Geophysical Journal International

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1 Geophysical Journal International Geophys. J. Int. (2010) 182, doi: /j X x Shear wave velocity structure of the İzmit Bay area(turkey) estimated from active passive array surface wave and single-station microtremor methods Ekrem Zor, Serdar Özalaybey, Aylin Karaaslan, M. Cengiz Tapırdamaz, Suna Ç.Özalaybey, Adil Tarancıoğlu and Bora Erkan Earth and Marine Sciences Institute, TÜBİTAK, Marmara Research Center, Gebze-Kocaeli, Turkey. Accepted 2010 June 18. Received 2010 May 21; in original form 2009 December 14 1 INTRODUCTION The investigation of subsurface sedimentary structures and its relation with the underlying bedrock in the local geology became popular in the last decade since earthquake damage is often significantly greater on unconsolidated soil sites than on the rock sites even in the near field of destructive earthquakes (Wills et al. 2000). The remote settlements may be considered secure in terms of the distance to the earthquake source, but the settlements populated on sedimentary structures away from the epicentral region is likely to suffer from heavy damage. An example from the 1999 August 17 İzmit earthquake (M w 7.4) showed that the Avcılar district of İstanbul was heavily damaged despite being 150 km away from the epicentre. This damage was explained by local site effects (e.g. Özel et al. 2002; Ergin et al. 2004; Bozdağ &Kocaoğlu 2005). SUMMARY To provide quantitative information on the shear wave velocity structure of the İzmit Bay area, we conduct active passive array surface wave and single-station microtremor measurements at 60 sites. We process these array measurements to produce combined Rayleigh wave dispersion curves that span a broad-frequency range ( Hz). We also make use of horizontal-to-vertical spectral ratio (HVSR) curves obtained from the single-station microtremor measurements to benefit from their close relation to the ellipticity of Rayleigh waves. Using the dispersion curve sensitivity to the absolute velocities and the shape of the HVSR curve sensitivity to the velocity contrasts of the velocity-depth model, we have applied a combined inversion technique to derive better constrained shear velocity models at each site. The derived shear velocity models are used to provide a V s 30 site classification map and information on the sediment-bedrock structure for the İzmit Bay area. The V s 30 map shows that the entire shoreline regions including artificial infill areas of the İzmit Bay have V s 30 values less than 200 m s 1, locally as low as 80 m s 1. The older sediment areas of the İzmit basin have V s 30 values ranging between 250 and 350 m s 1. The highest V s 30 values are associated with rock sites reaching about m s 1. We also present a high correlation between the V s 30 values and the phase velocity of Rayleigh wave corresponding to the 40 m wavelength (C40). The important implication of this correlation is that V s 30 may be estimated from C40 without inverting the dispersion curve. The inferred sediment-bedrock interface along a crosssection shows an antisymmetric V shaped basin with a sedimentary cover thickness reaching about 1200 m at the deepest part of the İzmit basin. This deepest part coincides in the map view where the North Anatolian fault zone crosses the basin in the east west direction. The sedimentary cover thickness is found to be 750 m in the Gölcük Derince basin. Key words: Surface waves and free oscillations; Site effects. The estimation of shear wave velocity profiles for sedimentary structures is the key to contribute developing the reliable earthquake-hazard mitigation strategies such as seismic risk assessment, emergency response-preparedness and land-use planning by taking into account the proposed and existing constructions. An accurate determination of shear velocity profiles on sedimentary structures including the bedrock is crucial for a complete assessment of seismic hazard and simulation of strong ground motions (e.g. Frankel 1993; Olsen et al. 1995; Joyner 2000; Field et al. 2000; Satoh et al. 2001b), while the shallow shear velocity profiles,especiallytoadepthof30m(v s 30), are required to quantify local site conditions and effects used for building codes such as the US National Hazard Reduction Program-Uniform Building Code NEHRP-UBC (International Conference of Building Officials 1997). GJI Seismology C 2010 The Authors 1603

2 1604 E. Zor et al. The single-station microtremor method first introduced by Nogoshi & Igarashi (1971), the so-called Nakamura s method (Nakamura 1989), has been increasingly popular in the investigation of both shallow- and deep-sedimentary structures. This method is fast and cost-effective since it is based on a single-station measurement of ambient noise. The horizontal-to-vertical spectral ratio (HVSR) is assumed to be related to the ellipticity of Rayleigh waves, which gives a sharp peak at the resonance frequency of a given site when there is high impedance contrast between surface sedimentary layers and underlying bedrock (Lachet & Bard 1994; Konno & Ohmachi 1998; Seht & Wohlenberg 1999). This sharp peak information is either used as a direct measure of resonance frequency of a given site (e.g. Lermo & Chávez-Garcia 1993; Parolai et al. 2001) or used in constraining the shear velocity profile in conjunction with surface wave dispersion information (e.g. Scherbaum et al. 2003; Arai & Tokimatsu 2005; Parolai et al. 2005; Picozzi et al. 2005b). Based on the assumption of surface wave pre-dominance, array-processing techniques have been proposed such as spatial auto-correlation (SPAC) (Aki 1957; Okada 2003) and frequency wavenumber (f k) beam forming (Capon 1969; Lacoss et al. 1969) to obtain phase velocities of surface waves as a function of frequency, that is, the dispersion curve, from the array recordings of microtremors for site investigation. The successful results from the microtremor array methods (MAM) producing reliable dispersion curves have been accepted as an indirect proof for the assumption of surface wave pre-dominance (Bard 1998). The MAM can be used to estimate Rayleigh as well as Love-wave dispersion curves using three component recordings of the ambient noise wavefield (e.g. Aki 1957; Tokimatsu 1997; Satoh et al. 2001a; Saccorotti et al. 2003; Köhler et al. 2007; Tada et al. 2009). These methods are successful in resolving phase velocities of the lower frequency band (deeper part of the V s profile) depending on the bandwidth of sources, resonant sensor frequency and the largest interstation distances covered in the array. The application of multichannel analysis of surface waves (MASW) (Park et al. 1999) is a powerful active source method for obtaining phase velocities for the high-frequency band. Thus, the combination of dispersion curves obtained by the MAM and MASW methods (e.g. Park et al. 2005; Di Guilio et al. 2006) may be used to provide V s profiles that contain information on both deep and shallow sedimentary structures. In this work, we use the HVSR, MAM and MASW measurements taken at 60 different sites to investigate the shear velocity structure of the İzmit Bay area, including widespread sedimentary structures hosting dense settlements (Fig. 1). We obtain local shear velocity profiles from this data set by a combined inversion of the Rayleigh wave phase velocities and HVSR curves. The derived shear velocity profiles are used to provide a V s 30 site classification map and information on the bedrock depth distribution of the İzmit basin. Our results show that most of the sites within the İzmit basin show low V s 30 values and that the sedimentary cover thickness reaches 1200 m in the deepest part of the İzmit basin, and 750 m in the Gölcük-Derince basin. 2 GEOLOGICAL SETTING AND PREVIOUS STUDIES The North Anatolian Fault Zone (NAFZ) is one of the most prominent dextral, strike-slip fault zones in the world. The northern main strand of the NAFZ extends into the Marmara region of Turkey and it plays a major role in the formation of a number of young sedimentary basins in the region (Şengör et al. 2005). Two important sedimentary basins are located in the eastern Marmara region along the main strand of the NAFZ in the study area. They are the Gölcük Derince basin, housing the epicentre of the 1999 İzmit earthquake and the İzmit basin. Compared to the Gölcük Derince basin, the İzmit basin covers a larger area and extends approximately 10 km in the NS and 17 km the EW directions, with an average elevation of approximately 30 m (Fig. 1). These quaternary basins are bounded by Triassic, Cretaceous and Eocene aged geological units, which can be classified as firm or hard rock sites (Fig. 1). The geological map is a simplified version for the geology of the study area. The number of geological units is reduced to four Figure 1. The alphanumeric-coded numbers show 52 array measurement sites on a simplified geological map of the study area. There are also eight more array sites outside the area of the map. The red line on the map is used to prepare a 1.5-D S-wave velocity pseudo-depth section. DB, GB and IB are the abbreviations showing Derince, Gölcük and İzmit Basins, respectively.

3 units by grouping them with respect to their ages. The Pliocene sediments from the southern side of the NAFZ are included in the Quaternary Alluvium unit for the sake of simplification. Similarly, some sandstone, limestone and assemblage of metamorphic units in Triassic, Permian, Ordovician and Silurian ages are also shown as the Triassic rocks (Fig. 1). The shear velocity structures and the basement depths of these basins are mostly unknown, except for the Gölcük Derince basin studied by Kudo et al. (2002), who derived local shear velocity profiles at two sites, which indicated that the bedrock velocities are reached deeper than 600 m. A previous estimation based on a geological survey by Akartuna (1968) suggests a total sediment thickness exceeding 500 m in the Gölcük Derince basin. In a recent study based on magnetotelluric surveys, the thickness of the young sediments is reported to vary between 2.5 and 5 km, obtained along the two profiles crossing the İzmit Bay and basin (Oshiman et al. 2002; Tank et al. 2005). Another adjacent Quaternary basin is the Adapazarı basin, which merges eastwards with the İzmit basin. This basin was geophysically well studied including a 2-D subsurface model (Komazawa et al. 2002) and 3-D subsurface model (Goto et al. 2005) were estimated using the refraction and reflection data, gravity data and the observations of microseisms. The depth to the bedrock in the 2-D model is m beneath the survey line, whereas the depth to the bedrock beneath downtown Adapazari varies from 600 to 1000 m in the 3-D model. 3 FIELD MEASUREMENTS AND DATA We use Reftek recorders for array as well as single-station measurements. A Reftek DAS 130 recorder is deployed together with a three-component L43C seismometer having a natural frequency of 1 Hz to collect data for the HVSR analysis. The Reftek DAS 130 equipped with a Global Positioning System (GPS) antenna is operated in 500 sps mode to comply with array measurements using the same sampling rate. Each component of L43C seismometer is injected with a step function after each measurement to make sure that the calibration parameters of each component does not deviate significantly from each other. The deviation of the calibration parameters is less than 4 per cent among the components in our L43C seismometer. Thus, we do not consider that such deviations are significant in the HVSR computations. We use Reftek Texan- 125 single-channel recorders for the active (MASW) and passive (MAM) measurements, each mated to a 4.5-Hz vertical-component geophone in the active one and a 1-Hz L41C vertical-component seismometer in the passive one. The Texan 125 acquisition systems work independently from each other using their internal clocks with no cable connection between them. The HVSR, MAM and MASW surveys take about 4 hr to complete at each site. 3.1 Errors in phase velocity estimation due to instrumental effects The array measurements targeting to obtain phase velocities are essentially based on the estimation of the time delay between the stations in the array. The timing accuracy in the field experiments is therefore very important to obtain reliable phase velocities. The two instrumental effects that are critical for measuring the time delays between two different instruments are the internal clock stability and synchronizations of the data acquisition system and the phase delays of seismometers used in the field experiments (Ohrnberger et al. 2005). Shear velocity structure of the İzmit area 1605 All instruments are synchronized with a common GPS time mark signal simultaneously before and after deploying in the field. Their internal clock drifts are computed after the field deployment and a time correction for each individual acquisition system is applied to minimize the timing errors among the recorders. The maximum time corrections in this process did not exceed 12 ms over 18 hr of recording time. This corresponds to a time base stability value of 0.18 part per million (ppm). This value is in accordance with the time base stability range given between ±0.1 and 0.3 ppm for varying operating temperatures for the Texan 125 acquisition system by the manufacturer s specifications sheet. We also make a detailed analysis of phase velocity errors that may be caused by the instrumental phase delay of the seismometers. Each L41C, 1 Hz seismometer has unique calibration parameters, which are natural frequency (f o ) and damping constant (h). The determination of calibration parameters for two seismometers is explained in Fig. 2. Each seismometer is injected with a step function and the resulting calibration pulses (solid lines in Figs 2a and c) are modelled to estimate calibration parameters by a 2-D grid search algorithm. The grid search is used to minimize the difference between the observed and theoretically calculated calibration pulses (dashed lines in Figs 2a and c) over trial values of f o and h. The estimated calibration parameters for the two seismometers show that their f o and h values differ by 5 per cent and 3 per cent, respectively. This procedure was applied to all 29 seismometers that we use in the MAM measurements to determine their calibration parameters. Once the calibration parameters have been determined, we compute phase delay of each seismometer as a function of frequency using the phase response equation given by (Aki & Richards (1980). Then, we convert analytically computed differential phase delays to relative time difference curves for all possible pairs from the 29 seismometers. The time difference curves obtained this way show that the maximum time difference reaches ±34.4 ms below the natural frequency of the seismometers (Fig. 2b). The sign in the time difference value is due to the order of the seismometers while taking phase delay differences. As can be seen from the figure, the relative time difference drops fast below 10 ms beyond the natural frequency of the seismometers and goes to zero at the high-frequency end. We observe that the instrumental time differences for frequencies higher than 1.5 Hz are less than 5 ms, which would not introduce significant phase velocity errors (Fig. 2b). A histogram plot has been prepared for 0.5, 1.0 and 1.5 Hz to show the distribution of the time difference in Fig. 2(d). The relative time differences are less than 15 ms in 85 per cent of all possible pairs at 1Hz. The arrival time difference of a surface plane wave travelling with a propagation velocity of 500 m s 1 (or slowness of s m 1 ) between two stations having an interstation distance of 50 m would be 100 ms. For this case, allowing ±15 ms timing error at 1 Hz would result in 18 per cent maximum error on the estimated phase velocity (or 15 per cent in terms of slowness). The maximum error would decrease to 8 per cent (or 7.5 per cent in slowness) by either increasing the interstation distance to 100 m or decreasing the propagation velocity to 250 m s 1. In addition, the timing errors serve as a time delay or advance depending on the order of the seismometers. The plane wavefield may arrive to a station pair from different directions and the variation of its direction may switch their order. The estimated phase velocity would be fast in one direction and slow in other direction. Also, the random distribution of the seismometers in the field may bring different pairs together creating a mixture of delayed and advanced pairs. Hence, we would estimate the average phase

4 1606 E. Zor et al. Figure 2. The two L41C seismometer calibration pulses (solid lines) obtained in response to a step function on the left (a and c). The seismometer codes and the calibration parameters (f o and h) obtained using a grid search algorithm is given on the top right-hand side of each plot. The theoretical calibration pulses calculated for these parameters are also shown (dashed grey lines). The time difference curves for all possible seismometer pairs (b), black solid line shows the time difference curve for the seismometer pair shown on the left-hand side and the vertical coloured lines show different sections taken to prepare histograms shown in (d). The histogram graphs for different frequencies showing the time difference distributions in percentage. velocity in statistical point of view with increasing observations using multiwindowed analysis of the recorded wavefield and the error in the estimated phase velocity would be less than 10 per cent for a multidirectional, energetic wavefield. 3.2 Array geometry and its resolution capabilities Since we have no control on the ambient noise sources, the success of phase velocity estimations based on ambient noise wavefield using 2-D arrays, especially with short duration recordings, is strongly dependent on how the array is designed spatially. We have used two semi-circular arrays: one is small (S) and another is large (L) array (Fig. 3). Our S array consists of 19 and L array consists of 25 stations both using vertical component seismometers with a natural frequency of 1 Hz. For the S array, three semi-circles were formed with the radii of 20, 50, and 75 m around a central station and each semi-circle had six sensors deployed at 30 azimuthal increments (Fig. 3a). The L array is larger in dimensions compared to the S array to increase the wavelength resolution capabilities. This array consists of four semi-circles each having six sensors again deployed at 30 azimuthal increments from the central station with the radii of 20, 50, 90 and 150 m (Fig. 3b). Thus, the total number of sensors for the S and L array was 19 and 25, respectively. For both of the arrays, the recordings of microtremor wavefield were taken for about 2 hr after all the sensors had been deployed. The S array was used where the estimated bedrock depth would not be too deep and the L array was used at sites where the bedrock would be deeper than 500 m. Since we use both SPAC and f k methods in the processing of the microtremor array data, the circular array that we use is the most convenient and ideal geometry for both methods (e.g. Chouet et al. 1998; Asten et al. 2004; Ohrnberger et al. 2004). As discussed by Asten et al. (2004) circular arrays with good azimuthal sampling are important to obtain reliable phase velocities when using the SPAC method, especially when the microtremor sources are distributed over a narrow azimuthal range. Our circular arrays provide spatial (azimuthal) averaging at six directions that are 30 apart. Such azimuthal sampling allows the evaluation of spatial correlation functions, represented by the zero-order Bessel function of the first kind, to at least the third zero crossing minimum as a function of frequency, even if the incident wavefield has a limited, narrow 5 azimuthal spread (see figure 4 of Asten et al. 2004). We make use of the modified SPAC method (MSPAC) proposed by Bettig et al. (2001) as it allows the coverage of multiple interstation distances as much as possible. For instance with the MSPAC method, it is possible to calculate spatial correlation functions for station pairs having interstation distances of 10, 25, 30, 40, 55 and 105 m in addition to regular interstation distances of 20, 50 and 75 m for the S array. These correlation distances for the L array become for regular SPAC 20, 50, m and 10, 30, 75, 100, 130 and 200 m for MSPAC. In terms of conventional f k method, well-resolved dispersion curves can be obtained by adapting array aperture and interstation

5 200 a Shear velocity structure of the İzmit area 1607 b Y(m) X (m) X (m) Array Transfer Function k in k min Wavenumber (rad/m) c km in m u l k min Wavenumber (rad/m) Figure 3. The array geometries for (a) the S array and (b) the L array. The array transfer functions of both arrays showing directional dependence of the main lobe widths as a function of wavenumber. The upper (kmin u )andlower(kl min ) limits of the resolvable wavenumbers measured from the main lobe width shown on the ATF of (c) S array and (d) L array. distances for distinct target wavelength ranges from shorter to longer wavelengths (Ohrnberger et al. 2004). The f k method suffers from the resolution limit in low frequencies due to limited array aperture. The insufficient resolution may, for example, cause difficulty in picking the wavenumber at low frequencies in the f k domain especially in the case of multiple sources arriving at the same time from different directions (Woods & Lintz 1973). The resolution limit of an array is controlled by the minimum wavenumber (k min ), which is determined by the geometry and maximum aperture of the array. In a simplified view, the array performance may be evaluated using minimum, D min, and maximum, D max, sensor spacing for linear arrays (Tokimatsu 1997). However, for 2-D array layouts, the array performance may differ for different directions since D min and D max vary from one direction to another (Henstridge 1979; Asten & Henstridge 1984; Wathelet et al. 2008). We therefore compute the theoretical array transfer function (ATF) to determine the resolving power of our arrays using the methodology proposed by Woods & Lintz (1973) and Asten & Henstridge (1984). In this study, we use the build_array tool of the open-source SESARRAY software package developed during the SESAME European Project (Bard et al. 2000) to calculate theoretical ATFs for both arrays. Fig. 3(c) shows the theoretical ATF calculated for the S array. This ATF shows that minimum resolvable wavelengths vary as a function of the wavenumber as a result of antisymmetric geometry and different directional response of the array. Thus, we find that the resolvable wavenumber values vary from an upper value of k u min = rad m 1 to a lower value of k l min = rad m 1, determined from the width of the outer and inner main lobes at their mid-height in the theoretical ATF, respectively (Fig. 3c). To define the maximum resolvable wavenumber of the array (k max) without aliasing effects, we use the half of the wavenumber distance between the u l main lobe peak and the closest sidelobe exceeding 50 per cent of the main lobe amplitude in the ATF as the k max (Wathelet et al. 2008). This definition results in a value of k max = rad m 1. We obtain an upper value of k u min = rad m 1 and a lower value of k l min = rad m 1 from the evaluation of ATF calculated for the L array with the same k max value determined for the S array. In the application of the f k methods, it is common to find that the half of the minimum and maximum wavenumbers obtained from the ATF analysis are used as acceptable resolution limits (Cornou et al. 2006; Wathelet et al. 2008). The MSPAC method can produce more successful results for the estimation of phase velocities for the long wavelengths than the f k methods reported in the literature (e.g. Okada 2003; Asten et al. 2004; Claprood & Asten 2009). A detailed study carried out by Tada et al. (2007, 2009), on the wavelength resolution of circular arrays employing different processing algorithms, including the SPAC method, report successful results using wavelengths as large as times the radius of the circular array. Consequently, maximum wavelengths for phase velocity estimations may reach up to 1000 m for the S array and 2000 m for the L array using the MSPAC method. Due to the relatively low frequency content of microtremors, the MAM is ideal to investigate intermediate to deep sedimentary structures on the order of a several hundred metres (Satoh et al. 2001a; Kudo et al. 2002; Di Guilio et al. 2006). Active source MASW method, with its higher frequency content compared to the MAM, can be used to extend the high-frequency end of the phase velocity estimations using the f k analysis (Park et al. 2005; Di Guilio et al. 2006). We therefore use MASW to complement the phase velocity estimations obtained by the application of MAM at each site. At almost all sites, we use L = 150 m long seismic line with d

6 1608 E. Zor et al. d min = 5 m geophone spacing, a 10 kg sledge hammer to acquire multichannel records for the MASW measurements. The maximum wavenumber detectable can be calculated by 2π/2d min resulting in k max = rad m 1 and minimum wavenumber resolution limit is k min = rad m 1 as calculated by 2π/L (Park et al. 1999) for the MASW measurements. 4 DATA PROCESSING To determine shear wave velocity structures, we use the passive MAM and active source MASW and HVSR measurements at each site shown in Fig. 1. The Rayleigh wave dispersion curves have been produced by combining the individual dispersion curves obtained from the MAM and MASW methods. The SESARRAY software package has been used in all these processes. We invert the dispersion and HVSR curves in a combined fashion to derive shear wave velocity profiles. We present data processing and inversion steps in the following sections. 4.1 HVSR measurements The HVSR computation has been performed on the windowed portions of whole recorded waveform after removing mean and trend. The windows with transient noise have been removed with a detection algorithm using STA/LTA ratio. To get a reliable spectral amplitude estimation of the frequency down to 0.1 Hz, the window length has been chosen as 100 s to have at least 10 cycles of this frequency and at least 20 windows were required for an acceptable HVSR measurement. In terms of the sensor used in the HVSR measurements, the data collected using a three-component L43C sensor having a natural frequency of 1 Hz allows us to detect ambient seismic vibrations down to Hz as reported by Strollo et al. (2008). 4.2 Rayleigh wave dispersion measurements To show the processing steps taken for the extraction of combined dispersion curves from the MAM and MASW measurements, we select three sites (SP08, SP54 and SP60) located in different parts of the İzmit basin (Fig. 1) as representative examples. We use the S-array layout for site SP08, whereas we kept same array layout for site SP54, except the three far stations inserted to increase the wavenumber resolution limits. Taking into account the field conditions, these far stations were installed at 60,90 and 120 having azimuthal distance of 150, 125 and 150 m, respectively. Site SP60 is in the middle of the İzmit basin where we expect a deeper bedrock structure. For this reason, we use the L-array layout for this and many other sites that are located in the middle of the basin. The details of the f k analysis we employ to estimate phase velocities from the application of the MAM can be found in Wathelet et al. (2008). In short, we process the microtremor array data collected at each site with the conventional beam powerbased frequency wavenumber decomposition (CVFK) method. The CVFK method is applied in the wavenumber plane through a sliding time window analysis of the filtered data in narrow frequency bands. The time delays for a plane wave travelling across the array are applied by phase shifting in the wavenumber domain to calculate the beam power. Thus, for each frequency band, a histogram image of velocities is constructed from the phase velocity estimations using the calculated beam power for each time window analysed. This velocity-histogram image is then used to pick the estimated phase velocities along with an estimate of their uncertainties (Wathelet et al. 2008). The resulting image of the velocity-histogram obtained by the CVFK method for site SP54 is shown in Fig. 4(a). The blue symbols in Fig. 4(c) show the estimated phase velocities along with their standard deviations picked from the velocity-histogram image within the limits outlined by the minimum and maximum wavenumber curves shown by grey lines (Fig. 4a). At this site, we observe not only the fundamental mode, but also well-developed first higher mode dispersion. We also constructed a velocity image, similar to the CVFK method, from the active source multichannel records of surface waves to extract a dispersion curve using the MASW method described by Park et al. (1999). The dispersion curve is picked using the maxima of the energy accumulation for each frequency from the velocity image shown in Fig. 4(b). The standard deviations on the estimated phase velocities (red symbols in Fig. 4c) are determined using the width of the pick above 80 per cent of the maxima for the corresponding frequency. The dispersion curve picked using the MASW velocity image confirms and complements the fundamental and first higher mode observations in the higher frequency range (i.e. between 6 and 17 Hz) (Fig. 4b) obtained from the CVFK method. As discussed previously, the MSPAC method has superior performance in estimating the dispersion curve for lower frequencies and complements the dispersion picks obtained from the CVFK method. Thus, we estimated phase velocities between 1.5 and 2.8 Hz (magenta symbols in Fig. 4c) from the observed SPAC functions only. To check how well we are able to pick the dispersion curve by using the MSPAC method, we computed the zero-order Bessel function of the first kind with an argument having the combined phase velocity values shown in Fig. 4(c) for the radii of 50, 105, 130 and 165 m. Then, we decided to use the dispersion curve only if we observe an acceptable fit between the observed SPAC and computed Bessel functions within the standard deviation limits of each SPAC function (Fig. 5). For frequencies higher than 5 Hz, there is a low correlation between the two functions observable at short distance correlations (e.g. at 50 m), which is most probably caused by the first higher mode contribution as strongly evidenced from the CVFK and MASW analysis. The low correlation of this kind caused by higher mode contribution was previously reported by Ohrnberger et al. (2005). In fact, the Bessel function computed using the first higher mode dispersion curve (dashed grey line in Fig. 5, shown for the radius of 50 m), correlates well with the observed SPAC function further confirming the presence of energetic higher mode propagation at this site. For this site, SPAC dispersion picking is not done below 1.5 Hz where the SPAC functions show low correlation values than expected. Thus, we extracted a combined dispersion curve (solid line in Fig. 4c) over a frequency band between 1.5 and 17 Hz, including both fundamental and first higher modes. The second example is given for site SP08 for the extraction of combined dispersion curve (Figs 6 and 7). At this site, we could also pick phase velocities in the low-frequency band (1.9 5 Hz) from the MSPAC (Fig. 7), in the medium-frequency band (3.5 8 Hz) from the CVFK (Fig. 6a) and in the high-frequency band (6 20 Hz) from the MASW (Fig. 6b) velocity panels. The final example is for site SP60 where we could obtain phase velocities over a wide frequency band ( Hz) (Figs 8 and 9). The high quality SPAC functions obtained for this site allow us to pick phase velocities down to 0.47 Hz (Fig. 9). We follow the same processing steps for all 60 sites to extract combined dispersion curves. Our general observation has been that the sites located in the centre of the İzmit basin had phase

7 Shear velocity structure of the İzmit area 1609 Figure 4. The determination of the combined dispersion curve at site SP54. (a) The resulting image of the velocity-histogram using the CVFK method. (b) The velocity image obtained from MASW method using linear array recordings for an active source. The fundamental and first higher modes are identified in these plots. (c) The combined dispersion curve (black) obtained from the CVFK (blue), MASW (red) and SPAC (magenta) methods. The grey lines in (a) labelled as k l min and ku min show lower and upper wavenumber resolution limits and k max shows maximum wavenumber aliasing limit determined from the ATF calculated for the SP54 array geometry. The grey lines in (b) labelled as k min and k max show wavenumber limits computed using the maximum and minimum interstation distances of the linear MASW array. Correlation Value Correlation Value m 105 m 130 m 160 m Frequency (Hz) Frequency (Hz) Figure 5. The fit between the Bessel functions (solid line) computed from the combined dispersion curve of SP54 and its observed SPAC functions (grey dots) with their standard deviations for four different radii to show the accuracy of the dispersion picking in SPAC analysis. Dashed grey line shows the correlation values computed for the first higher mode dispersion curve for the radius of 50 m. velocities estimated going down to 0.5 Hz and with sharp HVSR peaks occurring at frequencies as low as Hz, similar to what we have presented for site SP60. The sites located near the edges of the basin had dispersion and HVSR curves very similar to those of SP08 and SP54. In general, we could not measure reliable phase velocities using SPAC functions at and below the HVSR peak frequencies. This might be related to high-pass filter effect of the near-surface ground structure by decreasing the Rayleigh wave energy at and below the HVSR peak frequency as reported by recent studies (e.g. Scherbaum et al. 2003; Picozzi et al. 2005a; Wathelet et al. 2008). 5 RESULTS 5.1 Combined inversion of dispersion and HVSR data for shear velocity structure The sharp peaks observed in the HVSR curves, interpreted as a result of Rayleigh wave ellipticity, is most sensitive to a sharp velocity contrast with a trade-off between the average shear velocity of the material above the velocity contrast and the depth to the given velocity contrast. On the contrary, Rayleigh wave phase velocities are sensitive to the absolute average shear velocities of the material

8 1610 E. Zor et al. Figure 6. The determination of the combined dispersion curve for SP08. The detail explanation is the same as in Fig. 4. Correlation Value Correlation Value m 75 m 90 m 110 m Frequency (Hz) Frequency (Hz) Figure 7. The fit between the Bessel functions (solid line) computed from the combined dispersion curve of SP08 and its observed SPAC functions (grey dots) with their standard deviations for four different radii to show the accuracy of the dispersion picking in SPAC analysis. Figure 8. The determination of the combined dispersion curve for SP60. The detail explanation is the same as in Fig. 4.

9 Shear velocity structure of the İzmit area 1611 Correlation Value m 75 m Correlation Value m 200 m Frequency (Hz) Frequency (Hz) Figure 9. The fit between the Bessel functions (solid line) computed from the combined dispersion curve of SP60 and its observed SPAC functions (grey dots) with their standard deviations for four different radii to check the accuracy of the dispersion picking in SPAC analysis. in the depth ranges to which they penetrate. Thus, a combined or joint inversion of both data sets can be preferred to obtain a better constrained shear velocity model. There are a number of studies using a joint inversion scheme (e.g. Arai & Tokimatsu 2005; Parolai et al. 2005; Picozzi et al. 2005b) or a combined inversion scheme (e.g. Satoh et al. 2001b; Scherbaum et al. 2003) to exploit the information contained in the HVSR and Rayleigh wave dispersion data for a better constrained shear velocity model. In this study, we also adopt a combined inversion scheme. In this combined scheme, first we invert the observed dispersion curves using an iterative, linear inversion code provided by Hermann (2002) to find inverted shear velocity models as a first step. These inverted velocity models produce the best fit, in the least-squares sense, to the combined dispersion data. In the final step, we compare the fundamental mode Rayleigh wave ellipticities calculated for the inverted shear velocity models with the observed HVSR curves measured at each site. In the presence of the unknown contribution of Love and body waves to the ambient noise wavefield and the effect of sourcedistance on the HVSR curves (e.g. Fäh et al. 2001; Scherbaum et al. 2003), we also favour using only the shape of the HVSR curve, especially peak and trough frequencies present in the HVSR curves, but not their absolute values. Thus, we obtain final velocity models by forward modelling that aim to reduce the misfit between the shape of the observed HVSR and modelled ellipticities calculated by applying small velocity perturbations to the inverted velocity models while trying to keep the fit between the observed and modelled dispersion unchanged. The misfit is quantified by maximizing the normalized, zero-lag cross-correlation value (r ell ) computed between the observed and modelled elipticities in a frequency band including peak and trough frequencies. An initial, layered, subsurface model of the site, consisting of P-wave and S-wave velocities, density and thickness parameters, is required to obtain shear velocity structures using the iterative linear inversion algorithm. Park et al. (1999) emphasize the importance of initial v s profiles for a reliable and accurate convergence of the inversion process. Hence, we use the observed dispersion curve to calculate an initial model using the approach described by Park et al. (1999). In this approach, the measured dispersion curve is first transformed from c( f ) to c( λ) domain by simply dividing the phase velocities to their corresponding frequencies. Later, c( λ) is multiplied by 1.09 (Stokoe et al. 1994) and λ is divided by 2 to obtain initial v s profile, v s (z) as a function of depth. Then, finally this v s (z) is converted to a layered initial model. To obtain stable inversions using layered initial models, the layer thicknesses have been chosen from thinner to thicker towards the deepest part of the model, including a maximum of 22 layers. S-wave velocities have stronger and dominant effect on the reliable convergence in the inversion, but v p /v s ratios also contribute to a more accurate convergence of the inversion. Hence, we used the multichannel data collected for the MASW measurements to extract P-wave velocities and related v p /v s ratios for the first 30 m in all sites. Starting from these near-surface v p /v s ratio values, v p /v s ratios are adjusted with an exponential decrease towards the deeper portion of the models. In the İzmit basin, we find that the v p /v s ratio values between 4 and 7 for the near surface and between 2 and 3 for the deepest layers produce stable convergence. In the linear inversion, we iterated the procedure until no significant change in the L2 norm of the fit value between observed and theoretically calculated dispersion. Also, the linear inversion code uses the smoothness condition to produce smooth inverted models, which may be set as 0 or 1, and the damping value (the default value is 1). Inversion with a lower value of damping relaxes the smoothing condition, which helps to increase the model roughness and obtain better fit in some cases. We made a series of inversions for each dispersion curve using different smoothness conditions and the damping values to decide which ones are suitable to obtain stable convergence and reasonable velocity model. We present detailed results obtained from the combined inversion of dispersion and HVSR data for the three sites (SP54, SP08 and SP60) that we used in the previous sections as representative examples of all sites investigated. SP54 is a site located in the northern edge of the İzmit basin, behind a local hill (Fig. 10b). At

10 1612 E. Zor et al. Figure 10. Combined inversion (Dispersion + HVSR) results for site SP54. (a) The fit between the observed HVSR and Rayleigh wave ellipticity curves calculated using the inverted (green) and final (magenta) velocity models. (b) The location of site SP54. (c) The fit between the observed Rayleigh wave dispersion curves (fundamental and first higher mode, black and grey circles, respectively) and calculated dispersion curves obtained for the inverted and final velocity models. (d) The final shear velocity model is shown together with initial and inverted models and PS-logging measurement results. this site, we observe not only fundamental mode, but also the first higher mode Rayleigh-wave dispersions. The observed dispersion data are shown by black dots with their corresponding standard deviations in Fig. 10(c). The resulting misfit within these standard deviations is regarded as insignificant. We invert the fundamental and first higher mode data jointly using an initial model generated from the observed fundamental mode dispersion to obtain an inverted velocity model (Fig. 10d). The theoretical fundamental and higher mode dispersion (Fig. 10c) and ellipticity (Fig. 10a) curves are computed using this inverted model and they are compared with the observed data. As can be seen from Fig. 10(a), there is a large mismatch between fundamental mode ellipticity calculated for the inverted model and the observed HVSR curve. The fundamental peak frequency (1.8 Hz) and the part from the peak (1.8 Hz) to the trough (4 Hz) may have better match to the HVSR curve without violating the fit between observed and calculated dispersion curves. With an interactive forward modelling tool written in Matlab, we are able to check the sensitivity of the dispersion as well as ellipticity curves simultaneously when we perturb the velocity of any layer in the inverted model. Using this tool, we observe that the fundamental mode ellipticity is much more sensitive to the velocity contrast present around 50 m depth. Hence, a better match might possibly exist between the theoretical ellipticity and the HVSR curves just by rearranging this contrast on the inverted model. This approach results in a final velocity model that provides a much better match between the two curves from 1.8 to 4 Hz, with no significant misfit on the observed dispersion data. The r ell value of 0.93 measured between the theoretical ellipticity of the inverted model and HVSR curve for the frequency band in question becomes 0.97 for the final velocity model. The final shear velocity model tuned with the HVSR data modelling pronounced the velocity contrast at 50 m depth, which also agrees well with the PS-logging result (Fig. 10d). The second site (SP08) for which we present combined inversion results is located in the southern alluvial fan region of the İzmit basin (Fig. 11b). This is a site where we estimated that the bedrock would not be too deep, based on the surface geology. This is also, why we had a PS-logging measurement done at this site since we wanted to ensure that the PS-logging measurement sees bedrock velocities. The inverted velocity model for this site indicates a gradual increase in velocities with depth (Fig. 11d). The Rayleigh wave ellipticity computed for this model again does not provide a satisfactory fit to the shape of HVSR curve observed at this site. Using the interactive forward modelling tool starting from the inverted model, we find a final velocity model (Fig. 11d) that produces a much better match to the observed HVSR curve shown in Fig. 11(a), without creating a significant misfit in the observed dispersion curve (Fig. 11c). We find that the ellipticity is very sensitive to the velocity contrast around 75 m. Increasing the individual layer velocities towards the half-space velocity one by one simply from bottom

11 Shear velocity structure of the İzmit area 1613 Figure 11. Combined inversion (Dispersion + HVSR) results for the SP08. The detail explanation is the same as in Fig. 10. to 75 m depth make the theoretical ellipticity match the HVSR curve well between the peak (1.6 Hz) and trough (3.2 Hz) frequencies. The r ell value of 0.93 for the inverted velocity model becomes 0.98 for the final velocity model. The resulting misfit between observed and model derived dispersion curve is adjusted with a small decrease in the layer velocities above the velocity contrast. The final velocity model agrees well with the PS-logging measurements both indicating bedrock velocities below 75 m depth (Fig. 11d). The final example is given for site SP60, located in the middle of the basin where we anticipate a deep sediment-bedrock structure (Fig. 12b). The dispersion data at this site is obtained down to 0.47 Hz with a phase velocity of 1070 m s 1. This leads us to a wavelength of λ = 2275 m, which results in an initial velocity model going down to 1200 m depth using the λ/2 formulation (Park et al. 1999). The linear inversion for this site converged to the inverted model shown in Fig. 12(d). The poor match between the theoretical ellipticity for this model and observed HVSR curve (Fig. 12a) has been improved with positive velocity perturbations applied only to the deepest layers (mostly the half-space velocity) of the inverted model. These perturbations resulted in a final velocity model that has a much sharper velocity jump at about 850 m depth, where the velocity is greater than 1500 m s 1, which can be taken to represent bedrock velocity. We emphasize here that the inverted and final velocity models predict quite different phase velocities for frequencies lower than 0.5 Hz, where we do not have phase velocity observations. Whereas both models predict phase velocities that match the observed dispersion almost equally well. The HVSR data on the other hand strongly favours the final velocity model, which provides a much better ellipticity curve fit (the r ell value of 0.96). Thus, the HVSR data again seems to be the main factor to obtain a sharp sediment-bedrock interface. 5.2 Evaluation of V s profiles The geotechnical engineering society respects average shear velocity of the top 30 m (V s 30) for a site to evaluate the potential site amplifications. This approximation was adopted for site classification by almost all-existing seismic design and building codes (e.g. NEHRP-UBC, EuroCode 8). In addition to the V s 30, 3-D simulations of seismic waves show that sediment-bedrock depth and velocity contrasts within sedimentary structures have strong influence on the reliable prediction of the ground motion (e.g. Frankel 1993; Olsen et al. 1995). The basin depth effect is also taken into consideration for the new generation empirical ground motion models (e.g. Campbell & Bozorgnia 2008) to predict the peak ground acceleration as well as spectral accelerations. Recent studies have also shown that not only basin depth, but also the shape of the basin is found to be important in terms of basin edge effects (Joyner 2000; Olsen 2000; Field et al. 2000). Thus, below we provide an evaluation of the obtained V s profiles to generate a V s 30 site classification map and estimation of sediment-bedrock structure along a selected profile of the İzmit basin.

12 1614 E. Zor et al. Figure 12. Combined inversion (Dispersion + HVSR) results for the SP60. The detail explanation is the same as in Fig. 10. The V s 30 values, evaluated by taking the average shear velocity of the top 30 m from the V s profiles determined at 60 sites, and site classes determined using NEHRP-UBC classification (International Conference of Building Officials 1997) scheme are listed in Table 1 as one of the main products of this study. The lowest V s 30 value (80ms 1 ) was observed on site SP42 located in the artificially filled shoreline of the İzmit Bay, whereas the highest V s 30 value wasmeasuredonsitesp40( 1300 m s 1 ), which is the westernmost site (Fig. 1) located on the highland, firm-rock units of the study area. Almost all sites within the İzmit basin were classified as site class D (180 m s 1 < V s ms 1 ) except eight sites (SP06, SP10, SP17, SP20, SP31, SP42, SP49 and SP56) as site class E(V s m s 1 ) according to NEHRP-UBC classification scheme. Among the rest of them, 16 sites were classified as site class C (360 m s 1 < V s m s 1 ) and two sites were in the site class B (V s 30 > 760 m s 1 ). These sites are mostly on the transition zone between the İzmit basin and the highland of the region, where the geological units are either the Eocene-aged firm rock or the Pliocene sediments. For the generation of the V s 30 site classification map, the surface geological map was simplified to four units in accordance with the geology-based classification scheme given by Wills et al. (2000). To produce a background V s 30 map of the study area, shear velocity values of 1250, 900, 523 and 255 m s 1 have been assigned to the four geological units in the order of older to younger units, respectively. Hence, the shear velocity values assigned by the surface geology-based classifications and the V s 30 values in Table 1 have been gridded together with a nearest neighbourhood algorithm to generate the V s 30 map of the İzmit Bay. The resulting V s 30 map is enhanced in terms of V s 30 variation especially inside the İzmit basin (Fig. 13). The V s 30 values may be compared with the velocities averaged by the phase velocity of Rayleigh wave corresponding to the 40 m wavelength (C40) to seek for a probable correlation. A high correlation between the V s 30 and C40 values was observed by Konno & Kataoka (2000) using 85 V s profiles around Tokyo, Japan. We search for a similar correlation and find that such correlation also exists in our V s 30 and C40 data set, as shown in Fig. 14. Finally, we present a sediment-bedrock depth cross-section along a selected profile running from the southern to the northern margin of the İzmit basin (Fig. 1). We prepared this coloured pseudo-depth section by the projection and gridding of the V s profiles obtained at 11 sites (Fig. 15). The sediment-bedrock interface is defined at the depth where the shear velocity first exceeds 1500 m s 1. This value was chosen since 1500 m s 1 is defined as hard rock in the site classification scheme of the NEHRP-UBC provisions. On this pseudo-colour section, the solid black line, separating the red-green coloured zone sediments from the blue zone bedrock, is used to indicate the sediment-bedrock interface beneath the İzmit basin (Fig. 15). This interface defines an antisymmetric V-shaped basin with a sedimentary cover thickness reaching about 1200 m at the deepest part of the İzmit basin. This deepest part coincides

13 Table 1. The site locations and V s 30 values with their site class using NEHRP-UBC site classification (International Conference of Building Officials 1997). Site code Latitude Longitude V s 30 (m s 1 ) Site class SP N E 336 D SP N E 224 D SP N E 474 C SP N E 451 C SP N E 211 D SP N E 166 E SP N E 227 D SP N E 293 D SP N E 362 C SP N E 177 E SP N E 239 D SP N E 230 D SP N E 513 C SP N E 253 D SP N E 372 C SP N E 219 D SP N E 170 E SP N E 212 D SP N E 257 D SP N E 155 E SP N E 194 D SP N E 362 C SP N E 251 D SP N E 257 D SP N E 191 D SP N E 222 D SP N E 368 C SP N E 212 D SP N E 239 D SP N E 236 D SP N E 167 E SP N E 212 D SP N E 248 D SP N E 376 C SP N E 337 D SP N E 229 D SP N E 282 D SP N E 662 C SP N E 268 D SP N E 1318 B SP N E 614 C SP N E 81 E SP N E 950 B SP N E 200 D SP N E 206 D SP N E 400 C SP N E 321 D SP N E 491 C SP N E 150 E SP N E 442 C SP N E 457 C SP N E 373 C SP N E 278 D SP N E 277 D SP N E 264 D SP N E 167 E SP N E 186 D SP N E 417 C SP N E 297 D SP N E 279 D Shear velocity structure of the İzmit area 1615 in the map view where the NAFZ crosses the İzmit basin in the east west direction. Using the two V s profiles determined over the Gölcük Derince basin, we estimated that the sediment-bedrock depth is about 750 m beneath the Gölcük side (site SP24) and Derince side (site SP36, Fig. 1). We estimate that the uncertainties on the sediment-bedrock interface is on the order of ±20 per cent for a given depth in Fig. 15 based on the sensitivity analysis performed by interactive forward modelling on the final V s profiles and considering standard deviations on the dispersion and HVSR data. The average shear velocity of the sediments down to the bedrock varies from 700 to 800 m s 1. The average sediment velocities should be considered to vary within ±10 per cent. However, the assumed V s of 1500 m s 1 to define the bedrock may be as high as 2000 m s 1 based on the sensitivity tests. 6 CONCLUSIONS Using the MAM, MASW and HVSR measurements, we have estimated shear wave velocity structures at 60 sites located in the İzmit Bay area, including the İzmit and Gölcük Derince basins. We obtain combined Rayleigh-wave dispersion curves covering a broad frequency range from the processing of passive-source microtremor array ( Hz) and from the analysis of active-source MASW data (6 20 Hz). The better performance of the MSPAC method in resolving phase velocities for lower frequencies and the MASW method with its power resolving phase velocities for higher frequencies together with the CVFK method is exploited to derive the combined dispersion curves. As a result, we succeeded to estimate V s profiles for 60 sites, sampling different parts of the İzmit Bay area, employing a combined inversion scheme based on two steps. In the first step, we use a linearized, iterative, inversion algorithm to obtain inverted V s profiles from the combined dispersion. In the second step, we focus on obtaining final V s profiles by forward modelling to minimize the misfit between the shape of the observed HVSR and theoretical ellipticity curves computed by velocity perturbations applied to the inverted V s profiles, while trying the keep the misfit between the observed and modelled dispersions unchanged. This inversion scheme results in better constrained V s profiles since we let the absolute velocities be determined by the dispersion data and the sharpness of the velocity contrasts be determined by the shape of the HVSR curve. The final V s profiles estimated by the combined inversion scheme are consistent with the PS-logging results compared to the dispersion only inverted V s models. The V s 30 site classification map (Fig. 13) that we produce for the İzmit Bay area shows that the entire shoreline regions including artificial infill areas of the İzmit Bay have V s 30 values less than 200 m s 1, locally as low as 80 m s 1. The older sediment areas of the İzmit basin have V s 30 values ranging between 250 and 350 m s 1. The highest V s 30 values are associated with firm-rock sites reaching about m s 1. The Next Generation of Ground Motion Attenuation (NGA) relationships used to provide empirical ground motion models (Campbell & Bozorgnia 2008) utilize V s 30 to account for shallow site effects. Thus, the V s 30 map presented here is expected to serve as a starting ground for site-effect studies and assessment of seismic hazard of the İzmit Bay area. The existence of a high correlation between the V s 30 and C40 values presented in this study (Fig. 14) prompts us to propose that the V s 30 may be estimated from C40, which can be directly computed from the observed dispersion data, without the

14 1616 E. Zor et al. Figure 13. The map showing V s 30 variation in the study area obtained from the shear wave velocity profiles of the sites shown with alphanumeric-coded numbers. Vs30 (m/s) C40 (m/s) Figure 14. TheplotofV s 30 versus C40 values. The dashed line is drawn to show V s 30 = C40 constant line. the sediment-bedrock interface extends from the north towards the south with a gentle dip and reaches a maximum depth of 1200 m just above the NAFZ, and steeply rises up to the surface on the southern side of the fault trace. Thus, the inferred sediment-bedrock interface defines an antisymmetric V-shaped structure for the İzmit basin. For the Gölcük Derince basin, which is a continuation of İzmit basin to the west, we estimated that the sediment-bedrock depth is about 750 m. This estimation is in good agreement with the results obtained by Kudo et al. (2002) for the Gölcük Derince basin. Their velocity models show that the bedrock depth is greater than 600 m in this region. The 2-D subsurface (Komazawa et al. 2002) and 3-D subsurface models (Goto et al. 2005) for the Adapazari basin, located just to the east of the İzmit basin, show that the depth to the bedrock varies between 600 and 1500 m. These Quaternary basins, formed under the influence of the NAFZ, show comparable subsurface models. The average shear velocity of the sediments down to the bedrock, defined in this paper with V s > 1500 m s 1, varies from 700 to 800 m s 1 using the V s profiles from the sites located in the centre of İzmit basin (sites SP05, SP47, SP60 and SP01 in Fig. 15). Similarly, the average shear velocity of the sediments down to the bedrock depth is about 700 m s 1 in the Gölcük Derince basin. need for an inversion of the dispersion data and determination of V s profiles. The deepest point of the sediment-bedrock interface was found to be 1200 m in the İzmit basin based on the pseudo-depth crosssectionproducedfrom11selectedv s profiles (Fig. 15). Generally, ACKNOWLEDGMENTS This study was funded by the Kocaeli Metropolitan Municipality under TÜBİTAK project no We thank the Department of Housing and Urban Development, Kocaeli Metropoltian Municipality for their valuable collaborations and the members of the Directorate of Ground and Earthquake Investigation for their

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