Empirical correlations between shear wave velocity and

Abstract Prediction of the ground shaking response

at soil sites requires knowledge of the soil, expressed in

terms of shear wave velocity. Although it is preferable

to measure this dynamic soil parameter in situ, this is

often not economic at all locations. Existing correla-

tions between shear wave velocity and penetration

resistance have been assessed in this study and com-

pared with correlations with SPT values obtained

based on geotechnical and geoseismic data collected

from a first-degree earthquake zone in Turkey. The

results obtained support the findings of earlier studies

that blow-count is a significant parameter in these

correlations while type of soil has no important influ-

ence. The regression equations developed in this study

compare well with most of the previous equations and

exhibit good prediction performance. It is noted that

better correlations are obtained when uncorrected

blow-counts are used.

Keywords Correlation equation Æ Geotechnical

borehole Æ Seismic refraction Æ Shear wave velocity ÆStandard penetration test Æ Turkey

Resume La prevision de la reponse d’un site a une

sollicitation sismique necessite des connaissances sur le

sol, relatives en particulier a la vitesse de propagation

des ondes de cisaillement. Il est preferable de mesurer

ce parametre de dynamique des sols in situ. Cependant

ceci n’est pas toujours possible en raison de la config-

uration du site et de contraintes economiques. Des

correlations entre la vitesse de propagation des ondes

de cisaillement et des donnees penetrometriques ont

ete evaluees et comparees avec des correlations entre

la vitesse de propagation des ondes de cisaillement et

des donnees SPT, ces dernieres obtenues a partir de

donnees geotechniques et sismiques issues d’une zone

de forte sismicite en Turquie. Les resultats obtenus

confortent de precedentes etudes montrant que les

donnees SPT apportent un parametre significatif, tan-

dis que le type de sol ne joue pas un role important

pour les correlations etablies. Des equations de

regression ont ete etablies et permettent de prevoir la

reponse d’un site a une sollicitation sismique.

Mots cles Equation de regression Æ Sondage

geotechnique Æ Refraction sismique Æ Vitesse de

propagation des ondes de cisaillement Æ Essai SPT ÆTurquie

Introduction

It has been recognized for a very long time that

earthquake damage is generally larger over soft sedi-

ments than on firm bedrock outcrops. This is particu-

larly important because most urban settlements have

occurred along river valleys over such young and soft

surface deposits. For this reason, particular consider-

ation is paid to the effect of local site conditions when

assessing ground motion characteristics for the seismic

design of buildings and other structures. Shear modu-

lus, damping ratio and shear wave velocity profiles are

important input parameters in site response analysis.

Prediction of the ground shaking response at soil sites

N. Hasancebi Æ R. Ulusay (&)Department of Geological Engineering,Hacettepe University, Beytepe, Ankara 06800, Turkeye-mail: [email protected]

Bull Eng Geol Environ (2007) 66:203–213

DOI 10.1007/s10064-006-0063-0

123

ORIGINAL PAPER

Empirical correlations between shear wave velocity andpenetration resistance for ground shaking assessments

Nilsun Hasancebi Æ Resat Ulusay

Received: 30 March 2006 / Accepted: 7 July 2006 / Published online: 29 August 2006� Springer-Verlag 2006

requires a knowledge of the stiffness of the soil, ex-

pressed in terms of shear wave velocity (Vs), which is

measured at small strain levels by in situ seismic

methods. While it is preferable to determine Vs directly

from field tests, it is often not economically feasible at

all locations. For this reason, a reliable correlation

between Vs and penetration resistance would be a

considerable advantage, reducing the number of field

verifications required.

In this study, which is an integral part of a research

study on soil amplification (Hasancebi 2005), the var-

iation of shear wave velocity measured by seismic

refraction and SPT blow-count (SPT-N) was investi-

gated and new correlations have been developed for

estimating the shear wave velocity. For this purpose, a

site with recorded high seismicity at Yenisehir, foun-

ded on an alluvial plain located in the Marmara Region

of Turkey (Fig. 1), was selected. The investiga-

tion programme included SPT borings at different

locations, seismic refraction studies, laboratory soil

classification tests, the use of borehole data from the

previous work in the study site and statistical assess-

ments. Based on the statistical assessments and taking

into account the type of soil, a series of empirical

equations for the prediction of Vs from SPT-N

were developed and compared with those suggested in

previous studies in order to evaluate the prediction

capability of the equations.

General setting of the study site

Geology and seismotectonics

Yenisehir town is located within an alluvial basin which

is surrounded by ridges both to the north and south

(Fig. 2). The study site is geologically represented by

the basement rocks of pre-Neogene age and Neogene

and Quaternary deposits. The basement rocks seen in

the southern part of the site consist of schists and

Fig. 1 Location map of thestudy site

204 N. Hasancebi and R. Ulusay

123

marbles. The Neogene deposits which appear on the

gentle slopes at the north and south consist predomi-

nantly of loosely cemented conglomerate, sandstone,

claystone and marl and unconformably overlie the

basement rocks (Genc 1992). The Quaternary deposits

are represented by alluvial soils and detritus and are

observed in the middle of the basin. Based on the data

from the records of the boreholes drilled by the State

Hydraulic Works (DSI), the thickness of the alluvial

sequence in the basin ranges between 25 and 115 m.

Yenisehir is located within a first-degree earthquake

zone of Turkey (GDDA 1996). The study site is sur-

rounded by a number of active faults as shown in

Fig. 3. The southern strand of the North Anatolian

Fault Zone (NAFZ) and the Bursa and Inonu–

Eskisehir faults are the most important earthquake

sources in the study site. The 1999 Kocaeli earthquake,

which resulted in extensive loss of life and damage to

structures particularly in the Marmara Region, was

also felt in Yenisehir and its vicinity.

SPT soundings, geoseismic investigations

and laboratory testing

In the present and future settlement areas of Yenisehir,

geotechnical studies for the assessment of foundation

conditions and a railway route were conducted by

Doyuran et al. (2000) and the State Port and Airport

Directory (DLH 2002). These previous studies in-

cluded a total of 37 boreholes and associated SPTs.

Twelve of these boreholes are relevant to the present

study. It is well known that the average shear wave

velocity in the upper 30 m of the ground is an impor-

tant factor for ground characterization (Borcherdt

1994; Dobry et al. 2000). Therefore, for the present

study, the boreholes were planned to penetrate to a

depth of 30 m if possible. In fact, 9 extended to 30.45 m

while the others ranged between 4.5 and 17 m. SPT

tests were conducted at 1 m intervals and the samples

from SPT tubes were used for laboratory testing. The

groundwater table in each hole was also measured.

Locations of the previous and recent boreholes and the

geoseismic investigations are shown in Fig. 2.

The most commonly used seismic methods for

velocity logging are the cross-hole and down-hole

techniques. Seismic refraction is largely used in deter-

mining the dynamic properties of the underlying layers.

In this study, shear wave velocities were measured

using seismic refraction with the assistance of the

General Directorate of Disaster Affairs (Dikmen et al.

2004) and Geophysical Engineering Department of

Ankara University. These measurements were taken at

the locations of nine boreholes drilled during the study.

Due to some restrictions at the locations of boreholes

H6 and H7 and the very shallow depth of borehole

H12, seismic studies were not undertaken at these

locations.

A total of 149 specimens extracted from SPT tubes

were tested in the laboratory to determine their grain

size distribution and Atterberg limits. The tests were

conducted in accordance with the methods given by

Fig. 2 Geological map of the study site, and locations ofgeotechnical and geoseismic investigations (modified fromDoyuran et al. 2000)

Fig. 3 Siesmotectonic map of the Eastern Marmara Region(after Doyuran et al. 2000)

Connection of shear wave velocity with SPT 205

123

ASTM (1994). Based on these results, the specimens

were classified according to the Unified Soil Classifi-

cation System.

Subsurface conditions

The data from the previous and recent boreholes and

the resistivity study (Dikmen et al. 2004) suggest that

the alluvial sequence generally starts with silty clay.

This clay, with high SPT-N values, is a stiff soil. Below

this, there exists medium dense to loose silty sand.

However, at some localities the silty clay may also ap-

pear below the sandy zone. Occasionally, gravel layers

of variable thickness can be observed in the Quaternary

deposits at shallow depths. A typical cross-section

through the Yenisehir settlement area, some selected

geotechnical logs and two typical seismic refraction

profiles showing the variation of Vs at the locations of

boreholes H3 and H8 are depicted in Fig. 5, respec-

tively. As can be seen from the Vs–SPT(N) versus depth

plots for some selected borehole locations in Fig. 6, Vs

increases with increasing SPT values.

Statistical evaluations of the data from grain size

analyses are given in Table 1. Sand sized material in

the Quaternary deposits is dominant at the southern

part of the site and these soils are represented by SP

and SW, and SC and SM soil classes. Towards the

north, grain size decreases and clays and silty clays with

high plasticity dominate. Most of the tested soils from

the north of the site fall into the CH and CL soil

classes.

The groundwater table in the study site is shallow,

generally ranging between 3 and 8 m. However, based

on the data from Doyuran et al. (2000), it is deeper

(‡14 m) at the north and shallower in the south.

Fig. 4 Geological cross sections (a) and some typical engineer-ing logs (b) illustrating the subsurface ground conditions atYenisehir settlement and its vicinity

Fig. 5 Seismic refractionprofiles at the locations ofboreholes H3 and H8


123

Proposed empirical correlations for Vs–SPT(N)

While it is preferable to determine Vs directly from

field tests, it is often not economically feasible to make

Vs measurements at all locations. Many correlations

between Vs and penetration resistance have been

proposed; 17 are quoted in Table 2, the majority based

on uncorrected SPT-N values. Sykora and Stokoe

(1983) suggest that geological age and soil type are not

Fig. 6 Variation of Vs and SPT-N with depth at some boreholelocations

Table 1 Statistical evaluation of grain size distribution of soilsamples

Grain size Max Min Mean Standarderror

Standarddeviation

Gravel (%) 0 49 11 12.47 0.084Sand (%) 4 100 49 27.74 0.186Silt (%) 0 76 30 23.91 0.160Clay (%) 0 34 10 9.3 0.066

Fig. 7 Correlations between Vs and SPT-N for all soils (a), sandysoils (b) and clayey soils (c)


123

important parameters in determining Vs, while the

SPT-N value is of prime importance. However, as can

be seen from Table 2, some investigators have also

proposed correlations between Vs and SPT-N for dif-

ferent soils, such as clays, silts and sands. In addition,

the soil properties considered in the regression analy-

ses for some correlations included stress-corrected Vs,

energy-corrected SPT-N, energy- and stress-corrected

SPT-N, depth (D) and fines content (FC).

In this study, 97 data pairs (Vs and SPT-N) were

employed in the assessments. The correlations were

developed using a simple regression analysis for the

existing database. In the first series of analyses, new

relationships were proposed between uncorrected Vs

(m/s) and corresponding SPT-N values in three cate-

gories, i.e. for all soils, sandy soils and clayey soils

(Fig. 7). Because few data from the silty layers were

available, this category was not included in the evalu-

ations. The following relationships with their correla-

tion coefficients (r) are proposed between Vs (m/s) and

SPT-N values for the three different soil categories.

Vs¼ 90N0:309 ðr ¼ 0:73Þ; All soils ð1Þ

Vs ¼ 90:8N0:319 ðr ¼ 0:65Þ; Sandy soils ð2Þ

Vs ¼ 97:9N0:269 ðr ¼ 0:75Þ; Clayey soils ð3Þ

Comparisons between the measured Vs and Vs pre-

dicted from Eqs 1–3 are presented in Fig. 8. The

plotted data are scattered between the lines with 1:0.5

and 1:2 slopes, with smaller Vs values (Vs < 250 m/s)

falling close to the line 1:1.

The correlations from the present study are plotted

in Fig. 9 to assess the effect of soil type. Figure 9

suggests that the correlations for different soil catego-

ries yield similar values of Vs indicating that soil type

has little effect on these correlations. This is consistent

with the findings of Iyisan (1996). However, Iyisan

(1996), who also studied gravely soils in Turkey, indi-

cated that the situation for gravels is different because

the correlation for gravels estimates higher Vs values

when compared to those from other soils, due to the

effect of grain size and cementation.

Equations 1–3 are plotted in Fig. 10a, c together

with several of the earlier regression equations given in

Table 2. Except the relationships of Ohsaki and Iwa-

saki (1973), Seed and Idriss (1981), Sisman (1995),

Iyisan (1996), Jafari et al. (1997) and Kiku et al. (2001)

in Fig. 10a (which were recommended for all soils), all

the equations including the equation of the present

study (Eq. 1) yield similar Vs values. There is only a

slight difference between Eq. 1 and those developed by

Ohba and Toriumi (1970) and Imai and Yoshimura

(1970); Eq. 1 proposed in this study estimates Vs values

considerably closer to those derived from most of the

existing equations.

Similar comparisons made for sands (Fig. 10b)

indicated that except the equation developed by Lee

(1990), the proposed equation (Eq. 2) compares well

with the other equations for the prediction of the Vs of

sands. Based on the distribution of the plotted data, the

equation of Lee (1990) generally over-predicts Vs for

N > 20 and under-predicts Vs for N £ 20.

Table 2 Some existing correlations between Vs and SPT-N

Author(s) Vs (m/s)

All soils Sands Clays

Ohba and Toriumi (1970) Vs = 84N0.31 – –Imai and Yoshimura (1970) Vs = 76N0.33 – –Fujiwara (1972) Vs = 92.1N0.337 – –Ohsaki and Iwasaki (1973) Vs = 82N0.39 – –Imai (1977) Vs = 91N0.337 Vs = 80.6N0.331 Vs = 80.2N0.292

Ohta and Goto (1978) Vs = 85.35N0.348 – –Seed and Idriss (1981) Vs = 61N0.5 – –Imai and Tonouchi (1982) Vs = 97N0.314 – –Sykora and Stokoe (1983) – Vs = 100.5N0.29 –Jinan (1987) Vs = 116.1(N + 0.3185)0.202 – –Lee (1990) – Vs = 57.4N0.49 Vs = 114.43N0.31

Sisman (1995) Vs = 32.8N0.51 – –Iyisan (1996) Vs = 51.5N0.516 – –Jafari et al. (1997) Vs = 22N0.85 – –Pitilakis et al. (1999) – Vs = 145(N60)0.178 Vs = 132(N60)0.271

Kiku et al. (2001) Vs = 68.3N0.292 – –Jafari et al. (2002) – – Vs = 27N0.73


123

The comparison for clays given in Fig. 10c suggests

that the equations developed by Imai (1977) and Lee

(1990) predict higher Vs values when compared to

those from Eq. 3 of the present study. The equation of

Jafari et al. (2002) differs from the other three equa-

tions and yields under-predicted and over-predicted Vs

values for SPT-N £ 20 and SPT > 20 conditions,

respectively. The specific geotechnical conditions of

the studied area are probably the main cause of this

while the quantity of the processed data, the SPT

procedure and the different methods of shear wave

velocity measurements employed in various studies

may be other causes of difference.

In addition to the comparisons shown in Fig. 10, the

scaled percent error (Eq. 4) versus cumulative fre-

quency graphs have also been drawn in Fig. 11.

Scaled percent error ¼ ½ðVsc � VsmÞ=Vsm� � 100 ð4Þ

where Vsc and Vsm are the predicted and measured

shear wave velocities, respectively.

Fig. 8 Measured versus predicted shear wave velocities for allsoils (a), sandy soils (b) and clayey soils (c)

Fig. 9 Effect of soil type on Vs–SPT(N) relationship

Fig. 10 Comparisons between proposed and previous correla-tions for Vs and SPT-N for all soils (a), sandy soils (b) and clayeysoils (c)


123

As seen in Fig. 11a, c, about 85% of the Vs values

predicted from Eqs. 1 to 3 for all soils, sands and clays

respectively, are within 20% of the scaled percent er-

ror, indicating a better estimate than those from the

existing equations.

The relationship between Vs and energy-corrected

SPT-N(N60) was also investigated and equations for all

soils, sands and clays were established. These were

compared to those suggested by Pitilakis et al. (1999)

who previously investigated N60–Vs relationships for

clays and sands. The SPT blow-counts were corrected

for striking energy during the test employed in this

study (donut-type hammer raised and dropped by two

turns of rope). The developed relationships for differ-

ent soils are given in Fig. 12a, c. When the correlation

coefficients obtained from Vs to N60 relationships are

compared to those obtained from Eqs. 1 to 3, the

equations based on uncorrected SPT-N values provide

a somewhat better fit than the equations based on

energy-corrected measurements. This situation is also

seen from Fig. 12d, f. The equations given in Fig. 12b, c

are plotted in Fig. 13a, b respectively, together with the

Fig. 11 Scaled percent errorof Vs predicted for all soils(a), sandy soils (b) and clayeysoils (c)


123

regression equations developed by Pitilakis et al.

(1999) for sands and clays. As shown in Fig. 13a, the

equation in Fig. 12b compares well with the regression

equation of Pitilakis et al. (1999) for sands. However,

the equation of Pitilakis et al. (1999) for clays yields

considerably higher Vs estimations when compared to

those from the equation developed in this study

(Fig. 13b). It appears from these assessments that the

equations based on uncorrected SPT-N values are

preferable for indirect estimations of Vs.

Conclusions

In this study, based on the geotechnical and geoseismic

data from the Yenisehir settlement situated in the

Marmara Region of Turkey, an attempt was made to

develop new relationships between SPT-N and Vs to

indirectly estimate the Vs to be used for practical

purposes. The results obtained from the study support

the findings of earlier work suggesting that blow-count

is a significant parameter in Vs–SPT(N) correlations,

while the type of soil has little influence.

The regression equations developed in this study

compare well with most of the previous equations and

exhibit a good prediction performance. The equations

based on uncorrected SPT-N values provide a some-

what better fit than the equations based on energy-

corrected SPT-N values. Therefore, the use of an

equation developed for all soils based on uncorrected

blow-counts is recommended for practical purposes.

The regression equations developed provide a viable

way of estimating Vs from SPT blow-count for pre-

liminary regional ground shaking mapping and site-

specific response analysis. The differences between

existing and proposed equations are mainly due to the

specific geotechnical conditions of the studied sites, the

quantity of processed data and the procedures used in

Fig. 12 Vs–N60 relationshipsfor all soils (a), sandy soils (b)and clayey soils (c), andmeasured versus predictedshear wave velocities for allsoils (d), sandy soils (e) andclayey soils (f)


123

undertaking the SPTs and geoseismic surveys. In view

of this, these empirical equations should be carefully

used and wherever possible checked against measured

Vs values.

Acknowledgments This study was supported by Project No.0302602008 of the Research Projects, Division of HacettepeUniversity. The authors would like to thank the GeneralDirectorate of Disaster Affairs and the geophysical team of thisorganization for their cooperation and the geophysical surveys;the Municipality of Yenisehir for providing the logistic support;the Geophysical Engineering Department of Ankara Universityfor seismic refraction equipment and interpretation of the mea-sured data; and the General Directorate of State HydraulicWorks (DSI) for permission to use the borehole logs.

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