فصلنامه فیزیک زمین و فضا
سال چهل و هشتم شماره 4 (زمستان 1401)

Saltwater intrusion is as an environmental hazard in coastal lines if not appropriately managed. The over-exploitation, over-population and climate change have invited and pushed the saltwater landwards and polluted the freshwater aquifers. This research studies the results of the implemented project at the coast of Saint Andre' located in Koksijde, Belgium, to study this phenomenon through near-surface geophysics. Two geophysical methods, including Electrical Resistivity Tomography (ERT) and Electromagnetic Induction (EMI) were used to identify the saltwater intrusion. The present study aimed to investigate the possibility of saltwater intrusion, its extension and assess the government reclamation attempts to push back the saltwater. In the inversions, the Depth of Investigation Index (DOI) and the topography effect were evaluated. The subsurface conductivity of both methods was compared. The reliability of both methods to identify the saltwater intrusion has been established; however, the ERT survey provided a more comprehensive visualization than the EMI. The saltwater intrusion was found in the first 80 m of the coastal line with resistivity values of 2 to 5 Ohm.m; however, the infiltration of freshwater and the reclamation operation have stopped the further progress salinity into the dunes. Local possibilities of brackish water or clay lenses were identified with 7 to 25 Ohm.m resistivity values. The freshwater body was observed at distances between 120 and 220 m of the ERT line with values between 46 and 136 Ohm.m. The results were correlated with other studies, proving the reliability of the models.

This study was carried out to delineate possible mineralized zones within Nkalagu and Abakaliki by mapping the structural and hydrothermal alteration zones deduced from the available aeromagnetic and aeroradiometric datasets. Magnetic enhancement techniques such as total magnetic intensity (TMI), reduction to the equator (RTE), analytical signal (AS) and center for exploration targeting (CET) were utilized. The Potassium, Thorium, Uranium, ternary image maps and the K/Th ratio map were produced to aid the interpretation process of alteration areas. The results obtained from the analysis of the airborne magnetic data identified and enhanced the magnetic signatures that reflect the structural features (lineament) of the study area, by revealing the structural trends at the ENE-WSW, NE-SW and WNW-ESE as major trends and NNE-SSW, NW-SE, NNW-SSE as minor trends. The analysis of radiometric data revealed the concentrations of Thorium (eTh), Uranium (eU), and Potassium (%K) concentrations, which were used for the classification of the rock types present in the area. These classifications identified intrusions of basically igneous rocks such as granite, gabbro, rhyolite, diabase, and metamorphic rocks such as quartzite and schist. The areas believed to be hydrothermally altered, aligned NW-SW, NNE-SSW, SE, central potions, and NE borders were identified based on the concentration of radioelements, using K/Th ratio and the ternary maps. Hence, the results obtained from the analysis of the two methods mapped geological structures, geological boundaries, and alteration areas that could be target areas of possible mineral deposits.

Because of the use of seismic ambient noise as a low-cost tool for researching subsurface structure and hazard assessments in recent decades, urban seismology has become an active research subject both with seismological objectives, as obtaining better microzonation maps in highly populated areas, and with engineering objectives, as the monitoring of traffic or the surveying of historical buildings. As a result, urban seismology has been used in the metropolis of Tehran, which is one of the world's most populated cities. The city is situated on the southern slopes of the Central Alborz Mountains on Quaternary alluvial deposits, and its southern section is situated on the northwest side of Central Iran's Great Desert, surrounded by active faults such as the Mosha Fault, North Tehran Fault and South Rey Fault.By using cultural noises caused by human activities such as traffic, subway, concerts, and rituals in metropolitan settings, urban seismology explains underlying structures, enhances seismic hazard management, and zoning. As a result of the high level of noise created by human activities in Tehran, as well as the presence of subterranean structures in this metropolis, the necessity of urban seismology and seismic ambient noise approaches is clear. The data from Tehran's accelerometer networks that named Tehran Disaster Mitigation and Management Organization (TDMMO) and the Road, Housing and Urban Development Research Center (BHRC) which are equipped with a Guralp CMG-5T three component accelerometer and the power spectral density-probability density function (PSD-PDF) approach by PQLX software, which was made available to the seismologist community in June 2004 were utilized in this study to analyze the spatial and temporal fluctuations of seismic ambient noise in the frequency domain. For this purpose, the period of 10 December to 24 December 2020 was investigated. In addition, the effect of the Corona virus pandemic on the frequency and time domain level of seismic ambient noise was explored in period of 16 March to 26 March 2019 and 15 March to 25 March 2020. This period was chosen because the ancient Nowruz festival is in this period.Finally, considering the energy level of cultural noise denoted by the large daytime/nighttime variation with large energy during working hours and much less during nighttime and weekends, most of the stations have been experiencing the lowest level of cultural noise between the hours of 3:30-4:30 AM across all three frequency ranges that include human movement, traffic and subway, and in terms of spatial variation, D011 station has been experiencing the lowest noise levels in all three frequency ranges due to its construction on a stone structure. Furthermore, investigations on the change of noise levels during the Corona epidemic revealed a drop of 1-4% and a rise of 1-15% for certain stations depending on their location in all three frequency bands.

Due to the population growth in metropolitan regions such as Tehran and the existence of the underground constructions, the importance of seismic investigation is evident to reduce damages caused by probable earthquakes. Accordingly, the precise detection of micro to medium earthquakes is effective tool for tracking fault dynamics in seismic cycles, as well as for earthquake prediction and seismic hazard assessment. In this study, the recorded ambient noise at Tehran Disaster Mitigation and Management Organization (TDMMO) as well as Road, Housing and Urban Development Research Center (BHRC) networks as an accelerometer network installed in Tehran city, have been used on the point of characterizing the noise spectrum for each station as a function of time for obtaining the detection threshold of these networks. Therefore, an indirect approach based on the signal-to-noise ratio (SNR) in the time domain, with parameterization in the frequency domain is applied. Based on SNR method, the source signature is simulated by a simple source model called a circular fault model. Thus, the signal is estimated via the Brune function as most common models for circular faults. While, to determine the noise, the real data of 13 accelerometer stations of the TDMMO and seven joint stations with the BHRC are used. In this respect, the Power Spectral Density (PSD) of noise is calculated using PQLX software in the frequency domain and then is transferred to the time domain by the Parsville theorem. Eventually, the SNR value is acquired for each station by dividing these two quantities. As a result, the minimum detectable magnitude in at least five stations with an SNR larger than 5 is 3.0 for S-waves and 3.3 for P-waves, which frequently occurs in the center of the network.Another finding of these studies is to analyze the effect of spatial variations of the noise on the detection ability. For this, a constant noise is allotted to all stations, lowest observed noise level, as a result of which, the smallest magnitude detectable is 1.7 for S-waves and 2.2 for P-waves.At last, the sensitivity of the detection capability to three fundamental parameters, including stress drop, focal depth and reduced time, which are assumed as constant values within the network, are investigated. In fact, these parameters are strongly affected by uncertainty and are not absolute values. Consequently, the impact of their changes was studied. In our case, it is implied that the variation in the stress drop has no effect on the detection threshold, but the focal depth and the reduced time are effectual. A 15 km variation in the focal depth, the detectable magnitude changes by 0.3 units, and by changing the reduced time from 0.015 s to 0.035 s, the detectable magnitude varies by 0.4 units in Mw.

Ignoring electrical anisotropy, if present, results in inaccurate modeling of electromagnetic data and unreliable subsequent interpretation. Its identification through the data analysis procedure, therefore, can lead to the selection of the correct algorithm for modeling and inversion and ultimately trustworthy interpretation. In this study, a part of the magnetotelluric data acquired on Sabalan volcano, located in northwestern Iran, was examined in terms of the presence of electrical anisotropy. For this purpose, penetration depths, anisotropy coefficients, phase tensor, induction vectors, and distortion parameters were considered. The results confirm significant signatures for anisotropic features in the area in the form of different depths of two polarizations, high anisotropy magnitudes, and consistent deviation of the phase tensor main axes and anisotropy directions from the regional trend. This is consistent with the outflow direction towards the Moil valley, indicated by previous studies and the high density of fractures and faults related to the setting of hydrothermal reservoirs as the main path of fluid flow.

Indonesia is located at the Pacific Ring of Fire and the meeting place of the world's four tectonic plates, which makes Indonesia to have a high tectonic activity and to be prone to earthquakes. Currently, early earthquake detection service in Indonesia is based on seismometers network. However, seismometer instruments that observe seismic waveforms might become saturated, and as such may lead to incorrect earthquake magnitude detection at an early stage. Therefore, a new approach is needed to detect earthquake coseismic information. Global Navigation Satellite System (GNSS) is a good instrument to measure the surface displacement due to an earthquake. However, previous studies in Indonesia still predominantly used daily solution data. To carry out early detection, it is not possible to use daily solutions. Therefore it is needed to use the data with a higher frequency solution than the daily solution. In this study, we used 30-second sampling rate data available from Indonesian Continuously Operating Reference Station (Ina-CORS) and Sumatran GPS Array (SuGAr). We will see how the 30-second GNSS data responds to earthquakes to estimate the value of coseismic displacement compared to daily solution data. The estimated value of this coseismic displacement can be used for earthquake early detection.

Water saturation is one of the key petrophysical parameters that mainly affects the accuracy of initial oil estimation related to a hydrocarbon reservoir. Approximation of this parameter is inevitable since it has a high effect on economic development of hydrocarbon reservoirs. In this paper, we approximate a function, using two wells with two core data sets belonging to each well, to predict water saturation by means of Support Vector Machine (SVM) algorithm in one of the gas reservoirs in the Persian Gulf. Due to the inevitability of noise and outliers in the measured data, SVM is modified to Fuzzy SVM (FSVM). For this purpose, a membership function is applied on the points, so each data point receives a membership degree. In this case, each input point is able to contribute to the learning of decision function. In other words, FSVM is able to enhance SVM by devoting less value to noise and outliers, as a result, better models compared to SVM can be produced. In this study, application of SVM for regression purpose (Support Vector Regression) is carried out on eight logs of DT, GR, RHOB, NPHI, LLD, LLS, MSFL, PEF as input with relevant core data belonging to a gas zone. Then, we determine the coefficients based on the comparison between predicted water saturation (using both SVR and fuzzy SVR algorithm) and core data. Our results show that the predicted water saturation from fuzzy SVR and SVR are 95% and 71%, respectively (higher for fuzzy SVR than SVR).

The Fin doublet earthquakes with magnitudes MN 6.2 and 6.3 occurred on November 14, 2021 in Hormozgan province, south of Iran, and were followed by many aftershocks with magnitude range between MN 2.5 and MN 5.0. In this study, first we conducted the InSAR analysis using the satellite data from European Space Agency (ESA) to the Fin doublet earthquakes. The displacement field obtained from interferometric observations in ascending and descending directions, exhibit ~E-W oriented pattern reverse fault. Then, we relocated aftershocks that were recorded between November 14, 2021 and January 14, 2022, using the double-difference relocation method (hypoDD). The general pattern of relocated aftershocks distribution shows a seismic zone covering an area of approximately 25×17 km2. The cross-sections through aftershock locations show that the dominant depth range of aftershocks is from ~4 to ~23 km. The results show that the focal depths decrease toward the northeastern part of the region and deeper-aftershocks are located in the southwestern part. The interferometric observations and distribution of relocated aftershocks suggest the source fault(s) of the Fin doublet earthquakes strikes along a nearly west–east line and dip toward south-to-southeast.

The study of mantle convection is one of the most important topics in geodynamics. Mantle convection causes the transfer of internal heat to the cold parts of the Earth, and the effects of this heat transfer are observed as the motion of tectonic plates on the Earth's surface. Earthquakes, volcanism, and mountain building at the plate margins result from the movement of tectonic plates. Although the mantle occupies a large volume of the Earth, there are many fundamental questions about mantle composition, rheology, dynamics, and history. Many of these questions remain unanswered due to our indirect observations of the mantle. A major tool to study mantle dynamics is numerically analyzing mantle convection equations. In this work, we used Aspect -short for Advanced Solver for Problems in Earth's Convection- code to simulate mantle convection. The geometric model used in the simulation is a box of 4200 km by 3000 km. Using this code, we investigated the effect of different Rayleigh numbers on controlling the mantle convection and creating mantle plumes. Results show that the number of mantle plumes increases with increasing Rayleigh number, and the rising mantle plumes become thinner with the Rayleigh number increasing. Finally, we studied the relationship between the Rayleigh number and the Nusselt number (surface heat flux). We conclude that there is a power-law relation between Rayleigh and Nusselt numbers.

Geophysical inverse problems seek to provide quantitative information about geophysical characteristics of the Earth’s subsurface for indirectly related data and measurements. It is generally formulated as an ill-posed non-linear optimization problem commonly solved through deterministic gradient-based approaches. Using these methods, despite fast convergence properties, may lead to local minima as well as impend accurate uncertainty analysis. On the contrary, formulating a geophysical inverse problem in a probabilistic framework and solving it by constructing the multi-dimensional posterior probability density (PPD) allow for complete sampling of the parameter space and the uncertainty quantification. The PPD is numerically characterized using Markov Chain Monte Carlo (MCMC) approaches. However, the convergence of the MCMC algorithm (i.e. sampling efficiency) toward the target stationary distribution highly depends upon the choice of the proposal distribution. In this paper, we develop an efficient proposal distribution based on perturbing the model parameters through an eigenvalue decomposition of the model covariance matrix in a principal component space. The covariance matrix is retrieved from an initial burn-in sampling, which is itself initiated using a linearized covariance estimate. The proposed strategy is first illustrated for inversion of hydrogeological parameters and then applied to synthetic and real geo-electrical data sets. The numerical experiments demonstrate that the presented proposal distribution takes advantage of the benefits from an accelerated convergence and mixing rate compared to the conventional Gaussian proposal distribution.

Located in Alp-Himalayan belt and an active tectonic plate, Iran is annually struck by major earthquakes. Since shallow earthquakes cause considerable loss of lives and property in this region, using any method to decrease the time of magnitude estimation of great earthquakes is very important for making a prompt decision about what to do. To achieve this aim, mB was computed as a rapid estimator for 38 earthquakes with magnitudes greater than 6 occurred in Iran and adjacent areas (24°-44°N, 42°-66°E) from 1990 to 2018. The magnitudes that estimated by using the calibration function by Saul & Bormann (2007) have a standard error of 0.49 from Mw (in this study). Therefore, mB’s calibration function was modified. As a result, the magnitudes obtained are approximately equal to those of reported Mw (a standard error of 0.18). The calibration function acquired in this study for Iran’s earthquakes is lower than the mB’s global calibration function obtained by Saul & Bormann (2007). Their difference is nearly one unit at short distances, which can be related to the earthquakes located in subduction zones and plates boundaries used by Saul & Bormann (2007) that systemically have lower stress drops than intraplate earthquakes considered here. Thus it is needed to develop improved region-specific calibration functions for mB. However, the difference became smaller at distances greater than 20°. Consequently, this method and new calibration function can be employed to estimate magnitudes as early as possible across Iran plateau.

While Surface Heat Flow (SHF) is an important indicator of the hydrocarbon reservoirs and mineral potentials, the measurements over the Iranian plateau are very sparse. In light of accessing the crustal and lithospheric structure derived from a well-constrained geophysical-petrological model, this study provides a 3D SHF, Curie depth isotherm (580 ºC), Moho temperature and low-temperature sedimentary basins (<150 ºC) over the Iranian plateau and surrounding areas. We solve heat transfer equation using certain thermal boundary condition and user-defined thermophysical parameters for crust. Thermal conductivity of the lithosphere is calculated iteratively. The results indicate that the iron deposits (within the igneous provinces) are spatially correlated with highs in the 3D map of SHF (>60 mW/m2), the shallow Curie isotherm (<40 km) and warm Moho boundary (>800 ºC) where lithospheric thinning or crustal thickening occurs. SHF highs are observed in the northern part of the Zagros collision zone, Central Iran micro-continent and Kopet Dagh. The low-temperature sedimentary basins (<150 ºC) are illustrated by the lows in the 3D map of SHF (<60 mW/m2), deep Curie isotherm (>40 km), and cold Moho boundary (<800 ºC) where lithosphere thickening or crustal thinning is taken place. These basins are distributed in the Oman Sea, Persian Gulf, northern margin of the Arabian plate (Mesopotamian foreland basin), the Caspian Sea and Turan platform.

The proposed software solution is a tool developed for the analysis, forecast and visualization of geophysical data, which is collected and provided by a set of spatially distributed heterogeneous data repositories via standard web protocols (HTTP, HTTPs, FTP, etc.). They include ground magnetic observatories and stations, satellites, as well as various numerical models based on geophysical standards and specifications. The technological stack is limited with the tool’s web-based implementation and represented by integrated client- and server-side technologies with specialized frameworks and APIs. Client-side implementation is represented by several markup, styling and interaction software technologies, which are HTML5/CSS3/JavaScript with geospatial ESRI ArcGIS API for JavaScript available as the RESTful resources. Django web framework based on the “Model – View – Controller” architectural model represents server-side implementation, where Python is the main programming language used for the application’s business logic. The complete Web-based GIS represents a web portal with a set of services providing a rich instrumentation for the appropriate geophysical data analysis, processing, and visualization. Each tool upon execution provides an interactive geospatial image, which is generated according to the user request parameters or by default date-time settings. The proposed web services are freely available at https://aurora-forecast.ru and https://geomagnetic.ru through the web browsers.

Land surface temperature (LST) plays a key role in the transfer of heat to the atmosphere and to the subsurface layers of soil. This study aims at examining the determination coefficient of MODIS LST on air temperature and soil temperature at different depths of Iran. A new method was employed to create a time consistent LST from Terra and Aqua MODIS products, to eliminate the observation differences in local solar time. Preceding the production of time consistent MODIS LST for 12:30 PM, a comparison was carried out with temperature measurements of meteorological stations. The correlation of MODIS LST and Meteorological Station Measurement (hereafter MSM) demonstrate high values, especially for air temperature and 5cm-deep subsurface soil temperature (R2>0.95). The lowest value was obtained for 100cm-deep soil temperature (R2=0.83). The results of intra annual analysis revealed significant relationship between MODIS LST and MSM temperatures. In the comparison of MODIS LST with subsurface soil temperatures, the scatter plot changes from 1:1 to fusiform due to the delay in heat transfer from surface to the subsurface of soil layers. This result postulates that MODIS LST is consonant with MSM temperatures in arid and semiarid regions of Iran. Spatial variation of correlation is higher for 100cm-deep soil temperature (16%). On the contrary, for air temperature and 5cm-deep soil temperature showing the highest correlation, the spatial variation is negligible throughout Iran (6.2%). However, Root Mean Square Error (RMSE) analysis revealed LST differences from 2.43 to 24.88 ˚C throughout Iran rather than MSM temperatures.

The particulate matter with a diameter of 2.5 μm (PM2.5) concentration seriously impacts the environment, climate, and human health. PM2.5 emissions are caused by anthropogenic or natural sources and are still a problem worldwide. In this study, monthly, seasonal, and annual spatial distributions of PM2.5 concentrations were analyzed over Iraq for the period 2003 to 2020 by use of the geographic information system technique. The results indicated that the PM2.5 concentration was higher in summer than in winter and autumn. The monthly mean maximum values of PM2.5 occurred during June and July with 8.4 and 8.7 µg/m3 over central and southern regions of Iraq, respectively, while monthly means of minimum values were observed during November over northern and western regions. These results conclude that the magnitude of outdoor PM2.5 concentrations varies among seasons and regions. Also, the annual means of PM2.5 were less than the standard maximum permissible limits, and their seasonal means were smaller than this limit at all seasons.

The current study compares the effect of dust aerosols on two meteorological variables, temperature and relative humidity, in two different regions. For this purpose, AOD data from the Moderate Resolution Imaging Spectroradiometer (MODIS) were used for Kermanshah and Ahvaz from 2010 to 2015. In a subjective review, a day with the highest AOD value was highlighted. The effects of dust on temperature and relative humidity variations were investigated on the selected day and compared with a clean day. The effect of aerosols on the vertical profile of temperature shows that increasing aerosol concentrations in Kermanshah causes a rise in temperature at lower atmosphere during the day due to the absorption of solar radiation by dust aerosols and a decrease in temperature at night due to the longwave radiative cooling. Because of the high seasonal humidity in Ahvaz, the nature of the aerosols has resulted in the greenhouse effect, which has raised the temperature by absorbing radiation at night. The effect of aerosols on the vertical profile of relative humidity differs between Kermanshah and Ahvaz. The relative humidity has risen, particularly at lower levels in Ahvaz during the dusty days and nights. The increase in aerosols in both Ahvaz and Kermanshah regions had no effect on precipitation based on data from the Iran Meteorological Organization. The reason could be lack of precipitating systems in the two regions during the warm seasons.

In this work, the longitudinal variations of equatorial electrojet (EEJ) and its effect on the diurnal behavior of the EIA during quiet days in the period of 2011- 2012 were investigated. EEJ has been estimated using a pair of ground-based magnetometers data from six longitudinal sectors, and the Global Positioning System (GPS) TEC have also been obtained at each longitudinal sector from three stations at Northern and Southern crests and trough regions. The statistical results show that the monthly mean variations of EIA crest are consistent with that of the strength of equatorial electrojet in most regions of the investigation. The mean EEJ and EIA crests are strongest around equinoctial months in the Peruvian and Southeast Asian sectors followed by the West African regions throughout the years investigated. The weakest EEJ peaks and TEC of EIA are observed over the Pacific sectors throughout the periods of investigation. The monthly mean characteristics of EEJ/counter electrojets (CEJ) and EIA are also presented. The results also show that the CEJ events occur more frequently in the Brazilian sectors followed by in the Peruvian and West African sectors. However, in most of the equinoctial months, the strongest equatorial EIA trough and weakest of EIA crests are observed in the Brazilian sector. The temporal extent of the well-developed EIA crest and its properties show a substantial dependence on the diurnal characteristics of the EEJ for each specific day.

The behavior of ion acoustic wave (IAW) is studied in an electron-ion plasma consisting of cold ions and nonextensive electrons. In this study, the reductive perturbation method is used and the new point is the non-uniformity of the nonextensive parameter in the media. We want to achieve more realistic results of ion acoustic wave behavior by better using the reductive method. In fact, the variation in the behavior of ion acoustic wave when it encounters the nonextensity perturbation region is examined. Perturbation area is a part of plasma where the nonextensivity changes slightly. Therefore, the presence of nonextensivity is introduced as the first order perturbation and the phase velocity is applied as a fixed parameter in the calculations. The modified KdV (mKdV) equation is derived to describe the behavior of the ion acoustic wave propagation in this model. The obtained equation clarifies the change of the soliton profile when moving in all through the perturbation area. Our numerical results show that part of ion acoustic waves propagates as oscillatory shock wave in the perturbed area. The results of this investigation can be helpful for understanding the behavior of ion acoustic waves in an astrophysical environment and space plasmas with varying nonextensivity (Qiu et al., 2020; Silva et al., 1998; Lima et al., 2000).