The style of deformation changes from the hinterland (Sanandaj-Sirjan zone) to the foreland (Zagros) through the Zagros Orogen containing thick-skinned and thin-skinned deformation respectively. NW-SE trending thrust faults dipping to northeast have carried the older rock sequences to the surface. The Zagros collision zone could be divided into two distinct parts based on deformation mode that is separated by the Main Zagros Thrust. The southwestern part contains imbricate thrust sheets instead, to the northeastern part large amount of shortening is documented by basement deformation with duplex structures. Abundant crystalline deep origin thrust sheets have transported (2 up to 20 km) the metamorphic rock units upon the Zagros suture zone by gravity or tectonic forces. Despite the collision thrust faults, both NW oriented (Main Recent Fault) and NE oriented (named here Azna Fault) basement wrench faults have also activated and caused different style and amount of deformation in the collision zone.

The Zagros orogenic belt was formed approximately 12 million years ago due to the convergence between the Arabian and Eurasian plates upon the closing of the Neo-Tethys Ocean. The Zagros is categorized as one of the youngest such settings on Earth, at an early stage of this collision. Many geophysical multiscale studies have been performed in the Zagros region based on different seismic and non-seismic data. Based on these studies, it can be concluded that the Zagros thrust belt has a crustal thickness of 45 ± 3 km, whereas beneath the Sanandaj-Sirjan zone, the Moho depth significantly increases up to 65 3 ± km. Among the many geophysical studies of Zagros and surrounding areas, local earthquake tomography (LET), which uses travel time data of both stations and earthquakes located in the study area, has never been performed for the entire Zagros. In this research, a 3D velocity model of body waves has been extracted using the information of the arrival time of 7783 earthquakes in the period of 2006 to 2018, recorded in the National Seismological Center and the broadband seismic network of Iran. The dataset used for tomography consists of 123, 575 P-and 11, 520 S-picks from 7783 events with magnitude greater than 2. 5. We used the LOTOS code (Koulakov, 2009a) developed for simultaneous inversion for the 3D distributions of the P and S wave velocity anomalies and source locations. In the first step, LOTOS determines initial source locations using tabulated values of travel times previously calculated in a 1-D velocity model. The iterative algorithm of tomographic inversion includes the following steps: (1) Source relocations in the updated 3-D velocity structure based on the ray tracing bending method, (2) calculation of the first derivative matrix and (3) simultaneous inversion for P and S wave velocity anomalies, earthquake source parameters (4 parameters for each source), and station corrections. The inversion uses the LSQR method39. The distribution of estimated 3D velocity models correlates well with tectonic and geological conditions. The Vp and Vs anomalies, which are obtained independently, appear to be almost identical in the crust (depths smaller than 45 km). According to the results, the low velocity anomaly observed in the obtained models in the upper crust can be interpreted due to the presence of Cambrian-Miocene sediments with a thickness of at least 10 km that are spread throughout the Zagros. According to the obtained velocity models in the vertical sections, the Moho depth in the Sanandaj-Sirjan area increases significantly compared to the Zagros region. This increase in Moho depth is related to the subduction of the Arabic plate below the micro-continent of Central Iran, which increases the thickness of the crust (double crust) in the Sanandaj-Sirjan region. Using LOTOS code, the optimal one-dimensional velocity model for the whole Zagros collision zone is also presented. In this model, we can distinguish a ∼10 km thick sedimentary (Vp ∼4. 90 km s-1), the upper crust down to ∼30 km (Vp ∼ 5. 54 km s-1) and the lower crust down to ∼45 km (Vp ∼6. 30 km s-1).

Two distinct collision events have occurred between Arabia and Central Iran plates, closing of the Neo-Tethys. Structural sections along the collision zone in northwest Iran show characteristics of collision structure. The first collision occurred during obduction of the oceanic components of the Neo-Tethys over the Arabian passive margin during the Late Cretaceous. Deformation along the Arabian passive margin in radiolarite and the high Zagros zones was the result of this event. The high Zagros frontal thrust fault is the maximum limit of this collision tectonic event. The obducted oceanic components, including the ophiolites in this region, unconformably are overlain by Oligocene-Miocene sediments. By the last continent-continent collision event during Late Miocene, the hinterland of the orogen was transported over the collided zone and deformation occurred by rejuvenation of the existing thrust faults in previously collided zone and the Zagros foreland basin was formed (Zagros fold-thrust belt).

The Zagros collision zone is known as an active tectonic zone that represents the tectonic boundary between the Eurasian and Arabian plates. A popular strategy for gaining insight into the upper mantle processes is to examine the splitting of seismic shear waves and interpret them in terms of upper mantle anisotropy and deformation. Core phases SK(K)S from over 278 earthquakes (MW ≥ 6. 0) occurred between years 2010 and 2017 at epicentral distances between 90° and 145° are examined, which were recorded by 27 broadband stations located in the Zagros collision zone. In compressional tectonic regimes such as the Zagros collision zone, a dominant pure shear deformation in the mantle is expected that could develop lattice preferred orientation (thus anisotropic fabrics) subparallel to the strike of the mountain belt. The findings show that the majority of the fast axes of seismic anisotropy are oriented in the NE-SW direction (perpendicular to the trend of the belt) with delay times (a proxy for the strength of anisotropy) varying between 1 and 1. 5 seconds. If deformation in the mantle lithosphere was the main factor of the observed anisotropy, then the fast direction of anisotropy would be parallel to the belt. Therefore, the main source of anisotropy is thought to be residing in the sub-lithosphere mantle. Crack-induced anisotropy in the upper crust that can be perpendicular to the trend of the belt (parallel to the maximum compressional stress direction) may also have some contribution to the observed splitting of shear-waves.

In the Northern part of Suture zone (Kermanshah) the deep sea sediments, oceanic crust remnants, platform carbonates, igneous and metamorphosed rock of active margin and carbonate sequence of passive margin are assembled in this studied area. This convergent area has provided a very complicated structural zone. The main purpose of this study is stress characteristic analysis. A great data has gathered from the faults which are appeared within the rocks specially the radiolaritic rocks. The data includes characteristics of fault surface geometry, fault slip and lineation slip related. By using the method Right Dihedral, the position of main stress was obtained. The great number of reverse faults have a NW-SW trend, while the strike-slip faults, show a NE-SW direction. The Normal faults with a different displacements appeared younger than the other faults. The result of this study that we obtained the situation of main stress σ 1, σ 2 and σ 3 respectively is 059, 305 and 195.

The targeted area of this research includes E Anatoly, NW Zagros, and Caucasus. These structures are known as a complex and active area and in the early stage of continent-continent collision, which give us unique possibility to monitor such collision in real time. Therefore, it is very important to study this active area to have a better knowledge about its tectonic behavior and lithospheric structure. Key parameters that we are looking for in this research are Moho depth, lithosphere-asthenosphere boundary (LAB) and average crustal density.There are methods, which can give us some information about lithospheric structure such as the seismological method, seismic (controlled source) method, magnetotelluric, volcanology etc. The method used here is a direct, linearized, iterative inversion procedure in order to determine lateral variations in crustal thickness, average crustal density and lithospheric thickness via potential field data. The area of interest is subdivided into rectangular columns of constant size in E-W (X) and N-S (Y) directions. In depth (Z), each column is subdivided into four layers: seawater if present (with known thickness, i.e. bathymetry, and a density of 1030 kg/m3), crust, lithospheric mantle, and asthenosphere. For our research, the definition of the LAB is an isotherm and we try to calculate the temperature distribution in the lithosphere. During the inversion process, a cost function has to be minimized defined as C=Ed+lEp+mEs. The factor l allows controlling the overall importance of parameter variability (Ep) with respect to data adjustment (Ed), whereas m is a factor controlling the importance of smoothing, which can be different for each parameter set.The method uses potential field data (free air gravity, geoid, and topography) which are globally available by satellite measurement and are freely accessible on the internet. The potential field data are sensitive to the lateral density variations, which happen across these two boundaries but at different depth. Free air gravity data are 2.5´2.5 arc-minute grid, which was taken from the database of Bureau Gravimétrique International (BGI). Geoid height variations correspond to the EGM2008 model. In order to avoid the effects of sublithospheric density variations on the geoid, we have removed the long-wavelength geoid signature corresponding to spherical harmonics until degree and order 10, tapered between 8 and 12. Topography data are taken from the 1-minute TOPEX global data sets. All data were interpolated on a regular 10x10 km grid.Inverting potential field and topography data suffers from non-uniqueness since these data are not sensitive to vertical density variations, which may produce instabilities of the solution. Stabilization of the inversion process may be obtained through parameter damping and smoothing as well as the use of a priori information like crustal thicknesses from seismic profiles.The 3D results show an important crustal root under Caucasus and relatively thick Moho for the eastern part of Anatolia and NW Zagros and a thin crust under the southern part of the Black Sea, which is thickening northward. Regarding LAB, the 3D results show thin lithosphere under the E-Anatolia, NW Zagros and the western part of Caucasus. The LAB thickens northward towards the Eurasia and in the western part of Anatolia.

One way of gridding two dimensional vector data is gridding each component separately. Alternatively, using Green’s functions we can grid two components simultaneously in a way that couples them through elastic deformation theory. This is particularly suited, though not exclusive, to data that represent elastic/semi-elastic deformation, like horizontal GPS velocity fields. Measurements made on the surface of the Earth are often sparse and unevenly distributed. For example, GPS displacement measurements are limited by the availability of ground stations and airborne geophysical measurements are highly sampled along flight lines but there is often a large gap between lines. Many data processing methods require data distributed on a uniform regular grid, particularly methods involving the Fourier transform or the computation of directional derivatives. Hence, the interpolation of sparse measurements onto a regular grid (known as gridding) is a prominent problem in the Earth Sciences. In this research, sparse two-dimensional vector data of the horizontal GPS velocity field are interpolated using Green’s functions derived from elastic constraints. The method is based on the Green’s functions of an elastic body subjected to in-plane forces. This approach ensures elastic coupling between the two components of the interpolation. Users may adjust the coupling by varying Poisson’s ratio. Smoothing can be achieved by ignoring the smallest eigenvalues in the matrix solution for the strengths of the unknown body forces. The study area is the oblique collision zone of Arabia-Eurasia tectonic plates, which has a GPS velocity field with sparse distribution. Since the Green’s functions developed for the half-space environment, the Mercator map projection used to create the half-space for interpolation and gridding. Data split into a training and testing set. We will fit the gridder on the training set and use the testing set to evaluate how well the gridder is performing. The vector gridding was done using the Poisson's ratio 0. 5 to couple the two horizontal components. Then score on the testing data. The best possible score is 1, meaning a perfect prediction of the test data. By calculating the mean square deviation ratio (MSDR) to evaluate the gridding accuracy, the score of 0. 86 obtained for this statistic. While this method is not new, it provides some insight into the behavior of the coupled interpolation for a wide range of Poisson’s ratio. This approach provides improved interpolation of sparse vector data when the physics of the deforming material follows elasticity equations. We interpolated our horizontal GPS velocities onto a regular geographic grid with 1 arc second spacing and masked the data that were far from the observation points and finally the residuals between the predictions and the original input data were calculated. Interpolation of horizontal GPS velocity fields of local geodynamic networks were proposed to obtain an estimate for Poisson's ratio values in the best case for gridding validation. In this study, two dimensional GPS data were interpolated. Three dimensional GPS data gridding can also be done using the Green’s functions provided by Uieda et al., (2018). It is also recommended to use different Green’s functions to grid different types of spatial data.

GPS velocity fields consist of a set of geodetic observations of displacement with an irregular spatial distribution on the sphere. In this study, multiscale analysis based on spherical wavelet is used to estimate the GPS velocity field in the oblique collision zone of Arabia-Eurasia tectonic plates. Multiscale velocity field estimation is well suited for dense geodetic networks and is straightforward to implement.We show that for DOG wavelet a scale of 3 to 8 is suitable for GPS velocity field analysis in the study area. Estimation output can be used as a data layer in GIS analysis. Regularization is required to obtain a smooth estimated velocity field from the discrete observations. This is achieved through two possible actions. First, one can cull the set of possible spherical wavelets based on the coverage of observations. If each spherical wavelet has a sufficient number of observations constraining its coefficient, then no regularization is needed (λ = 0). Second, if all spherical wavelets are used for the inverse problem, then extensive regularization will be needed, since most wavelets will have zero observations for constraining their corresponding coefficients. In this research, we have chosen something in between these two extreme cases, where we at the outset eliminate many candidate spherical wavelets based on data coverage, but we still require a moderate amount of explicit regularization in the inversion.As the adopted spherical wavelets are analytically differentiable, spatial gradient tensor quantities such as strain rate, dilatation rate and rotation rate can be directly computed using the same coefficients. The gradient quantities are then calculated directly from the estimated field to identify potential deformation signals. The first factor controlling the estimation is the distance between the network stations. Wherever stations are dense, short-scale spherical wavelets participate in the estimation; and where stations are sparse, only long-scale spherical wavelets is used to do the estimation. As we allow shorter length-scale frame functions to be used in estimating the velocity field, the residual field vectors decrease in magnitude. The smallest residuals occur at observation points that are dense enough to fall within the support of the smallest length-scale frame functions which also have the smallest estimated uncertainties in the data. The largest residuals overall are associated with the largest uncertainties in the data.From the perspective of monitoring a GPS network, the residual map may be helpful in detecting spurious behaviour of singles at stations. If unusual strain, dilation, or rotation are observed around a station, such an observation would warrant additional analysis of the GPS time-series and error estimate. We remove a rotational field from the observation set to obtain the velocity field. We then estimate the horizontal velocity field. Once we have estimated the multiscale velocity field, we can readily compute other scalar quantities, such as dilatation, strain and rotation. The high density of stations near the fault system could capture the spatial gradient in the velocity field, and give rise to estimate strain-rates with a maximum of 1.410×10-7, an average of 1.786×10-8 and a standard deviation of 1.626×10-8 per year. The dilation rate is obtained with a maximum of -8.684×10-8, an average of -3.487×10-9 and a standard deviation of 1.144×10-8 per year and the rotation rate is obtained with a maximum of 7.771×10-8, an average of 7.720×10-9 and a standard deviation of 7.040×10-9 radians per year in the study area.Due to the shorter distance of observation stations in the southern part of central Alborz and northwestern Iran, the values of strain, dilatation and rotation rate can be observed in these areas on large scales.In multiscale estimation, the residual field between the original field and estimated field may reveal two key features. First, if there are systematic residuals in a particular region, then it is probable that one needs to include shorter-scale wavelets in the estimation. Second, if there is a strong residual at a single station, then the station is anomalous and is either malfunctioning or is capturing a signal that is not spatially resolved. The advantages of the multiscale approach are its ability to localize the deformation field in space and scale, as well as its ability to identify outliers in the set of observations. This approach can also locally match the smallest process obtained with the local density of observations, thus maximizing both the amount of information extracted and the possibility of comparing the resulting quantities in different regions of a scale. Multiscale estimation of the three-dimensional GPS velocity field is also possible using spherical wavelet frame functions. The vertical component, if any, should be used to estimate the velocity field, as deformation may not be predominant in horizontal directions. This formulation may be easily applied either regionally or globally and is ideally suited as the spatial parametrization used in any automatic time-dependent geodetic transient detector.

The studied zone is in the Northern part of Zagros Suture zone (Kermanshah). The presence of deep sea sediments, oceanic crust remnants, platform carbonates, igneous and metamorphosed rocks of active margin and carbonate sequence of passive margin that are assembled in the studied area show a compressional tectonic regime from the late Cretaceous up to the present. As a result of convergent regime, a very complicated structural zone is developed. The main purpose of this study is stress characteristic analysis in Zagros Suture zone (Kermanshah). To recognize and study the arrangement of stress axes a great amount of data were gathered from the folds axial surface and the faults which are appeared within the rocks specially the radiolaritic rocks. The data includes characteristics of fault surface geometry, fault slip and lineation slip. The stress recording patterns for data in this study is Multiple Inverse Method and comparison with stress position by using folds axial surface. By studying folds it was obtained the situation of main stress σ 1, σ 2 and σ 3 respectively as 029, 127, 234 and by using the method Multiple Inverse Method, the situation of main stress is obtained as 059, 304, 194. Based on the investigations in the study area and measurements on Cretaceous rocks, the results show that the main stress direction since Cretaceous up to the present is northeastern with minor changes. The estimations of stress direction were the same in both folds and faults. As a result, the shortening direction has been constant, so the shortening faults all show one direction of stress.