@article { author = {Mahallati, Ali Reza and Montahaei, Mansooreh}, title = {Application of MT Forward Modeling Responses for Time-Lapse Monitoring of the Subsurface Electrical Resistivity Changes}, journal = {Journal of the Earth and Space Physics}, volume = {46}, number = {4}, pages = {1-12}, year = {2021}, publisher = {Institute of Geophysics, University of Tehran}, issn = {2538-371X}, eissn = {2538-3906}, doi = {10.22059/jesphys.2019.279194.1007107}, abstract = {Monitoring fracture developments in the rupture area of an earthquake or unconventional energy reservoirs (ex: enhanced geothermal systems (EGS), coal seam gas (CGS) or shale- gas reservoirs, where massive fluid injection enhances ground permeability) are crucial to determine the stress field direction and optimize well placement and energy production. In addition to microseismic tomography, magnetotelluric (MT) monitoring method provides an independent verification tool to determine more constraints on fluid distribution and migration in target lithologies. MT phase tensors (PT) and apparent resistivity tensors (RT) are calculated from impedance tensor. Assuming that geological and geo-engineering processes leave an electrically anisotropic volume in their corresponding damage zones, we investigate the time variation of RT and PT residuals for time-lapse MT monitoring purposes. First, we see how the PT and RT are influenced by layered models containing dipping and azimuthal anisotropy and then two synthetic models, representative of real earth situations including general 2D anisotropic features are studied. The results of our numerical experiments show that despite the phase tensor ellipses, the real part of apparent resistivity tensor could discriminate between isotropic, azimuthally and generally anisotropic half spaces. Furthermore, the PT and RT residuals provide complementary tools for MT monitoring of the variations in the subsurface electrical resistivity structure. Although PT residuals could confine the anomalous region more accurately, the RT residuals determine whether a conductive or resistive variation has been occurred in the anomalous region.}, keywords = {monitoring,magnetotelluric,electrical anisotropy,phase tensor,apparent resistivity tensor}, title_fa = {Application of MT Forward Modeling Responses for Time-Lapse Monitoring of the Subsurface Electrical Resistivity Changes}, abstract_fa = {Monitoring fracture developments in the rupture area of an earthquake or unconventional energy reservoirs (ex: enhanced geothermal systems (EGS), coal seam gas (CGS) or shale- gas reservoirs, where massive fluid injection enhances ground permeability) are crucial to determine the stress field direction and optimize well placement and energy production. In addition to microseismic tomography, magnetotelluric (MT) monitoring method provides an independent verification tool to determine more constraints on fluid distribution and migration in target lithologies. MT phase tensors (PT) and apparent resistivity tensors (RT) are calculated from impedance tensor. Assuming that geological and geo-engineering processes leave an electrically anisotropic volume in their corresponding damage zones, we investigate the time variation of RT and PT residuals for time-lapse MT monitoring purposes. First, we see how the PT and RT are influenced by layered models containing dipping and azimuthal anisotropy and then two synthetic models, representative of real earth situations including general 2D anisotropic features are studied. The results of our numerical experiments show that despite the phase tensor ellipses, the real part of apparent resistivity tensor could discriminate between isotropic, azimuthally and generally anisotropic half spaces. Furthermore, the PT and RT residuals provide complementary tools for MT monitoring of the variations in the subsurface electrical resistivity structure. Although PT residuals could confine the anomalous region more accurately, the RT residuals determine whether a conductive or resistive variation has been occurred in the anomalous region.}, keywords_fa = {monitoring,magnetotelluric,electrical anisotropy,phase tensor,apparent resistivity tensor}, url = {https://jesphys.ut.ac.ir/article_72930.html}, eprint = {https://jesphys.ut.ac.ir/article_72930_2cbf3a5a6b593e5b24b749d7c63271a4.pdf} } @article { author = {Gomaa, Mohamed M.}, title = {Using Electrical Properties of Some Subsurface Sedimentary Rocks as a Tool to Detect Bedding Direction}, journal = {Journal of the Earth and Space Physics}, volume = {46}, number = {4}, pages = {13-26}, year = {2021}, publisher = {Institute of Geophysics, University of Tehran}, issn = {2538-371X}, eissn = {2538-3906}, doi = {10.22059/jesphys.2020.280457.1007112}, abstract = {The direction of bedding is not natural to be detected using laboratory measurements. Cretaceous rocks are mainly composed of sandstone and clay (clastic facies, sandstones, siltstones, mudstone). Electrical characteristics were measured perpendicular and parallel to layer direction (42 Hz to 5 MHz) to detect anisotropy and homogeneity of samples. Electrical characteristics of samples were measured at the dry state and three different salines (NaCl) concentrations at a constant temperature. Electrical anisotropy and homogeneity of samples are contributed mainly to load pressure direction compaction. Previous factors are an excellent diagenetic feature and changes from one example to another. Elongation of conductor and insulator grains will change electrical properties. Due to the homogeneity of samples, the only variable in electrical characteristics will relate to the anisotropy of grains. When the grains are, more or less, spherical, then electrical components will be similar at two perpendicular directions. Whereas, when grains are needles or disks, later, electrical characteristics will be changed. This paper tries to detect qualitatively and as a quick tool, anisotropy and homogeneity of samples by measuring their electrical properties. Anisotropy in studied samples was described by slight to moderate electric lineation and foliation.}, keywords = {electric,Dielectric Constant,complex conductivity,clastic,Anisotropy,Heterogeneity}, title_fa = {Using Electrical Properties of Some Subsurface Sedimentary Rocks as a Tool to Detect Bedding Direction}, abstract_fa = {The direction of bedding is not natural to be detected using laboratory measurements. Cretaceous rocks are mainly composed of sandstone and clay (clastic facies, sandstones, siltstones, mudstone). Electrical characteristics were measured perpendicular and parallel to layer direction (42 Hz to 5 MHz) to detect anisotropy and homogeneity of samples. Electrical characteristics of samples were measured at the dry state and three different salines (NaCl) concentrations at a constant temperature. Electrical anisotropy and homogeneity of samples are contributed mainly to load pressure direction compaction. Previous factors are an excellent diagenetic feature and changes from one example to another. Elongation of conductor and insulator grains will change electrical properties. Due to the homogeneity of samples, the only variable in electrical characteristics will relate to the anisotropy of grains. When the grains are, more or less, spherical, then electrical components will be similar at two perpendicular directions. Whereas, when grains are needles or disks, later, electrical characteristics will be changed. This paper tries to detect qualitatively and as a quick tool, anisotropy and homogeneity of samples by measuring their electrical properties. Anisotropy in studied samples was described by slight to moderate electric lineation and foliation.}, keywords_fa = {electric,Dielectric Constant,complex conductivity,clastic,Anisotropy,Heterogeneity}, url = {https://jesphys.ut.ac.ir/article_74726.html}, eprint = {https://jesphys.ut.ac.ir/article_74726_4ed27b8110e20461e30bc93f4e72d6bb.pdf} } @article { author = {Fanaee Kheirabad, Gholam Abbas and Oskooi, Behrooz}, title = {Two-Dimensional Magnetotelluric Modeling of the Sabalan Geothermal Field, North-West Iran}, journal = {Journal of the Earth and Space Physics}, volume = {46}, number = {4}, pages = {27-37}, year = {2021}, publisher = {Institute of Geophysics, University of Tehran}, issn = {2538-371X}, eissn = {2538-3906}, doi = {10.22059/jesphys.2020.280925.1007114}, abstract = {During 2007, a magnetotelluric (MT) survey in the frequency range of 0.002-320 Hz was carried out on southwestern of Sabalan geothermal region (Moeil valley, Ardabil); the aim of which was modeling of the shallow and deep electrical resistivity structures related to the local geothermal reservoirs and heat system recharge at depth. Twenty eight soundings were conducted in the study area, and the collected MT data were found to be two-dimensional (2D), based on dimensionality (skew parameter) analysis. The NNW-SSE (30°W) direction was identified as the dominant electrical strike in the area. Data along a profile crossing the hot springs with seven MT stations, have been implemented for modeling and inversion. Dimensionality analysis shows that a 2D interpretation of the data is justified, although the presumed geoelectric strike direction is not consistent over the whole profile and frequencies. MT data were analyzed and modeled using MT2DInvMatlab inversion source codes and the finite elements (FEM) method for forward modeling. Inversion parameters as an input file and appropriate mesh blocks design are prepared before start of the modeling and inversion. MT2DInvMatlab software includes a topography file into a forward model for terrain effects compensation in the inversion process. After setting up the model parameter, 2D inversion of the Sabalan magnetotelluric data was performed. Smoothness–constrained least square methods with a spatially regularization parameter estimation and the ACB (Active Constraint Balancing) algorithm were employed in MT2DInvMatlab to stabilize the model. Both apparent resistivity and phase data were used to have models with minimum misfit for TM, TE and joint TE+TM mode data. The TM mode apparent resistivity and phase are better fitted than the TE mode, as a consequence of the inductive nature of the 2D TE response in a 3-D geothermal field structures. However, the apparent resistivity and phase data are also well fitted in the joint inversion of TM and TE mode data. Although the TM mode data is often used for 2-D modeling of MT data in geothermal field studies, we have shown the other two dimensional electrical resistivity models, using apparent resistivity and phase data of TM, TE and joint TE+TM mode data. These models resolved a good correlation between the features of the geothermal field and resistivity distribution at depth. The resulting models reveal the presence of a resistive cover layer (Cap-rock) underlain by an anomalous conductive layer and other geological structures such as fluid-filled faults (about 500-1000 m below the ground surface). A very low resistivity (3-5 ohm-m) feature was found at the depths below 2000 m, bounded by two more resistive (100-500 ohm-m) features that can be interpreted as the main reservoir of the geothermal system in the area. At shallow depths, the resistivity model obtained from the MT data is consistent with the general conceptual resistivity model proposed for high-temperature geothermal systems. The deeper electrical structure was found to be more resistive (100 ohm-m) due to the presence of metamorphic rock formations. According to this results, heat source of the geothermal structure and heat transition zone from deep sources to shallow reservoir, is predicted at 2~7Km at depth.}, keywords = {magnetotellurics,Geothermal,Reservoir,MT2DinvMatlab,Sabalan}, title_fa = {Two-Dimensional Magnetotelluric Modeling of the Sabalan Geothermal Field, North-West Iran}, abstract_fa = {During 2007, a magnetotelluric (MT) survey in the frequency range of 0.002-320 Hz was carried out on southwestern of Sabalan geothermal region (Moeil valley, Ardabil); the aim of which was modeling of the shallow and deep electrical resistivity structures related to the local geothermal reservoirs and heat system recharge at depth. Twenty eight soundings were conducted in the study area, and the collected MT data were found to be two-dimensional (2D), based on dimensionality (skew parameter) analysis. The NNW-SSE (30°W) direction was identified as the dominant electrical strike in the area. Data along a profile crossing the hot springs with seven MT stations, have been implemented for modeling and inversion. Dimensionality analysis shows that a 2D interpretation of the data is justified, although the presumed geoelectric strike direction is not consistent over the whole profile and frequencies. MT data were analyzed and modeled using MT2DInvMatlab inversion source codes and the finite elements (FEM) method for forward modeling. Inversion parameters as an input file and appropriate mesh blocks design are prepared before start of the modeling and inversion. MT2DInvMatlab software includes a topography file into a forward model for terrain effects compensation in the inversion process. After setting up the model parameter, 2D inversion of the Sabalan magnetotelluric data was performed. Smoothness–constrained least square methods with a spatially regularization parameter estimation and the ACB (Active Constraint Balancing) algorithm were employed in MT2DInvMatlab to stabilize the model. Both apparent resistivity and phase data were used to have models with minimum misfit for TM, TE and joint TE+TM mode data. The TM mode apparent resistivity and phase are better fitted than the TE mode, as a consequence of the inductive nature of the 2D TE response in a 3-D geothermal field structures. However, the apparent resistivity and phase data are also well fitted in the joint inversion of TM and TE mode data. Although the TM mode data is often used for 2-D modeling of MT data in geothermal field studies, we have shown the other two dimensional electrical resistivity models, using apparent resistivity and phase data of TM, TE and joint TE+TM mode data. These models resolved a good correlation between the features of the geothermal field and resistivity distribution at depth. The resulting models reveal the presence of a resistive cover layer (Cap-rock) underlain by an anomalous conductive layer and other geological structures such as fluid-filled faults (about 500-1000 m below the ground surface). A very low resistivity (3-5 ohm-m) feature was found at the depths below 2000 m, bounded by two more resistive (100-500 ohm-m) features that can be interpreted as the main reservoir of the geothermal system in the area. At shallow depths, the resistivity model obtained from the MT data is consistent with the general conceptual resistivity model proposed for high-temperature geothermal systems. The deeper electrical structure was found to be more resistive (100 ohm-m) due to the presence of metamorphic rock formations. According to this results, heat source of the geothermal structure and heat transition zone from deep sources to shallow reservoir, is predicted at 2~7Km at depth.}, keywords_fa = {magnetotellurics,Geothermal,Reservoir,MT2DinvMatlab,Sabalan}, url = {https://jesphys.ut.ac.ir/article_74727.html}, eprint = {https://jesphys.ut.ac.ir/article_74727_df807a3280c73fd7af0bc3537d9cee0c.pdf} } @article { author = {Safarkhani, Mahsa and Shirzad, Taghi}, title = {Improvement in the Empirical Green's Function Extraction Using Root Mean Square Ratio Stacking}, journal = {Journal of the Earth and Space Physics}, volume = {46}, number = {4}, pages = {39-48}, year = {2021}, publisher = {Institute of Geophysics, University of Tehran}, issn = {2538-371X}, eissn = {2538-3906}, doi = {10.22059/jesphys.2020.281801.1007119}, abstract = {Seismic interferometry is an efficient technique to extract the Empirical Green's Function (EGF) between station pairs when the source is considered at one of the stations. The geometry and energy flux of asymmetric noise sources have unavoidable impacts on the extracted EGFs, deduced from ambient seismic noise recorded in pairs of stations. In this study, to consider these effects, three methods of noise correlation functions stacking (linear, root mean square, root mean square ratio) are investigated using synthetic and real data processing. During synthetic data processing, effects of the noise sources geometry and energy flux inside and outside the Fresnel zone are examined. After separating stationary and non-stationary sources, the results have shown that the root mean square ratio contains the least effects of non-stationary signals compared to other methods of stacking. Moreover, comparison of the EGFs from the recorded data in Azerbaijan (NW Iran), indicates that the signal retrieved by root mean square ratio is more reliable than the other stacking methods' signals (e.g., linear, root mean square).}, keywords = {Asymmetric distribution of noise energy flux,Empirical Green's functions,Fresnel zone,Non-stationary signals,Root Mean Square Ratio stacking}, title_fa = {Improvement in the Empirical Green's Function Extraction Using Root Mean Square Ratio Stacking}, abstract_fa = {Seismic interferometry is an efficient technique to extract the Empirical Green's Function (EGF) between station pairs when the source is considered at one of the stations. The geometry and energy flux of asymmetric noise sources have unavoidable impacts on the extracted EGFs, deduced from ambient seismic noise recorded in pairs of stations. In this study, to consider these effects, three methods of noise correlation functions stacking (linear, root mean square, root mean square ratio) are investigated using synthetic and real data processing. During synthetic data processing, effects of the noise sources geometry and energy flux inside and outside the Fresnel zone are examined. After separating stationary and non-stationary sources, the results have shown that the root mean square ratio contains the least effects of non-stationary signals compared to other methods of stacking. Moreover, comparison of the EGFs from the recorded data in Azerbaijan (NW Iran), indicates that the signal retrieved by root mean square ratio is more reliable than the other stacking methods' signals (e.g., linear, root mean square).}, keywords_fa = {Asymmetric distribution of noise energy flux,Empirical Green's functions,Fresnel zone,Non-stationary signals,Root Mean Square Ratio stacking}, url = {https://jesphys.ut.ac.ir/article_74728.html}, eprint = {https://jesphys.ut.ac.ir/article_74728_9ed3a159c5df3f1ea1573d6e677812f7.pdf} } @article { author = {Farzaneh, Saeed and Sharifi, Mohammad Ali and Kosary, Mona}, title = {Automatic Satellite’s Streak Detection in Astronomical Images Based on Intelligent Methods}, journal = {Journal of the Earth and Space Physics}, volume = {46}, number = {4}, pages = {49-64}, year = {2021}, publisher = {Institute of Geophysics, University of Tehran}, issn = {2538-371X}, eissn = {2538-3906}, doi = {10.22059/jesphys.2020.281849.1007120}, abstract = {The orbit determination in one sentence is the application of a variety of techniques for estimating the orbits of objects such as the moon, planets and spacecraft. In dynamic astronomy, the orbit determination is the process of determining orbital parameters with observations. Considering the visibility of the satellite motion trace and the fundamental need to determine and modify satellites’ orbital parameters as well as identify special satellites, determining the positional parameters of the satellite is also one of the modern and important applications of vision-based astronomical systems. In the modern vision-based astronomical systems, data collection is done using a charge-coupled device (CCD) array. In this paper, a new method is presented for satellite streak detection through an optical imaging system. This automatic and efficient method, which has the ability of real-time data analysis, is based on the sidereal image using CCDs. The images captured by this method have a large amount of information about stars, galaxy, and satellites’ streaks. In this paper, an automatic method is presented for streak detection. The purpose of this research is to find an optimal method for satellite streak detection and different methods in clustering such as k_means, particle swarm optimization (PSO), genetic algorithm (GA), and Gaussian mixture model (GMM). Finally, some assessment criteria were compared and concluded that GA is an optimal algorithm in satellite streak detection.}, keywords = {satellite tracking,satellite streak detection,MSAC,Clustering,swarm intelligence}, title_fa = {Automatic Satellite’s Streak Detection in Astronomical Images Based on Intelligent Methods}, abstract_fa = {The orbit determination in one sentence is the application of a variety of techniques for estimating the orbits of objects such as the moon, planets and spacecraft. In dynamic astronomy, the orbit determination is the process of determining orbital parameters with observations. Considering the visibility of the satellite motion trace and the fundamental need to determine and modify satellites’ orbital parameters as well as identify special satellites, determining the positional parameters of the satellite is also one of the modern and important applications of vision-based astronomical systems. In the modern vision-based astronomical systems, data collection is done using a charge-coupled device (CCD) array. In this paper, a new method is presented for satellite streak detection through an optical imaging system. This automatic and efficient method, which has the ability of real-time data analysis, is based on the sidereal image using CCDs. The images captured by this method have a large amount of information about stars, galaxy, and satellites’ streaks. In this paper, an automatic method is presented for streak detection. The purpose of this research is to find an optimal method for satellite streak detection and different methods in clustering such as k_means, particle swarm optimization (PSO), genetic algorithm (GA), and Gaussian mixture model (GMM). Finally, some assessment criteria were compared and concluded that GA is an optimal algorithm in satellite streak detection.}, keywords_fa = {satellite tracking,satellite streak detection,MSAC,Clustering,swarm intelligence}, url = {https://jesphys.ut.ac.ir/article_77989.html}, eprint = {https://jesphys.ut.ac.ir/article_77989_2097ffb69dac0aab6400f45cf04ca3e1.pdf} } @article { author = {Varfinezhad, Ramin and Oskooi, Behrooz}, title = {A Semi-Automatic 2-D Linear Inversion Algorithm Including Depth Weighting Function for DC Resistivity Data: A Case Study on Archeological Data Sets of Pompeii}, journal = {Journal of the Earth and Space Physics}, volume = {46}, number = {4}, pages = {65-77}, year = {2021}, publisher = {Institute of Geophysics, University of Tehran}, issn = {2538-371X}, eissn = {2538-3906}, doi = {10.22059/jesphys.2020.282486.1007124}, abstract = {In this paper, a new simple, efficient and semi-automatic algorithm including depth weighting constraint is introduced for 2-D DC resistivity data inversion. Inversion procedure is linear; however, DC resistivity data inversion is generally nonlinear due to the nonlinearity of Maxwell’s equation relative to resistivity (conductivity). We took the advantage of the 2-D forward operator formula obtained based on integral equations (IE) by Perez- Flores et al. (2001), for the inversion algorithm. Inversion algorithm is iterative and regularization parameter and depth weighting exponent are the critical parameters that have default values of 0.1 and 1, respectively. The presented technique was used only for dipole-dipole array by Perez-Flores et al. (2001), but here in addition to improving results for dipole-dipole array, its productivity is demonstrated for other geo-electrical arrays such as Wenner alfa, Wenner Schlumberger. Three synthetic data sets computed by Res2dmod software are utilized to investigate the performance of the algorithm through comparing the results with Res2dinv software output sections. Finally, the algorithm is applied on an archeological data set of Pompeii, which was collected by dipole-dipole array. IE inversion algorithm lead to satisfactory inversion models for both synthetic and real cases which reconstruct the subsurface better than or as well as that of the software.}, keywords = {DC resistivity,depth weighting,integral equation,inversion,Res2dinv}, title_fa = {A Semi-Automatic 2-D Linear Inversion Algorithm Including Depth Weighting Function for DC Resistivity Data: A Case Study on Archeological Data Sets of Pompeii}, abstract_fa = {In this paper, a new simple, efficient and semi-automatic algorithm including depth weighting constraint is introduced for 2-D DC resistivity data inversion. Inversion procedure is linear; however, DC resistivity data inversion is generally nonlinear due to the nonlinearity of Maxwell’s equation relative to resistivity (conductivity). We took the advantage of the 2-D forward operator formula obtained based on integral equations (IE) by Perez- Flores et al. (2001), for the inversion algorithm. Inversion algorithm is iterative and regularization parameter and depth weighting exponent are the critical parameters that have default values of 0.1 and 1, respectively. The presented technique was used only for dipole-dipole array by Perez-Flores et al. (2001), but here in addition to improving results for dipole-dipole array, its productivity is demonstrated for other geo-electrical arrays such as Wenner alfa, Wenner Schlumberger. Three synthetic data sets computed by Res2dmod software are utilized to investigate the performance of the algorithm through comparing the results with Res2dinv software output sections. Finally, the algorithm is applied on an archeological data set of Pompeii, which was collected by dipole-dipole array. IE inversion algorithm lead to satisfactory inversion models for both synthetic and real cases which reconstruct the subsurface better than or as well as that of the software.}, keywords_fa = {DC resistivity,depth weighting,integral equation,inversion,Res2dinv}, url = {https://jesphys.ut.ac.ir/article_74729.html}, eprint = {https://jesphys.ut.ac.ir/article_74729_58c4bf51cb9b4145b14695f011294d51.pdf} } @article { author = {Eshaghzadeh, Ata and Seyedi Sahebari, Sanaz and Kalantari, Roghayeh Sadat}, title = {2-D Anticlinal Structure Modeling Using Feed-Forward Neural Network (FNN) Inversion of Profile Gravity Data: A Case Study from Iran}, journal = {Journal of the Earth and Space Physics}, volume = {46}, number = {4}, pages = {79-91}, year = {2021}, publisher = {Institute of Geophysics, University of Tehran}, issn = {2538-371X}, eissn = {2538-3906}, doi = {10.22059/jesphys.2021.286888.1007148}, abstract = {The Anticlines are the main hydrocarbon traps on land or at sea. This structure is considered as the target of the many projects of gravity exploration all over the world. Artificial neural networks (ANNs) are used in order to solve prediction, estimation, and optimization problems. In this paper, the feed-forward neural network (FNN) is applied for modeling the anticlinal structure using gravity anomaly profile and the back propagation algorithm is used for artificial neural network training. Moreover, the scalene triangle model is employed to describe the geometry of anticlinal structure in analyzing gravity anomalies. In terms of neural network training, eight features among the synthetic gravity field variations curves along 22500 profiles are defined. These gravity profiles are computed based on different values of the scalene triangle parameters consisting of the top depth, bottom depth, limb angles and density contrast. The defined neural network contain three layers, eight neurons (the number of features) in the input layer, 30 neurons in the hidden layer and six neurons (the number of scalene triangle parameters) in the output layer. In order to evaluate the performance of the trained neural network, the specified features related to a synthetic model, with and without random noise, are applied as the input data to train neural network. The parameters estimation error by FNN is negligible. The proposed method is illustrated with a real gravity data set from Korand region, Iran. The inferred anticlinal structures are compared with the interpreted map of the seismic data.}, keywords = {Anticlinal structure,Feed-forward neural network (FNN),Gravity,Scalene triangle,Iran}, title_fa = {2-D Anticlinal Structure Modeling Using Feed-Forward Neural Network (FNN) Inversion of Profile Gravity Data: A Case Study from Iran}, abstract_fa = {The Anticlines are the main hydrocarbon traps on land or at sea. This structure is considered as the target of the many projects of gravity exploration all over the world. Artificial neural networks (ANNs) are used in order to solve prediction, estimation, and optimization problems. In this paper, the feed-forward neural network (FNN) is applied for modeling the anticlinal structure using gravity anomaly profile and the back propagation algorithm is used for artificial neural network training. Moreover, the scalene triangle model is employed to describe the geometry of anticlinal structure in analyzing gravity anomalies. In terms of neural network training, eight features among the synthetic gravity field variations curves along 22500 profiles are defined. These gravity profiles are computed based on different values of the scalene triangle parameters consisting of the top depth, bottom depth, limb angles and density contrast. The defined neural network contain three layers, eight neurons (the number of features) in the input layer, 30 neurons in the hidden layer and six neurons (the number of scalene triangle parameters) in the output layer. In order to evaluate the performance of the trained neural network, the specified features related to a synthetic model, with and without random noise, are applied as the input data to train neural network. The parameters estimation error by FNN is negligible. The proposed method is illustrated with a real gravity data set from Korand region, Iran. The inferred anticlinal structures are compared with the interpreted map of the seismic data.}, keywords_fa = {Anticlinal structure,Feed-forward neural network (FNN),Gravity,Scalene triangle,Iran}, url = {https://jesphys.ut.ac.ir/article_79564.html}, eprint = {https://jesphys.ut.ac.ir/article_79564_34c83ae75b026c7ec80f444eec9af24a.pdf} } @article { author = {Zakeri, Sajjad and Farzaneh, Saeed}, title = {Measurement Methods for Cross-Sections of Tunnels Using Reflectorless Total Stations}, journal = {Journal of the Earth and Space Physics}, volume = {46}, number = {4}, pages = {93-101}, year = {2021}, publisher = {Institute of Geophysics, University of Tehran}, issn = {2538-371X}, eissn = {2538-3906}, doi = {10.22059/jesphys.2020.289995.1007167}, abstract = {Owing to the technical and economic aspects of the project management, pre-estimating the volumes of excavating, shotcreting, and concreting operations have been of great importance for the underground construction industry, especially in metro and highway tunnels. In this respect, we offer a reliable method based on the trigonometric geometry for estimating the required parameters of the conventional tunnels that are manually excavated via explosions and road-header machines. To this end, a geodetic network consisting of dense benchmarks are firstly realized outside the trench and throughout the excavated tunnel. The cross-sections of the tunnel are then mapped in the coordinate frame attached to the reference lines after orienting the reflectorless total station with respect to the geodetic network points and the predesigned reference lines. Consequently, by comparing the resultant coordinates of each cross-section at the excavating, shotcreting, and concreting stages, one can arrive at accurate estimation of the corresponding thickness, areas and volumes during different phases of the tunnel construction. The performance of the proposed method has been evaluated as a function of the central angles between the consecutive points on the arc of tunnel cross-section via a simulated dataset from an assumed D-shape tunnel. The numerical results have indicated that in the case of the consecutive central angle of 25 deg the estimated thickness, area, and volume errors are about 0.0057 m, 0.199 m2, and 0.399 m3, which can be considered as a clear indication of the reliability and applicability of the presented method.}, keywords = {Cross-section mapping,Manual excavation,Conventional tunneling,Reflectorless total station,Concreting volume,lining}, title_fa = {Measurement Methods for Cross-Sections of Tunnels Using Reflectorless Total Stations}, abstract_fa = {Owing to the technical and economic aspects of the project management, pre-estimating the volumes of excavating, shotcreting, and concreting operations have been of great importance for the underground construction industry, especially in metro and highway tunnels. In this respect, we offer a reliable method based on the trigonometric geometry for estimating the required parameters of the conventional tunnels that are manually excavated via explosions and road-header machines. To this end, a geodetic network consisting of dense benchmarks are firstly realized outside the trench and throughout the excavated tunnel. The cross-sections of the tunnel are then mapped in the coordinate frame attached to the reference lines after orienting the reflectorless total station with respect to the geodetic network points and the predesigned reference lines. Consequently, by comparing the resultant coordinates of each cross-section at the excavating, shotcreting, and concreting stages, one can arrive at accurate estimation of the corresponding thickness, areas and volumes during different phases of the tunnel construction. The performance of the proposed method has been evaluated as a function of the central angles between the consecutive points on the arc of tunnel cross-section via a simulated dataset from an assumed D-shape tunnel. The numerical results have indicated that in the case of the consecutive central angle of 25 deg the estimated thickness, area, and volume errors are about 0.0057 m, 0.199 m2, and 0.399 m3, which can be considered as a clear indication of the reliability and applicability of the presented method.}, keywords_fa = {Cross-section mapping,Manual excavation,Conventional tunneling,Reflectorless total station,Concreting volume,lining}, url = {https://jesphys.ut.ac.ir/article_76430.html}, eprint = {https://jesphys.ut.ac.ir/article_76430_7174aa679dd73f59f15cefbcfd3117bc.pdf} } @article { author = {Haerudin, Nandi and Yogi, Ida Bagus Suananda}, title = {A Combination of Monte-Carlo and Damped Least Square Inversion Method for Determining Radon Source in Geothermal Case}, journal = {Journal of the Earth and Space Physics}, volume = {46}, number = {4}, pages = {103-116}, year = {2021}, publisher = {Institute of Geophysics, University of Tehran}, issn = {2538-371X}, eissn = {2538-3906}, doi = {10.22059/jesphys.2020.291763.1007174}, abstract = {Radon measurement on the surface can represent the subsurface condition. The measured Radon in geothermal field is caused by the source, which is usually a geothermal reservoir. This study did the inversion process for determining the depth and value of Radon Source. Another fact, non-uniqueness of the solution can produce a result with different model parameter combinations. Hence, it can confuse the interpreter to determine the correct model. Based on this case, we proposed an inversion scheme that can minimize the non-uniqueness effect in the Radon data inversion. The scheme is started by Monte-Carlo inversion and finished by damped least-square. Monte-Carlo inversion, as one of the global optimizations, produce an appropriate starting model for the damped least squares. The damped least square method will finish the scheme fast. In order to be sure with the result, the whole scheme is repeated 19 times. The relative RMS error for the synthetic data is 0.07% to 0.32%  to  a depth difference of 7% from the synthetic model. With this synthetic data inversion test, the inversion scheme was applied to the real data from the Rajabasa Geothermal field. With this scheme, the section AA’ gives an error of 0.51% to 0.88% with a depth of 712 m and section BB’ gives an error of 5.79% to 5.27% with a depth of 728 m. This result is coherent with the magnetotelluric data in this area.}, keywords = {Damped Least Square,Geothermal,Monte Carlo,Radon,Reservoir}, title_fa = {A Combination of Monte-Carlo and Damped Least Square Inversion Method for Determining Radon Source in Geothermal Case}, abstract_fa = {Radon measurement on the surface can represent the subsurface condition. The measured Radon in geothermal field is caused by the source, which is usually a geothermal reservoir. This study did the inversion process for determining the depth and value of Radon Source. Another fact, non-uniqueness of the solution can produce a result with different model parameter combinations. Hence, it can confuse the interpreter to determine the correct model. Based on this case, we proposed an inversion scheme that can minimize the non-uniqueness effect in the Radon data inversion. The scheme is started by Monte-Carlo inversion and finished by damped least-square. Monte-Carlo inversion, as one of the global optimizations, produce an appropriate starting model for the damped least squares. The damped least square method will finish the scheme fast. In order to be sure with the result, the whole scheme is repeated 19 times. The relative RMS error for the synthetic data is 0.07% to 0.32%  to  a depth difference of 7% from the synthetic model. With this synthetic data inversion test, the inversion scheme was applied to the real data from the Rajabasa Geothermal field. With this scheme, the section AA’ gives an error of 0.51% to 0.88% with a depth of 712 m and section BB’ gives an error of 5.79% to 5.27% with a depth of 728 m. This result is coherent with the magnetotelluric data in this area.}, keywords_fa = {Damped Least Square,Geothermal,Monte Carlo,Radon,Reservoir}, url = {https://jesphys.ut.ac.ir/article_76441.html}, eprint = {https://jesphys.ut.ac.ir/article_76441_e166c34d684c13d2fc1a583898959b5f.pdf} } @article { author = {Layade, Gideon O, and Edunjobi, Hazeez O. and Makinde, Victor and Bada, B. Saheed}, title = {Application of Forward and Inverse Modelling to High-Resolution Gravity Data for Mineral Exploration}, journal = {Journal of the Earth and Space Physics}, volume = {46}, number = {4}, pages = {117-129}, year = {2021}, publisher = {Institute of Geophysics, University of Tehran}, issn = {2538-371X}, eissn = {2538-3906}, doi = {10.22059/jesphys.2020.296560.1007192}, abstract = {Gravity survey is a geophysical tool used to investigate the subsurface by measuring the differences in Earth’s gravitational field. The high-resolution gravity data within latitude 70.00׀ - 70.30 ׀N, and longitude 30.00 ׀- 30.30 ׀E was acquired through Bureau Gravimetrique Internationale (EGM2008). The research work employed the methods of the filtering techniques as well as forward and inverse modelling for data analysis and interpretations. The qualitative results of the gravity anomaly of the field through the regional-residual separation technique and the high pass filters show the local and geologic features of the study area. The low, fairly high and high-density areas are characterized by alluvial, meta-sediments/sedimentary and igneous deposits respectively. The derivative maps aided the locations, boundaries and edges of anomalous bodies, including the transition zones and sedimentary intrusions of the study area. Forward and inverse modeling techniques were applied to profiles (P1-P4) in a quantitative approach, to describe the geometry, density contrast, depth, position, strike, dip and plunge. The depth range of 1268 m to 3111 m was calculated, while the density contrasts of gravity bodies suggest the presence of mineral rocks such as limestone, quartz, gneiss, sandstone, schist, granite, quartzite and gypsum.}, keywords = {Gravity,Density,Filtering,high-resolution,modelling,Depth}, title_fa = {Application of Forward and Inverse Modelling to High-Resolution Gravity Data for Mineral Exploration}, abstract_fa = {Gravity survey is a geophysical tool used to investigate the subsurface by measuring the differences in Earth’s gravitational field. The high-resolution gravity data within latitude 70.00׀ - 70.30 ׀N, and longitude 30.00 ׀- 30.30 ׀E was acquired through Bureau Gravimetrique Internationale (EGM2008). The research work employed the methods of the filtering techniques as well as forward and inverse modelling for data analysis and interpretations. The qualitative results of the gravity anomaly of the field through the regional-residual separation technique and the high pass filters show the local and geologic features of the study area. The low, fairly high and high-density areas are characterized by alluvial, meta-sediments/sedimentary and igneous deposits respectively. The derivative maps aided the locations, boundaries and edges of anomalous bodies, including the transition zones and sedimentary intrusions of the study area. Forward and inverse modeling techniques were applied to profiles (P1-P4) in a quantitative approach, to describe the geometry, density contrast, depth, position, strike, dip and plunge. The depth range of 1268 m to 3111 m was calculated, while the density contrasts of gravity bodies suggest the presence of mineral rocks such as limestone, quartz, gneiss, sandstone, schist, granite, quartzite and gypsum.}, keywords_fa = {Gravity,Density,Filtering,high-resolution,modelling,Depth}, url = {https://jesphys.ut.ac.ir/article_76426.html}, eprint = {https://jesphys.ut.ac.ir/article_76426_cfca7b71bc599a55f26a173049be9434.pdf} } @article { author = {Ahmadi, Iman and Ghorbani, Ahmad and Ansari, Abdol Hamid}, title = {3D Gravity Cross-Correlation Imaging for Large Scale Data Analysis: Application to the Crustal Structure of Iran}, journal = {Journal of the Earth and Space Physics}, volume = {46}, number = {4}, pages = {131-145}, year = {2021}, publisher = {Institute of Geophysics, University of Tehran}, issn = {2538-371X}, eissn = {2538-3906}, doi = {10.22059/jesphys.2020.298815.1007197}, abstract = {We propose the 3D gravity cross-correlation method to large scale data analyses as a fast analysis method to image the underground mass distribution. This method presents the cross-correlation product of the observed gravity anomaly (or its vertical gradient) and the calculated field due to an elementary mass contrast source. The cross-correlation product of the domain is used to highlight the zones of the highest probability of mass concentrations. First, some synthetic examples demonstrate the reliability and resolution of the method. The synthetic models discover different parameters of investigation space as space dimensions and densities. Tests with synthetic bodies show that the resultant correlation coefficients of the approach can delineate causative bodies in the subsurface. Finally, terrestrial gravity anomaly data of Iran is used to study the crustal structure and the Moho depth of Iran. The result is in a good agreement compared with other research studies of the domain. This technique took about five minutes to calculate the 3D gravity cross-correlation of the whole terrestrial gravity data set of Iran (25,937 data) a computer. Hence, it can easily be used repeatedly to monitor changes of gravity field.}, keywords = {Cross-correlation,gravity anomaly,Vertical Gradient,Iran}, title_fa = {3D Gravity Cross-Correlation Imaging for Large Scale Data Analysis: Application to the Crustal Structure of Iran}, abstract_fa = {We propose the 3D gravity cross-correlation method to large scale data analyses as a fast analysis method to image the underground mass distribution. This method presents the cross-correlation product of the observed gravity anomaly (or its vertical gradient) and the calculated field due to an elementary mass contrast source. The cross-correlation product of the domain is used to highlight the zones of the highest probability of mass concentrations. First, some synthetic examples demonstrate the reliability and resolution of the method. The synthetic models discover different parameters of investigation space as space dimensions and densities. Tests with synthetic bodies show that the resultant correlation coefficients of the approach can delineate causative bodies in the subsurface. Finally, terrestrial gravity anomaly data of Iran is used to study the crustal structure and the Moho depth of Iran. The result is in a good agreement compared with other research studies of the domain. This technique took about five minutes to calculate the 3D gravity cross-correlation of the whole terrestrial gravity data set of Iran (25,937 data) a computer. Hence, it can easily be used repeatedly to monitor changes of gravity field.}, keywords_fa = {Cross-correlation,gravity anomaly,Vertical Gradient,Iran}, url = {https://jesphys.ut.ac.ir/article_77996.html}, eprint = {https://jesphys.ut.ac.ir/article_77996_182581906573c2917cdd108ffad72878.pdf} } @article { author = {Suleiman, Taufiq and Okeke, F. Nneka and Obiora, N. Daniel}, title = {Spectral Analysis of High-Resolution Aeromagnetic Data for Geothermal Energy Reconnaissance across Sokoto Basin, Northwest, Nigeria}, journal = {Journal of the Earth and Space Physics}, volume = {46}, number = {4}, pages = {147-158}, year = {2021}, publisher = {Institute of Geophysics, University of Tehran}, issn = {2538-371X}, eissn = {2538-3906}, doi = {10.22059/jesphys.2020.299866.1007205}, abstract = {This study interprets aeromagnetic data across Sokoto Basin with the aim of estimating the Curie point depth, geothermal gradient and heat flow for geothermal energy exploration. The study area lies between the longitude of 30E and 60E and latitudes 110N and 130N. The total magnetic intensity of the area was subjected to regional/residual separation using polynomial fitting. The residual data was divided into 30 overlapping spectral blocks, where the log of spectral energies was plotted against the frequency; hence, the centroid depth and the top to the magnetic sources were deduced. These depth results were used in estimating the Curie point Depth and geothermal gradient. The total magnetic intensity indicated a variation of 32932.84 to 33118.27 nT, while the residual map shows magnetic anomalies that vary from -82 to 51 nT, both maps indicated high, low and intermediary magnetic anomalies. The centroid depth results vary from 4.67 to 28.80 km, and the top to the magnetic source varies from 1.04 to 4.65 km with an average depth of 2.21 km. The Curie point depth range from 6.92 to 55.04 km with an average depth of 18.65 km, and the geothermal gradients revealed ranges from 10.54 oCkm-1 at the Southwest (Danko and Gummi) areas to 83.82oCkm-1 at the northwest (Argungu) area. Therefore, these areas with high geothermal gradients are good indicators of geothermal energy potential and should be exploited for more power generation.}, keywords = {Magnetic anomalies,Spectral analysis,Curie point depth,Geothermal energy,heat flow}, title_fa = {Spectral Analysis of High-Resolution Aeromagnetic Data for Geothermal Energy Reconnaissance across Sokoto Basin, Northwest, Nigeria}, abstract_fa = {This study interprets aeromagnetic data across Sokoto Basin with the aim of estimating the Curie point depth, geothermal gradient and heat flow for geothermal energy exploration. The study area lies between the longitude of 30E and 60E and latitudes 110N and 130N. The total magnetic intensity of the area was subjected to regional/residual separation using polynomial fitting. The residual data was divided into 30 overlapping spectral blocks, where the log of spectral energies was plotted against the frequency; hence, the centroid depth and the top to the magnetic sources were deduced. These depth results were used in estimating the Curie point Depth and geothermal gradient. The total magnetic intensity indicated a variation of 32932.84 to 33118.27 nT, while the residual map shows magnetic anomalies that vary from -82 to 51 nT, both maps indicated high, low and intermediary magnetic anomalies. The centroid depth results vary from 4.67 to 28.80 km, and the top to the magnetic source varies from 1.04 to 4.65 km with an average depth of 2.21 km. The Curie point depth range from 6.92 to 55.04 km with an average depth of 18.65 km, and the geothermal gradients revealed ranges from 10.54 oCkm-1 at the Southwest (Danko and Gummi) areas to 83.82oCkm-1 at the northwest (Argungu) area. Therefore, these areas with high geothermal gradients are good indicators of geothermal energy potential and should be exploited for more power generation.}, keywords_fa = {Magnetic anomalies,Spectral analysis,Curie point depth,Geothermal energy,heat flow}, url = {https://jesphys.ut.ac.ir/article_77998.html}, eprint = {https://jesphys.ut.ac.ir/article_77998_02492b9c5a469395c2bb658f05cfc5e8.pdf} } @article { author = {Layade, Gideon O. and Edunjobi, Hazeez O. and Ajayi, Kehinde D. and Olujimi, D. P.}, title = {Ground Based Gravimetric for the Detection and Depth Mapping of Subsurface Geological Features of Ilesha, Southwest Nigeria}, journal = {Journal of the Earth and Space Physics}, volume = {46}, number = {4}, pages = {159-171}, year = {2021}, publisher = {Institute of Geophysics, University of Tehran}, issn = {2538-371X}, eissn = {2538-3906}, doi = {10.22059/jesphys.2020.301010.1007209}, abstract = {This paper presents the analysis and interpretation of ground gravity data of Ilesha and its environs in southwest Nigeria. The work is aimed at complementing researches done in this locality with magnetic survey for both ground and airborne data. The ground gravity data of the area within latitude (7o30ˈ - 8o00ˈ) N and longitude (4o30ˈ - 5o00ˈ) E was acquired from the Nigerian Geological Survey Agency (NGSA). The data set was interpreted qualitatively and quantitatively to derive information about the structural features of the subsurface. The qualitative analysis was carried out by filtering techniques and interpreted by making visual inspection of grids to map low and high-density regions. Equally, the quantitative interpretation employed were Euler 3-D deconvolution and Source Parameter Imaging (SPI) methods, which revealed the boundary, location and depth of gravity sources defining the study area. The minimum and maximum depths of anomalous sources obtained are 781.43 m and 4,208.85 m, while the average depth to the target is 2,537.215 m. The average depth of gravity anomalous sources estimated predicted the area to hold a worthy prospect for the accumulation of near surface rock minerals.}, keywords = {Density,Filtering,Gravity,qualitative,quantitative}, title_fa = {Ground Based Gravimetric for the Detection and Depth Mapping of Subsurface Geological Features of Ilesha, Southwest Nigeria}, abstract_fa = {This paper presents the analysis and interpretation of ground gravity data of Ilesha and its environs in southwest Nigeria. The work is aimed at complementing researches done in this locality with magnetic survey for both ground and airborne data. The ground gravity data of the area within latitude (7o30ˈ - 8o00ˈ) N and longitude (4o30ˈ - 5o00ˈ) E was acquired from the Nigerian Geological Survey Agency (NGSA). The data set was interpreted qualitatively and quantitatively to derive information about the structural features of the subsurface. The qualitative analysis was carried out by filtering techniques and interpreted by making visual inspection of grids to map low and high-density regions. Equally, the quantitative interpretation employed were Euler 3-D deconvolution and Source Parameter Imaging (SPI) methods, which revealed the boundary, location and depth of gravity sources defining the study area. The minimum and maximum depths of anomalous sources obtained are 781.43 m and 4,208.85 m, while the average depth to the target is 2,537.215 m. The average depth of gravity anomalous sources estimated predicted the area to hold a worthy prospect for the accumulation of near surface rock minerals.}, keywords_fa = {Density,Filtering,Gravity,qualitative,quantitative}, url = {https://jesphys.ut.ac.ir/article_77997.html}, eprint = {https://jesphys.ut.ac.ir/article_77997_9f22c27ca779cb319a59c7d7fb7abf4b.pdf} } @article { author = {Sadeghi, Babak and Taghavi, Farahnaz and Shayegani Akmal, Amir Abbas}, title = {Effect of Earth’s Magnetic Field on Prerequisites for Lightning Initiation in Thunderstorm}, journal = {Journal of the Earth and Space Physics}, volume = {46}, number = {4}, pages = {173-188}, year = {2021}, publisher = {Institute of Geophysics, University of Tehran}, issn = {2538-371X}, eissn = {2538-3906}, doi = {10.22059/jesphys.2019.279456.1007108}, abstract = {In this study, a hypothesis is proposed about the possible effect of Earth’s magnetic field (EMF) on the charge structure of thundercloud based on the Lorentz force equation. To prove this hypothesis, a simulation using the 12th International Geomagnetic Reference Field (IGRF) model has been conducted. In this simulation, three scenarios are considered based on updrafts/downdrafts categories of the charge motion to analyze how a change in velocity of hydrometeor could influence the charge structure of a thunderstorm. The results of simulations show that by stronger velocities, the charged hydrometeors will experience higher amounts of magnetic force. In fact, after cloud electrification and creation of individual charged hydrometeors, Earth’s magnetic force could push the separated charges. Therefore, the distance between separated charges will increase more and more, that leads to the collection of the same sign charges in some layers, which are called charge layers of thunderclouds. Consequently, the probability of electric field and lightning initiation will increase. Finally, results indicate that the effect of EMF on charged hydrometeors might be one of the mechanisms of forming thundercloud’s charge structure and lightning initiation.}, keywords = {EMF,Hydrometeor,Cloud Electrification,Charge Separation,Thunderstorm,Weather}, title_fa = {Effect of Earth’s Magnetic Field on Prerequisites for Lightning Initiation in Thunderstorm}, abstract_fa = {In this study, a hypothesis is proposed about the possible effect of Earth’s magnetic field (EMF) on the charge structure of thundercloud based on the Lorentz force equation. To prove this hypothesis, a simulation using the 12th International Geomagnetic Reference Field (IGRF) model has been conducted. In this simulation, three scenarios are considered based on updrafts/downdrafts categories of the charge motion to analyze how a change in velocity of hydrometeor could influence the charge structure of a thunderstorm. The results of simulations show that by stronger velocities, the charged hydrometeors will experience higher amounts of magnetic force. In fact, after cloud electrification and creation of individual charged hydrometeors, Earth’s magnetic force could push the separated charges. Therefore, the distance between separated charges will increase more and more, that leads to the collection of the same sign charges in some layers, which are called charge layers of thunderclouds. Consequently, the probability of electric field and lightning initiation will increase. Finally, results indicate that the effect of EMF on charged hydrometeors might be one of the mechanisms of forming thundercloud’s charge structure and lightning initiation.}, keywords_fa = {EMF,Hydrometeor,Cloud Electrification,Charge Separation,Thunderstorm,Weather}, url = {https://jesphys.ut.ac.ir/article_72942.html}, eprint = {https://jesphys.ut.ac.ir/article_72942_ff3aa90735f7e9a83c7ea46e6c7e7a47.pdf} } @article { author = {Zaiee, Nabiollah and Akbarinasab, Mohammad and Sadrinasab, Masoud}, title = {Investigation of the Effect of Persian Gulf Outflow Intrusion into the Oman Sea on the Acoustic Signal Fluctuations}, journal = {Journal of the Earth and Space Physics}, volume = {46}, number = {4}, pages = {189-197}, year = {2021}, publisher = {Institute of Geophysics, University of Tehran}, issn = {2538-371X}, eissn = {2538-3906}, doi = {10.22059/jesphys.2020.281401.1007118}, abstract = {Outflow intrusions are often detected in the vertical profiles of temperature and salinity in the ocean (for example, the Red Sea and Persian Gulf outflow into the India Ocean and Oman Sea, respectively). They are being visible by large fluctuations or inversions within the profiles and as zig-zag patterns in the temperature-salinity plots. In this study, first, using the collected salinity and temperature data in the region of the Oman Sea during spring 1996, the sound speed is calculated via Makenzie formula. Then, by plotting the sound speed profile, it was seen that the vertical structure meet anomaly at depth 200 to 400 meter of the profile. Moreover, the effects of presence and absence of the temperature inversion have been examined on the acoustic signal fluctuations with similar boundary conditions using SPARC model at frequency of 100 Hz. The results show that, when the acoustic source is installed below the inversion layer, receivers that are located in the low temperature inversion layer, receive the signal with time delay, and amplitude is greater than that with the absent inversion temperature. Thereby, the present achievements indicate that the outflow intrusion may affect the shapes and delay times of the received signals.}, keywords = {outflow intrusion,acoustic signal fluctuations,SPARC model,Persian Gulf,temperature inversion}, title_fa = {Investigation of the Effect of Persian Gulf Outflow Intrusion into the Oman Sea on the Acoustic Signal Fluctuations}, abstract_fa = {Outflow intrusions are often detected in the vertical profiles of temperature and salinity in the ocean (for example, the Red Sea and Persian Gulf outflow into the India Ocean and Oman Sea, respectively). They are being visible by large fluctuations or inversions within the profiles and as zig-zag patterns in the temperature-salinity plots. In this study, first, using the collected salinity and temperature data in the region of the Oman Sea during spring 1996, the sound speed is calculated via Makenzie formula. Then, by plotting the sound speed profile, it was seen that the vertical structure meet anomaly at depth 200 to 400 meter of the profile. Moreover, the effects of presence and absence of the temperature inversion have been examined on the acoustic signal fluctuations with similar boundary conditions using SPARC model at frequency of 100 Hz. The results show that, when the acoustic source is installed below the inversion layer, receivers that are located in the low temperature inversion layer, receive the signal with time delay, and amplitude is greater than that with the absent inversion temperature. Thereby, the present achievements indicate that the outflow intrusion may affect the shapes and delay times of the received signals.}, keywords_fa = {outflow intrusion,acoustic signal fluctuations,SPARC model,Persian Gulf,temperature inversion}, url = {https://jesphys.ut.ac.ir/article_76434.html}, eprint = {https://jesphys.ut.ac.ir/article_76434_fb30c24518d6ed2683aa05a6fd967e5c.pdf} } @article { author = {Al-Khalidi, Jasim and Bakr, Dher and Hadi, Azhar and Omar, Meeran}, title = {Investigating the Linkage between Precipitation and Temperature Changes in Iraq and Greenhouse Gas Variability}, journal = {Journal of the Earth and Space Physics}, volume = {46}, number = {4}, pages = {199-212}, year = {2021}, publisher = {Institute of Geophysics, University of Tehran}, issn = {2538-371X}, eissn = {2538-3906}, doi = {10.22059/jesphys.2020.288915.1007160}, abstract = {In this study, the homogeneity of annual precipitation and temperature in Iraq were examined for the periods 1981-2010 and 1971-2010, respectively in terms of Greenhouse Gases (GHGs) and their link to climate change. Observational data of precipitation and temperature were provided by Iraqi meteorological stations along with information on GHG concentrations from the Emission Database for Global Atmospheric Research (EDGAR V4.3.2). The homogeneity characterisations of both precipitation and temperature were undertaken, noting that precipitation was homogeneous over the period of study, whereas, temperature, on the other hand, had breakpoints for the meteorological stations investigated. The Mann-Kendall test was performed to determine the trend and magnitude of changes in climate conditions. The time series for precipitation showed a significant decline trend in six stations. However, temperature had a slight trend throughout the period of study. The annual time series of GHG emissions in Iraq and the link with the country’s climate was also investigated in this study indicating that the time series of N2O and CO2 increased over time, but CH4 decreased over the same period. The correlation coefficient values of both temperature and GHG were substantial and were found to increase in the southern stations, given the abundance of intense heat and industrial activities, while the relationship between GHG and precipitation were found to be low. Accordingly, GHG emissions have a direct link with the climatic conditions in Iraq due to the development and contribution of various industries, oil refineries, pollutants and population growth that contributed towards climatic change in Iraq.}, keywords = {Iraq,Precipitation,temperature,homogeneity,Greenhouse,Mann-Kendall,climate change}, title_fa = {Investigating the Linkage between Precipitation and Temperature Changes in Iraq and Greenhouse Gas Variability}, abstract_fa = {In this study, the homogeneity of annual precipitation and temperature in Iraq were examined for the periods 1981-2010 and 1971-2010, respectively in terms of Greenhouse Gases (GHGs) and their link to climate change. Observational data of precipitation and temperature were provided by Iraqi meteorological stations along with information on GHG concentrations from the Emission Database for Global Atmospheric Research (EDGAR V4.3.2). The homogeneity characterisations of both precipitation and temperature were undertaken, noting that precipitation was homogeneous over the period of study, whereas, temperature, on the other hand, had breakpoints for the meteorological stations investigated. The Mann-Kendall test was performed to determine the trend and magnitude of changes in climate conditions. The time series for precipitation showed a significant decline trend in six stations. However, temperature had a slight trend throughout the period of study. The annual time series of GHG emissions in Iraq and the link with the country’s climate was also investigated in this study indicating that the time series of N2O and CO2 increased over time, but CH4 decreased over the same period. The correlation coefficient values of both temperature and GHG were substantial and were found to increase in the southern stations, given the abundance of intense heat and industrial activities, while the relationship between GHG and precipitation were found to be low. Accordingly, GHG emissions have a direct link with the climatic conditions in Iraq due to the development and contribution of various industries, oil refineries, pollutants and population growth that contributed towards climatic change in Iraq.}, keywords_fa = {Iraq,Precipitation,temperature,homogeneity,Greenhouse,Mann-Kendall,climate change}, url = {https://jesphys.ut.ac.ir/article_74740.html}, eprint = {https://jesphys.ut.ac.ir/article_74740_dbbec8c9541f34df8bca12997f6f9893.pdf} } @article { author = {Zeydalinejad, Nejat and Nassery, Hamid Reza and Shakiba, Ali Reza and Alijani, Farshad}, title = {The Evaluations of NEX-GDDP and Marksim Downscaled Data Sets Over Lali Region, Southwest Iran}, journal = {Journal of the Earth and Space Physics}, volume = {46}, number = {4}, pages = {213-230}, year = {2021}, publisher = {Institute of Geophysics, University of Tehran}, issn = {2538-371X}, eissn = {2538-3906}, doi = {10.22059/jesphys.2020.295152.1007186}, abstract = {Downscaling of climatic variables is a difficult problem in the climate change impact studies. However, some climatic data sets exist that have been universally downscaled. These data sets introduce climatic data even in regions with scarce observations. In this study, NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP) and Markov simulation (Marksim) downscaled data sets were evaluated over Lali region, southwest Iran by comparing the monthly RMSE, average and variance differences between the observation data and General Circulation Models' (GCMs') outputs during the time period 2010-2016. The NEX-GDDP data set contains 21 GCMs under two Representative Concentration Pathways (RCPs), i.e. RCP4.5 and RCP8.5, from 1951 to 2099, and the Marksim data set includes 17 GCMs under all RCPs from 2010 to 2095. Results acknowledged the ability of both data sets in projecting the climatic variables in the study area. Finally, NorESM1-M and GFDL-CM3 depicted the best operation for precipitation and temperature, respectively.}, keywords = {NEX-GDDP,Marksim,GCM,Lali region,RCP}, title_fa = {The Evaluations of NEX-GDDP and Marksim Downscaled Data Sets Over Lali Region, Southwest Iran}, abstract_fa = {Downscaling of climatic variables is a difficult problem in the climate change impact studies. However, some climatic data sets exist that have been universally downscaled. These data sets introduce climatic data even in regions with scarce observations. In this study, NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP) and Markov simulation (Marksim) downscaled data sets were evaluated over Lali region, southwest Iran by comparing the monthly RMSE, average and variance differences between the observation data and General Circulation Models' (GCMs') outputs during the time period 2010-2016. The NEX-GDDP data set contains 21 GCMs under two Representative Concentration Pathways (RCPs), i.e. RCP4.5 and RCP8.5, from 1951 to 2099, and the Marksim data set includes 17 GCMs under all RCPs from 2010 to 2095. Results acknowledged the ability of both data sets in projecting the climatic variables in the study area. Finally, NorESM1-M and GFDL-CM3 depicted the best operation for precipitation and temperature, respectively.}, keywords_fa = {NEX-GDDP,Marksim,GCM,Lali region,RCP}, url = {https://jesphys.ut.ac.ir/article_76438.html}, eprint = {https://jesphys.ut.ac.ir/article_76438_0ee445276a6a0f6135febedaa7a4fb69.pdf} } @article { author = {Mokhtari, Ramin and Akhoondzadeh, Mehdi}, title = {Data Fusion and Machine Learning Algorithms for Drought Forecasting Using Satellite Data}, journal = {Journal of the Earth and Space Physics}, volume = {46}, number = {4}, pages = {231-246}, year = {2021}, publisher = {Institute of Geophysics, University of Tehran}, issn = {2538-371X}, eissn = {2538-3906}, doi = {10.22059/jesphys.2020.299445.1007199}, abstract = {Drought is one of the natural disasters in the world, which is associated with various global factors, most of which can be observed using remote sensing techniques. One of the factors affecting agricultural drought is the vegetation associated with other drought-related factors. These parameters have a complicated relationship with each other, so machine learning algorithms can be used to predict better and model this phenomenon. Factors considered in this study include vegetation as the most critical factor, Land Surface Temperature (LST), Evapo Transpiration (ET), snow cover, rainfall, soil moisture these are derived from the active and passive sensors of satellite sensors as the products of LST, snow cover and vegetation using images of products of the MODIS sensor, rainfall using the images of the TRMM satellite, and soil moisture using the images of the SMOS satellite during a period from June 2010 to the end of 2018 for the central region of Iran. After that, primary processing was performed on these images. The vegetation index (NDVI) is modelled and predicted using an Artificial Neural Network algorithm (ANN), Support Vector Regression (SVR), Decision Tree (DT), Random Forest (RF) for monthly periods. By using these methods we have been able to present a model with desirable accuracy. The ANN approach has provided higher accuracy than the other three algorithms. Also, an average accuracy with RMSE=0.0385 and =0.8740 was achieved.}, keywords = {Drought,Machine learning,TRMM,MODIS,SMOS}, title_fa = {Data Fusion and Machine Learning Algorithms for Drought Forecasting Using Satellite Data}, abstract_fa = {Drought is one of the natural disasters in the world, which is associated with various global factors, most of which can be observed using remote sensing techniques. One of the factors affecting agricultural drought is the vegetation associated with other drought-related factors. These parameters have a complicated relationship with each other, so machine learning algorithms can be used to predict better and model this phenomenon. Factors considered in this study include vegetation as the most critical factor, Land Surface Temperature (LST), Evapo Transpiration (ET), snow cover, rainfall, soil moisture these are derived from the active and passive sensors of satellite sensors as the products of LST, snow cover and vegetation using images of products of the MODIS sensor, rainfall using the images of the TRMM satellite, and soil moisture using the images of the SMOS satellite during a period from June 2010 to the end of 2018 for the central region of Iran. After that, primary processing was performed on these images. The vegetation index (NDVI) is modelled and predicted using an Artificial Neural Network algorithm (ANN), Support Vector Regression (SVR), Decision Tree (DT), Random Forest (RF) for monthly periods. By using these methods we have been able to present a model with desirable accuracy. The ANN approach has provided higher accuracy than the other three algorithms. Also, an average accuracy with RMSE=0.0385 and =0.8740 was achieved.}, keywords_fa = {Drought,Machine learning,TRMM,MODIS,SMOS}, url = {https://jesphys.ut.ac.ir/article_77987.html}, eprint = {https://jesphys.ut.ac.ir/article_77987_e03e8e498a288152fbeb11eb029b20ba.pdf} } @article { author = {Nguyen, Van Thang and Van Khiem, Mai and Nguyen, Hoang-Minh and Thang, Vu Van}, title = {Verification of Rainfall Forecasts for the South Central Climate Region of Vietnam}, journal = {Journal of the Earth and Space Physics}, volume = {46}, number = {4}, pages = {247-258}, year = {2021}, publisher = {Institute of Geophysics, University of Tehran}, issn = {2538-371X}, eissn = {2538-3906}, doi = {10.22059/jesphys.2020.300651.1007208}, abstract = {This study aims to investigate the performance of the Weather Research and Forecasting (WRF) model for rainfall forecasts in the South Central climate region of Vietnam. The investigation was carried out by analyzing the accuracy of the model outputs at station sites and the spatial structure of rain events for different rainfall thresholds over the whole year and in the flood and dry seasons. The traditional (standard) method was utilized to analyze the accuracy of the WRF model in predicting precipitation point-by-point, whereas the Contiguous Rain Area (CRA) method was applied to analyze the spatial structure of rain events. The results showed that rainfall forecasts by the WRF model for the South Central region had certain limitations because the model scores and measured error criteria were not close to their perfect values. The proportion of hit forecasts decreased from 30 % with the traditional verification method to 10% with the spatial structure verification method. The pattern error was a main contributor to the total error at 53%, followed by the intensity error at 34%. The location error accounted for the lowest percentage contribution to the total error, at only 13%. The performance of this model could lead to substantial errors in weather and streamflow predictions for the south-central region and may lead to a lack of forecast effectiveness for mitigating the damage from natural disasters. Thus, improvements in the performance of the Numerical Weather Prediction (NWP) model for the studied area are necessary.}, keywords = {QPF,WRF model,traditional and spatial structure verification,South Central,Vietnam}, title_fa = {Verification of Rainfall Forecasts for the South Central Climate Region of Vietnam}, abstract_fa = {This study aims to investigate the performance of the Weather Research and Forecasting (WRF) model for rainfall forecasts in the South Central climate region of Vietnam. The investigation was carried out by analyzing the accuracy of the model outputs at station sites and the spatial structure of rain events for different rainfall thresholds over the whole year and in the flood and dry seasons. The traditional (standard) method was utilized to analyze the accuracy of the WRF model in predicting precipitation point-by-point, whereas the Contiguous Rain Area (CRA) method was applied to analyze the spatial structure of rain events. The results showed that rainfall forecasts by the WRF model for the South Central region had certain limitations because the model scores and measured error criteria were not close to their perfect values. The proportion of hit forecasts decreased from 30 % with the traditional verification method to 10% with the spatial structure verification method. The pattern error was a main contributor to the total error at 53%, followed by the intensity error at 34%. The location error accounted for the lowest percentage contribution to the total error, at only 13%. The performance of this model could lead to substantial errors in weather and streamflow predictions for the south-central region and may lead to a lack of forecast effectiveness for mitigating the damage from natural disasters. Thus, improvements in the performance of the Numerical Weather Prediction (NWP) model for the studied area are necessary.}, keywords_fa = {QPF,WRF model,traditional and spatial structure verification,South Central,Vietnam}, url = {https://jesphys.ut.ac.ir/article_76436.html}, eprint = {https://jesphys.ut.ac.ir/article_76436_752013c4919aed8a6255f5a926e88f62.pdf} } @article { author = {Thang, Vu Van and Thanh, Cong and Tuan, Bui Minh}, title = {Multiple-Scale Interactions during an Extreme Rainfall Event over Southern Vietnam}, journal = {Journal of the Earth and Space Physics}, volume = {46}, number = {4}, pages = {259-271}, year = {2021}, publisher = {Institute of Geophysics, University of Tehran}, issn = {2538-371X}, eissn = {2538-3906}, doi = {10.22059/jesphys.2021.303443.1007215}, abstract = {In August 2019, southern Vietnam suffered its worst flooding to date, which was also associated with record-breaking extreme rainfall. This study seeks to explain how this extreme rainfall event can be distinguished from normal rainfall events. The bandpass filter applied to the observed rainfall shows that there were significant intensifications of 3–10-day variation and 11–60-day oscillations during the event. While the latter is characterized by the intensification of westerly flows from the Bay of Bengal to southern Vietnam, the former is related to more complex movements of a series of synoptic-scale disturbances over the western North Pacific. The notion of multiple-scale interactions, inducing the extreme rainfall event is supported by diagnosing the anomalous columnwise moisture divergence over the southern plain region of Vietnam. It is demonstrated that the anomalous convergences associated with the long-term mean moisture and the synoptic-scale moisture transported by the long-term mean flow are the most important factors for formation of the extreme rainfall event.}, keywords = {synoptic wave-train,large-scale circulation,Intraseasonal oscillation,Moisture convergence,extreme rainfall}, title_fa = {Multiple-Scale Interactions during an Extreme Rainfall Event over Southern Vietnam}, abstract_fa = {In August 2019, southern Vietnam suffered its worst flooding to date, which was also associated with record-breaking extreme rainfall. This study seeks to explain how this extreme rainfall event can be distinguished from normal rainfall events. The bandpass filter applied to the observed rainfall shows that there were significant intensifications of 3–10-day variation and 11–60-day oscillations during the event. While the latter is characterized by the intensification of westerly flows from the Bay of Bengal to southern Vietnam, the former is related to more complex movements of a series of synoptic-scale disturbances over the western North Pacific. The notion of multiple-scale interactions, inducing the extreme rainfall event is supported by diagnosing the anomalous columnwise moisture divergence over the southern plain region of Vietnam. It is demonstrated that the anomalous convergences associated with the long-term mean moisture and the synoptic-scale moisture transported by the long-term mean flow are the most important factors for formation of the extreme rainfall event.}, keywords_fa = {synoptic wave-train,large-scale circulation,Intraseasonal oscillation,Moisture convergence,extreme rainfall}, url = {https://jesphys.ut.ac.ir/article_79565.html}, eprint = {https://jesphys.ut.ac.ir/article_79565_3630bdb83f02ab643c001f08c9e9c1df.pdf} }