Bulletin of Earthquake Engineering

, Volume 16, Issue 12, pp 5843–5874 | Cite as

Proposal of an empirical site classification method based on target simulated horizontal over vertical spectral ratio

  • Nasser LaouamiEmail author
  • Mohamed Hadid
  • Noureddine Mezouar
Original Research


Nowadays, most of the site classifications schemes are based on the predominant period of the site as determined from the average horizontal to vertical spectral ratios of seismic motion or microtremor. However, the difficulty lies in the identification of the predominant period in particular if the observed average response spectral ratio does not present a clear peak but rather a broadband amplification or multiple peaks. In this work, based on the Eurocode-8 (2004) site classification, and assuming bounded random fields for both shear and compression waves-velocities, damping coefficient, natural period and depth of soil profile, one propose a new site-classification approach, based on “target” simulated average \( H/V \) spectral ratios, defined for each soil class. Taking advantage of the relationship of Kawase et al. (Bull Seismol Soc Am 101:2001–2014, 2011), which link the \( H/V \) spectral ratio to the horizontal (\( HTF \)) over the vertical (\( VTF \)) transfer functions, statistics of \( H/V \) spectral ratio via deterministic visco-elastic seismic analysis using the wave propagation theory are computed for the 4 soil classes. The obtained results show that \( H/V \) and \( HTF \) have amplitudes and shapes remarkably different among the four soil classes and exhibit fundamental peaks in the period ranges remarkably similar. Moreover, the “target” simulated average \( H/V \) spectral ratios for the 4 soil classes are in good agreement with the experimental ones obtained by Zhao et al. (Bull Seismol Soc Am 96:914–925, 2006) from the abundant and reliable Japanese strong motions database Kik-net, Ghasemi et al. (Soil Dyn Earthq Eng 29:121–132, 2009) from the Iranian strong motion data, and Di Alessandro et al. (Bull Sesismol Soc Am 106:2, 2011. from the Italian strong motion data. In addition to the 4 EC-8 standard soil classes (A, B, C and D), the superposition of the 4 target \( H/V \) reveals 3 new boundary site classes; AB, BC and CD, for overlapping \( V_{s,30} \) ranges when the predominant peak is not clearly consistent with any of the 4 proposed classes. Finally, one proposes a site classification index based on the ratio between the cross-correlation and the mean quadratic error between the in situ \( H/V \) spectral ratio and the “target” one. In order to test the reliability of the proposed approach, data from 139 sites were used, 132 collected from the Kik-net network database from Japan and 7 from Algeria. The site classification success rate per site class are around 93, 82, 89 and 100% for rock, hard soil, medium soil and soft soil, respectively. Zhao et al. (2006) found an average success for the 4 classes of soil close to 60%, similar to what one found in the present study (63%) without considering the new soil classes, but much smaller if one considers them (86%). In the absence of \( V_{s,30} \) data, the proposed approach can be an alternative to site classification.


Site-classification index EC-8 design code Strong motion Simulation HVSR Kik-net database 



The authors appreciate the invaluable discussion with Dr PY Bard and thank the associate editor and two anonymous reviewers for their constructive comments and suggestions that helped us to improve this manuscript.


  1. Akkar S, Sandikaya MA, Ay BO (2014) Compatible ground-motion prediction equations for damping scaling factors and vertical-to-horizontal spectral amplitude ratios for the broader Europe region. Bull Earthq Eng 12:517–547. CrossRefGoogle Scholar
  2. Albarello D, Lunedei E (2013) Combining horizontal ambient vibration components for H/V spectral ratio estimates. Geophys J Int 194:936–951. CrossRefGoogle Scholar
  3. Ambraseys NN, Douglas J, Sarma SK, Smit PM (2005) Equations for the estimation of strong ground motions from shallow crustal earthquakes using data from Europe and the middle east: vertical peak ground acceleration and spectral acceleration. Bull Earthq Eng 3(1):55–73. CrossRefGoogle Scholar
  4. Beneldjouzi M, Laouami N (2015) A stochastic based approach for a New site classification method: application to the algerian seismic code. Earthq Eng Eng Vib 14:663–681CrossRefGoogle Scholar
  5. Bindi D, Parolai S, Cara F, Di Giulio G, Ferretti G, Luzi L, MonachesiG Pacor F, Rovelli A (2009) Site amplification observed in the Gubbio basin, central Italy: hints for lateral propagation effects. Bull Seismol Soc Am 99(2A):741–760CrossRefGoogle Scholar
  6. Bommer JJ, Akkar S, Kale O (2011) A model for vertical-to-horizontal response spectral ratios for Europe and the middle east. Bull Seismol Soc Am 101(4):1783–1806. CrossRefGoogle Scholar
  7. Building Seismic Safety Council (BSSC) (2000) The 2000 NEHRP recommended provisions for new buildings and other structures, part I (Provisions) and part II (Commentary), FEMA 368/369, Washington, D.CGoogle Scholar
  8. Cadet H, Bard PY, Duval AM (2008) A new proposal for site classification based on ambient vibration measurements and the Kiknet strong motion data set. In: Proceeding of the 14th world conference on earthquake engineering, Beijing, 12–17 Oct 2008Google Scholar
  9. CEN. Eurocode 8 (2004) Design of structures for earthquake resistance—part 1: general rules, seismic actions and rules for buildings. EN 1998-1: 2004. Comite Europeen de Normalisation, BrusselsGoogle Scholar
  10. Di Alessandro C, Bonilla LF, Boore DM, Rovelli A, Scotti O (2011) Predominant-period site classification for response spectra prediction equations in Italy. Bull Seismol Soc Am 102(2):680–695. CrossRefGoogle Scholar
  11. Di Capua G, Lanzo G, Pessina V, Peppoloni S, Scasserra G (2011) The recording stations of the Italian strong motion network: geological information and site classification. Bull Earthq Eng 9:1779–1796CrossRefGoogle Scholar
  12. Ducelier A, Kawase H, Matsushima S (2013) Validation of a new velocity structure inversion method based on horizontal-to-vertical (h/v) spectral ratios of earthquake motions in the Tohoku Area, Japan. Bull Seismol Soc Am 103(2A):958–970. CrossRefGoogle Scholar
  13. Fenton AG, Griffiths DV (2000) Bearing capacity of spatially random soils. In: 8th ASCE conference on probabilistic mechanics and structural reliability, PMC2000-097Google Scholar
  14. Fukushima Y, Bonilla LF, Scotti O, Douglas J (2007) Site classification using horizontal to vertical response spectral ratios and its impact when deriving empirical ground motion prediction equations. J Earthq Eng 11:712–724CrossRefGoogle Scholar
  15. Ghofrani H, Atkinson GM (2014) Site condition evaluation using horizontal-to-vertical response spectral ratios of earthquakes in the NGA-West 2 and Japanese databases. Soil Dyn Earthq Eng 67:30–43. CrossRefGoogle Scholar
  16. Ghasemi H, Zare M, Fukushima Y, Sinaeian F (2009) Applying empirical method in site classification, using response spectral ratio (H/V). A case study on Iranian strong motion network (ISMN). Soil Dyn Earthq Eng 29:121–132CrossRefGoogle Scholar
  17. Japan Road Association (1980) Specifications for highway bridges part V, seismic design. Maruzen Co. Ltd, TokyoGoogle Scholar
  18. Japan Road Association (1990) Specifications for highway bridges part V, seismic design. Maruzen Co. Ltd, TokyoGoogle Scholar
  19. JICA and CGS (2006) A Study of seismic microzoning of the wilaya of Algiers in the People’s Democratic Republic of Algeria, final report, volume 2, Oyo International Corp. Nippon Koei Co., LtdGoogle Scholar
  20. Kanai K (1957) Semi-empirical formula for the seismic characteristics of the ground. Bull Earthq Res Inst 35:309–325Google Scholar
  21. Kawase H, Sanchez-Sesma FJ, Matsushima S (2011) The optimal use of horizontal to vertical ratios of earthquake motions for velocity inversions based on diffuse field theory for plane waves. Bull Seismol Soc Am 101:2001–2014CrossRefGoogle Scholar
  22. Konno K, Ohmachi T (1998) Ground-motion characteristics estimated from spectral ratio between horizontal and vertical components of microtremor. Bull Seismol Soc Am 88(1):228–241Google Scholar
  23. Laib A, Laouami N, Slimani A (2015) Modeling of soil heterogeneity and its effects on seismic response of multi-support structures. Earthqu Eng Eng Vib 14(3):423–437. CrossRefGoogle Scholar
  24. Luzi L, Puglia R, Pacor F, Gallipoli MR, Bindi D, Mucciarelli M (2011) Proposal for a soil classification based on parameters alternative or complementary to Vs, 30. Bull Earthq Eng 9:1877–1898CrossRefGoogle Scholar
  25. Nour A, Slimani A, Laouami N, Afra H (2003) Finite element model for the probabilistic seismic response of heterogeneous soil profile. Soil Dyn Earthq Eng 23(5):331–348. CrossRefGoogle Scholar
  26. Olsen K, Day S, Bradley C (2003) Estimation of Q for long-period (> 2sec) waves in the Los Angeles basin. Bull Seismol Soc Am 93:627–638CrossRefGoogle Scholar
  27. RPA (2003) Règlement Parasismique Algérien. CGS Earthquake Engineering Research Center, Rue Kaddour Rahim, BP 252, Hussein Dey, Algiers, AlgeriaGoogle Scholar
  28. SESAME (2004) Guidelines for the implementation of H/V spectral ratio technique on ambient vibration measurements, processing and interpretation. Available at: uidelines.pdf. Last Accessed July 2011
  29. Stewart JP, Boore DM, Seyhan E, Atkinson GM (2016) NGA-West2 equations for predicting vertical-component PGA, PGV, and 5%-Damped PSA from shallow crustal earthquakes. Earthqu Spectra 32(2):1005–1031CrossRefGoogle Scholar
  30. Tajimi HA (1960) statistical method of determining the maximum response of a building structure during an earthquake. In: Proceedings of the second world conference on earthquake engineering, Tokyo and Kyoto, JapanGoogle Scholar
  31. Wills CJ, Petersen M, Bryant WA, Reichle M, Saucedo GJ, Tan S, Taylor G, Treiman J (2000) A site-conditions map for California based on geology and shear-wave velocity. Bull Seismol Soc Am 90:S187–S208CrossRefGoogle Scholar
  32. Yamazaki F, Ansary MA (1997) Horizontal-to-vertical spectrum ratio of earthquake ground motion for site characterization. Earthqu Eng Struct Dyn 26:671–689CrossRefGoogle Scholar
  33. Zhao JX, Irikura K, Zhang J, Fukushima Y, Somerville PG, Saiki T, Okada Takahashi HT (2004) Site classification for strong motion stations in Japan using H/V response spectral ration. In: 13th World conference of earthquake engineering, Vancouver, B.C., Canada, 1–6 August 2004Google Scholar
  34. Zhao JX, Irikura K, Zhang J, Fukushima Y, Somerville PG, Asano A et al (2006) An empirical site-classification method for strong strong-motion stations in Japan using H/V response spectral ratio. Bull Seismol Soc Am 96:914–925CrossRefGoogle Scholar

Copyright information

© Springer Nature B.V. 2018

Authors and Affiliations

  • Nasser Laouami
    • 1
    Email author
  • Mohamed Hadid
    • 2
  • Noureddine Mezouar
    • 1
  1. 1.Centre National de Recherche Appliquée En Génie Parasismique (CGS)Hussein Dey AlgiersAlgeria
  2. 2.Ecole Nationale Supérieure des Travaux publicsGaridi KoubaAlgeria

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