Bollettino di Geofisica Teorica ed Applicata Vol. 61, n. 4, pp. 469-486; December 2020 DOI 10.4430/bgta0314
Joint inversion approach to estimate earthquake source parameters using InSAR observations and strong ground motion data (2008 Qeshm earthquake in Iran)
Z. Golshadi1, M.S. Pakdaman2 and M. Rezapour1 1 Institute of Geophysics, University of Tehran, Tehran, Iran 2 Department of Environment and Energy at Science and Research Branch, Islamic Azad University, Tehran, Iran
(Received: 9 October 2018; accepted: 31 December 2019)
ABSTRACT We define the geometric and kinematic characteristics of the fault activated during the 10 September 2008 Qeshm earthquake, from the joint inversion of three InSAR observation sets (L-band, C-band, and X-band) and permanent displacement obtained from strong ground motion data. Our best-fit solution for the mainshock is represented by a reverse fault with a left-lateral component, dipping 54°SE with a maximum slip of ~200 cm at the centre of fault. The more realistic surface movements in three directions are extracted from the modelled displacements too. The fault investigated in this study affected the sedimentary cover approximately at a depth of Hormoz salt while it does not reach the basement and surface. The Hormoz salt and Gurpi formations have a vital role as a barrier against slip. Coulomb stress changes suggest that this faulting originates the vertical growth of the Laft anticline with no effect on the Ramkan syncline. Our findings show a significant relationship between this earthquake and the annual continental convergence in NE direction.
Key words: interferometry, strong ground motion, source parameter, slip distribution, stress transfer.
1. Introduction
The 2008 Qeshm earthquake occurred at 14:30 IRST (11:00 UTC) on 10 September with the magnitude 6.0 on the moment magnitude scale, in Qeshm province, southern Iran. The reports on the mechanism of the mainshock of the Qeshm earthquake are shown in Table 1. Nissen et al. (2010) investigated the depth and geometry of reverse faulting and the influence of Hormoz salt as a barrier of slip propagation over four years with interferometric synthetic aperture radar (InSAR) and teleseismic data. The link between buried reverse faulting and surface folding was examined in Nissen et al. (2011), who suggested the detachment folding, not a forced one. Lohman and Barnhart (2010) also used the InSAR data and, in addition to source parameters of faulting, investigated the stress triggering between the November 2005 and September 2008 Qeshm earthquakes. The Global Centroid Moment Tensor (GCMT) solution provided by the Harvard group is consistent with a nearly pure reverse-slip motion. The U.S. Geological Survey (USGS) fault-plane solution is very similar to the GCMT solution, but a low seismic moment release is preferred. The locations of the mainshock and its 11 most
© 2020 – OGS 469 Boll. Geof. Teor. Appl., 61, 469-486 Golshadi et al.
Table 1 - Mechanism of the mainshock of the 2008 Qeshm earthquake for the best fault with uniform slip derived from seismic and geodetic observations adopted from various studies. The locations correspond to the epicentral coordinates for RHDRC and IGUT agencies except for GCMT, which corresponds to the centroid. Also, the location values reported by other authors correspond to the coordinates of fault-plane-centre. FM indicates the focal mechanism. Legend: RHDRC, Road, Housing and Development Research Center; IGUT, Institute of Geophysics, University of Tehran; GCMT, Global Centroid Moment Tensor.
Reported by Width Length Depth Strike Dip Longitude Latitude Rake Slip MW MN ML FM (km) (km) (km) (°) (°) (°) (m) RHDRC - - 6 - - 55.58 26.95 - - 6 - 6.1 - IGUT - - 9.5 - - 55.829 27.002 - - - 6 - - 9 15 12 71 58 55.83 26.74 99 0.26 6.1 - - GCMT 9 15 12 234 33 55.83 26.74 76 0.26 6.1 - - Nissen 7.7 12.8 5.5 34 50 55.89 26.89 55 0.65 6 - - et al., 2010 Lohman and 6 10 6.2 30 55 55.94 26.88 67 0.8 6 - - Barnhart, 2010
significant aftershocks [obtained from Road, Housing and Development Research Center (RHDRC)] are shown in Fig. 1. Earthquake source parameters are a noteworthy database for synthesisers in successive seismological modelling. Even though we know the source parameters of the 2008 Qeshm earthquake using various studies, including the Earth’s surface deformation field, body wave modelling, microseismicity, and rupture characteristics [GCMT: Lohman and Barnhart (2010) and Nissen et al. (2010)], there is a significant difference in the reported locations and mechanisms relying on a single method alone (Fig. 1 and Table 1). Some of the applied techniques like teleseismic body-wave modelling, a way of modelling the source using waveform data of body wave phases (Langston and Helmberger, 1975), programmed by McCaffrey (1988), can constrain the centroid depth of the earthquake more appropriately than the routinely low-pass filtered solutions reported by the GCMT catalogue (Nissen et al., 2010). On the other hand, the presence of inhomogeneity in the real Earth, but not in the model, and complications from the Earth’s crust and outer core causes errors in modelling results. Thus, the distance range for the choice of recorded waveforms in teleseismic body-wave modelling is essential (Nissen et al., 2007). Also, modelling via seismic waveform cannot construct and model the high-frequency part of waveforms (Sokos and Zahradnik, 2008) and it is difficult to distinguish the real fault plane solution without data on surface faulting and ground deformation (He et al., 2016). SAR chain processing and modelling the surface deformation field, according to Okada (1985), have some advantages, compared with other geophysical methods, such as: covering the wide-area, quick monitoring, continuous measurement (Massonnet et al., 1993), acceptable high resolution, precision, and being inexpensive (Boerner et al., 1997). Factors that cause limitation in InSAR results are atmospheric perturbations (Zebker et al., 1997) and a direct path from the source to the receiver that leads to determine one component of displacement in the direction of the line of sight (LOS). Also, the InSAR data does not set constraints on the location where the slip initiated.
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Fig. 1 - Location of Qeshm Island and its earthquake sequence (IGUT) in Iran. The faults (Hessami et al., 2003) and the mainshock 2008 Qeshm earthquake reports and its aftershocks (retrieved from RHDRC) are also shown. The rectangles indicate the causative fault. Red star, pentagon, plus, diamond, and triangle are GCMT, RHDRC, Nissen et al. (2010), IGUT, and Lohman and Barnhart (2010) locations for the Qeshm earthquake, respectively. The plotted locations correspond to the epicentral coordinates for RHDRC and IGUT agencies except for GCMT, which corresponds to the centroid. Also, the plotted locations for other authors correspond to the coordinates of fault-plane-centre. The Ramkan and Laft structures are also shown.
The aims of this paper are twofold. First, we document the source characteristics of the Qeshm mainshock using a comprehensive set of geodetic data that includes not only freely available InSAR but also local strong ground motion data, which are used as extra geodetic data. Second, we use the mainshock to investigate its effects as induced stress on surface structures. The strong focus of this paper is on the link between buried faults and the surface structure of Qeshm Island, the exact centroid point, slip distribution, and focal mechanism of this earthquake. Despite the absence of rupture on the surface, the main concern arising from the Qeshm 2008 earthquake is whether events of similar magnitude could affect the formation or deformation of anticlines and synclines on the ground. Due to the many differences (up to 20 km) obtained from reported locations of this earthquake and consequently the reported causative fault (Fig. 1 and Table 1) and to compensate the limitations of the methods mentioned above, permanent displacements obtained from the strong ground motion data, are used jointly with the displacements obtained from InSAR
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observations. A joint approach is described for three couples of ascending and descending SAR data, i.e. L-band, C-band, and X-band interferograms and strong ground motion data, to precisely assess the geometry and location of the rupture process associated with this earthquake. It allows us to improve the source parameters and simultaneously modify the solution for the moment tensor. Lastly, the three components of displacement, and slip distribution are computed and its effects on surface structures, as induced stress, are examined. Meanwhile, single inversions are also performed on the L-band, C-band, and X-band observations, separately, and their differences are shown and discussed, too.
2. Geological and seismotectonic setting
Qeshm is the biggest Persian Gulf island located parallel to Iran’s southern coastline, between the latitudes of 26°32΄N and 26°59΄N and longitudes of 55°15΄E and 56°17΄E. Iran lies within the zone of collision between the Eurasian and the Arabian plates (Talebian and Jackson, 2004). In the vicinity of Qeshm, the annual rate of convergence is about 25 mm (Vernant et al., 2004). Based on the existing correspondence between Qeshm Island’s big anticlines and Zagros’ anticlines, as well as the external sedimentological and tectonic similarities of the island with Zagros, Qeshm can be included in the southern part of the Zagros Mountains (Amrikazemi et al., 2004). Some of these anticlines and synclines are shown in Fig. 1. The stratigraphy of the formations in the Qeshm Island includes: Hormoz Series, Mishan formation dating back to the late Miocene, with an estimated thickness of 100 m, Aghajari formation dating back to the late Pliocene, Qeshm limestone unit with a thickness of 4-5 m dating back to 25 to 30 thousand years ago, Dulab conglomerate dating back to the early Holocene, Suza sandstone with a thickness varying from 3 to 4 m dating back to 4 to 5 thousand years ago, and the late Holocene sediments (Samadian, 1982; Nissen et al., 2010). The deposits are affected by a series of broad, mainly anticlinal folds that show a variety of trends in the central part of the island. Based on the evidence such as earthquake focal mechanisms and hypocentral depths, shortening in this area is accommodated by a mixture of high-angle and low-angle reverse faulting with dips greater than 30°, within either the lowest part of the sedimentary cover or in the basement beneath the Hormoz salt (Talebian and Jackson, 2004). The location of Qeshm Island, its earthquake sequence and folds are shown in Fig. 1.
3. Data and methods
3.1. Strong ground motion data and processing Strong ground motion data provides researchers with important information on the simulation of ground motion, earthquake rupture processing, and, consequently, source parameters of an earthquake. The data were recorded by the Iranian Strong Motion Network which is run by the RHDRC using three-component SSA-2 accelerometers with a threshold of 10 Gals at a sampling rate of 200 samples per second. All components of these data types are used in this study. The recording stations are shown in Fig. 3.
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3.1.1. Permanent displacement from strong ground motion data To obtain permanent displacement from strong ground motion data, we apply the baseline correction method. The baseline correction procedure is used to remove long-period noise combined with the records. This correction aims to recover the most plausible velocities and displacements. The approach used in this study is based on the baseline correction of the velocity trace, obtained by integration of the raw accelerogram, and, then, subdividing the velocity trace into three intervals defined by the two-time periods t1 and t2. These correction points are chosen following the procedure proposed by Wu and Wu (2007). Within these intervals (the pre-event window between the time of the first sample time t0 and time t1 from which the ground starts moving towards the permanent displacement, transient window, between time points t1 and t2, and post-event window from t2 to the end of the signal), a least squares linear regression defines the segments that interpolate the data. In the pre-event and post-event sections of the velocity trace, we apply a least squares regression to set the baseline to be removed. In the transient window, we use the correction on the acceleration time series as proposed by Boore (2001). The identified segment is, then, subtracted from the signal itself. The advantage of the baseline fitting technique is that the obtained displacement trace can show a constant value at the end of the record that can be interpreted as the residual displacement in the vicinity of the fault. The order of magnitude of this residual displacement depends on the distance from the fault, the depth of the earthquake, and the event magnitude. To obtain the permanent displacement from strong ground motion data, we use two stations with a maximum distance of 50 km from the mainshock (Suza and Tomban stations of RHDRC centre). For greater distances, this method cannot be applied to obtain permanent displacement. Every station has three components of longitudinal (L), vertical (V), and transverse (T) components that are oriented N-S, vertical, and E-W, respectively. The displacement traces and their permanent displacements are shown in Fig. 2.
3.2. SAR data and InSAR processing InSAR is a commonly used technique to measure surface deformation. Measurements by the SAR satellites are made obliquely below the satellite during both ascending and descending orbits. In this study, ALOS-1/PALSAR, ENVISAT/ASAR and TerraSAR-X images acquired from both ascending and descending orbits are available to study the coseismic deformation field of the 2008 Qeshm earthquake (Table 2). The borders of these three images are presented in Fig. 3.
3.2.1. Elastic dislocation modelling InSAR measurements, which are the phase difference between two images, i.e. master and slave images, acquired at difference times, are especially sensitive to topography, the electrical properties of the ground, atmospheric conditions, spatial separation between satellites, and ground motion (Ferretti et al., 2001; Colesanti et al., 2003). The interferometric phase contains different constituents as follows (Zebker and Rosen, 1994):
φint = W {φtopo + φdef + φnoise + φatm + φorb + φflat} (1)
where φdef is the phase of ground surface deformation, φatm is the phase resulting from the
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Fig. 2 - Permanent displacement obtained by double integration of raw accelerograms and applying the baseline correction method at Suza and Tomban stations. The red dashed line between the first and last part of the displacement trace in longitudinal (L), vertical (V) and transverse (T) components corresponds to the permanent displacement after Qeshm earthquake. Comp indicate component.
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Table 2 - Available satellite/sensor’s images to study the coseismic deformation field of the Qeshm earthquake. Legend: λ is wavelength; ∆t is the temporal baseline; B⊥ is the perpendicular baseline; ASC and DSC are ascending and descending respectively.
Satellite/Sensor λ Pass Track Master Date Slave Date Δt (day) B⊥ (m) 2 PI Ambiguity displacement (m) ALOS1/PALSAR L ASC 520 2008/08/19 2008/10/04 64 910.144 0.118 ENVISAT/ASAR C DSC 435 2008/04/17 2008/10/09 175 -96.013 0.028 TerraSAR-X X ASC 30 2008/04/30 2008/10/12 165 -33.291 0.016
atmosphere caused by the different atmospheric delay, φorb is the orbital error, φtopo is the phase contribution caused by the topography, φnoise is the noise caused by decorrelation, φflat is the effects of a spherical Earth and W is the wrapping operator. The main idea is to estimate and remove all the phase components to retrieve the deformation phase contribution. Phase unwrapping estimates the number of phase cycles detected by the radar. We process the images with SARscape Sarmap (sarmap, CH) software that is a modular set of functions available under ENVI (Environment for Visualizing Images) platform.
Fig. 3 - Illustration of the available image borders and the location of the RHDRC stations that have recorded the main shock of the 2008 Qeshm earthquake.
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To improve the signal-to-noise ratio, we averaged the images in azimuth and range, and the output resolution of all interferograms become about 20 m. To subtract the topographic contribution from the images, we use the 90 m SRTM digital elevation model. We further reduce the interferometric phase noise by applying an adaptive filter (Goldstein and Werner, 1998) and, then, unwrap the DInSAR maps using a region growing approach (Reigber and Moreira, 1997). Since each 2π cycle (interferometric fringe) of differential phase corresponds to the half wavelength of displacement along the LOS direction, the absolute unwrapped phase values are converted to displacement and directly geocoded into a map projection. The Minimum Cost Flow (square grid) unwrapping method is used, and pixels with coherence values smaller than the desired threshold are not unwrapped (Costantini, 1998). In an interferometric correlation, the complexity of the phase signal of the two SAR images and their coherency at each location are measured. Correlation between the interferometric phase measurements in a small region is used as an estimate of the signal coherence (Zebker and Villasenor, 1992). Measurements used in the inversion are done by resampling the displacements obtained from unwrapped interferograms on a variable size mesh, with 500 m of maximum resolution in the fault proximity and 1000 m elsewhere, taking into account the impact of Digital Elevation Model (DEM), azimuth line of sight (an image that is created by the azimuth of antenna corresponds to each pixel), and incidence line of sight (an image created with incidence angle of the line of sight of antenna which corresponds to each pixel) for a given data set. After a regular mesh of points sampled on user-defined areas with a proper resolution, coseismic displacement modelling is carried out with a consolidated two-step approach via non-linear inversion to solve coseismic displacements on a rectangular dislocation for the strike, dip, rake, slip, dimensions, location, and depth of the fault, and linear inversion for slip distribution on the fault plane that can provide useful information from a tectonic point of view (Atzori et al., 2009). In both steps, the underlying model is a rectangular dislocation in a homogeneous and elastic half-space (Okada, 1985). To model the earthquake source parameters, we employ the non-linear inversion approach. The non-linear inversion is based on the Levenberg-Marquardt minimisation algorithm (Marquardt, 1963). The Levenberg-Marquardt algorithm can be seen as a regularisation of the Gauss-Newton method. The objective function of the Levenberg-Marquardt inversion algorithm is given as:
(2) where d is the observation, σ is the standard deviation associated with each datum, N is the number of data cells, m is the model parameters vector, and f is the non-linear forward model which is the Okada model (Okada, 1985). The primary purpose is to find the model parameter vector m, which minimises F. To find the parameters of the causative fault as an analytical model, we constrain the inversion processing to minimise the difference between observed and predicted data in a least squares sense.
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The linear inversion is performed to retrieve the slip distribution over the fault with fixed geometry and rake. The applied algorithm is similar to the one described by Atzori et al. (2008). We invert the data set jointly to find the best fit for slip distribution. The algorithm is based on the linear inversion of the matrix:
(3)
where da is the ascending and descending observed data vector and dd is the permanent displacement obtained from strong ground motion data; m is the vector of slip values; G is the Green’s matrix, ∇2 weighted by the coefficient k (Wright et al., 2003; Funning et al., 2005). To prevent changing the direction of slip on the fault, we use the non-negative least squares algorithm for this solution. The starting point for the linear inversion is the source calculated by the non-linear inversion (Table 3). All parameters other than slip are fixed according to Table 3, and the dimension of the fault is extended. The dimensions of the fault are considered as 30×12 km2 given by 30 patches along strike and 12 patches along with the dip directions.
Table 3 - Reported source parameters for the Qeshm 2008 earthquake. The depth denotes focal depth here.
Satellite Frequency Width Length Depth Strike Dip Longitude Latitude Rake Slip (m) Focal Bands (km) (km) (km) (°) (°) (°) Mechanism
L-band 7.2 13.6 6.9 38 45 55.92 26.84 41 0.74
C-band 7.2 13.5 6.4 35 48 55.94 26.87 66 0.45
X-band 7.2 22 5.9 26 57 55.97 26.93 55 0.47
Joint inversion 5.5 13.3 6.1 38 54 55.92 26.87 76 0.57
3.2.2. Extraction of induced stress After calculating the source parameters and the slip distribution, we investigate the possible interactions among the causative fault and surface structures. We hypothesise a triggering effect from the causative fault of the Qeshm earthquake and calculate the stress change induced onto the structures with previously retrieved geometries (anticlines and synclines), through the static analysis of the Coulomb Failure Function (CFF) (Harris, 1998). Positive CFF means that the effect of the main event increased the likelihood of subsequent shocks toward failure, while negative CFF represents fault relaxation and failure-time delay.
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3.3. Joint inversion for earthquake modelling To model the earthquake, we apply the joint non-linear inversion method to three different data sets of L-band, C-band, and X-band and permanent displacement obtained from strong ground motion data. Moreover, for the comparison, the source parameters are also separately estimated from each data set in a single inversion method. In the joint inversion of three different data sets, a new objective function, G, is defined as follows:
G = αX FX + αC FC + (1 – αX – αC) FL (4)
where FX, FC, and FL are the difference between the observed and simulated displacement for L-band, C-band, and X-band, respectively. α indicates the weight coefficient, which is the relative importance of the data sets. In our study, due to the decorrelation effect that mostly occurred in the SAR data with small wavelengths, the data sets obtained from InSAR observations are not equally weighted. The histograms of the coherency values of three data sets are illustrated in Fig. 4. According to Fig. 4, L-band and C-band observations contain more coherent pixels than the X-band and, consequently, have more weights in the joint inversion procedure. However, these observations not only complement each other but also lead to more reliable results. The assigned weight to the permanent displacement obtained from strong ground motion data, due to the existence of uncertainty for choosing the time interval, is less than what is assigned to InSAR data.
Fig. 4 - Histograms of the coherency values of L-band, C-band, and X-band SAR observations with a mean (μ) and standard deviation (α) values.
Although the source parameters are assumed to be completely unknown, we must set, for each parameter, a range between lower and upper values. Proposed values are directly taken from the reported event parameters (GCMT catalogue) or the parameter standard deviation derived with the Wells and Coppersmith (1994) relations and field observations. Since the GCMT catalogue provides two solutions corresponding to the alternative focal planes, we should know which one is the correct solution. To choose between two planes,
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we create two elastic dislocation fields based on Okada’s model using two sets of parameters corresponding to plane 1 and 2 via forward modelling. After the comparison with the observed one, plane two is selected. With the joint inversion of three LOS deformation fields and permanent displacements obtained from strong ground motion data, source parameters of the causative fault of the Qeshm earthquake are calculated. The number of tests for global minimum and cost function tolerance is considered 300 and 0.001, respectively. Finally, the slip distribution of causative fault is obtained from joint linear inversion of four SAR deformation fields and permanent displacement from the strong ground motion data.
4. Results and discussion
In Fig. 5, the observed and predicted displacement fields for the ascending and descending tracks are shown. Then, to interpret the similarity between real and obtained parameters, the residuals between observed and synthetic displacements are created. Then, the three components (east, north, and up components) of this earthquake are extracted (Fig. 6). These results show that the higher the diversity of the geometric configuration of the SAR data and permanent displacement, the more accurate the N-S retrieval results will be. This method provides an effective way to improve the accuracy of N-S deformation retrieval, while the equal-precision 3D deformation estimation cannot be obtained from other approaches [such as a combination of ascending/descending SAR acquisitions, the multi-aperture interferometry (MAI) algorithm, offset-tracking technology, and combining the D-InSAR with global positioning system (GPS) data]. Compared to the previous studies, the 3D deformation map enables us to identify the more realistic surface movements due to the earthquake and provides a new understanding of the mechanism and behaviour of the fault. The single inversion results obtained from individual data sets as well as those obtained from the joint inversion approach are shown in Table 3. 2D faults extracted from single and joint inversion and other studies are shown in Fig. 7. As observed, the fault geometry derived from the inversion of the InSAR observations, except for the X-band, is highly comparable with the one given by Lohman and Barnhart (2010). Those provided by GCMT catalogue and reported by Nissen et al. (2010) are significantly different from the others. The joint solution has fewer residuals compared to single solutions for each data set, and its results are more reliable (Fig. 5). We find that the total seismic moment released 18 is 1.32×10 with MW = 6.0. The causative fault is a ESE-dipping fault plane towards the south-eastern part of Qeshm Island. The rake obtained from the joint inversion is estimated to be 76°. Thus, the Qeshm earthquake causative fault is a reverse one with a left-lateral component that causes the projection of the hanging wall moving towards the NE of Qeshm Island. However, the reverse component has overcome the strike-slip component. The source position is referred to as the source centre point vertically projected on the ground surface. Depth is calculated as a distance between the source upper edge and the ground surface (positive downwards). The rupture plane is located at depths between 6.1 and
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Fig. 5 - Data misfit for our best model derived by single (3 top rows) and joint (3 bottom rows) linear least squares inversion for L-band, C-band, and X-band observations, respectively. Observed (left), modelled (middle), and residual (right) displacement maps of unwrapped interferograms relating to the Qeshm earthquake are shown. Colour legends are scaled according to the minimum/maximum value for the observed and modelled maps, while the same discrete colour scheme is adopted for the residual maps.
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Fig. 5 - continued.
Fig. 6 - E-W, N-S and Up (ENU) displacement components: a) synthetic east component, b) synthetic north component, and c) synthetic up component of the deformation field. One notable point is that the northern part of the Qeshm Island shows a high asymmetry. It means the north part of the fault could be affected by a low-dipping slip motion. Most of displacement is vertical indicating a reverse fault. The east and north components show a left-lateral component too.
11.6 km. It should be noted that the reported depth in this study has been corrected concerning the topography. In other words, the final extent is a combination of the estimated depth and the topography extracted from DEM (Simons et al., 2002; Oth et al., 2007). The coordinates indicate the centre of the fault rather than the earthquake epicentre, but because the maximum slip (Fig. 8) has occurred in the centre of fault, it can be considered as the centroid point too. Observed and synthetic permanent displacement values obtained from the baseline correction of two accelerograms at Suza and Tomban stations with root-mean-square 0.009 are shown in Table 4.
Table 4 - Values of observed and synthetic permanent displacement [in the longitudinal (L), vertical (V), and transverse (T) components] obtained from baseline correction of two accelerograms at Suza and Tomban stations.
Observed Permanent displacement (cm) Synthetic Permanent displacement (cm) Station Comp L Comp V Comp T Comp L Comp V Comp T Suza -1.00 0.72 -0.30 -1.20 0.58 -0.37 Tomban -2.20 -0.50 -0.50 -1.86 -0.39 -0.90
Fig. 8 shows the slip distribution resulting from a joint linear inversion of the coseismic displacement fields. The maximum amount of slip distribution matches the centroid point and is located in the centre of the fault.
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Fig. 7 - Illustration of 2D fault reported by Lohman and Barnhart (2010), Nissen et al. (2010), GCMT catalogue and our study.
As shown in Fig. 1, the coseismic uplift is on a prominent anticline (Laft anticline) in the northern part of Qeshm Island, which implies that the reverse fault directly beneath this particular fold can control its growth. This fault can be the origin of the southern syncline. To investigate this hypothesis, we examine the possible interactions between the faulting
Fig. 8 - Slip distribution of the causative fault of the Qeshm earthquake.
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and folding. We hypothesise a triggering effect from the fault onto the anticline and syncline fold axes and calculate the induced stress changes through the CFF (Harris, 1998). Two near folds (Fig. 1) are examined in this study (Laft anticline and Ramkan syncline). The folds are considered symmetric (Nissen et al., 2011) and flat. Induced stress is shown in Fig. 9. When the joint inversion solution is compared to the simplified stratigraphic column for the far south-eastern Zagros (Molinaro et al., 2005) proposed by Nissen et al. (2010), it is concluded that the fault estimated in this study affected the sedimentary sequence cover approximately at a depth of the Hormoz salt, while it does not reach the basement and surface. The slip distribution confirms these observations. Consequently, the Hormoz salt plays an essential role as a barrier to slip distribution. Considering the rate of convergence of about 25 mm (Vernant et al., 2004) and the maximum displacement observed in Fig. 6, this earthquake accommodates most of the annual convergence.
Fig. 9 - Stress change induced by the Qeshm earthquake on two fold axes (Laft anticline and Ramkan syncline) based on the CFF (Harris, 1998). The causative fault of the Qeshm earthquake is gridded. The surface topography is shown in yellow-brown range colour.
Most displacement related to the Qeshm earthquake occurred as upward displacement (Fig. 6) and demonstrated, assuming the effect on folds, that the vertical growth is dominant in the region and can affect the topography. The induced stress on fold axes (Fig. 9) shows that it could reach the surface exactly beneath the Laft anticline and has an effect on its vertical growth with no impact on the Ramkan syncline. This earthquake is related to a fold that engages the Sarvak to Faraghan formations [for more information about the stratigraphic column refer to Nissen et al. (2010)].
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5. Conclusions
In this paper, we use a joint inversion approach to estimate the source parameters of the 2008 Qeshm earthquake. In this procedure, we use three different InSAR data sets and strong ground motion data with an appropriate cost function leading to more reliable results of the joint inversion method. The results depict a significant LOS deformation in the centre of the study area. According to the source parameters estimated from the joint inversion, it is found that the Qeshm earthquake causative fault is a reverse fault with a left-lateral component. This fault has affected the sedimentary sequence cover approximately at a depth of the Hormoz salt while it does not reach the basement and surface. The vertical growth is dominant in the region and affects the topography and folding in the Laft anticline too. The thrust mechanism of this event is compatible with a fault which accommodates the convergence of the Arabian and Eurasian plates. The total seismic moment released is 1.32×1018, and the centroid location of slip is 55.93° easting and 26.86° northing at a depth of 8 km in the Dalan formation [for more information about the stratigraphic column refer to Nissen et al. (2010)].
Acknowledgements. We are grateful to the German Aerospace Center (DLR) for supplying TerraSAR-X data. The ENVISAT ASAR data has been provided by the European Space Agency (ESA). ALOS data was provided by the Japan Aerospace Exploration Agency (JAXA) and the Alaska Satellite Facility (ASF). We convey our sincere gratitude to the Road, Housing and Development Research Center (RHDRC) of Iran for providing acceleration data of the Qeshm earthquake. All InSAR processing was carried out using SARscape 5.4 module within an ENVI environment. We wish to express our special thanks of gratitude to Earthquake Precursors Center of Iran. The authors would like to acknowledge the software providers Sarmap SA and prof. Mohammad Sharifikia (Tarbiat Modares University) for providing the software license of SARscape 5.4. The authors also acknowledge the helpful comments of the editor and reviewers.
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Corresponding author: Mehdi Rezapour Institute of Geophysics, University of Tehran Street Amirabad Shomali, Tehran, Iran Phone: +98 216 1118228; e-mail: [email protected]
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