فهرست مطالب mohammad reza sepahvand

Crust velocity structure beneath two broadband seismic stations of Iran National Seismic Network (INSN), DAMV and THKV located in Central Alborz has been investigated by joint inversion of receiver function and Rayleigh wave phase and group velocity dispersion curves. The result suggests that Moho depth beneath the THKV and DAMV stations are 50-51 km and 52-54 km, respectively. Beneath the THKV station, there is a thin layer of very low-velocity materials at the surface and a sedimentary layer having a thickness of 10-12 km above a crystalline crust with a thickness of 34 km. Beneath the DAMV station, there is a thin sedimentary layer of low velocity with a thickness of 3-4 km, and also, a velocity change from 3.2 to 3.6 km/s at the depth of 14-16 km, indicating a discontinuity, which might be attributed to the border between the upper and lower crusts. The average Moho depth on the southern edge of Central Alborz is 52±2 km.

Crustal velocity structure in the Western Alborz have been investigated using joint inversion of receiver functions and Rayleigh wave group velocity dispersion curves. To determine the receiver functions, time domain iterative deconvolution and teleseismic events, which are recorded at five broadband seismic stations of the Iranian Seismological Center (IRSC), were used. The fundamental mode Rayleigh wave group velocity dispersion curves were provided by the study on the structure of crust and upper mantle of the Iranian Plateau. The results show that the average thickness of the crust in the southern margin of the Caspian Sea beneath of the CSN1 and RST1 stations is 38 km. Toward south, the depth of Moho increases up to 52, 54 and 50 km beneath the QALM, QCNT and QSDN stations. The low thickness of the crust in the southern shore of the Caspian Sea indicates that the Caspian crust is thin. Moreover, the moderate thickness of the crust in western Alborz, which is not in balance with its elevation, indicates the lack of root in Alborz.

Designing and launching rapid warning systems to reduce financial and human losses is one of the requirements of seismic areas. The main goal of these systems is to estimate the magnitude of the earthquake and the epicentral distance in a very short time and to announce a warning. A new method, called B-Δ, is used in these systems. It is based on information from a station and estimates the magnitude and epicentral distance of an earthquake using the initial seconds of the P wave. In this study, these two parameters have been estimated in east of Kerman Province after examining and processing of the vertical component of the accelerograms of the earthquakes in this area.

Crustal velocity structure and Moho discontinuity depth have investigated beneath 7 the broadband seismic stations, AFRZ, TKDS, TPRV, TNSJ, ANAR, KRSH of the Iranian Seismological Center (ISC) and YZKH of Iranian National Seismic Network (INSN) located in the center of Iran by joint inversion of receiver functions and Rayleigh waves group velocity dispersion. Three years (2012 to 2014) teleseismic waveforms (with epicentral distance 25o-90o) for computation receiver functions by iterative approach in time domain have been processed. The Rayleigh waves group velocity dispersion curves were incorporated into our joint inversion scheme from an independent surface wave tomography study. Receiver function is response of local structure of ground (located beneath the three–component broadband seismic station) to teleseismic P-wave, that is sensitive to seismic discontinuities. Since there is very little absolute-velocity information contained in the receiver function, its inversion for shear-wave velocity structure is non-unique (velocity-depth trade-off). On the other hand, dispersion curves are sensitive to the average velocity structure of the upper layers rather than to seismic discontinuities. So the non-uniqueness problem can be solved by combining receiver function inversion with surface-wave dispersion. Results from joint inversion in center of Iran indicates that Moho discontinuity depth depth beneath AFRZ, TKDS and TPRV stations is 40 Km, beneath TKDS 42 Km, beneath ANAR is 38 Km and beneath KRSH and YZKH stations are 44 Km. It was shown that the joint inversion method can cause ±2 kilometers of error. The average Moho depth is about 42±2 kilometers beneath center of Iran.

Summary: Crustal velocity structure beneath four broadband seismic stations located in northeast of Iran, including Shahrood (SHRO) and Maraveh Tappeh (MRVT) stations set up by Iran National Seismic Network (INSN) and Sabzevar (SZBV) and Jarkhoshk (JRKH) stations set up by Iranian Seismology Center (IRSC), have been investigated by joint inversion of P receiver function and Rayleigh wave phase and group velocity dispersion curves. A three-year teleseismic data (2012 -2014) with epicentral distance of 25o-90o and magnitude more than 5.5 have been used to determine the receiver functions by iterative deconvolution in time domain proposed by Ligorria and Ammon (1999). Iterative deconvolution in time domain to determine the receiver functions are more stable with noisy data in comparison to frequency domain. The fundamental mode of Rayleigh wave group and phase velocity dispersion curves have been provided by the study on the structure of crust and upper mantle of the Iranian Plateau for the period interval of 10-100 seconds made by Rahimi (2010). A combined inversion of body wave receiver functions and Rayleigh wave velocities increases the uniqueness of the solution over the separate inversions, and also, facilitates explicit parameterization of the layer thickness in the model space. Moho discontinuity depth is one of the most important parameters for investigation of crustal structure. The results of this study indicate an average crustal thickness varying from 38 km beneath Maraveh Tappeh (MRVT) station in north of the study region up to 44 km beneath Shahrood (SHRO) station in west of the region. Moreover, the results of this study suggest that the average crust thickness beneath Sabzevar (SZBV) and Jarkhoshk (JRKH) stations located in center and east of the study region is 40 km. In general, northeastern Iran region has a thin crust compared to the crusts in the other areas investigated in this research work. It has also been shown that the joint inversion method can cause ±2 kilometers of error.
Introduction: Iran is situated in one of the world's seismic regions and the possibility of destructive earthquakes in most regions of the country has given great significance to recognition of Iranian seismic nature from a seismic and seismotectonic standpoint. The seismicity within Iran suggests that much of the deformation is concentrated in the Zagros, Alborz and Koppeh Dagh mountains, and in east of Iran, surrounding Central Iran and the Lut desert. The aim of this research is to study the crustal structure and Moho discontinuity of northeastern Iran region, Binalood mountains and Koppeh Dagh by the analysis of receiver function and surface waves dispersion.

Methodology and Approaches: Receivers functions are time series obtained from three-component seismometers, and are created by deconvolving the vertical component from the radial and transverse components of the seismogram to isolate the receiver site effects from the other information contained in a teleseismic P and S wave. The depth-velocity trade-off in receiver function causes nonuniqueness in the inverse problem. However, by incorporating information of absolute shear wave from dispersion estimates and joint inversion of these two datasets, this shortcoming can be compromised. To determine the receiver functions, we have used iterative deconvolution in time domain, proposed by Ligorria and Ammon (1999) that is more stable with noisy data in comparison to frequency domain. We have processed teleseismic events with epicentral distance of 25o-90o and magnitudes more than 5.5 that are recorded at a three-year time interval of 2012 to 2014. We have set the parameter a of the Gaussian filter to 1.00, which gives an effective high frequency limit of about 0.5 in the P wave. In order to eliminate the source, path and instrument effects, deconvolution of the vertical component from the horizontal components of the seismograms has been used. All receiver functions have been grouped by azimuth (<10◦) and distance (<15◦), and in order to improve the signal-to-noise ratio, the individual receiver functions within each group have been stacked. The fundamental mode of the Rayleigh wave group and phase velocities dispersion curves have been provided from the study carried out by Rahimi et al., (2014) on the structure of crust and upper mantle of the Iranian Plateau for the period interval of 10-100 seconds. Joint inversion of two independent data sets has been performed by considering appropriate weighting parameter obtained from Herrmann and Ammon program (2003). Minimizing standard error between real and predicted data is the criteria for getting the desired final and close to the earth real model. The inversion package requires that the real velocity structure is represented by a set of flat-lying, homogeneous, isotropic velocity layers. The starting model comprises of the layers having 1-km thick as the top 6 km of the model space, 2-km thick between the depths of 6 and 66 km, and 4 km thick between the depths of 66 and 78 km. The starting velocity for each layer in the model has been Vp=8.0 km/s, which equates to upper mantle velocity.

Results and Conclusions: The results of this study suggest that the average crust thickness beneath Shahrood (SHRO) station, located in west of the study region is 44 km and the average crust thickness beneath Sabzevar (SZBV) and Jarkhoshk (JRKH) stations located in center and east of the study region is 40 km. Furthermore, the crust thickness beneath Maraveh Tappeh (MRVT) station located in north of Koppeh Dagh region in is 38 km. In general, northeastern Iran region has a thin crust compared to the crust in other areas of northeast of Iran.

Today, due to the accumulation of resources in urban areas, urbanization has been increased and consequently, city limits have been increased. Thus, considering the population distribution in these areas as well as the existence of a large number of these areas in sedimentary region, the significance of the study of seismology and earthquake engineering for earthquake retrofitting and reduction of the risk of earthquakes has been increased. A phenomenon that enhances damage during the earthquake, even at great distances is the site effect. Mexico City earthquake, occurred in the epicentral distance of 300 km and caused damage, is a clear example of the enhanced damage caused by site effect. Thus, this study emphasizes on the site effect and underground structures affected by shear wave velocity in earthquakes.

One of the important issues in infrastructure's destruction by earthquake is the impact of soil on the bedrock, which is known as “site effect”. Considering the fact that city of Kerman is located in the tectonic seismic state of eastern Iran and is situated near the Golbaf, Koohbanan, Sirch and Nayband faults, it is essential to reduce the dangers of the earthquake. Moreover, one of the most important structures which will be damaged during an earthquake is urban bridges. Thus, in designing the bridges, the impact of earthquake and vulnerability of bridges in places in which earthquake is likely to occur must be taken into consideration. In this study, recorded microtremor data in 52 three-component seismometric stations have been used. To have data with minimum environmental noise, all the measurements were performed in time period of midnight to 5 am in the morning. In this paper, the microtremor data related to the developing areas in Kerman and the erection site of four important bridges which are under construction has been investigated. Considering the objective of the study, which is estimation of the natural frequency and the earth vulnerability index, the recorded microtremors in the seismometric stations were processed using spectral ratio of H/V horizontal to vertical components. Results showed that frequency values vary from 0.3 to 1.2 Hz. Based on the achieved frequencies and comparison to the standard tables, it has been concluded that all the stations are of the soft-soil type in site class I. Finally, the frequency zoning map and vulnerability indices were drawn. Results showed that vulnerability index is high in the developing areas of the city of Kerman .

Iran is one of the seismically active areas of the world because it is located in the Alpine-Himalayan orogenic belt, at a 1000-km-wide zone of the compression between the colliding Eurasian and Arabian continents. Studying the crust velocity structure and Moho discontinuity in Iranian plateau is conducive to an understanding of its evolution and the tectonic history of its seismotectonic zones. Nowadays, it is indispensable to acquire sufficient and accurate data from the crust and upper mantle velocity structure or its specification.
To specify the receiver functions with an iterative approach, we made use of a two-year teleseismic data (with epicentral distance 25o-90o) recorded by six seismic stations located in the southeast Zagros (BNDS, NIAN and GENO), Makran (CHBR) and eastern Iran (SZD1 and ZHSF) . In order to delete high frequencies, Gaussian parameter 1.0 was used. So as to augment the signal to noise ratio, RFs were clustered in 10˚ azimuthal and less than 15˚ epicentral distance ranges. Finally, the RFs were stacked.
Receiver functions (RFs) show Earth’s local structure response to P-wave vertical arrival approximately beneath a three-component seismometer; these functions are sensitive to shear-wave velocity impedance. Depth-velocity trade-off in RFs information poses inversion non-uniqueness issues, but a combined inversion of receiver functions and surface wave dispersion increases the uniqueness of the solution over separate inversions, further facilitating the explicit parameterization of layer thickness in the model space, providing more exact constraints as to the crustal structure. Surface wave velocity dispersion depends more on S wave velocity than on P wave velocity, and its dependence on density is slight. In previous studies, it has been shown that it improves the inversions of receiver functions for crustal structures (Julia et al. 2000). Surface wave velocity dispersion provides information as to the absolute seismic shear velocity, yet is relatively insensitive to sharp velocity changes. The group velocities were incorporated into our joint inversion scheme from an independent surface wave tomography study by Rham (2009). Group velocities from regional events, recorded at permanent and broadband stations, were measured for fundamental mode Rayleigh waves within 10–100s period range. The region was parameterized using a uniform, 1×1°, grid of constant slowness cells. The dispersion curve is the result of separate tomographic imaging for each period. Fundamental mode Rayleigh wave group velocities are taken from the corresponding tomographic cell containing the stations. The joint inversion of the two independent data sets was performed considering a proper combination of weighting parameters done by Herrmann and Ammon’s program (2003). Minimizing the standard error between the real and predicted data is the criterion for the desired final model which is close to Earth’s real model.
Models resulting from joint inversion in the south-east Zagros (Hormozgan province) suggest that Moho discontinuity depths beneath BNDS, GENO and NIAN stations are about 54, 54 and 48 kilometers, respectively, while the average depth of Moho discontinuity in the region is about 52±2 kilometers. In the Makran’s seismotectonic state, the resulted models pertaining to single station in the region (CHBR, near the city of Chabahar) show that the average depth of Moho discontinuity in this region is about 28 kilometers and thickness of the sediments is about 10 km, consistent with the shallow subduction of a high-velocity oceanic crust of Arabian plate beneath the southern side of Makran. In the Flysch zone (eastern Iran), the models of the two stations (SZD1, ZHSF) show that the average depth of Moho is about 40±2 kilometers.

The Magnetotelluric (MT) method is an electromagnetic geophysical exploration technique that images the electrical conductivity distribution of the Earth crust and upper mantle. The source of energy in the MT method is natural. When the external energy, known as the primary electromagnetic field, reaches the Earth's surface, part of it is reflected, whereas the remainder penetrates into the Earth, which by interaction with the conductors, induces an electric field (known as telluric currents) and at the same time produces a secondary magnetic field which can be measured at the surface and the impedance tensor is calculated.
In the fall of 2014 MT measurements were carried out at northern Aqqala of Golestan plain in the northeast of Iran, close to the southeastern shore of the Caspian Sea. It was carried out in a wide frequency range to recognize the Conductive layers in depths of less than 2000 m in the region. Determining the potential of the area in terms of electrically conductive layers which represent the iodine bearing saltwater structures was our objective.
The electric and magnetic field components were acquired along two EW profiles (with 1500 meter distance) at 20 stations with a 900 meter distance between stations using GMS05 (Metronix, Germany) systems. Three magnetometers and two pairs of non-polarizable electrodes were connected to this five-channel data logger. The experimental setup included four electrodes distributed at a distance of 100 m in north-south (Ex) and east–west (Ey) directions.
In the MT method, conductive structures are ideal targets when located in a considerably resistive host. They produce strong variations in underground electrical resistivity. A robust single site processing followed by the one dimensional and two dimensional modeling that were performed for the MT data along profiles A and B. Analysis of the MT data-set suggests signatures of salt water reservoirs in the area which are distinguished potentially positive to contain iodine. We could recognize the more conductive zones in the less conductive host as layers of saline water.
Aqqala of Golestan plain geologically is a part of the Kopeh-Dagh sedimentary basin. Kopeh- Dagh was formed by the last orogeny phase of Alpine and the subsequent erosion. Topography relief is very smooth and basically it is a flat plain consisting of loesses occurring naturally between the Alborz mountain range and the desert of Turkmenistan. Quaternary sediments including clay and evaporates and particularly salt are impenetrable.
The MT data were processed using a code from Smirnov (2003) aiming at a robust single site estimate of electromagnetic transfer functions. 1D and 2D inversions were conducted to resolve the conductive structures. 1D inversion of the determinant (DET) data using the code of Pedersen (2004) as well as the 2D inversion of DET mode data using a code from Siripunvaraporn and Egbert (2000) were performed. The data were calculated as apparent resistivity and phases. The determinant mod provides a useful average of the impedance for all current directions. Since the quality of the determinant data was acceptable, 2D modeling of the determinant data would be expected to provide a more reasonable approximation of the true subsurface structure. Therefore, we used the model obtained from the DET mode data as a final interpretation model
The purpose of this study is to evaluate the possibility of using surface MT measurements on the very conductive sediments to monitor the underground salt water bearing layers or bodies. In this study one and two dimensional interpretations for recognizing conductivity structures were performed. The resistivity sections showed a clear picture of the resistivity changes both laterally and with depth. The inversion results revealed a highly conductive layers iodine bearing saltwater structures which are at the depths of over 450 meters along some profiles. One of the sites was proposed for exploratory excavations.

Hence Iran locates on Alpine-Himalayan seismic belt and it has high seismicity, Study of earthquake seismology is necessary. Part of alpine-Himalayan seismic belt is Iran plateau that demonstrates high seismicity behavior and it has unique deformation.
Seismotectonic studies indicate very density of active fault existence in this plateau. In all of Iran seismotectonic regime, east of Iran seismotectonic zone due to presence of strike slip fault system and occurrence of large earthquake has a great importance. Happening of destructive earthquakes such as Bam (2003) 6.6 Mw and Rigan (2010) 6.7 Mw reveal high potential of occurring. Intended area in this study is Rigan that locates in Kerman province, Iran. This area has important faults such Kahurak, Bam, Nosratabad, Shahdad, Guk, Golbaf, Sirch and Sabzevaran that they are have high seismicity.
In this paper, we considered cloud formation as earthquake precursor for Mohammad Abad Rigan earthquake (2011) that ever known less. Also thermal precursor was considered in this study. According to existing theories, raises in stress can produce initial fracture in region. So with raising in temperature, water evaporation in pore of stone is created. When vapor has appropriate condition (for example; lower temperature and existing enough water), it convert to clouds. One of fantastic feature of this phenomena is these clouds can’t move in presence of wind Because of steady source of their generation. This fact is a distinguishable thing for recognizing of this cloud among other clouds. In first part, panchromatic images of 62 days before the event was got and then these row images was georeferenced. So earthquake clouds digitally extracted and the result superposed on topography map of intended region. Also it should be mentioned that earthquake clouds, 10 days prior to earthquake (17th January) was detected. 10 days is suitable time for decision in determiner organization for example; Governorates, Municipalities and etc. for good conclusion about earthquake occurring, verdict based on cloud earthquake is not enough and it is necessary that we applied other precursors. One of them is thermal infrared that has great results.
In another part of study, temperature content of thermal bands (bands 31 and 32) of MODIS is extracted and Land Surface Temperature (LST) time series was created. Temperature variations is always considered as an important and effective factor in earthquake phenomenon studying. Thermal anomaly can be seen within 1-24 days before earthquake and the temperature increases 5-12 degrees and then returned to the previous mode after the earthquake. Some other researchers presented the increase of 2-10 degrees. The idea that earthquake may interrelated with temperature proved by applying it in Russia, China and Japan. However, notice that thermal anomaly may occur due to other reasons except earthquake. When it is because of earthquake, actually it is because of the stress exists in underground layers and change in soil properties. Zuji et al. (1990) proved that gases such as methane, carbon dioxide and hydrogen released from soil cracks before earthquake which lead to intensification of chlorofluorocarbons (CFC) and magnetic fields of the earth. There are some other theories about this phenomenon such as piezoelectric and expansion forces of the elastic strain that increase temperature.
After getting images from NASA website and preprocessing, by deduction of Air temperature time series from LST time series, atmosphere effects that exist because of air weather condition, is eliminated. Obtained signal was some noisy. In the next step, the wavelet as a powerful filter is applied on time series. For extracting Interpretable results, Statistical test such as standard deviation must be perform on filtered time series. Standard deviation (ST) can create normal limited area. By using limited area that produced by ST, thermal anomaly is detected 2 days prior to earthquake. Also with colorization of thermal images and then creation of visual time series, strike of fault line is found.
Finally, by Comparison between earthquake cloud line, focal mechanism and high temperature zone, high correlation was found. These results show that observed cloud related to Rigan earthquake and also show that high temperature zone related to earthquake event, too.
Results of this study can be used in two aspects. One of these is application in early warning system. Other aspect is application in geology usage. Second usage helps geophysicist and geologist to detect hidden and caused fault.

Summary In seismic data processing, the processing steps are completely affected by the data quality. Reflection seismic data are often affected by various noises including random and coherent noises. Low signal to noise ratio can produce problems for stacking and migration steps, which ultimately leads to poor interpretation. There are many methods that can be used for noise removal or attenuation of seismic data. The basic assumption of the Fourier transform is that it considers stationary signal, thus, for non-stationary signals, it is not always applicable. Based on this fact that the wavelet transform decomposes a function by translation and stretching, it can provide time-scale representation of a signal. In this paper, we have used SURE-LET method for noise removal in the wavelet transform domain. In the SURE-LET method, any assumptions of noise free signals are avoided.
Introduction The purpose of seismic data acquisition is to acquire data with the lowest possible noise level. The presence of noise in seismic data is inevitable (Yilmaz, 2001). To improve the signal-to-noise ratio, we can use two approaches: first, changing the seismic energy source or receiver array design and second, processing the seismic data for noise reduction. Considering the source of energy is absorbed by the earth, the increase of seismic energy sources or weighted receiver arrays is limited (Sheriff and Geldart, 1995). Therefore, reduction the noise in order to increase the signal to noise ratio of seismic data is very important. Morlet (1981) showed that by changing the width of the window, wavelet transform could provide better timefrequency distribution. By wavelet transform, various denoising methods based on thresholding of wavelet coefficients have been proposed. Donoho and Johnstone (1994) presented thresholding theory. Chang et al. (2000) presented Bayes shrink method to remove noise. The sensitivity of the soft thresholding function (to the upper limit of the threshold) for the minimization, does not give suitable results. Luisier et al. (2007), to optimize Stein’s Unbiased Risk Estimate (SURE), used another principle, such that the noise attenuation to be expressed as a linear expansion of thresholding (LET) functions. In fact, by combining the SURE and LET and solving a system of linear equations, the noise is attenuated. SURE is an unbiased statistical estimate of the mean squared error (MSE) between an original unknown signal and a processed version of its noisy observation. This estimate depends only on the observed data and does not require any prior assumption on the noise-free signal (Luisier et al., 2010). Blu and Luisier (2007) presented SURELET method based on pointwise thresholding function for image denoising. Luisier et al (2010) used SURE-LET method for orthonormal wavelet domain video denoising.
Methodology and Approaches Wavelet-based noise removal techniques including assumptions for the data are as follow (Luisier et al., 2007): 1. The statistical description of the distribution coefficients 2. A non-linear estimation of statistical parameters, 3. Finding the best noise attenuation algorithms for a variety of statistics For example, Chang et al. (2000), in The Bayes shrink approach, modeled wavelet coefficients of each sub-band with a general Gaussian distribution (GGD). Then the threshold is obtained for each sub-band for the Bayesian framework. For the SURE-LET method, the previous assumption of the noise-free signals is avoided. This method acts by calculating the unbiased estimates of the mean square error between the signal and denoised signal. There are other methods using SURE approach. For example, the sensitivity of the soft thresholding function to the upper limit of the threshold, in the minimization, does not give suitable results. Luisier et al. (2007) to optimize SURE, used another principle so that the noise attenuation as a linear combination of denoising elements (LET) was expressed. In fact, by combining the SURE and LET and solving a system of linear equations, the noise is attenuated.
Results and Conclusions The SURE-LET method comprises of two main sections: noise attenuator that consists of the interscale LET, and then, the linear parameters for minimizing of SURE between noisy and noise-free signals. Regarding secondary order estimation (MSE), the parameters are improved easily by solving a LET. The results of this study shows that Symlets and Coiflets provide better results using SURE-LET method for denoising non-stationary seismic signals.

Summary In this study, crustal velocity structure beneath two broadband seismic stations of Iran National Seismic Network (INSN), Ashtian-Arak (ASAO) and Naein (NASN) located in northwest of the Central Iran seimotectonic zone near the Ashtian and Nain cities have been investigated by joint inversion of P receiver function and of Rayleigh wave phase and group velocity dispersion curves. To determine the receiver functions, we have used iterative deconvolution in time domain proposed by Ligorria and Ammon (1999). which is more stable with noisy data in comparison to frequency domain. The fundamental mode Rayleigh wave group and phase velocities dispersion curves have been provided by the study of Rahimi et al. (2014) on the structure of crust and upper mantle of the Iranian Plateau for the period interval of 10-100 sec. The result of this study suggests that Moho discontinuity depth beneath Ashtian-Arak station (ASAO is 50 ± 2 km and beneath Naein station (NASN), it is 56 ± 2 km. Relative high crustal thickness beneath NASN station in comparison to other regions of central Iran can be attributed to abut the region to the Sanandaj–Sirjan zone (SSZ) and Urumieh– Dokhtar magmatic assemblage (UDMA). It can also attributed to the existence of thick Magma masses in Urumieh– Dokhtar magmatic assemblage and increase of the density and relative thickness of the area based on the isostasy theory. The average Moho depth in northwest edge of Central Iran is 53 ±2 km.
Introduction Iran is situated in one of the world seismic regions and the possibility of occurring destructive earthquakes in most regions of the country has given a great significance to recognition of Iranian seismic nature from a seismotectonic standpoint. The seismicity within Iran suggests that much of the deformation is concentrated in the Zagros, Alborz and Kopeh Dagh mountains, and also, in east Iran, surrounding Central Iran and the Lut desert, which are virtually aseismic and behave as relatively rigid . The aim of this research is the study of the crustal structure and Moho discontinuity of the northwest of the Central Iran from analysis of receiver function and surface waves dispersion.
Methodology and Approaches Receiver functions are the response of the local earth structure to the near-vertical arrival of p waves under a threecomponent seismogram and are susceptible to shear wave velocity contrasts. The depth-velocity trade-off in receiver function causes non-uniqueness in the inverse problem. However, by incorporating information of absolute shear wave from dispersion estimates and joint inversion of these two datasets, this shortcoming can be compromised. In this study, crustal velocity structure beneath two broadband seismic stations of INSN, i.e. ASAO and NASN located in northwest of the Central Iran seimotectonic zone near the Ashtian and Nain cities have been investigated by joint inversion of P receiver function and of Rayleigh wave phase and group velocity dispersion curves. To determine the receiver functions, we use iterative deconvolution in time domain proposed by Ligorria and Ammon (1999) which is more stable with noisy data in comparison with frequency domain and teleseismic events with source-receiver great circle paths larger than 30° and smaller than 90° with magnitudes more than 5.0 that are recorded at time period of 2009 to 2013. The 210 desired RFs have been recorded at two permanent stations. To remove high frequencies, Gaussian parameter 1.0 has been used. In order to eliminate the source, path and instrument effects, deconvolution of the vertical component from the horizontal components of the seismograms is used. For increasing signal to noise ratio, RFs have been clustered in 20˚ azimuthal and less than 15˚ epicentral distance ranges. Finally, the RFs are stacked. The fundamental mode Rayleigh wave group and phase velocities dispersion curves have been provided by the study of Rahimi et al. (2014) on the structure of crust and upper mantle of the Iranian Plateau for the period interval of 10-100 sec. In this way, more accurate information about the crustal structure can be obtained. Joint inversion of two independent data sets has been performed by considering combination of appropriate weighting parameter from Herrmann and Ammon program (2003). Minimizing standard error between real and predicted data is the criteria for getting to desired final and close to earth real model.
Results and Conclusions The result of this study suggests that Moho discontinuity depth beneath ASAO is 50 ± 2 km and beneath NASN is 56 ± 2 km. Relative high crustal thickness beneath NASN station in comparison to other regions of central Iran can be attributed to abut the region to the Sanandaj–Sirjan zone (SSZ) and Urumieh–Dokhtar magmatic assemblage (UDMA). It can also attributed to existence of thick Magma masses in Urumieh–Dokhtar magmatic assemblage and increase the density and relative thickness of the area based on the isostasy theory. The average Moho depth in northwest edge of Central Iran is 53 ± 2 km.

Iran is situated in one of the world's seismic regions and the possibility of destructive earthquakes in most regions of the country has given great significance to recognition of Iranian seismic nature from a seismic and seismotectonic standpoint. Study of the crust and upper mantle velocity structure in the Iranian plateau provides better understanding of its evolution and tectonic history of seismotectonic zones. Crustal velocity structure is used as initial information for various geological and geophysical studies, and therefore it is a basic and important issue in seismology. Receiver functions show Earth local structure response to P-wave vertical arrival approximately beneath of a three-component seismometer and are sensitive to shear-wave velocity impedance. Depth-velocity trade-off in RFs information is causing of inversion non-uniqueness problem, but one can overcome to this limitation by incorporating information from absolute velocity from dispersion estimations and joint inversion of this two data sets. By this, more exact constraints are provided about crustal structure. In this study, crustal velocity structure and Moho discontinuity depth beneath of four broadband stations of Kerman seismological network have been investigated from joint inversion of P-wave receiver functions (RFs) and Rayleigh wave group velocity dispersion. The teleseismic waveformes in time interval more than two years was used to compute RFs from the time domain iterative deconvolution procedure Ligorria and Ammon (1999) which has higher stability with noisy data compared to frequency-domain methods. The 165 desired RFs were computed from these waveforms that have magnitude bigger than 5.5 and have recorded at four permanent stations in epicentral distance 25˚-90˚. To delete high frequencies, Gaussian parameter 1.0 used. For increasing signal to noise ratio, RFs clustered in 10˚ azimuthal and less than 15˚ epicentral distance ranges. Finally, the RFs were stacked. This work performed under software SAC. Due to changes in group and phase velocity of surface waves with depth for different periods and dispersion in these waves and sensitivity of the waves dispersion curve to shear wave velocity, inversion of dispersion curve is an efficient method for determining the average shear wave velocity in a vast region of the depth between two seismic stations. Group velocity dispersion curves were incorporated into our joint-inversion scheme from an independent regional fundamental-mode Rayleigh waves tomography images for within the 20–80s period range in Iran by Rahimi et al. (2014). Joint inversion of two independent data sets was performed with considering combination weighting parameter appropriate performed from Herrmann and Ammon program (2003). Minimizing standard error between real and predicted data is the criteria for getting to desired final and close to earth real model.
The results from this study show that Moho discontinuity boundary is beneath of CHMN station at 52±2 km depth, beneath of KHGB station at 50±2 km depth, beneath of NGRK station at 54±2 km depth and beneath of TVBK station at 52±2 km depth. We used forward modeling test for error estimation and resulting models accuracy.
Relative high crustal thickness in this region compared to other regions of central Iran can be attributed to abut the region to the Sanandaj–Sirjan zone (SSZ) and Urumieh–Dokhtar magmatic assemblage (UDMA) that underthrusting of the Arabian plate beneath Central Iran along the main Zagros thrust fault is caused of thickening. It can also attributed to exist of thick Magma masses in Urumieh–Dokhtar magmatic assemblage and increase the density and relative thickness of the area based on the Isostasy theory.

The Zagros mountain belt is approximately 1500 km long, 250–400 km wide, and runs from eastern Turkey, where it connects to the North and East Anatolian faults, to Oman Gulf, where it dies out at Makran subduction zone. The Zagros Mountains were formed by closure of the Neotethys Ocean and collision of Central Iran and Arabia plates. GPS studies estimate a convergence rate of 22 mm/yr between Arabian and Eurasian plates and the Zagros accommodates about 6.5 ± 2 mm/yr of the overall shortening in Iran. However this rate is not constant along the Zagros and increases from 4.5 mm/yr in the northwest to 9 mm/yr in the southeast. Changes in the rate and direction of convergence across the Zagros cause changes in its strike and diversity of the deformation mechanism. The Main Recent Fault (MRF) and the Main Zagros Reverse Fault (MZRF) are located in the northwest and northeast of the Zagros collision zone, respectively, in a suture zone between central Iran and the Arabian plate. Based on GPS and seismology studies, the MZRF is presently inactive. On the contrary, as evidenced by high seismicity and the occurrence of earthquakes with magnitudes as large as 7, like 1909 Doroud Earthquake, the MRF is one the major active strike-slip faults in the Middle East. Geological studies on the MRF fault have identified the fault segmentation and the existence of pull-apart basins. The Main Recent Fault strikes NW–SE and can be traced as a narrow, linear series of fault segments from near the Turkey–Iran border at 37N for over 800 km to the SE. Based on strain partitioning theory, the strike-slip MRF fault is a response to a horizontal component of oblique convergence between Arabian and Eurasian plates and Zagros’s reverse fold belt accommodates the vertical component of this convergence. Seismological studies based on the teleseismic data have limited the location accuracy because they rely on global velocity models. Therefore, microearthquake local studies complement the teleseismic information because they locate seismic events with an accuracy of a few kilometers which is an order of magnitude better than teleseismic locations. The 2006 Silakhur earthquake with a magnitude of 6.1 and its aftershocks recorded by a local seismic network provide a unique opportunity for a high resolution study of the Doroud section of the MRF. The results of the aftershock analysis are presented in this paper. After occurring March 31, 2006 Silakhur Earthquake, Mw 6.1, a temporary seismic network including 10 stations was installed by International Institute of the Earthquake Engineering and Seismology for nearly two months. An aftershock analysis revealed a wide zone of the aftershocks trending southeast northwest. Another trend in east-west direction was deduced from the epicentral distribution of the aftershocks in the west of the Boroujerd. Depth distribution of the aftershocks showed that the majority of the aftershocks located in 4-11 km depth range, verified the brittle crust uppermost layer in this part of the Zagros. Depth profile showed the northeast trending of the aftershocks. The spatial distribution of the b value showed low values in the northern part of the aftershock zone that its reason could be the higher stress concentration in this region relative to the southern part.