مجله ژئوفیزیک ایران
سال شانزدهم شماره 4 (پیاپی 57، Winter 2022)

One of the largest earthquakes in the Zagros region occurred on November 12, 2017, in Sarpol-e Zahab with Mw=7.3. We considered the aftershocks of this event and collected the S-wave amplitude spectra from 87 strong-motion records to determine the source, path, and site effects using a non-parametric generalized inversion technique. The grid-searching method based on Brune’s ω2 model was employed to determine some of the source parameters. The corner frequency and seismic moment vary from 1.11 to 5.14 Hz and from 9.12×1014 to 1.36×1017 N.m, respectively. Also, The seismic moment and the cube of corner frequency are inversely related to each other. The stress drop of earthquakes is determined with the ε indicator. In this study ε is equal to 1.91; thus this value indicates that frictional overshoot has occurred with the dynamic frictional stress larger than the final stress. The S-wave quality factor is estimated as Q=101f0.67. The value of Q0 is small, which is characteristic of an active tectonic environment. We compared the site effects that were calculated by GIT and H/V methods. In most cases, a very good agreement was observed and the small difference between them is mainly due to the constraints and assumptions of these methods.

In order to investigate the scope of uncertainty in projections of GCMs for Tehran province, a multi-model projection composed of 15 models is employed. The projected changes in minimum temperature, maximum temperature, precipitation, and solar radiation under the A1B scenario equivalent to RCP4.5 for Tehran province are investigated for 2011-2030, 2046-2065, and 2080-2099. GCM projections for the study region are downscaled by the LARS-WG5 model. In climate change impact assessment studies, due to the influence of different sources of uncertainty on the output of the predicting system, projections do not have sufficient confidence. Therefore, it is recommended that for quantifying the range of uncertainty in the projections, the maximum number of available GCM models be used in simulations. In this regard, 15 GCMs used in this study are a subset of the CMIP4 models  used in the IPCC 4th assessment report published in 2007. All these models are the coupled Atmospheric-Oceanic models and have been run for the 1960-2100 period. Uncertainty among the projections is evaluated from three perspectives: large-scale climate scenarios, downscaled values, and mean decadal changes. 15 GCMs unanimously project an increasing trend in the temperature for the study region. Also, uncertainty in the projections for the summer months is greater than projection uncertainty for other months. The mean absolute surface temperature increase for the three periods is projected to be about 0.8°C, 2.4°C, and 3.8°C in the summers, respectively. The uncertainty of the multi-model projections for precipitation in summer seasons and the radiation in the springs and falls is higher than in other seasons for the study region. Model projections indicate that for the three future periods and relative to their baseline period, springtime precipitation will decrease about 5%, 10%, and 20%, and springtime radiation will increase about 0.5%, 1.5%, and 3%, respectively. The projected mean decadal changes indicate an increase in temperature and radiation and a decrease in precipitation. Furthermore, the performance of the GCMs in simulating the baseline climate by the MOTP method does not indicate any distinct pattern among the GCMs for the study region. The future projection of temperature confirms that Tehran will experience hotter summers in the future compared to the base period. This, together with the increased sunshine in the springs and summers, can increase the frequency of temperature- and radiation-related phenomena such as photochemical pollution and may degrade the future summertime air quality in the study region. Moreover, the projected reduction in winter and spring precipitation, together with increased temperature, may increase the demands in the region.

Geothermal energy potential investigation over parts of Middle Benue Trough, Nigeria, has been evaluated using aeromagnetic and aeroradiometric datasets. The input data consists of nine aeromagnetic and aeroradiometric sheets, respectively. The aeromagnetic data was assembled and digitized; this produces a total magnetic intensity anomalous map (TMI). Similarly, the radiometric data were contoured to produce maps for the three radiometric elements of K, Th, and U. The rose diagram showed that the structural trend in the study area is trending NE-SW and the minor ones are trending E-W and NNE-SSW directions. The radiometric heat model reveals areas of high and low geothermal gradient. The results of quantitative interpretation reveal that the depth to anomalous magnetic sources (the sedimentary infilling) ranges between 0.76 and 4.46 km; while the depth to centroid ranges between 7.29-19.6 km. The Curie point depth (CPD) corresponds to the depth to the bottom of the anomalous magnetic source. The CPD varies from 12.70-37.22 km, the geothermal gradient varies between 15.58-45.670C/km, and the geothermal heat flow varies from 38.9-114.17 mW/m2. The two dimensional structural models show uplifted crust and mantle in some areas due to magmatic intrusions, which gave rise to low CPDs (12 to 28 km), which resulted in high geothermal heat flow values (60 to 115 mW/m2). The geothermal heat flow values around Kwolla, Shendam, Lafia, Akiri, Ibi, and Wukari South fall between 60 and 100 mW/m2, which is the suitable standard for geothermal potentiality.

The 1641 Dehkhwargan-Tabriz earthquake (Ms 6.8) is the only destructive earthquake to have occurred in Azarshahr-Khosrowshahr-Osku region of northwestern Iran. Ambiguities regarding the causative fault of this earthquake were a motivation to someway declare its mechanism. In this study, by conducting a field survey in an area between Tabriz and Azarshahr, and use of satellite imagery and aerial photographs, we provide geologic and geomorphic indications to identify the poorly known Azarshahr-Tabriz fault zone (ATF), which passes through the meizoseismal region of the 1641 earthquake. Our observations highlight the presence of a sinistral active fault zone that extends ~40 km in length from south of Tabriz to the northeast and north of Azarshahr to the southwest. The ATF is a structural assemblage of several fault strands with a variety of extensional and compressional mesoscale structures. We estimated slip rates ranging from ~0.01 mm yr−1 to <1 mm yr−1, based on drainage offset measurements, which demonstrate a relatively stable tectonic environment located immediately south of the well-known seismically active dextral North Tabriz fault.

The use of a Geographic Information System (GIS) for assessing landslide susceptibility in the steeply rugged mountainous terrain of Chilas Basin, Pakistan, is covered in this research. Chilas is the part of Karakorum mountain ranges that lie north of Gilgit. Northern Pakistan is the region in which all the catastrophic events like earthquakes, mass wasting, and flash floods are routine marvels. Among them, catastrophic landslide events in this highly elevated and steeply mountainous region are a severe threat to human as well as economic property. To assess these catastrophic landslide events, a detailed landslide inventory map was constructed based on Google Earth images. Followed by field observation in which the selected spots of a landslide triggered locations were confirmed in the field. Four main controlling parameter groups were collaborated to generate landslide susceptibility maps: (1) Human-induced parameters like road distance, (2) Topographical parameters in terms of slope, and land cover, (3) Hydrological parameters, like rainfall, distance to stream, and temperature (4) Geological parameters in term of lithology and distance from major faults. These thematic layers were developed in a GIS environment to construct the landslide hazard map of the Chilas Basin. Among all the controlling parameters slope is regarded as the highest-ranked factor as followed by geology and landcover. Analytical Hierarchy Process (AHP) basis weighted overlay technique was used to assess the final susceptibility map followed by Area under Curve (AUC) model. Based on these analyses, four distinct susceptible regions were detected in the area, with severe mass wasting activities. The AUC model gives an 81% result, which is satisfactory.

For more than two decades, the Global Positioning System (GPS) under a method called GPS meteorology, has been providing valuable products and parameters for meteorologists and climatologists in addition to its main purpose, which is positioning. GPS meteorology can be used in both space-based and ground-based modes. The space-based approach, called GPS Radio Occultation (RO), is used to provide the profiles of refractivity, temperature, pressure, and water vapor pressure in a neutral atmosphere and electron density in the ionosphere. However, ground-based GPS meteorology is utilized to estimate the tropospheric delay of the GPS signals and Precipitable Water Vapor (PWV) value. To date, GPS RO profiles have been used in several researches to study ionosphere and troposphere layers in Iran. However, no studies have yet used these data to estimate and evaluate PWV. In this study, GPS RO profiles were used to calculate and evaluate PWV over the study area. For statistical comparison, ground-based PWV (GB PWV) estimates in 41 stations in the study region have been considered reliable values. After selecting the pair of PWV values obtained from the space-based and ground-based GPS meteorology in the region, statistical parameters were extracted. In general, the results showed that the GPSRO PWV values have 80% correlation with the corresponding values obtained from the ground-based method. The average and RMSE of the GB-GPSRO PWV differences in the region were estimated at 3 mm and 5.2 mm, respectively. Also, the effective parameters on the accuracy of GPSRO PWV values such as seasonal changes, the position of stations, the difference in height of the lowest point of the GPS RO profile from the ground (dh), and the horizontal distance between the profile and the ground station were examined. The correlation of GPSRO PWV and GB PWV for winter, spring, summer, and autumn seasons were estimated at 0.75, 0.72, 0.73, and 0.85, respectively. The reason for the greater correlation between these two methods in the cold seasons of the year can be attributed to the lower variation of PWV values in these seasons. After sensitivity analysis of the factors considered in relation to the quality of GPSRO PWV values, statistical comparison between GB and GPS RO methods was performed using new conditions. The results showed that with dh <500m condition, the MBE and RMSE of GPSRO PWV compare to ground-based method decreased by about 50% and 25%, respectively, and the correlation between these two methods improved by 5%.

In this research, patterning of rainstorm (more than 10 mm) was conducted by instability indices in Ahvaz. At first, rainfall data from 2000 to 2015 was extracted and statistically examined. Instability indices for rainy days were calculated by the Skew-T diagram. Then, patterning was done by using hierarchical clustering, Ward method, and Euclidean distance. As the sample, one day was selected from each cluster and was synoptically analyzed. The results revealed 60 rainstorms for the respective period. More rainstorms occurred in January and December. Autumn and winter had the most frequent days of rainstorm, while it did not occur in the summer. The results of classification divided rainstorms into 4 patterns and more days were in the fourth class, while the least was in the second class. In the second and fourth classes, instability indices were severe and could predict possible rainstorms, but the first and third classes couldn’t predict because synoptic systems caused the occurrence of the rainstorm. In the second and fourth classes, rainstorms were convectional. The synoptic analysis showed that every time rainstorm occurred in Ahvaz, a deep trough at 500 hPa was formed in the East Mediterranean and the area was in front of it. Also, at sea level pressure, a low-pressure system formed in Iraq and winds got humid by passing through the Persian Gulf and entered into the atmosphere of Ahvaz. Due to the unstable atmosphere, the air would rise to heights causing rainstorm.

Amidst the blend of trepidation about dwindling petroleum reserves, a latent frenzy towards improving reserves worldwide, and the ironical call for replacement of fossil fuels, the need still persists, to leverage on legacy data and increasing technological advantages to re-characterize existing fields for optimal reserve recovery. Reservoir evaluation and hydrocarbon play assessment of a typical Niger delta field has been carried out in this research work. This involved delineation of reservoir rocks, characterizations of the fluid within the reservoir, and assessment of the structural relations of the seal, source, and trap (Play Type) in the study location. By inspection of the signatures of a suit of petrophysical logs (comprising of resistivity, gamma ray, shale volume, and density), the HD2000 reservoir was delineated. The reservoir is sandwiched between two impermeable shale beds (seals/caps) bordering the top and bottom of the reservoir. Using Lambda-Rho, Mu-Rho, P-Impedance, Vp/Vs Ratio, and porosity, petrophysical cross plot analyses was carried out. Advanced post-stack 3-D acoustic impedance inversion yielded petrophysical attribute slices which helped to validate the observations in the cross plots. Results showed that the wells cut through zones of low values of P- Impedance, Mu-Rho, Lambda-Rho, and Vp/Vs ratio, corresponding to hydrocarbon saturated sands. Event time structure maps at both horizons and a seismicsection showing faults, fractures, and an anticline structural trend, confirmed that the play type is a fault and fracture infested rollover anticline, which combines with the delineated seals/caps at the top and bottom of the reservoir to form a structural trap for hydrocarbon within the reservoir. These observations correspond to the characteristics of plays in the oil rich belt of the Niger delta petroleum field, where rollover anticlines in front of growth faults form the main objectives of oil exploration.

Multi-model projections in climate studies are performed to quantify and narrow uncertainty and improve reliability in climate projections. The challenging issue is that there is no unique way to obtain performance metrics, nor is there any consensus about which method would be exactly the best method for combining models. The goal of this study was to investigate whether combining climate model projections using an artificial neural network approach could improve climate projections and therefore reduce the range of uncertainty. The equally-weighted model averaging (the mean model) and single climate model projections (the best model) were also considered as a reference of comparison for our artificial neural network combination approach. Simulations of historical climate and future projections from 15 General Circulation Models for temperature and precipitation were employed.Our results indicate that based on calculated performance indices combining General Circulation Models projections by using the artificial neural network approach significantly improves the simulations of temperature and precipitation for the historical period compared to the best model approach and the mean model approach. Our results also indicate that based on the calculated performance indices for the three approaches, projections based on single model simulation might not yield reliable results because the best model changed between temperature and precipitation, and also among stations that were studied. Therefore, there was no a unique model which could represent the best model for all climate variables and/or stations in the study region. The mean model was also not skillful enough in giving an accurate projection of historical climate compared to the other two approaches. Therefore, the ANN approach was used to estimate projections of future temperature and precipitation for the study region based on three different emission scenarios.Simulation of temperature indicated that the artificial neural network approach had the best skill at simulating monthly means of the historical period compared to other approaches in all stations. Simulation of precipitation in the historical period, however, indicated that the artificial neural network approach was not the best approach in all stations, although this modeling approach performed better than the mean model approach. Multi-model projections of future climate variables for this study region performed by the artificial neural network approach projected an increase in temperature and reduction in precipitation in all stations and for all scenarios.The artificial neural network approach can benefit projections of the climate variables and has the potential to reduce the uncertainty aspects in constructing and combining metrics used for weighting the models. However, this approach is subject to some limitations which exist in similar skill-based performance studies of models and should be considered in future similar studies.

The ill-posed problems could be seen anywhere in our daily lives. An ill-posed problem is a problem that there are no uniqueness solutions (there is no solution or two or more solutions for the problem) or the solutions are unstable; i.e., an arbitrarily small error in the observation may lead to extremely large errors in the solutions. The main difficulty in solving ill-posed problems is instability of their solutions with respect to small variations of input data. A regularized estimation of an ill-posed problem is always biased; thus, it's worth obtaining the solution from different methods for reliable evaluation of the uncertainty in our estimation. The regularization methods, such as Tikhonov's method, are used to obtain stable solutions for solving ill-posed problems. In Tikhonov's regularization method, a scalar quantity is used as the stabilization parameter to solve ill-posed problems; whereas, In the Optimally Scaled Vector Regularization Method (OSVRM), a vector is used as the stabilization parameter. In this paper, a comparison has been made between the results of Tikhonov, TSVD, and OSVRM methods in terms of accuracy of the results for estimation of the earth gravity field from GOCE satellite data. The RMSE of the results of Tikhonov, EGM96 model, and the OSVRM method – that use a vector instead of scalar as regularization parameter – in the order of 10-5, 10-9, and 10-13, respectively. It is seen that the results obtained from the OSVRM method are much better compared to the Tikhonov method and EGM96 model for solving linear ill-posed problems. On the other hand, a significant improvement has been achieved in the stability and accuracy of numerical results for linear problems solution.

Groundwater is one of the most precious assets for supplying water to the world's population. The main goal of this research paper is to use the GIS technique to determine the best drilling sites for new groundwater wells, based on hydro-geoelectrical factors and using a weighted overlay approach. Weighted Overlay Approach (WOA) assessment is a geographical approach for analysing multiclass charts, that are influenced by the various relevances of every layer as well as the classification of a layer. The advantage of WOA is its ability to makes the more favourable criteria with the higher values in the output raster, that help thereafter identifying those locations as the priority. The aquifer hydro-geoelectrical parameters such as resistivity, thickness, depth, and transmissivity.obtained by using the vertical electrical sounding (VES) technique allow together to determine the best locations for drilling.    The GIS technique is conjointly used herein to accurately identify the best location for the aquifers using the mentioned hydro-geoelectrical data. Weighted overlay has been applied to normalize the criteria layers, and blende to finally generate the suitability maps. The geospatial datasets are combined by using GIS to create and establish a suitability chart for determining efficient suitable locations for drilling successful water boreholes. The most suitable locations have been well recognized. The study area is divided into four categories: poorly suitable, fairly suitable, suitable, and excellently suitable. The different findings of this research can be consequently used to plan effective groundwater management in the region.

Investigation of historical and instrumental seismicity and fault kinematics of major faults are used to deduce the stress state in the northeast of Greater Tehran. In the present study, we have identified the Mw 5.1 earthquake and its related aftershocks in northeast Tehran that occurred on May 7, 2020. In this regard, after combining the waveforms of seismograms recorded in the seismic stations of Tehran and neighbouring provinces, the location, magnitude, and exact time of occurrence of the main shock and its six aftershocks have been calculated. Then, using three methods, including waveform modelling, P wave polarity and the ratio of P and S wave amplitudes, the focal mechanism of the fault causing seismic events is estimated. Fault kinematic study and the epicenter of the seismic event and related aftershocks suggest that the Mosha fault could be responsible for the event. Furthermore, the regional tectonic stress field has been calculated by focal mechanism inversion. Comparisons between stress field orientations and stress ratio provide new information on the local stress field. The variation of the stress ratio in the lower and upper crust is considerably high, demonstrating an inhomogeneity of deformation related to the Mosha fault.

Deformation monitoring is a crucial engineering task for public safety. Any incorrect estimation of displacement rates can cause economical and deadly effects on engineering structures. Three methods have already been developed for structure deformation monitoring in the geodetic community: the single point method, and the robust and combinatorial estimation methods. In this article, the methods were implemented on a simulated dataset of the Global Navigation Satellite System. As a result, the Simultaneous Adjustment of Two Epochs and Multiple Sub Sample using distance differences methods were defined as the most optimal methods to find the stable and unstable points in the simulated network. To show the performance of the methods on a real dataset, the optimal methods were employed on the real GNSS observations collected of a pedestrian steel bridge in Tehran. The GNSS receiver type is LEICA GRX1200+GNSS. Moreover, two scenarios are investigated: all epochs have the same global coordinate systems (Scenario A), and analysis of the earth’s surface movements with the local coordinate system in the first epoch of observations and the global WGS84 coordinate system for the others (Scenario B). The 3-D Helmert transformation was also used to transfer the global coordinate systems to the local one. Scenario B showed better results with a smaller RMS error with an amount of 7e-5.

A distinctive attribute of basement complex terrain is the widespread manifestation of structural deformations. Locating these structural deformations, such as faults, fractures, folds, and joints of the basement complex terrain, is a preface to hydrogeologic, engineering, and environmental studies as well as mineral resource exploration programs. The present study aims to delineate the subsurface structures and establish geometry and depths of magnetic anomalies in the region of Igarra Schist Belt of parts of the Southwestern Precambrian Basement Complex of Nigeria using gradient (Euler deconvolution and filtering) techniques. The 3D Euler approach estimates the location of a simple entity using magnetic field measurements by splitting the data into windows of subsequent measurements. Based on its structural index, each window calculates a single average depth and magnetic source position, while filtering is essentially employed to delineate subsurface geologic features using standard deviation. To filter data, the standard deviation filter returns the data's local distribution, with the magnitude of the effect depending on the feature's quantity. The finding showed lots of these geological features (± 95%) are located at shallow depths 0f 0 - 300 m and few are located at depths >300 m. The research region's combined data was used to generate a consistent structural map that depicted the likely placements and trends of the putatively fractured/faulted zone, as well as additional basement structures that formed in tetra-modal NE-SW, ESE-WNW, ENE-WSW, and E-W directions. These structural tendencies, which vary in intensity and length, are sturdily related to tectonic activities and over and above guidance for geoelectric studies required for hydrogeologic and engineering explorations.