مجله ژئوفیزیک ایران
سال هفدهم شماره 2 (پیاپی 59، تابستان 1402)

The Ground Penetrating Radar (GPR) method is high-resolution surveys with an electromagnetic pulse reflection method for shallow earth layers. This method is similar to reflection seismography, which operates on the basis of wave propagation and reflection. In a simple case, a GPR device consists of a signal generator. The signal generated by this generator is sent into the earth by the transmitter antenna. Waves travel through the earth at a high speed and when these waves hit an object or reflection surface, due to the change of electromagnetic impedance in these places, part of the waves will be reflected from the surface. The receiving antenna located in the device shows these reflections as a high peak and records the movement time and amplitudes of the reflections. The electromagnetic wave inside the earth moves downwards in the form of a three-dimensional cone, and at the same time, factors affect the speed and loss of the amplitude of these waves. In fact, the electromagnetic characteristics of the materials, which depend on the constituent materials and the amount of water in them, will have a great effect on the speed and loss of the range of the radar waves penetrating the ground. Some materials, such as polar ice, are transparent to ground-penetrating radar waves, and these waves can pass through it without much loss. Some other materials such as clays saturated with water and also sea water is cloudy to these waves and reflect or absorb these waves. Therefore, radar waves penetrating the ground are attenuated in short distances and cannot propagate in such environments.    Considering the high-resolution power of the ground penetrating radar method, as well as the high speed and ease of acquisition, it can be said that this method is useful in investigating and detecting shallow subsurface targets similar to subsurface holes, canals and other targets that have a different dielectric constant from the surrounding environment. It is an acceptable method. In addition to the effect of the frequency of the waves sent from the GPR antenna, other factors such as soil moisture, the amount of fine-grained clay materials, or the fineness of the sediments in general, reduce the depth of investigation or penetration of GPR waves. This problem is mainly caused by the higher electrical conductivity due to the presence of moisture or fine-grained sediment particles compared to coarse-grained sediments. In this study, a ground penetrating radar device with 80 MHz antenna was used and seven profiles with a total length of 662 meters were taken to investigate the intersection of Kargar Street in Tehran. The radargrams have been processed and the anomalies related to the meetings have been identified on them. These anomalies are discussed in the next step on the positioning satellite images and on the obtained results. According to the estimated results, there is a good agreement between the anomalies detected in the parallel profiles, which can be proof of the acceptable identification of possible anomalies in the study area.

Due to the direct sensitivity to the hydrogen of water molecules, magnetic resonance sounding (MRS) provides estimate of hydro-geophysical parameters such as water content and hydraulic conductivity. The use of this method makes it possible to determine the presence or absence of water below the surface more precisely and to determine the important characteristics of the hydrogeology parameters of the aquifer layer such as water content and hydraulic conductivity. The MRS technique is based on the Nuclear Magnetic Resonance principles to determine the subsurface distribution of hydrogen protons. MRS measurements are carried out with a surface antenna as transmitter/receiver of electromagnetic signals. To obtain depth information, a series of measurements at different pulse moments, are passed through the loop. By varying the pulse moment, a spatial distribution of aquifer properties with respect to the depth can be obtained from the MRS data inversion. From data space point of view, in the inversion of magnetic resonance sounding data, three types of algorithms have been presented:  Initial Amplitude Inversion, Time Step Inversion, and Full waveform inversion. Given that in the two first above-mentioned methods only a portion of the data is used for inversion, it is not possible to provide a stable solution with a suitable depth resolution in the inversion process, while the use of the full waveform inversion of the magnetic resonance signal (i.e., using whole data space) increases the stability and resolution of water content and relaxation time.
    One of the important issues to be considered in the inversion of geophysical data is the evaluation of the quality of inverted models. This means that using mathematical tools, the degree of certainty or uncertainty of the models obtained from solving the inverse problem is determined quantitatively, and this helps to better interpret geophysical models. Evaluating the quality of water content and relaxation time models resulting from the inversion of surface nuclear magnetic resonance data is also essential.
In this research, we extract the model resolution matrix using singular value analysis of the leading MRS function. This method consists of evaluating the components of loop size, maximum moment pulse, distribution of subsurface layers as well as ambient noise level conditions as inputs on the resolution and depth of MRS data. The effect of each of these components on the resolution of magnetic resonance sounding data is measured through artificial models and field data. The results show that the loop size increases the penetration and also increases the vertical resolution if the maximum moment pulse is constant. This is also true if the loop size is constant and the maximum moment pulse is increasing. Increasing the noise level reduces the resolution and is managed through depth. The results of this dissertation will be an important step in optimizing measurement components to improve vertical resolution in water content and relaxation time models and also increase the penetration depth in magnetic resonance sounding studies. The hydro-geophysical sources of water and relaxation time are reviewed in the inversion of the polynomial using the GSVD method.

The complex process of turbulent mixing in the Persian Gulf which is a semi-closed sea makes it a good option for testing the performance of different turbulence schemes in the numerical simulation of water circulation in it.
    Calculating or predicting the flow and water circulation in such semi-enclosed sea, by taking the turbulence into account, is important in every respect, for example in terms of spread of contaminations, environmental, fisheries, shipping, and even the military. In this study, the 3D ocean model COHERENS (COupled Hydrodynamical Ecological model for REgioNal
Shelf seas) is used for water circulation simulation of the Persian Gulf. Cartesian coordinate system is used for horizontal direction and sigma coordinate with 10 layers is used for the vertical direction. Persian Gulf coastline and its bathymetry are based on ETOPO-2 data, which are obtained from the digital data of seabed and bulge of the earth with latitudinal and longitudinal geographical two-minute networks. The model is forced by climatologic monthly mean atmospheric forcing at 10-m reference height above ground derived from 54 years (1948–2002) of National Oceanic and Atmospheric Administration (NOAA) data. The advection scheme that is used for momentum and scalars is either total variation diminishing (TVD) scheme, which uses the super bee limiter. The uniform bottom friction coefficient was chosen at 0.005 (m/s) and uniform value for the bottom roughness length that was chosen as 0.015 (m), based on the bottom roughness of the basin. Four turbulence schemes are implemented in the model to test their performance. These include two turbulence closure schemes of k-ε, k-l (Mellor–Yamada), and two algebraic schemes of Pacanowski and Philander and flow-dependent scheme. For the k-ε and k-l models, we used one-equation model for transport equation, the “Blackadar” formulation for mixing length, and limiting conditions for turbulence variables are enabled. The stability functions are expressed in terms of the Richardson number. In the numerical simulation of water circulation in the Persian Gulf, the turbulence schemes are studied to investigate salinity and temperature parameters, flow patterns in the surface and bottom, meso-scale eddies and turbulence parameters including the turbulent kinetic energy and energy dissipation rate, the mixing length, eddy adhesion and eddy diffusivity. The model has been successful in simulating the intrusion of low salinity waters into the Persian Gulf and baroclinic instability and the formation of mesoscale eddies in the center of the basin. In comparison between the performance of schemas, the results show that the schemes are very sensitive in estimating the turbulence parameters and simulation of flow patterns, vorticity, salinity and temperature, show less sensitivity to the performance of various turbulence schemes.

While temperature is an important climatic variable in the majority of the fields such as hydrological and climatological modelling, spatial and temporal separation of this variable is a weakness all over the world which makes challenges in its usages. Lots of studies have been conducted to solve this problem; using Temperature Laps Rate (TLR) is one popular way to handle this challenge. Although TLR is an effective tool to interpolate temperature,an insufficient number of stations or inefficient spatial distribution of the stations could make calculated TLRs very uncertain. To cope with this discontinuity in temperature, satellite-sensed temperature data have been utilized. In comparison to station-based temperature, satellite-sensed temperature data is a well choice to map the temporal and spatial pattern of temperature in a wide area. With recent developments in Moderate-resolution Imaging Spectroradiometer (MODIS), Land Surface Temperature (LST) data has been successfully employed in several areas such as earth surface radiation, evaporation, urban heat islands, climate change, hydrological modeling, sea surface and air temperature estimation. Iran is located in the arid and semi-arid region that has been always faces with water shortages. This has been worthen with global warming which has caused increases in water demand, too. Thus, having temperature data with good spatial resolution has been always a need and challenge in the area and lots of the fields. In this study, an approach was introduced to estimate TLR utilizing MODIS LST with good spatial resolution. These estimated TLRs were then used to downscale ERA5, CFS, and MERRA2 daily reanalysis temperature data sets to 1 km spatial resolution. The downscaled data was compared with the recorded data at the stations in different climate regions and elevation clusters. The results showed that improvements resulted in all climate regions and elevation levels. On average 15, 18, and 4 percent improvements were seen in RMSE, MAE, and NSE, respectively.

Earthquakes with a large magnitude affect people, man-made buildings and environments. This information can be a dataset of the earthquake description consisting of people’s feelings, the building damages, and the effects on the earth. For the building damages, different types of buildings should be considered to find the best dataset of the earthquake. For the effects on the earth, various environmental effects such as the displacements, landslides, rock falls, liquefactions, surface and chemical changes on the rivers and springs, etc. should be considered; more information of more situations, more accurate exports of the earthquake. According to global research in this field, using this information can be useful to assess the macroseismic intensity of the affected areas and the epicentral earthquake. Moreover, having a good dataset of these descriptions, the macroseismic parameters of the earthquake can also be estimated. It can be useful especially for the earthquakes with low or/ and lack of information in the earthquake catalogs and also paleo-earthquakes. This study concentrates on the Tabas earthquake, which occurred on September 16, 1978, in the Tabas region located in eastern Iran. This was a shallow earthquake felt in a region with 1130000km2 total affected area. Such as every large earthquake, several phenomena were observed related to this event. For example, it destroyed 1500 building units and 30 Qantas. Although the epicenter of the earthquake was located in a situation with a poor population, it destroyed or severely damaged 90 villages and slightly damaged other 50 villages. The surface rupture of this event was extended for about 85km with no connection on the surface with a trust mechanism. Moreover, 150cm vertical displacement and 300cm horizontal displacement were reported for this event. According to these descriptions of Tabas earthquake with magnitude more than 6, occurring more earthquakes in the past can be usual for this region; then, more investigation on this field is necessary. Therefore, in this study, primarily investigation on this region was started using the available maps (e.g. geology map) and images (e.g. Landsat) and for the following researches the locations near Ali Abad in NW of Tabas were suggested for the field study and sampling to date their absolute ages.

Zagros is very active in terms of seismicity and is the most seismic region of Iran. In the book on the history of earthquakes in Iran, two major earthquakes have been reported on 1st January 958 Mw 6.3, and 1st April 1150 Mw 6.1 (Ambraseys & Melville, 1982). It is well-known that the historical earthquakes consist of valuable information for identifying the hazard of earthquakes, completing the earthquake catalogs, better understanding the Zagros area, and better preparing for this natural phenomenon; on 12th November 2017, an earthquake with a magnitude of 7.3 occurred at a distance of 10 km from the Ezgleh and about 37 km northwest of Sarpolzahab city in Kermanshah province, located at the Iran-Iraq border. The earthquake location was close to historical earthquakes. In this regard, we used the empirical Green's function method to simulate the historical earthquake. Empirical Green's function evaluates parameters of strong ground motion such as time history, frequency content, effective duration, P and S wave arrival time, the Earth response spectrum, and the maximum acceleration of the earth that occurred during the earthquake. Empirical Green's function method is one of the most common and simple simulation methods for generating strong ground motion with geological heterogeneity effects, which is used to model ground motions using foreshocks and aftershocks. In this study, the simulation of one of the Sarpolzahab earthquake aftershocks was conducted by small aftershocks recorded in the Ezgeleh region, using the empirical function method. The temporary network data of the International Institute of Seismology and Earthquake Engineering was used for this study. The simulation results show that there is a good similarity between the waveforms, the Fourier amplitude spectra, and the simulated response spectra observed at the existing stations and that the errors are acceptable. The parameters of the acquired model consist of rupture velocity of 2.6 to 3.5 km/sec equivalent to 0.8 to 0.9 times the S-wave speed and healing velocity equal to 0.95 times the rupture velocity. The dimensions of the fault grids were 0.05x0.05 and the scalar seismic moment of the aftershock was 1.04×1023 Nm. In the simulation, asperities were not considered. The source time function was Kostrov-ramp and fault roughness was taken into account. Furthermore, the waveforms, Fourier amplitude spectra, and response spectra for the mentioned historical earthquakes were constructed with the results obtained from the reference earthquake for simulation. The results are reasonable; however, some errors are unavoidable.

The water environment is considered as a suitable conductor for sound waves propagation and the changes in the horizontal and vertical structures of physical parameters are effective on the speed and propagation of sound. One of the effective vertical processes in the water column is the double diffusion process with two structures of salt-fingering and diffusive convection, which are created due to the vertical gradient of temperature and salinity with different diffusion coefficients. Salt-fingering occurs when a layer of warm and salty water is located above cold and fresh water. In areas such as the Strait of Hormuz, with thermohaline exchange between the salty basin (Persian Gulf) and the open sea (Oman Sea), the conditions for the formation of salt fingers and their growth are significant. To determine double diffusion structures, the Turner angle (Tu) method is used in terms of density ratio (Rρ). Turner angle values (in degree) for the formation of double diffusion structures are defined in the range of -90 < Tu < 90. So that the diffusive convection structure is formed for the values of -90 < Tu < -45 and the salt finger structure is formed for the values of 45 < Tu < 90. With the increase of the warm water inflow entering from the Oman Sea into the Persian Gulf, in spring and summer and the increase of evaporation in late spring, the conditions for the formation of salt fingers are strengthened and salt fall occurs in all the eastern and middle stations of the Strait Hormuz. Also, in the southern stations, salt fingers extend from the surface to a depth of 65 m. The vertical gradients of temperature and salinity in the eastern cross-section of the Strait of Hormuz form a warm and salty surface layer (34 °C and 39 psu) over a cold and fresh water layer (29 °C and 37.5 psu) so that the warm and Salty water mass spreads on the surface and falls from the surface to a depth of 40-70 m as salt fingers. The fall of salt fingers causes the speed of sound waves to be not uniform along the channel so from the surface to the depth of salt finger fall, it has the highest value (1557 m/s). In this study, sound signal propagation at frequencies above 500 Hz (600 Hz and 60 kHz) is simulated using Ray theory and the Bellhop model. The results show that sound rays with a small propagation angle are scattered on the surface after passing through the salt fingers. But by increasing the depth of the sound source, the dissipative effect of the salt structure decreases while the deviation from the location of the strong structure is observed. In general, the propagation and transmission of the sound signal along the channel depend on the stratification leading to the salt finger structure, and the sound rays are propagated with significant deviation and 80-85 dB loss in transmission (10-15 dB increase in loss), while these salt fingers exist in water.

Natural hazards are one of the factors that cause financial loss every year, and they occur in most regions of the world, including Iran. One of the hazards that mankind has been dealing with in recent decades, especially in alluvial plains is the phenomenon of land subsidence and sinkhole. Land subsidence and sinkhole due to natural and human causes have been reported in many places. Subsidence or sinkhole will damage human structures that are supported by the earth. Land subsidence is the most important environmental problem in Iran. A major cause of this phenomenon is overexploitation of underground water resources has led to land subsidence, and underground water extraction plays an important role in causing land subsidence. The study area is Abarkooh plain with an area of about 250 square kilometers is a part of the Eqlid-Abarkooh watershed. The lowlands are covered by Quaternary alluvial and some older sediments such as unconsolidated conglomerate, clayey, sandy, and saline areas. Based on geographical location, the study area is located in the geographical range of 53 degrees to 53 degrees and 32 minutes east longitude and 30 degrees and 50 minutes to 31 degrees and 12 minutes north latitude. This area contains medium to fine alluvial fan sediments that end in the salt playa or Abarkooh desert. To determine the high-risk and low-risk areas and routes in the study area, to discover subsurface holes and stratigraphic fractures underground up to a depth of 5 meters and the safe route for contracting works, etc., was used the ground penetrating radar (GPR) method. The results showed that in the areas where there are sinkhole traces in the determined distances around in current research, the attenuation signal of the ground penetrating radar, including the effects of subsurface cavities and stratigraphic fractures was discovered and revealed by GPR. On the side of the mountain slopes and high altitudes in the upstream region, no signal attenuation was observed, and sediments and soil were observed uniformly underground. The ultimate goal of the GPR section is to obtain a cross-section that is most consistent with the geological realities of the region and finally, at the final stage, we can talk about the characteristics, effects, and objectives of the research. The GPR method is an easy and low-cost method that is widely used in the field of natural resources and it is also used in other scientific fields. Regarding the common phenomenon of subsidence and sinkhole, these effects can be found underground, so that humans can prevent the development and expansion of this phenomenon. Also, this method can determine the route and safe area for contracting works, urban development, etc.

Longshore sediment transport is considered as one of the most important and influential factors in the functioning of coastal areas. Forecasting and determining the rate of this parameter along the coast and in the vicinity of coastal structures is one the most important for shoreline management during any construction and coastal management mission. This study aims to put different pieces of knowledge together, including field measurements, neural networks, and numerical modelling to obtain a more realistic estimation of the LST rate along the undeveloped Makran Coastline. The focus of this paper is mostly on accurate wave and sediment transport modelling, verified against available field data and morphological evidence. A neural network for the correction of wave data and a numerical model of Mike21 is applied for simulating the transportation process of sediments along the Makran Coastline. Zarabad port on the coast of Makran has selected the case study of this research. The results of this study showed that the observed data are not in good agreement with the output data of the model (except wave height) and need to be modified with the neural network and considering the effective parameters such as the different conditions of the waves in the monsoon and non-monsoon seasons in the Neural network. Neural network can help a lot in improving and correcting data. The results also showed that the sediment transport process occurs in different directions and depending on the wave height at depths more than 4m and at greater depths the sediment transport is insignificant, also, wave force in the region is able to transfer approximately 235000 m3 / year sediment.

Climate change has significantly increased the frequency and intensity of heat stress and has more effects than increasing average temperature. This study has investigated the spatial distribution of the universal thermal climate index (UTCI) during historical and future periods in Iran. The UTCI (°C) refers to “the isothermal air temperature of the reference condition that would elicit the same dynamic response (strain) of the physiological model” (Jendritzky et al., 2012). In this way, the UTCI is an equivalent temperature, similar to PT. The thermal impact of the meteorological conditions is compared to the one of a standardized reference “indoor” environment with RH = 50% (Ta < 29 °C), WS = 0.5 m s−1, pa = 20 hPa (Ta < 29 °C), and Tmrt = Ta (Shin et al. 2022). Three variables of daily temperature, relative humidity, and wind speed from two sets of data, including 124 meteorological stations and five models from the Coupled Model Intercomparison Project phase 6 (CMIP6) model, including GFDL-ESM4, IPSL-CM6A-LR, MPI-ESM1-2-HR, MRI-ESM2-0, and UKESM1-0-LL were investigated with a horizontal resolution of 0.5o. Then, an ensemble model (CMIP6-MME) was generated from these five models using the independent weighted mean (IWM) method. The performances of individual models and the generated ensemble model were examined by Taylor's diagram. The results showed that the multi-model ensemble has higher performance than individual models for all three variables. The results revealed that the spatial distribution of the seasonal averages of the UTCI index has significant variability in Iran, and the variability of this index is affected by the latitude, complex topography, and distance to water resources in Iran. In general, heat stress will increase significantly in Iran by the end of the century. So, we will witness a significant decrease in areas with no heat stress until the end of this century. On the contrary, strong to very strong heat stress events will increase significantly in the country at the end of the century. While the areas with no thermal stress show a spatial displacement to mountainous regions and higher latitudes. These results show that effective adaptation methods should be taken to adapt to global warming and reduce its consequences to avoid the adverse effect of increasing heat stress events in Iran. The results show the overall increasing trend of Iran's heat stress in the near and far future. The highest increase in heat stress anomalies (13.3 degrees Celsius in winter during the far future period under the SSP5-8.5 scenario) can be found in the northwest and west of the country. The increasing intensity of heat stress in the western and northwestern parts of Iran may be related to elevation-dependent warming (EDW).

GPS observations over the Earth surface occur at the location of stations. So, they have a discrete form and are often sparse and irregularly distributed. Most of the data processing approaches require the data over a regular grid. As such, the interpolation of sparse observations onto a regular grid, known as gridding, is a challenging step in geosciences. To overcome this problem, interpolation with spline functions can be used.
In this method, the geographic coordinates and velocity components of GPS stations are inputs, and the two-dimensional velocity field components on a regular grid are outputs. The sparse vector data of horizontal displacements of 86 GPS stations with non-uniform distribution in the Alborz region located in the north of Iran has been analyzed. Due to ample GPS stations and a tectonically active area, this region has been selected for study.
Interpolation is done for each component separately and in coupled form. Both cases are based on the Green functions of an elastic body subjected to in-plane forces. The second approach ensures elastic coupling between the two components. Coupling could be adjusted by varying Poisson’s ratio. Vector gridding is done using the Poisson's ratio 0.5 to couple the two horizontal components.
Since the used Green functions developed for the half-space, an arbitrary map projection e.g., Mercator used to create it. Trend analysis was done on the input data first. Then residuals were calculated by subtracting predicted trend from the input data. The output is passed onto block reduction to generate reduced data. Then, the spline is fitted to the residuals of trend analysis and block reduction.
To validate the model, ten percent of the data are selected for testing and the rest for training. The coefficient of determination for eastern and northern components are as 0.25 and 0.88, respectively. To reduce the correlation effect of data with close distances in the validation results, data reduction is done with 50 km blocks. In this case, the coefficient of determination for eastern and northern components are -0.18 and 0.47. For the coupled interpolation of two components, the coefficient of determination is 0.88 and by reducing the data with 50 km blocks, it is 0.84. Validations show that the coupled interpolation of velocity components using elasticity constraint leads to improved interpolation of sparse vector data.
The results of velocity field interpolation show that the spatial distribution of the crustal deformation in the Alborz region is irregular and has partitioning characteristics. The range of the northern components is larger than the eastern components. The direction of the northern components is always towards Eurasia, but the direction of the eastern components changes in the region in such a way that the amplitude of the eastern component in the inner region is around zero. The amplitude of the northern components is decreasing from south to north and from west to east. Estimated strain rate from interpolated velocity field shows the convergence deformation in the study area and confirms the compressing of high-elevation region of Alborz.

In this research, the possible interrelationship between several global climatic indices has been investigated by employing four statistical methods. At the first step, the spectral content of the data and their intensities were obtained at different harmonics with using the spectral analysis. Then the correlation analysis was used to calculate the correlation coefficients between each pair of climatic signals, in order to check any linear relationship between them at different time lags. Finally, by exploiting the sophisticated wavelet coherence method, the correlation of indices was analyzed at different frequencies and times, and in addition, the linkage between the indices was examined from the scatter plots. 
The selected indices include the number of sunspots (SN), Southern Oscillation Index (SOI), Quasi-Biennial Oscillation (QBO), North Atlantic Oscillation (NAO) and Mediterranean Oscillation (MO). The monthly values for these indices were used for the statistical period from 1979 to 2021.
Based on the analysis, evidences of the presence of 11-year cycle of sunspots in the SOI signal were found. The results show that if the SN signal is considered as the cause and the SOI signal as the effect, the minimum value of the 11-year component of the SOI signal occurs about 3 years after the maximum value of the same component in the SN signal.
 The correlation method shows a weak linear relationship between other signals such as NAO, QBO, SOI and MO in all time lags, and the highest correlation in this case is between NAO and MO signals. However, a closer look at the wavelet coherence plots shows that these signals are strongly correlated at decadal and to some extent at inter-annual time scales.
The lagged correlation method and the scatter plots also confirm an increase in the linear relationship between sunspot cycle with the SOI index for the time lag of 33 to 36 months, and no significant linear relationship was generally observed among other indices. The highest correlation (about 0.2) at the time lag of zero is revealed to belong to the NAO and MO signals, which according to the wavelet coherence analysis, it is due to the decadal common in-phase oscillation between these two signals. Furthermore, common oscillations with consistent phase were found sporadically between each pair of selected signals in the inter-annual scales for some periods of time. The scatter plots also showed more details about the possible relationship between the data.
Our results show the potential of the spectral and wavelet coherence analysis (WTC) for identifying common or dominant frequency components of the important climatic signals, and they can be exploited as a complementary to the traditional lagged correlation analysis and other preliminary statistical analysis such as the analyzing the scatter plots.

Joint inversion of different geophysical data is used to identify different geological structures and estimate some physical parameters. This study is aimed to do joint inversion of gravity and adjoint-state first arrival tomography by using the Gardner relation. Gardner's relation is an equation that relates seismic velocity to density. 
In the gravity method, forward modeling aims to compute the gravity response at the surface due to a density distribution in the subsurface (Boulanger & Chouteau, 2001). RCG method introduced by Zhdanov (2015) has been used for inversion of gravity.
In the forward modeling of the seismic method, the eikonal equation is used to model the first arrival traveltime, which approximates the high-frequency wave equation. The eikonal equation is nonlinear. There are different methods to solve it, such as Raytracing, Fast Marching, Fast Sweeping, and Finite Difference. This solving method is usually based on a beam, grid, or graph. This study examines the fast sweeping method (FSM) based on rectangular grids by Zhao (2005) has presented.
Estimating model parameters from measured data generally minimizes the misfit function in geophysics. A classic way to solve a minimum problem is to determine the minimum of a series of linear problems sequentially. This formulation requires Frechet derivatives (Jacobin matrices), which need heavy and lengthy calculations. If minimization appears as a nonlinear optimization problem, only the misfit function gradient is required. In this study, the adjoint-state method is used to calculate the gradient.
In the 1970s, the adjoint-state method was developed to efficiently calculate the gradient. It is now a well-known numerical community method for calculating the gradient of a function misfit. It can be used when this function misfit depends on the model parameters through state variables.  State variables are solutions to the forward problem (Plessix, 2006).  For example, state equations can be beam equations in the tomography problem that is the subject of this study. State variables are spatial coordinates and slowness vectors that describe beam paths. The adjoint-state method is effective because only one additional linear system has to be solved.
This study performs the joint inversion of data based on the sequential inversion method using the petrophysical constraint, Gardner relation. The inversion process performs in several loops. In each loop, the individual seismic inversion is first performed in several iterations. The velocity model obtained using the Gardner relation is converted into a density model. The obtained density model is the initial model for individual inversion of gravity in the desired iterations. Finally, the obtained gravity model is converted to a velocity model using the inverse Gardner relation, and the above process is repeated to achieve the desired result. The results of the above inversion can be used to image shallow subsurface models and to limit the location of anomalies in hydrocarbon exploration in layered sediment environments such as basalt and salt dome modeling.

Drought is a natural phenomenon that is mainly caused by less than normal precipitation over a long period that occurs in almost all climates. Since the late 1970s, the occurrence of drought has increased globally due to increased evaporation (caused by global warming). This phenomenon occurs slowly and can be short-term or terminated within a few months or continue for several years. drought has increased significantly in Iran in recent decades. The increase in droughts has many negative consequences in different areas of agriculture, water resources, and wildfire. The purpose of this study is to investigate the drought situation in the vegetation areas of Iran using the Keetch-Byram drought index (KBDI). For this purpose, the KBDI drought index derived from the data set of the European Centre for Medium-Range Weather Forecasts (ECMWF) fifth edition (ERA5) with a horizontal resolution of 0.25o during the period of 1981-2020 has been used. Also, the combined product of surface soil moisture (SSM) from microwave sensors AMI-WS (ERS-1 and ERS-2 satellites) and ASCAT (MetOpA-B satellite) with a horizontal resolution of 0.25 o to evaluate the KBDI drought index results as well as the moisture condition. The results showed that the khalij-Omani and Irani-Turani vegetation areas have very low soil moisture and high drought in Iran. The amount of soil moisture in these areas is low and the area-averaged is equal to 12.65% and 18.42%, respectively, which has been somewhat constant in all months, in other words, dryness is the predominant climate feature of these areas. The monthly analysis of the KBDI index shows the spread of drought severity towards the west, i.e., the vegetation area of Zagros, in the hot months of the year. A decrease in soil moisture and dryness can be observed in a major part of Iran from early spring to mid-autumn. Also, in the Zagros region, from mid-summer to mid-autumn, increasing values of the drought index and decreasing soil moisture can be observed. The minimum drought index is in the vegetation areas of Hyrkani and Arsbaran. The correspondence between the results of the surface soil moisture (SSM) of the satellite product and the KBDI drought index obtained from ECMWF-ERA5 shows the appropriate efficiency of the KBDI drought index in identifying drought centers in Iran and investigating the spatio-temporal patterns of drought occurrence. frequent low-intensity drought may favor more drought-tolerant species and adapt forests and grasslands to future conditions without the need for management measures.