. Hayes GP, Wald DJ (2009) Developing framework to constrain the geometry of the seismic rupture plane on subduction interfaces a priori—a probabilistic approach. Geophys J Int 176:951–964CrossRefGoogle Scholar
  38. Jaiswal KS, Wald DJ (2008) Creating a global building inventory for earthquake loss assessment and risk management. Open-File Report 2008-1160. U.S. Geological Survey, Golden. 103 pGoogle Scholar
  39. Jaiswal KS, Wald DJ, Earle PS, Porter KA, Hearne M (2009a) Earthquake casualty models within the USGS Prompt Assessment of Global Earthquakes for Response (PAGER) System. In: Second International Workshop on Disaster Casualties, University of Cambridge, UK, 15–16 June 2009Google Scholar
  40. Jaiswal KS, Wald DJ, Hearne M (2009b) Estimating casualties for large earthquakes worldwide using an empirical approach. Open-File Report 2009-1136. U.S. Geological Survey, Golden. 78 pGoogle Scholar
  41. Ji C, Helmberger DV, Wald DJ, Ma K-F (2003) Slip history and dynamic implications of the 1999 Chi-Chi, Taiwan, earthquake. J Geophys Res 108 (B9): doi:10.1029/2002JB001764
  42. Johnston AC, Coppersmith KJ, Kanter LR, Cornell CA (1994) The earthquakes of stable continental regions, volume 1—assessment of large earthquake potential. vol TR-102261-V1. Electric Power Research Institute, Palo Alto, CaliforniaGoogle Scholar
  43. Miura H, Midorikawa S, Fujimoto K, Pacheco BM, Yamanaka H (2008) Earthquake damage estimation in Metro Manila, Philippines based on seismic performance of buildings evaluated by local experts’ judgments. Soil Dyn Earthq Eng 28:764–777CrossRefGoogle Scholar
  44. Musson RMW (2000) Intensity-based seismic risk assessment. Soil Dyn Earthq Eng 20:353–360CrossRefGoogle Scholar
  45. Musson RMW, Grünthal G, Stucchi M (2009) The comparison of macroseismic intensity scales. J Seismol. doi: 10.1007/s10950-10009-19172-10950
  46. National Institute of Building Sciences (2003) Multi-hazard loss estimation methodology, earthquake model, HAZUS-MH MR1: advanced engineering and building module, technical and user's manual. FEMA. Federal Emergency Management Agency. 119 ppGoogle Scholar
  47. Porter KA, Jaiswal KS, Wald DJ, Greene M, Comartin C (2008) WHE-PAGER Project: a new initiative in estimating global building inventory and its seismic vulnerability. In: 14th World Conf. Earthq. Eng., Beijing, China. Paper S23-016Google Scholar
  48. Rey J, Faccioli E, Bommer JJ (2002) Derivation of design soil coefficients (S) and response spectral shapes for Eurocode 8 using the European Strong-Motion Database. J Seismol 6:547–555CrossRefGoogle Scholar
  49. Scherbaum F, Schmedes J, Cotton F (2004) On the conversion of source-to-site distance measures for extended earthquake source models. Bull Seism Soc Am 94(3):1053–1069CrossRefGoogle Scholar
  50. Sokolov V, Furumura T, Wenzel F (2010) On the use of JMA intensity in earthquake early warning systems. Bull Earthq Eng 8:767–786CrossRefGoogle Scholar
  51. Sørensen MB, Stromeyer D, Grünthal G (2009) Attenuation of macroseismic intensity: a new relation for the Marmara Sea region, northwest Turkey. Bull Seism Soc Am 99(2A):538–553CrossRefGoogle Scholar
  52. The MathWorks (2010) MATLAB 7, 10th edn. The MathWorks, Inc, Natick, MAGoogle Scholar
  53. Thompson EM, Baise LG, Kayen RE, Morgan EC, Kaklamanos J (2011) Multiscale site-response mapping: a case study of Parkfield, California. Bull Seism Soc Am 101:1081–1100CrossRefGoogle Scholar
  54. Trifunac MD, Brady AG (1975) On the correlation of seismic intensity scales with the peaks of recorded strong ground motion. Bull Seism Soc Am 65(1):139–162Google Scholar
  55. Tselentis G-A, Danciu L (2008) Empirical relationships between Modified Mercalli Intensity and engineering ground-motion parameters in Greece. Bull Seism Soc Am 98(4):1863–1875CrossRefGoogle Scholar
  56. Wald DJ, Allen TI (2007) Topographic slope as a proxy for seismic site conditions and amplification. Bull Seism Soc Am 97(5):1379–1395CrossRefGoogle Scholar
  57. Wald DJ, Earle PS, Allen TI, Jaiswal K, Porter K, Hearne M (2008a) Development of the U.S. Geological Survey’s PAGER system (Prompt Assessment of Global Earthquakes for Response). In: 14th World Conf. Earthq. Eng., Beijing, China, October. Paper 10-0008Google Scholar
  58. Wald DJ, Helmberger DV, Heaton TH (1991) Rupture model of the 1989 Loma Prieta earthquake from the inversion of strong-motion and broadband teleseismic data. Bull Seism Soc Am 81(5):1540–1572Google Scholar
  59. Wald DJ, Lin K, Quitoriano V (2008b) Quantifying and qualifying ShakeMap uncertainty. Open-File Report 2008-1238. U.S. Geological Survey. 27 pGoogle Scholar
  60. Wald DJ, Quitoriano V, Heaton TH, Kanamori H (1999a) Relationship between peak ground acceleration, peak ground velocity, and Modified Mercalli Intensity in California. Earthq Spectra 15(3):557–564CrossRefGoogle Scholar
  61. Wald DJ, Quitoriano V, Heaton TH, Kanamori H, Scrivner CW, Worden BC (1999b) TriNet "ShakeMaps": rapid generation of peak ground-motion and intensity maps for earthquakes in southern California. Earthq Spectra 15(3):537–556CrossRefGoogle Scholar
  62. Wessel P, Smith WHF (1991) Free software helps map and display data. Eos Trans 72(41):441CrossRefGoogle Scholar
  63. Wills C, Gutierrez C (2008) Investigation of geographic rules for improving site-conditions mapping. Final Technical Report, Award Number 07HQGR0061. California Geological Survey, Sacramento, CA. 20 ppGoogle Scholar
  64. Worden CB, Wald DJ, Allen TI, Lin K, Cua G, Garcia D (2010) A revised ground-motion and intensity interpolation scheme for ShakeMap. Bull Seism Soc Am 100(6):3083–3096CrossRefGoogle Scholar
  65. Wyss M (2008) Estimated human losses in future earthquakes in central Myanmar. Seism Res Lett 79(4):520–525CrossRefGoogle Scholar

Copyright information

© Her Majesty the Queen in Right of Australia 2012, as represented by Geoscience Australia 2012

Authors and Affiliations

  • Trevor I. Allen
    • 1
  • David J. Wald
    • 2
  • C. Bruce Worden
    • 3
  1. 1.Energy Division, Geoscience AustraliaCanberraAustralia
  2. 2.National Earthquake Information Center, US Geological SurveyGoldenUSA
  3. 3.Synergetics, Inc.Fort CollinsUSA

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