1 Dokuz Eylül University, Engineering Faculty, Department of Geophysical Engineering, Tınaztepe Campus, Buca, TR−35160 İzmir, Turkey
(E-mail: [email protected])2 Çanakkale Onsekiz Mart University, Engineering & Architecture Faculty,
Department of Geophysical Engineering, Terzioğlu Campus, TR−17020 Çanakkale, Turkey
Received 05 May 2007; revised typescript received 04 September 2008; accepted 04 September 2008
Abstract: Seismic hazard studies have become progressively more important for earthquake engineering applicationsin western Anatolia, which contains one of the world’s best examples of a rapidly extending intra-continental tectonicregime. A two-stage regression analysis was applied to peak ground acceleration and 5%-damped spectral accelerationvalues of 168 recordings from 49 earthquakes in order to develop empirical attenuation relationships which can be usedto predict ground motion for western Anatolia. Moment magnitudes for earthquakes range between 4.0 and 6.4 whilethe hypocentral distances range between 15 and 200 km in our dataset. Site classifications, as one of the predictorvariables for the regression analysis, were obtained using horizontal to vertical spectral ratio estimates. These estimates,together with empirical attenuation relationship predictions, have shown that soil amplification is significant in westernAnatolia. Attenuation relationship models that are obtained explicitly account for nonlinear sediment effects for deepsoil sites in the region. Nonlinear effects of deep soil sites at lower periods are significant at the higher levels of shakingand manifest over-prediction for acceleration values, while they manifest lower prediction values at lower levels ofshaking. Both results from the horizontal to vertical ratio method and the regression analysis show that the number ofstrong motion stations located on the rock sites in the region should be increased and the present site classification ofstrong motion stations in Turkey should be re-evaluated in detail. When obtained attenuation relation models werecompared with the attenuation relationships based on data from tectonically similar regions, the attenuation relationsmodelled for a specific region could not, in general, be used in engineering applications realized for another region. Ourresults also indicate that the spectral acceleration model defined in the Turkish Building Code cannot adequatelyexplain magnitude and distance dependencies in western Anatolia.
Türkiye Batı Anadolu Bölgesi için Ampirik Azalım İlişkileri
Özet: Kıta içi gerilme rejiminin en iyi örneklerden biri olan Batı Anadolu’da, mühendislik uygulamaları için gereklisismik tehlike çalışmalarının önemi gün geçtikçe artmaktadır. Batı Anadolu için, yer hareketi tahminlerindekullanılabilecek ampirik azalım ilişkilerini geliştirmek amacıyla, toplam 49 depremden elde edilen 168 kayıda ait pikivme ve %5-sönümlü spektral ivme değerlerinden oluşan bir veri setine, iki aşamalı regresyon analizi uygulanmıştır.Veri setindeki depremlere ait moment büyüklüğü 4.0−6.4 arasında ve odak uzaklığı ise 15−200 km arasındadeğişmektedir. Regresyon analizinde yer alan zemin sınıflaması parametresine ulaşmak için yatay-düşey spektral orantahminleri kullanılmıştır. Bu tahminler ve regresyon analizinden elde edilen sonuçlar göstermiştir ki, bölgede sedimentdolgu zemin büyütmeleri oldukça belirgindir. Elde edilen azalım ilişkisi modelleri, net bir şekilde, derin sediment dolgubirimler için zeminin doğrusal olmayan davranışını sergilemektedir. Derin sediment dolgu birimlerde küçük periyotdeğerleri için gözlenen zeminin doğrusal olmayan davranışı, büyük depremler için yüksek ve küçük depremler için isedüşük yer hareketi tahminlerinin yapılabileceğini vurgulamaktadır. Yatay-düşey spektral oran yöntemi ve regresyonanalizinden elde edilen sonuçlar göstermiştir ki, bölgede sağlam zemin üzerinde bulunan kuvvetli yer hareketikayıtçılarının arttırılması ve Türkiye kuvvetli yer hareketi kayıtçıları zemin sınıflamasının, detaylı bir şekilde yeniden
IntroductionThe combination of the drag caused by subductionalong the Aegean Arc, the compression from thecontinental collision in eastern Anatolia (Turkey)and the Caucasus causes the Turkish plate to movewestwards (Figure 1) along two strike-slip fault zones(Taymaz et al. 1990, 1991, 2004, 2007; Tan & Taymaz2006), the North Anatolia Fault Zone to the northand the East Anatolia Fault Zone to the south. In thiscomplex tectonic framework, western Anatolia,which is a part of the ‘Aegean extensional province’(Taymaz et al. 1991), is one of the most seismicallyactive continental regions in the world and much ofit has been undergoing ~N−S-directed extensionaldeformation. Grabens, trending approximately E−Wbetween basin-bounding normal faults (e.g., Bozkurt2001) and strike-slip faults accommodating theextension (e.g., Zhu et al. 2006a) are the mostprominent neotectonic features of the region (Figure2). Besides several different suggestions of timingand origin of the extension in the region (Bozkurt2001, 2003), three main processes have beenproposed to explain the extension in the region: (1)orogenic collapse of thickened crust followingsuturing of the Neotethys Ocean; (2) back-arc riftingbehind a Tethyan subduction zone to the south; and(3) westward tectonic escape of Anatolia towards theAegean Sea.
Middle Miocene sediments beneath the youngerfill at some localities within actively extendinggrabens in the region (e.g., Koçyiğit et al. 1999;Bozkurt 2001, 2003) indicate that, when extensionbegan, some normal faults had cut through pre-existing depocentres (Westaway et al. 2004). Theseareas contain a high degree of fracturing andpermeability and because they are closer to theheating source, high thermal conductivity. The
region is a good example of a fast intra-continentalextensional tectonic regime with a stress rate of 3−4cm/year. Increasing lithospheric thinning causesincreasing geothermal activity in the region andactive tectonics have generated seismic activity withdestructive earthquakes.
Even though recent attention has focused onpossible strong ground motion in the Marmara Seain Turkey, historical earthquake activity in westernAnatolia shows clear evidence for significantdestruction during earthquakes along variousstructures in the region. Activity on the faults isshown by numerous earthquakes (e.g., 1919 Soma,M= 6.9; 1928 Torbalı, M= 6.3; 1933 Gökova, M= 6.8;1956 Söke-Balat, M= 7.1; 1965 Salihli, M= 5.8; 1969Demirci, M= 5.9; 1969 Alaşehir, M= 6.5; 1970 Gediz,M= 7.2; 1986 Çubukdağ, M= 5.5; 2003 Urla, M= 5.8;2003 Buldan, M=5.4). The earthquake swarm inOctober 2005 (Urla earthquakes) with severalhundred earthquakes per month (including threemoderate sized events) is one of the latestmanifestations of activity in that region. Moderate-sized earthquakes in western Anatolia (Taymaz &Price 1992; Taymaz 1993) might not cause extensivedamage compared to a possible large event in theMarmara Sea in Northwestern Turkey. Nevertheless,they are actually the dominant sources of seismichazard in the region, because of their largeramplitude at longer periods in deep basin structuresof the western Anatolia graben system.
Because of the real earthquake threat in westernAnatolia, the need for seismic hazard studies hasbecome progressively more important forearthquake engineering applications. A fundamentalrequirement for these studies is the determination ofpredictive attenuation relationships for groundmotion (Kramer 1996). Attenuation relationships are
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değerlendirilmesi gerekmektedir. Tektonik olarak benzer özelliklere sahip bölgeler için geliştirilen azalım ilişkileri ileelde ettiğimiz sonuçları karşılaştırdığımızda, belirli bir bölge için modellenen azalım ilişkilerinin, başka bir bölge içingerçekleştirilen mühendislik uygulamalarında genel olarak kullanılamayacağını görmekteyiz. Sonuçlar, aynı zamanda,ülkemiz yapı kodlarında tanımlanmakta olan spektral ivme modelinin, Batı Anadolu için büyüklük (magnitude) veuzaklık bağımlılığını yeterince ifade edemediğini göstermektedir.
Anahtar Sözcükler: azalım ilişkileri, yatay-düşey spektral oran, maksimum ivme, doğrusal olmayan zemin davranışı,batı Anadolu, Türkiye
commonly used to describe how amplitudes ofseismic waves decrease with distance, period andearthquake magnitude. Such relationships have beendeveloped for many regions of the world (e.g.,Abrahamson & Silva 1997; Gregor et al. 2002;Tavaloki & Pezeshk 2005; Bindi et al. 2006), mainlyby regression of strong-motion data. These studieshave shown that the ground motion levels can differsignificantly in different tectonic regimes.
Utilizing strong motion data from Turkey,workers have obtained attenuation relationships forseveral regions. For example, Gülkan & Kalkan(2002) derived empirical attenuation relationshipsthat consider site conditions and fault types, andobtained Peak Ground Acceleration (PGA) and 5%-damped Spectral Acceleration (SA) from a totalnumber of 93 records from 47 horizontal
components of 19 events. By using 221 recordings of122 events, Ulusay et al. (2006) generated a PGAattenuation relationship and then prepared an iso-acceleration map of Turkey based on thatrelationship. Utilizing a database consisting of 195recordings from 17 events in the Marmara Region,empirical attenuation models for PGA and SA weredeveloped by Özbey et al. (2004).
In this study, we have obtained predictiverelationships for the ground motion by regressingstrong-motion data only from western Anatolia.These relationships will not necessarily apply toother regions of Turkey. We used strong motionrecords from stations that are located in westernAnatolia and operated by the General Directorate ofthe Disaster Affairs’ Earthquake ResearchDepartment (ERD) and the data from the WASRE
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Figure 1. Simplified tectonic map of Turkey showing major neotectonic structures (modified from Taymaz et al. 1990,1991; Barka & Reilinger 1997; Kiratzi & Louvari 2001; Bozkurt & Sözbilir 2004; Akyol et al. 2006). DSFZ−Dead Sea Fault Zone, EAFZ− East Anatolia Fault Zone, NAFZ− North Anatolia Fault Zone. Heavy lines withhalf arrows are strike-slip faults with the arrows showing relative movement sense. Heavy lines with filledtriangles show major folds and thrust belts with the triangles indicating the direction of convergence. Heavylines with open triangles indicate an active subduction zone. Bold filled arrows indicate the movementdirections of the African and Arabian plates relative to Eurasia. Open arrows indicate the relative motions ofthe Anatolia and Aegean plates. The area outlined by dashed lines shows the region of Figure 2.
network (Akyol et al. 2006). We employed a two-stage regression procedure (e.g., Joyner & Boore1993; Ambraseys et al. 1996; Boore et al. 1997) toobtain the PGA and 5%-damped SA attenuationrelationships for the region.
Predictor Variables and Data SetThe parameters that must be clearly defined in orderto estimate ground motions are earthquakemagnitude, distance and local site conditions. Also,
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AKH
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Figure 2. Map showing main tectonic structures in western Anatolia (modified from Akyol et al. 2006). The distributionsof the events (red circles) and stations (white triangles and dark blue stars represent stations of WASRE and ERDnetworks, respectively) used in this study. Tectonic features were modified from Şengör et al. (1985), Şengör(1987), Konak & Şenel (2002), Şaroğlu et al. (1992) and Bozkurt (2000). GG− Gediz Graben, KMG− KüçükMenderes Graben and BMG− Büyük Menderes Graben.
because reverse and thrust earthquakes tend togenerate larger peak ground acceleration and high-frequency spectral acceleration than strike-slip andnormal earthquakes (Abrahamson & Shedlock1997), style of faulting should, ideally, be consideredwhen determining ground motion. In this study,however, the style of faulting parameters could notbe described, since fault mechanisms are stillunknown for most of the events in the region andour dataset is not large enough to distinguish thisparameter.
Different definitions for predictor variables inattenuation relationships make them difficult tocompare with each other. For example, Ambraseys etal. (1996) have generated attenuation relationshipsusing a large data set from European strong motionrecords. Three different site classes were utilized intheir relationship: rock, stiff soil and soft soil. Booreet al. (1997) determined a different relationshipusing strong motion records for shallow earthquakesin western North America. In both models, thedistance predictor is rjb, the closest horizontaldistance to vertical projection of the rupture (Booreet al. 1997). Site condition predictors depend on theaverage velocities in the upper 30 metres of the crustin the relationship of Boore et al. (1997). Sadigh et al.(1997) obtained an attenuation relationship forshallow crustal earthquakes based on Californiastrong motion data. They presented relationships forstrike-slip and reverse faulting earthquakes, rock anddeep firm soil deposits, earthquakes of Mw 4.0 to 8.0and distances up to 100 km. In their study, thedistance predictor is the minimum distance to therupture surface. Spudich et al. (1997) developed theirrelation based on data from extensional regimeearthquakes having Mw ≥ 5.0 everywhere in theworld and that are recorded at distances less than 105km. They presented relations for horizontal peakacceleration and 5%-damped pseudo-velocityresponse spectra. The Özbey et al. (2004) attenuationrelationship was obtained from 195 strong motionrecords of 17 earthquakes with Mw ≥ 5.0. Their dataset includes mainly the last largest events in theMarmara Region, the Kocaeli (Mw= 7.4), the Düzce(Mw= 7.1) events and their aftershocks. Theirpredictors and equation forms are the same as Booreet al. (1997). In this study, the predictor variables aredescribed in the following paragraphs.
Local Site Condition ParameterMost of the data used in this study was obtainedfrom the Turkish National Strong Motion Network(hereafter referred as TNSMN). The data from 18stations of that network was used (Table 1).Additionally, we used data from the temporaryWASRE (Western Anatolia Seismic RecordingExperiment [Akyol et al. 2006; Zhu et al. 2006b])network that operated between 2002 and 2003 in theregion (Table 1). Technical characteristics of theinstruments operated by the TNSMN and theWASRE networks were obtained from the internetsite of the General Directorate of Disaster AffairsEarthquake Research Department (ERD) of Turkey(http://deprem.gov.tr) and Akyol et al. (2006),respectively. One of the main problems is to getdetailed information about the Turkish networkfrom which the seismological data have beenretrieved. For example, the classifications of TNSMNsites were described in three different classes byERD, mostly from the properties of surface materialsof the sites. Thus, it was decided to classify therecords for site conditions according to thefrequency band of the fundamental frequency andamplification factor based on Horizontal to VerticalSpectral Ratio (HVSR) estimates for all stations,since there is no more detailed information aboutstrong motion sites in Turkey.
To apply the HVSR method, the initial time of theSH-wave window, which covers the S-wave portionon the seismograms, was selected visually. Only datawith S/N ratio greater than three were used tocompute the spectral ratios and the spectra weresmoothed using a nine-point moving averageoperator. The HVSR method is based on the so-called Receiver-Function technique applied tostudies of the upper mantle and crust usingteleseismic records. This method assumes that localsite conditions are relatively transparent to themotion that appears on the vertical component. TheHVSR method is able to identify resonantfrequencies, although the general tendency of themethod to underestimate the amplification value hasbeen shown by different workers (e.g., Lachet et al.1996; Theodulidis et al. 1996; Akyol et al. 2002).
Figure 3 shows individual HVSR results of eachevent and average site amplifications for MAN and
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Table 1. Data used in the development of the attenuation relationships for western Anatolia.
Event Data Date Time Latitude Longitude Site Depth Original M Mw Pga (g)No No (N) (E) (km)
* represents WASRE stations used in this study. GS, HRV, ATH magnitudes were reported by NEIC. ERD denotes the General Directorateof Disaster Affairs’ Earthquake Research Department. (a), (b) and (c) represents magnitude values from Ulusay et al. (2004), Zare &Bard (2002) and WASRE network database (Zhu et al. 2006a), respectively.
LA20 stations. In brief, there are four site categories:Sites 1, 2, 3 and 4 correspond to rock, stiff soil, soiland deep soil sites, respectively (Figure 4). The code,coordinates, site classifications and number of thedata used for HVSR estimates and regression analysisfor each station are given in Table 2. Since the qualityof data is insufficient for obtaining the siteparameters for the four different site classes, datafrom sites 1 and 2 were combined and designated asdata from site A. Similarly, data from sites 3 and 4were combined and designated as data from site B(Figure 5) in the regression analysis.
Distance ParameterDifferent source-to-site distance measures have beenused by different workers to predict empiricalattenuation relationships. These distance measures
include rjb, the closest horizontal distance to verticalprojection of the rupture (e.g., Boore et al. 1997;Gülkan & Kalkan 2002), rrup, the closest distance tothe rupture surface (e.g., Abrahamson & Silva 1997;Sadigh et al. 1997), rseis, the closest distance to theseismogenic rupture surface (e.g., Campell 1997),and rhypo, the hypocentral distance (e.g., Atkinson &Boore 1997). Atkinson & Boore (1997) had used rhypofor the data generated stochastically by using a Brunepoint source model characterized by stressparameter of 50 bars. Zare & Bard (2002) prepared astrong motion dataset for all of Turkey and theirestimate for the hypocentral distance is mainly basedon the well-known formula, rhypo= 8(ts−tp), in whichtp and ts are the first arrivals of P and S wave,respectively.
Since fault geometries are still unknown for mostmoderate-sized events in the region, rhypo was
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Figure 3. Amplification from all individual events (black lines) for (a) LA20 and (b) MAN stations from HVSR method.The mean site amplifications for (c) LA20 and (d) MAN sites (red lines) with 90% confidence intervals (blacklines).
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Figure 4. (a) The mean site amplifications from HVSR estimates for all stations in site classes 1, 2, 3 and 4. Red and blacklines represent ERD and WASRE stations, respectively; (b) the mean site amplifications (red lines) for fourdifferent site classes with 90% confidence intervals (black lines).
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Table 2. Stations with records used in this study.
No Station Code Station Station N1 N2 Site Class Site ClassLatitude (N) Longtitude (E) (ERD) (in this stuy)
*: WASRE network (Akyol et al. 2006) stations. N1 and N2 are total data number using for HVSR estimates and the regression analysis,respectively. According to ERD site classification R− rock, H− stiff soil and, S− soil sites. Site classes 1, 2, 3 and 4 represent rock, stiffsoil, soil and deep soil sites.
choosen as the predictor variable for distance. Inmany cases, it has been suggested that usingepicentral distance would not cause significant biasbecause the dimensions of the rupture area for smallearthquakes are usually much smaller than thedistance to the recording stations (e.g., Ambraseys etal. 1996; Gülkan & Kalkan 2002). We believe thatusing epicentral distance increases distanceuncertainties, since most of the events in the regionwere located by constraining the depth parameters.Thus, good crustal velocity structure (see Saunders etal. 1998 for a case study) and well-distributedstations are needed for better location processes.Recently, Zhu et al. (2006a) and Akyol et al. (2006)have shown that uncertainties of the location resultfrom poor event locations in the catalogues and theirlack of correlations with known faults in the region.
Magnitude ParameterMoment magnitude (MW) is the preferred magnitudemeasure to predict empirical attenuationrelationships because it is directly related to theseismic moment of the earthquake. However, themagnitude scale of the data from GeneralDirectorate of Disaster Affairs’ Earthquake ResearchDepartment (ERD) includes mostly ML or Md values.To homogenize our dataset, we used MW valuesreported by NEIC, Ulusay et al. (2004), Zare & Bard(2002) and the WASRE network database (Zhu et al.2006a). We have converted original magnitudes,
where given in other scales, to MW using theempirical relationships by Ulusay et al. (2004). Inthat study, based on a database of 170 events inTurkey, the values of MW (from ETHZ and Harvard)to MS (from ETHZ, ISC, USGS, Harvard and ISESD),Mb (from ETHZ, ISC, USGS and Harvard), Md andML (from ERD) were correlated. We used their MW-Md and MW-ML relations:
Mw = 0.9495 Md + 0.4181 (r=0.94, SD=0.716) (1)
Mw = 0.7768 ML + 1.5921 (r=0.94, SD=0.709) (2)
Data Selection Criteria and ProcessingWe first analyzed a total of 2123 acceleration recordsfrom all regions of Turkey. Recordings withunknown and poor estimates of magnitude, distanceand/or site conditions were discarded. The final dataset consists of 168 horizontal components from 49events, after applying some restrictions such as theneed to lie within certain boundaries (Figure 2),placing an upper limit on distance (rhypo < 200 km),and lower limits on magnitude (Mw ≥ 4.0) and PGAvalues (PGA > 0.0015 g). Low- and high-frequencynoise was checked for all the records. Much datafrom SMA-1 recorders have significant levels of longperiod noise (especially for events with lowmagnitudes or the records with large distances). No
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Figure 5. The mean site amplifications (red lines) for site A and B with 90% confidence level (black lines). Data from sites 1 and2 were combined and designated as data from site A. Similarly, data from sites 3 and 4 were combined and designatedas data from site B in the regression analysis.
filtering was applied to the data but all suspect datawere eliminated. In order to make the recordsuniform we (1) applied an instrument responsecorrection to all data, (2) numerically differentiatedthe WASRE network velocity data to obtainacceleration values, and (3) corrected the base linefor all data.
Table 1 lists the events, used in this study, withlocation parameters, sites, original/convertedmagnitude values and PGA values. The PGA valuespresented in this table are the largest peak betweenthe two horizontal components. To make the datasets uniform from two different networks, we usedlocation parameters reported by ERD, given in Table1. Location parameters and magnitude values of theevents reported in the WASRE network database(Akyol et al. 2006; Zhu et al. 2006a) and magnitudevalues given by ERD for the same events are given inTable 3, in order to compare the results.Distributions of the earthquakes in terms ofhypocentral distance, moment magnitude and siteconditions are given in Figure 6.
MethodThe general form of attenuation relationships can bewritten as follows:
(3)
where,Ai = specific amplitude factors for each
earthquake,Ei = 1 for earthquake i and 0 otherwise,N = earthquake number,
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Table 3. The location parameters and magnitude values of the events reported by the WASRE network database and magnitude valuesgiven by ERD.
Event No Date Time Latitude (N) Longitude (E) Depth Magnitude (ERD)* Mw
Figure 6. Distribution of the data for (a) site A and (b) site B interms of distance and moment magnitude.
(
) ε
log
log
y A E b r
b r cS
, ,
, ,
i j i i i j
i j i j
i
N
j
M1
2
1 1= + +
+ += =/ /
M = record number for each earthquake,b1 = coefficient for anelastic attenuation,b2 = coefficient for geometrical spreading,c = coefficient for site dependence,S = site classification (here, 0 for site A and 1 for
y is the ground motion parameter (e.g., PGA or SA)and ε = σP . σ, is the standard deviation of theresiduals. The value of P is based on the assumptionthat the prediction errors are normally distributedand P= 0.84 confidence level for ±1σ values.
In the recent attenuation relationships, the depthcoefficient, h, is estimated as part of the regressionand referred as a ‘fictitious’ depth measure (Boore etal. 1997). Abrahamson & Silva (1997) reported thatestimated h yielded a marginally better fit to the dataat short distances since h incorporated factors thattend to enhance the motion near the source,especially, directivity. To estimate h properly, veryclose distances between the sources and stations areneeded. Since our dataset lacks records withepicentral distance less than 10 km, we could not addthe h value as an unknown parameter in theregression.
The coefficients in equation 3 are determinedusing a two-stage regression procedure (e.g.,Ambraseys et al. 1996; Boore et al. 1997). Thedistance and site condition dependence, along with aset of amplitude factors, one for each earthquake,were determined in the first stage. In the secondstage, the amplitude factors were regressed againstmagnitude to determine magnitude dependence.Therefore, the data was divided into classes with thetwo-stage regression analysis, which is a well-knowntechnique (e.g., Draper & Smith 1966; Weisberg1980). The procedure decouples the determinationof magnitude dependence from the determination ofdistance dependence. If the regression analysis wascarried out in terms of magnitude and distancesimultaneously, errors in measuring magnitudewould affect the distance coefficients obtained from
the regression. In this approach, each earthquake hasthe same weight in determining magnitudedependence and each recording has the same weightin determining distance dependence (Joyner &Boore 1981).
After Ai values are obtained by the first stage, theywere used to find, by least squares, a first- or second-order polynomial representing the magnitudedependence.
Ai = a1 + a2 (Mi – 6) + a3 (Mi – 6)2 (4)Here, M is moment magnitude and a1, a2 and a3 arethe coefficients determined by the second regressionstage. Assuming that arbitrary magnitude anddistance parameters do not correlate with each other,we can use the covariance theorem to estimate thetotal standard error, σ, after two regression stages,using the equation;
σ = (σ12 + σ2
2)½ (5)where, σ1 is the standard deviation of the residualsfrom the first regression stage and σ2 is the standarddeviation of the residuals from the second regressionstage.
Researchers have used many different forms ofthis relation. For example, Joyner & Boore (1981)used equation 3, without the b2 coefficient. In thiscase, the form chosen for the regression is equivalentto:
(6)
where k is a function of M and q is a constant. Thiscorresponds to simple point source geometricspreading with constant-Q anelastic attenuation.This form would in fact apply only to a harmoniccomponent of ground motion, not to peakacceleration. However, Joyner and Boore (1981)suggested that its application to peak parameters isan appropriate approximation since coefficients aredetermined empirically.
Ambraseys et al. (1996) used equation 3 andapplied a third regression stage to residuals todistinguish different site condition coefficients.Their equation form includes both an anelasticattenuation coefficient (b1) and geometrical
y rk e qr= -
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spreading coefficient (b2) for distance dependence.However, they accepted values of b1 equal to zerosince they obtained positive b1 values, whilegenerating strong-motion attenuation relationshipfor Europe. The anelastic attenuation coefficient, b1,is also equal to zero attenuation relationship forearthquake ground motions in extensional tectonicregimes in Spudich et al. (1997).
Boore et al. (1997), Gülkan & Kalkan (2002) andÖzbey et al. (2004) used only b2 as the coefficientdependent on distance. They used the term ‘b2logr’as the sole distance dependent term and suggestedthat this term represents geometrical spreading for asimple point source model (b1r-logr). However, thisled to values of b1 greater than zero. This result showsthat ground motion attenuates less rapidly than 1/r,at least for distances less than 100 km. This isperhaps a result of the effect of critical-anglereflections from layers within and at the base of thecrust (Boore et al. 1997). In this study, we applied atwo-stage regression analysis utilizing the sameequation form to western Anatolian strong motiondata. Since there is no detailed information aboutnear-surface velocities of the sites, the siteclassifications based on HVSR estimates asmentioned above were used.
ResultsOur total data set consists of 168 recordings ofground motion from 49 earthquakes. Momentmagnitudes of the earthquakes range between 4.0and 6.4 while the hypocentral distance range isbetween 15 and 200 km (Figure 6). After applyingthe procedure described above, the followingattenuation relationship was obtained for the largestPGA values between the two horizontal components:
S= 1 for site A and S= 0 for site B. The standarddeviation, σ, is 0.27 and P is an 84% confidence levelfor the values of ±1σ. Distance and site conditiondependent coefficients determined together with aset of amplitude factors for this model are listed in
Table 4. In order to determine magnitudedependence, amplitude factors were regressedagainst magnitude values. All coefficients for themodels of PGA and SA values and their standarderrors along with the total and individual standarddeviations of the regressions are given in Table 5.Since the standard errors are large for the actualvalues, significance levels of site coefficient for allperiods were checked. As shown in Table 5, for theperiods between 0.075 and 0.15 sec, the sitecoefficients are statistically significant at an 88−89%confidence level. As suggested by Equation 7 there isno quadratic term for dependence on magnitude,because the solution quality was not improved withthe inclusion of this term at many of the periodvalues.
The distribution of normalized residuals of thePGA values versus the distance, magnitude andpredicted log(PGA) values are shown in Figure 7. Inthis figure, systematic trends were observed in thedistribution of residuals, especially for site Bresiduals versus magnitude values. A similar trendwas observed in the ratios between observed andpredicted PGA values versus magnitude values forsite B, although this trend lies within the ±1 standarddeviation limits of the model (Figure 8). Byexamining this linear trend, the correction terms forthe site coefficients were obtained. Table 6 lists SiteCoefficient Correction (SCC) terms for differentperiods. F-test statistics reveal that there is nostatistically meaningful trend betweenobserved/predicted SA and magnitude values, atperiods higher than 0.27 sec. After applying SCCterm, the improvements on the distributions of thenormalized residuals and the ratios betweenobserved and predicted PGA values are shown inFigures 9 and 10, respectively. The ratios ofobserved/predicted SA values at period values of0.15 and 0.5 sec for two different site classes withoutSCC term effect on site B are given in Figure 11.Figure 12 shows observed/predicted SA value ratiosat a period of 0.25 sec for two different site classesand SCC term effect on site B.
Figure 13 compares predicted PGA values for M=4.5, 5.0, 5.5 and 6.0 with observed PGA values.Predicted PGA values for M= 5.0, together withobserved PGA values from the events 24 and 26
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Table 4. The distance and site condition dependent coefficients determined along with a set of amplitude factors, by the firstregression stage.
Coeff. n Values Coefficient n Values Coefficient n Values(s.e.) (s.e.) (s.e.)
n is total data number for each parameter. (s.e.) denotes standard errors of the coefficients (bi) and obtained by using the well-known equationin where cii is the diagonal elements of variance-covariance matrix and s is the standard deviation values of the regression stages.
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Table 5. The attenuation relationships coefficients to estimate 5% damped SA values (g) in western Anatolia. The entries for zeroperiods are the coefficients for PGA.
T (sec) b c S.L.(c) σ1 a1 a2 σ2 σlog(Y)(s.e.) (s.e.) (s.e.) (s.e.)
S.L.(c) represents significance level of site coefficient. σlog(Y) represents obtained final standard deviation. σ1 and σ2 are the standarddeviations of the first and second regression stages, respectively. (s.e.) denotes standard errors of the coefficients.
(Buldan-2003 earthquakes, M= 4.9 and 5.1), and SAvalues for M= 6.0 at the period value of T= 0.25 sectogether with observed SA values from the event 18(Urla-2003 earthquake, M= 5.8) are given in Figure14a and b, respectively. Predicted SA values for M=4.5, 5.0, 5.5, 6.0 events and rhypo= 15 km, are given inFigure 15. This figure also shows much better theSCC term effects versus the different magnitudevalues. Increasing values of amplitudes anddominant periods with increasing magnitude areobserved in this figure. The effects of distance onpredicted SA values are given in Figure 16. In thisfigure, predicted SA values for distances of 15, 20, 25,30, 50 km and M= 6.0 are given. Decreasingamplitude values with increasing distance at allperiods are observed in this figure as well asincreasing dominant period values with increasingdistance.
Comparison with Other Ground MotionRelationshipsAs mentioned above, different definitions for thepredictor variables in attenuation relationships makethem to be difficult to compare. But we tried tocompare the predicted SA values with the models ofAmbraseys et al. (1996) and Boore et al. (1997)which are based on the data from tectonically similarregions (Figure 17). The relationship of Ambraseys etal. (1996) was generated using a large data set fromEuropean strong motion records (hereafter referredto as AMB96). The equations were recommended foruse in surface-wave magnitudes (MS) rangingbetween 4.0 and 7.5 and for source distances up to200 km. Their data set contained 422 records of 157events in Europe and adjacent regions and threedifferent site classes were utilized in this relationship:rock, stiff soil and soft soil. The relationship in Boore
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Figure 7. Distributions of the normalized residuals of the PGA values for (a) all data, (b) site A data and (c) site B data, versusthe distance, magnitude and predicted log(PGA) values. Red lines represent linear trends.
et al. (1997) was obtained using strong motionrecords for shallow earthquakes in western NorthAmerica (hereafter referred as BJF97). Thisrelationship could be used to predict groundmotions at distances within 80 km, and for Mw valuesbetween 5.5 and 7.5. The distance predictor wasdefined as rjb in both models. Both of therelationships have a constant h parameter (‘fictitious’depth measure, Boore et al. 1997) for each periodvalue.
In order to compare the predicted SA values withthe models of AMB96 and BJF97, an event with Mw=6.0 and rjb= 20 km was modelled (Figure 17). Sinceour distance predictor variable is hypocentraldistance, in our model rhypo was utilized as 22.4 km,by assuming that rhypo= 22.4 km corresponds to anepicentral distance of 20 km, with focal depth of 10km. Note that epicentral distance was used as rjb, inorder to compare the models. As described by the
authors, MS was used as a magnitude predictorvariable in the AMB96 model. The site A and the siteB models were compared with AMB96’s stiff soil andsoft soil models, respectively. In the BJF97 model,site condition predictors depend on the averagevelocities in the upper 30 metres of the crust. Asshown in Figure 5, dominant frequencies at sites Aand B are 4.71 and 2.0 Hz, respectively. According tothe quarter-wavelength rule (Boore & Brown 1998),average velocities for the upper 30 m are 565 m/s and240 m/s for the frequency values of 4.71 and 2 Hz,respectively. Utilizing these near-surface velocitiesand the BJM97 model, we predicted ground motionfor sites A and B (Figure 17).
Comparison with the Turkish Building CodeIn this study, we compared our models to SA modelsin the Turkish Building Code (hereafter referred as
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Figure 8. Distribution of the ratio between observed and predicted PGA values for (a) all data, (b) site A data and (c) site Bdata, versus the distance, magnitude and predicted log(PGA) values. Red lines represent linear trends.
TBC). In the TBC, the spectral acceleration modelwas defined as follows:
S(T) = 1 + 1.5 T / TA (0 ≤ T ≤ TA)S(T) = 2.5 (TA < T ≤ TB) (8)S(T) = 2.5 (TB / T )0.8 (T > TB)
where, S(T) denotes normalized SA values for thePGA and TA and TB denote spectrum characteristicperiods, depending on local site classes.
Definitions of local site classes and soil groupsutilizing site classification in the TBC are given inTables 7 and 8, respectively. As shown in equation 8,period values are the only independent variableshere. Comparisons of obtained models with SAmodels in the TBC are given in Figures 18 and 19.Figure 18 shows a decrease of the largest SA/PGAvalues against increasing magnitude. The effects ofdistance on predicted normalized SA values aregiven in Figure 19, where the largest SA/PGA anddominant period values increase with distances.
DiscussionOur results show that predicted PGA and 5%-damped SA values correlate well with the observedvalues. Only for the closer events (rhypo< 25 km) werelarger residuals observed between measured andpredicted values, possibly because of rupturedirectivity effects. However, no parameteraccounting for rupture directivity was included inthe model used in this study.
As shown in Figure 5, dominant frequencies ofthe site A and B classes are 4.71 and 2.0 Hz.According to the quarter-wavelength rule (Boore &Brown 1998), average velocities for the upper 30 mare 565 m/s and 240 m/s for frequencies of 4.71 and2 Hz, respectively. These velocities correspond tosites C and D in the NEHRP site categories. For thosereasons, sites A and B should be evaluated as stiff soiland soil sites in the region. 54% and 46% respectivelyof data in the dataset actually comes from sites A andB classes. Data from sites 1 and 2 were combined anddesignated as data from site A. Similarly, data fromsites 3 and 4 were combined and designated as data
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Table 6. Site Coefficient Correction (SCC) terms forattenuation relationship models to account for soilnonlinearity effect.
T (sec) Intercept Slope STS S.L.(s.e.) (s.e.)
0 1.364 -0.0736 0.116 0.0045(0.13) (0.025)
0.05 1.5375 -0.1124 0.131 0.0002(0.155) (0.029)
0.0625 1.5815 -0.1215 0.137 0.0006(0.161) (0.031)
0.075 1.6174 -0.1288 0.151 0.0019(0.183) (0.035)
0.0875 1.6456 -0.1343 0.157 0.0005(0.183) (0.035)
0.1 1.6665 -0.1383 0.166 0.0015(0.208) (0.04)
0.125 1.688 -0.1417 0.169 0.0002(0.202) (0.039)
0.15 1.6851 -0.1397 0.188 0.0058(0.228) (0.044)
0.175 1.6608 -0.1333 0.19 0.0002(0.216) (0.042)
0.2 1.6183 -0.1231 0.179 0.0025(0.212) (0.041)
0.225 1.5608 -0.11 0.161 0.0014(0.193) (0.037)
0.25 1.4913 -0.0946 0.156 0.006(0.184) (0.035)
0.275 1.413 -0.0779 0.159 0.0589(0.186) (0.036)
0.3 1.3292 -0.0605 0.141 0.2563(0.167) (0.032)
0.325 1.2428 -0.0432 0.136 0.4751(0.161) (0.031)
0.35 1.157 -0.0269 0.147 0.3508(0.169) (0.033)
0.375 1.0751 -0.0122 0.148 0.4916(0.169) (0.033)
STS and S.L. represent standard deviations and significance levelof fit, respectively. (s.e.) denotes standard errors of thecoefficients.
from site B (Figure 5) in the regression analysis. Asshown in Table 2, 65% of the data is from site 4 (deepsoil) in site B (deep soil) and 74% of the data is fromsite 2 (stiff soil) in site A.
Predicted 5%-damped SA values have shown thatsoil/deep soil amplifications are significant in the
region. For site A, dominant periods of M= 4.5, 5.0,5.5 and 6.0 events are about 0.15, 0.17, 0.19 and 0.2while these values are about 0.18, 0.21, 0.25, 0.31 and0.32 for site B, respectively (Figure 15). These resultsshow that deep basin effects and weakness of basinfill materials are significant in the graben systems of
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Figure 9. Distributions of normalized residuals of the PGA model, including the SCC term effect, top graphs for all data andbottom graphs for site B data, versus the distance, magnitude and predicted log(PGA) values. Red lines representlinear trends.
Figure 10. Distribution of the ratios between observed and predicted PGA, including the SCC term effect, top graphs for alldata and bottom graphs for site B data, versus the distance, magnitude and predicted log(PGA) values. Red linesrepresent linear trends.
western Anatolia. Geological observations suggestthat the Neogene sediments in the Gediz Graben(GG, in Figure 2) are about 1.3–1.5 km thick,measured at the detachment fault, which forms thecontact between the Neogene sediments andmetamorphic rocks (Bozkurt & Sözbilir 2004).Analysis of gravity data revealed that the maximumthickness of sedimentary cover is between 2.5 and3.5 km in the Büyük Menderes Graben (BMG, inFigure 2), and between 0.5 and 2.0 km in the GedizGraben (GG, in Figure 2) (Sarı & Şalk 2006).Another reason for the large dominant periods couldbe saturated soil deposits in the region: the lowcrustal velocities in the region are associated with ahigh degree of fracturing and the presence of fluidsat high pressure in the crust by Akyol et al. (2006).
Shean-Der et al. (1997) showed that the saturatedsoil deposit has a smaller surface amplitude andsignificantly lower resonant frequency than anunsaturated soil deposit of the same thickness.
Figure 16 shows lengthening of the dominantperiods and rapid decrease in the amplitudes withincreasing distance. This rapid decrease is consistentwith the reported high seismic attenuation forwestern Anatolia. Studies of attenuation of regionallyrecorded coda waves (Akıncı et al. 1994) and Lgwaves (Akıncı et al. 1995) have indicated that crustalseismic wave attenuation is high in the region.Tomographic studies of Lg coda Q have implied thatattenuation values in western Anatolia are among thehighest in all Eurasia (Mindevalli & Mitchell 1989;Cong & Mitchell 1999; Mitchell et al. 2008).
As shown in Figures 15 and 16, magnitude-dependent SCC terms cause lower estimates forlarger events and higher estimates for smaller eventsat lower periods. The existence of this term impliesnonlinearity of deep soil sites in the region.According to Field (2000), if nonlinear effects aresignificant at higher levels of shaking, they willprobably manifest themselves as an under-predictionof rock-site PGA rather than an over-prediction ofsediment-site PGA. Due to data limitations, wecould not examine whether or not soil nonlinearityeffects occur for site A. However, results obtained forsite B show that soil nonlinearity effects at lowerperiods (≤ 0.27 sec) are significant at higher levels ofshaking and manifest over-prediction of sediment-site acceleration values while they manifest lowerprediction at lower levels of shaking. Amplificationoccurs due to low-velocity deposits and resonancesin the soil column. At higher levels of shaking at siteB, nonlinearity attenuates periods less than 0.27second due to the increased damping in the soilcolumn. However, at longer periods, amplificationwithin the soil column controls site behavior andproduces larger SA values.
Figure 17 shows comparisons of the predicted SAvalues with the models of AMB96 and BJF97. Threemodels based on our site A class are consistent,except for SA values at larger periods of the AMB96model. For both site classes long-period values(T>1.5 sec), AMB96 model predictions are lowerthan the others. Figure 17 shows discrepancies
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Figure 11. The ratio between observed and predicted SA valuesat the period values of (a) 0.15 and (b) 0.5 sec for siteA and B classes without the SCC term effect. Redlines represent linear trends.
between three models based on our site B class. Ourpredicted values are smaller at short period valueswhile they are larger at medium periods. While theSCC term was not accounted in our model, the threemodels are consistent at short periods. Nevertheless,none of the AMB96 and BJF97 models account forthat effect. Field (2000) reported that the BJF97model does not explicitly account for the nonlinearsediment effect. Larger predictions for mediumperiods suggest that site amplifications in the regionand the basin effect are stronger than in otherregions. However, because the physical mechanismfor the basin effect has still been discussed andbecause different procedures were used by differentworkers any interpretation regarding with thiscomparison would be premature. For example, theBJF97 model was obtained using data that wasaveraged between two horizontal components. Thatcan cause smaller SA values generated by the model.Anderson (2000) suggested that the distance
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10 100Distance (km)
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Figure 13. Predicted PGA values for M= 4.5, 6.0, 5.5 and 6.0events, represented by black, green, blue and redlines, respectively. Black, green, blue and red circlesrepresent observed data from 4.00≤M<4.75,4.75≤M<5.25, 5.25≤M<5.75 and 5.75≤M events,respectively.
dependency does not vary with magnitude in theBJF97 model. On the other hand, the dataset ofAmbraseys et al. (1996) was taken from very largeregion including Europe and its environs in order toutilize attenuation relationships. Lee (1997)discussed the uncertainties in the AMB96 model. In
brief, all the relationships generated by the workershave been obtained by different definitions andprocedures in various equation forms.
Comparison of the obtained results with the SAmodels in TBC has been shown that it is not possibleto categorize the site A and B classes according to the
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Figure 14. (a) Predicted PGA values for M= 5.0 event together with observed PGA values from the events 24and 26 (Buldan-2003 earthquakes, M= 4.9 and 5.1, respectively) and (b) SA values for M= 6.0 eventat the period value of T= 0.25 sec together with observed SA values from the event 18 (Urla-2003earthquake, M= 5.8). Predicted values and their ±1 standard deviations are represented by thick andthin black lines, respectively. Crosses and circles represent observed data from site A and B classes,respectively.
TBC local site classification (Table 7) (Figures 18&19). The site A and B classes correspond to soilgroups B and C in TBC (Table 8). The SA/PGAamplitude values for smaller events (M<5) are higher
than the top level of the SA models in the TBC(Figure 18). A reason of this higher prediction couldbe lower prediction of PGA values. Nevertheless, ourresults imply that the observed and modeled PGA
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Figure 15. The effects of magnitude on SA values of (a) site A and (b) site B classes for rhypo= 15 km and M=6.0, 5.5, 5.0, 4.5 events. Amplitudes decrease with decreasing magnitude values. Dashed linesrepresent predictions without the SCC term effect.
Figure 16. The effects of distance on SA values of (a) site A and (b) site B classes for M= 6.0 event and rhypo=15, 20, 25, 30, 50 km. Amplitudes decrease with increasing distance values. Dashed lines representpredictions without the SCC term effects.
values are consistent (Figures 9, 10 & 13). On theother hand, because of small SA values generated bythose smaller events (Figure 15), they are lessimportant from an engineering point of view. Asshown in Figure 19, increasing amplitudes withincreasing distance (greater than 50 km) in themodels will cause higher predicted SA/PGA valuesthan the TBC model, especially for the site B class.This result implies that the SA model in TBC maynot result from deep basin effects at larger distances.
In this study, we tried to eliminate most of thesources of uncertainty in the regression analysis. Forexample, HVSR estimates were used for siteclassification, hypocentral distance was used as thedistance predictor variable to eliminate the errors inthe location processes and the source zonedefinition, while the form of the attenuationrelationship has been chosen with regard to thedataset limitations. The standard errors fordetermined coefficients were given in detail becauseuncertainties are brought into the regression analysiswith the usage of magnitude values reported bydifferent institutes/works and limited data.
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Figure 18. Comparison of obtained models with the SA models in the TBC. Predicted SA/PGA values for M=4.5, 5.0, 5.5, 6.0 events and rhypo= 15 km (black lines) for (a) site A and (b) site B. A decrease in thelargest SA/PGA value with increasing magnitude was observed. Red, blue, green and brown linesrepresent Z4, Z3, Z2 and Z1 site classes in the TBC, respectively.
Figure 17. Comparison of the predicted SA values with themodels of AMB96 and BJF97 for an event withMw=6.0 and rjb =20 km. Red, blue and green solidlines represent predictions for site B from the modelsof this study, BJF97 and AMB96, respectively.Dashed lines represent predictions for the site A. Theprediction without the SCC term effect is shown as athin black line.
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Figure 19. Comparison of obtained models with the SA models in the TBC. Predicted SA/PGA values for M=6.0 event and rhypo= 15, 25, 50, 75, 100 km (black lines) for (a) site A and (b) site B. An increase inthe largest SA/PGA and dominant period values with increasing distance was observed. Red, blue,green and brown lines represent Z4, Z3, Z2 and Z1 site classes in the TBC, respectively.
Table 7. Local Site Classes defined in the Turkish Building Code.
Local Site Class Soil Group and Topmost Layer Thickness (h1) TA(sec) TB(sec)
Z1 Group A soils and Group B soils with h1≤15 m 0.10 0.30 Z2 Group B soils with h1>15 m and Group C soils with h1 ≤15 m 0.15 0.40 Z3 Group C soils with 15 m < h1≤50 m and Group D soils with h1≤10 m 0.15 0.60 Z4 Group C soils with h1>50 m and Group D soils with h1>10 m 0.2 0.9
Table 8. Soil Groups defined in the Turkish Building Code.
2. Very dense sand, gravel,... > 7003. Hard clay, silty clay,… > 7001. Soft volcanic rocks such as tuff and agglomerate, weathered cemented sedimentary rocks with planes of discontinuity,… 700–1000
B 2. Dense sand, gravel,… 400–7003. Very stiff clay, silty clay,… 300–700 1. Highly weathered soft metamorphic rocks and cemented sedimentary rocks with planes of discontinuity 400–700
C 2. Medium dense sand and gravel,… 200–4003. Stiff clay, silty clay,… 200–3001. Soft, deep alluvial layers with high water table,… < 200
ATTENUATION RELATIONSHIPS FOR W ANATOLIAATTENUATION RELATIONSHIPS FOR W ANATOLIAATTENUATION RELATIONSHIPS FOR W ANATOLIAATTENUATION RELATIONSHIPS FOR W ANATOLIA
ConclusionsThe largest peaks between the two horizontalcomponents and 5%-damped spectral accelerationvalues of 168 recordings for 49 earthquakes wereused to obtain empirical attenuation relationships forwestern Anatolia. The moment magnitude range ofearthquakes in the data set, is between 4.0 and 6.4while the hypocentral distance range is between 15and 200 km. Obtained model coefficients should beused for these ranges of magnitude and distance.
The results of HVSR estimates used in the siteclassification and the regression analysis used toobtain attenuation relationships have shown thatdeep soil amplifications are significant in the region.Not only large earthquakes but also moderate sizedones in the region are the dominant source of seismichazard, because of their larger amplitude at longerperiods in deep basin structures of the westernAnatolia graben system.
Our inferred attenuation relation model explicitlyaccounts for nonlinear behaviour of soil sites in theregion. The nonlinear effects of soil/deep soil sites atlower periods (≤ 0.27 sec) are significant at higherlevels of shaking and manifest over prediction ofsediment-site acceleration values while they manifestlower prediction at lower levels of shaking.
Our results show that most of the strong motionstations in the region are located on soil sites. Tobetter compare rock and soil sites, the number of thestations located on the rock sites in the region shouldbe increased. The results also show that the presentsoil classification for strong motion sites in Turkeyshould be re-evaluated in detail.
Comparisons of the results with the attenuationrelationships based on data from tectonically similarregions have shown that ground motion attenuationrelationships modelled for a specific region cannotnormally be used in engineering analysis for other
regions. The ground motion levels can differ even insimilar tectonic regimes, since these levels are relatednot only to tectonics but also to the actual physicalattributes of the region. The results also indicate thatthe TBC models cannot explain magnitude anddistance dependencies adequately if only the periodvalues are used as independent variables.
In this study, we determined initial attenuationrelationships for western Anatolia. Previously strongmotion data have not been sufficiently abundant toutilize the regression procedures to constrain thedistance and magnitude dependence of groundmotion in the frequency range that is responsible forearthquake damage. The data from two differentnetworks (TNSMN and WASRE) were merged forthis purpose. It is hoped that this study will guidefuture developments and provide an interim solutionuntil updated models become available. However,standard deviations of the obtained relationshipsshould be taken into account if the results are goingto be utilized for engineering applications. Moreprecise modeling will be possible when much moredata and information become available for theregion. For that reason, well-distributed strongmotion networks, as well as detailed studies of thesite conditions and the source geometries, areneeded for seismic hazard studies in westernAnatolia.
AcknowledgmentsThe authors are grateful to Tuncay Taymaz and ananonymous reviewer for their dedicated support andconstructive criticisms, which significantly improvedthe manuscript. The authors would like to thankErtuğrul Benzeden, Brian J. Mitchell, Mustafa Ergün,Mine Orgun, Murat Çamyıldız and Türker Yas fortheir contributions. English of the final text is editedby John A. Winchester.
ABRAHAMSON, N.A. & SILVA, W.J. 1997. Empirical response spectralattenuation relations for shallow crustal earthquakes.Seismological Research Letters 68, 94−127.
AKINCI, A., IBANEZ, J.M., DEL PEZZO, E. & MORALES, J. 1995.Geometrical spreading and attenuation of Lg waves: acomparison between Western Anatolia (Turkey) and SouthernSpain. Tectonophysics 250, 47−60.
References
N. AKYOL & Ö. KARAGÖZ
381
AKINCI, A., TAKTAK, A.G. & ERGİNTAV, S. 1994. Attenuation of codawaves in Western Anatolia. Physics Earth and Planet Interior87, 155−165.
AKYOL, N., AKINCI, A. & EYİDOĞAN, H. 2002. Site amplification of S-waves in Bursa city and its vicinity, northwestern Turkey:comparison of different approaches. Soil Dynamics andEarthquake Engineering 22, 579−587.
AKYOL, N., ZHU, L., MITCHELL, B.J., SÖZBİLİR, H. & KEKOVALI K. 2006.Crustal structure and local seismicity in Western Anatolia.Geophysical Journal International 166, 1259−1269, doi:10.1111/j.1365-246X.2006.03053.x.
AMBRASEYS, N.N., SIMPSON, K.A. & BOMMER, J.J. 1996. Prediction ofhorizontal response spectra in Europe. Earthquake Engineeringand Structural Dynamics 25, 371−400.
ANDERSON, J.G. 2000. Expected shape of regressions for ground-motion parameters on rock. Bulletin Seismological Society ofAmerica 90, 43−52.
ATKINSON, G.M. & BOORE, D.M. 1997. Stochastic point-sourcemodeling of ground motions in the Cascadia region.Seismological Research Letters 68, 74−85.
BARKA, A. & REILINGER, R. 1997. Active tectonics of the EasternMediterranean region: deduced from GPS, neotectonic andseismicity data. Annali Geofisica 40, 587–610.
BINDI, D., LUZI, L., PACOR, F., FRANCESCHINA, G. & CASTRO, R.R. 2006.Ground-motion predictions from empirical attenuationrelationships versus recorded data: the case of the 1997−1998Umbria-Marche, central Italy, strong-motion data set. BulletinSeismological Society of America 96, 984−1002, doi:10.1785/0120050102.
BOORE, D.M. & BROWN, L.T. 1998. Comparing shear-wave velocityprofiles from inversion of surface-wave phase velocities withdownhole measurements: systematic differences between theCXW method and downhole measurements at six USCstrong-motion sites. Seismological Research Letters 69,222−229.
BOORE, D.M., JOYNER, W.B. & FUMAL T.E. 1997. Equations forestimating horizontal response spectra and peak accelerationfrom Western North American earthquakes: a summary ofRecent work. Seismological Research Letters 68, 128−153.
BOZKURT, E. 2000. Timing of extension on the Büyük MenderesGraben, Western Turkey, and its tectonic implications. In:BOZKURT, E., WINCHESTER, J.A. & PIPER, J.D.A. (eds), Tectonicsand Magmatism in Turkey and the Surrounding Area. TheGeological Society, London, Special Publications 173, 385–403.
BOZKURT, E. 2001. Neotectonics of Turkey – a synthesis.Geodinamica Acta 14, 3−30.
BOZKURT, E. 2003. Origin of NE-trending basins in Western Turkey.Geodinamica Acta 16, 61−81.
BOZKURT, E. & SÖZBİLİR, H. 2004. Tectonic evolution of the GedizGraben: field evidence for an episodic, two-stage extension inWestern Turkey. Geological Magazine 141, 63–79.
CAMPELL, W.K. 1997. Empirical near-source attenuationrelationships for horizontal and vertical components of peakground acceleration, peak ground velocity and pseudo-absolute acceleration response spectra. Seismological ResearchLetters 68, 154−179.
CONG, L. & MITCHELL, B.J. 1999. Lg Coda Q and its relation to thegeology and tectonics of the Middle East. Pure and AppliedGeophysics 153, 563−585.
FIELD, E.H. 2000. A modified ground-motion attenuationrelationship for southern California that accounts for detailedsite classification and a basin-depth effect. BulletinSeismological Society of America 90, 209−221.
GÜLKAN, P & KALKAN, E. 2002. Attenuation modeling of Recentearthquakes in Turkey. Journal of Seismology 6, 397−409.
GREGOR, N., SILVA, W.J., WONG, I.G. & YOUNGS, R.R. 2002. Ground-motion attenuation relationships for Cascadia subductionzone mega-thrust earthquakes based on a Stochastic FiniteSource. Bulletin Seismological Society of America 92,1923−1932.
JOYNER, W.B. & BOORE, D.M. 1981. Peak horizontal acceleration andvelocity from strong-motion records including records fromthe 1979 Imperial Valley, California, earthquake. BulletinSeismological Society of America 71, 2011−2038.
JOYNER, W.B. & BOORE, D.M. 1993. Methods for the regressionanalysis of strong-motion data. Bulletin Seismological Society ofAmerica 83, 469−487.
KIRATZI, A.A. & LOUVARI, E.K. 2001. On the active tectonics of theAegean Sea and the surrounding lands. In: TAYMAZ, T. (eds),Proceedings of Symposia on Seismotectonics of the North-Western Anatolia-Aegean and Recent Turkish Earthquakes, 88–95, İstanbul Technical University, Turkey.
KOÇYİĞİT, A., YUSUFOĞLU, H. & BOZKURT, E. 1999. Evidence from theGediz Graben for episodic two-stage extension in WesternTurkey. Journal of the Geological Society 156, 605−616.
KONAK, N. & ŞENEL, M. 2002. Geological Map of Turkey at 1:500000Scale. General Directorate of Mineral and ResearchExploration of Turkey Publications.
KRAMER, S.L. 1996. Geotechnical Earthquake Engineering. PrenticeHall. Inc., Upper Saddle River, New Jersey.
LACHET, C., HATZFELD, D., BARD, P.Y., THEODULIDIS, N., PAPAIOANNOU,C. & SAVVAIDIS, A. 1996. Site effects and microzonation in thecity of Thessaloniki (Greece): comparison of differentapproaches. Bulletin Seismological Society of America 86,1692−1703.
LEE, V.W. 1997. Discussion on ‘Prediction of horizontal responsespectra in Europe’. Earthquake Engineering and StructuralDynamics 26, 289−293.
MİNDEVALLI, Y.Ö. & MITCHELL, B.J. 1989. Crustal structure andpossible Anisotropy in Turkey form seismic surface wavedispersion. Geophysical Journal International 98, 93−106.
MITCHELL, B.J., CONG, L. & G. EKSTRÖM, G. 2008. A continent-widemap of 1-Hz Lg Coda Q variation across Eurasia and itsrelation to lithospheric evolution. Journal of GeophysicalResearch 113, B04303, doi:10.1029/2007JB005065.
ÖZBEY, C., SARI, A., MANUEL, L., ERDİK, M. & FAHJAN, Y. 2004. Anempirical attenuation relationship for northwestern Turkeyground motion using a Random Effects Approach. SoilDynamics and Earthquake Engineering 24, 115−125.
SADIGH, K., CHANG, C.Y., EGAN, J.A., MAKDISI, F. & YOUNGS, R.R.1997. Attenuation relationships for shallow crustalearthquakes based on California Strong Motion Data.Seismological Research Letters 68, 180−189.
SARI, C. & ŞALK, M. 2006. Sediment thicknesses of the WesternAnatolia graben structures determined by 2D and 3D analysisusing gravity data. Journal of Asian Earth Sciences 26, 39–48.
SAUNDERS, P., PRIESTLEY, K. & TAYMAZ, T. 1998. Variations in thecrustal structure beneath Western Turkey. Geophysical JournalInternational 134, 373−389.
SHEAN-DER, N., SIDDHARTHAN, V. & ANDERSON, J.G. 1997.Characteristics of nonlinear response of deep saturated soildeposits. Bulletin Seismological Society of America 87,342−355.
SPUDICH, P., FLECTHER, J.B., HELLWEG, M., BOATWRIGHT, C., SULLIVAN,C., JOYNER, W.B., HANKS, T.C., BOORE D.M., MCGARR A., BAKER
L.M. & LINDH A.G. 1997. SEA96 – a new predictive relation forearthquake ground motions in extensional tectonic regimes.Seismological Research Letters 68, 190−198.
ŞAROĞLU, F., EMRE, Ö. & KUŞCU, İ. 1992. Active Fault Map of Turkey.General Directorate of Mineral and Research Exploration ofTurkey Publication.
ŞENGÖR, A.M.C. 1987. Cross-faults and differential stretching ofhanging walls in regions of low-angle normal faulting:examples from Western Turkey. In: COWARD, M.P., DEWEY, J.F.& HANCOCK, P.L. (eds), Continental Extensional Tectonics. TheGeological Society, London Special Publications 28, 575–589.
ŞENGÖR, A.M.C., GÖRÜR, N. & ŞAROĞLU F., 1985. Strike-slip faultingand related basin formations in zones of tectonic escape:Turkey as a case study. In: BIDDLE, K.T. & CHRISTIE-BLICK, N.,Strike-slip Faulting and Basin Formation. Society of EconomicPaleontologits and Mineralogists, Special Publications 37,227–264.
TAN, O. & TAYMAZ, T. 2006. Active tectonics of the Caucasus:earthquake source mechanisms and rupture histories obtainedfrom inversion of teleseismic body waveforms. In: DİLEK, Y. &PAVLIDES, S. (eds), Postcollisional Tectonics and Magmatism inthe Mediterranean Region and Asia. Geological Society ofAmerica Special Paper 409, 531–578, doi:10.1130/2006.2409(25).
TAYMAZ, T. 1993. The source parameters of Çubukdağ (WesternTurkey) earthquake of 11 October 1986. Geophysical JournalInternational 113, 260−267.
TAYMAZ, T., JACKSON, J.A. & WESTAWAY, R. 1990. Earthquakemechanisms in the Hellenic trench near Crete. GeophysicalJournal International 102, 695–731.
TAYMAZ, T., JACKSON, J. & MCKENZIE, D. 1991. Active tectonics of thenorth and central Aegean Sea. Geophysical JournalInternational 106, 433–490.
TAYMAZ, T. & PRICE, S. 1992. The 1971 May 12 Burdur earthquakesequence, SW Turkey: a synthesis of seismological andgeological observations. Geophysical Journal International 108,589−603.
TAYMAZ, T., WESTAWAY, R. & REILINGER, R. 2004. Active faulting andcrustal deformation in the Eastern Mediterranean region.Special Issue of Tectonophysics, 391, Issues 1–4, 375 p., October29, 2004, Elsevier Publications, Amsterdam, The Netherlands.
TAYMAZ, T., YILMAZ, Y. & DİLEK, Y. 2007. The Geodynamics of theAegean and Anatolia: Introduction. In: TAYMAZ, T., YILMAZ, Y.& DİLEK, Y. (eds), The Geodynamics of the Aegean andAnatolia. The Geological Society, London, SpecialPublications 291, 1−16.
TAVALOKI, B. & PEZESHK, S. 2005. Empirical-stochastic ground-motion prediction for Eastern North America. BulletinSeismological Society of America 95, 2283−2296.
THEODULIDIS, N., BARD, P.Y., ARCHULETA, R. & BOUCHON, M. 1996.Horizontal to vertical spectral ratio and geological conditions:the case of Garner Valley Down Hole array in SouthernCalifornia. Bulletin Seismological Society of America 86,306−319.
ULUSAY, R., TUNCAY, E., SÖNMEZ, H. & GÖKÇEOĞLU, C. 2004. Anattenuation relationship based on Turkish strong motion dataand iso-acceleration map of Turkey. Engineering Geology 74,265−291.
WEISBERG, S. 1980. Applied Linear Regression. Wiley, New York.
WESTAWAY, R., PRINGLE, M., YURTMEN, S., DEMİR, T., BRINGLAND, D.,ROWBOTHAM, G. & MADDY, D. 2004. Pliocene and Quaternaryregional uplift in Western Turkey: the Gediz River terracestaircase and the volcanism at Kula. Tectonophysics 391,121−169.
ZARE, M. & BARD, P.Y. 2002. Strong motion dataset of Turkey: dataprocessing and site vlassification. Soil Dynamics andEarthquake Engineering 22, 703−718.
ZHU, L., AKYOL, N., MITCHELL, B.J. & SÖZBİLİR, H. 2006a.Seismotectonics of Western Turkey from high resolutionearthquake relocations and moment tensor determinations.Geophysical Research Letters 33, L07316, doi:10.1029/2006GL025842.
ZHU, L., MITCHELL, B.J., AKYOL, N., ÇEMEN, İ. & KEKOVALI, K. 2006b.Crustal thickness variations in the Aegean Region and itsimplications for the extension of continental crust. Journal ofGeophysical Research 111, B01301, doi:10.1029/2005JB003770.
