Acoustical imaging of the nearshore seafloor depositions and deformations,a key study for Western Istanbul,Türkiye

To protect the sustainability of the benefits from seas and near coastal areas,which have under the effect of the very complex hydrodynamic conditions and intensive human activities,without disrupting the balance of nature,it is necessary to image the status of the seafloor features.Therefore,this study presents the deformations,depositional conditions,underwater constructions,and the other non-natural impacts on the seafloor of the nearshore area at western Istanbul(between Küçükçekmece and Büyükçekmece lagoons)where it intensely used by the citizens.The results of the study may provide some guidance for understanding the impacts and risk factors of uses that are or will be conducted in coastal and/or near-coastal areas.Construction planning for civil coastal structures and areas should be done in great harmony with nature,minimizing negative environmental impacts.Although sediment distribution in the area is generally quite complex,the current state of the region,wave action,hydrodynamic conditions,the amount of material transported from the land,and bathymetry are important influencing factors.The seafloor has been damaged primarily by anchor deformation and associated bottom scanning,as well as disturbing trawl tracks.The seafloor was observed as partially shallowing near the constructions(such as natural gas pipelines,fishermen’s shelter,and port piles)of coastal areas and associated with sand deposits.Therefore,scanning the seafloor using side-scan sonar may provide valuable frequency data to prevent future disruptions.

High-resolution seismicity imaging and early aftershock migration of the 2023 Kahramanmara?(SE Türkiye)M_W7.9&7.8 earthquake doublet

We build a high-resolution early aftershock catalog for the 2023 SE Türkiye seismic sequence with PALM,a seamless workflow that sequentially performs phase picking,association,location,and matched filter for continuous data.The catalog contains 29,519 well-located events in the two mainshocks rupture region during 2023-02-01–2023-02-28,which significantly improves the detection completeness and relocation precision compared to the public routine catalog.Employing the new PALM catalog,we analyze the structure of the seismogenic fault system.We find that the Eastern Anatolian Fault(EAF)that generated the first M_(W)7.9 mainshock is overall near-vertical,whereas complexities are revealed in a small-scale,such as subparallel subfaults,unmapped branches,and stepovers.The seismicity on EAF is shallow(<15 km)and concentrated in depth distribution,indicating a clear lock-creep transition.In contrast,the SürgüFault(SF)that is responsible for the second M_(W)7.8 mainshock is shovel-shaped for the nucleation segment and has overall low dip angles(~40°–80°).Aftershocks on the SF distribute in a broad range of depth,extending down to~35 km.We also analyze the temporal behavior of seismicity,discovering no immediate foreshocks within~5 days preceding the first mainshock,and no seismic activity on the SF before the second mainshock.

Rapid source inversions of the 2023 SE Türkiye earthquakes with teleseismic and strong-motion data

We conducted rapid inversions of rupture process for the 2023 earthquake doublet occurred in SE Türkiye,the first with a magnitude of M_(W)7.8 and the second with a magnitude of M_(W)7.6,using teleseismic and strong-motion data.The teleseismic rupture models of the both events were obtained approximately 88 and 55 minutes after their occurrences,respectively.The rupture models indicated that the first event was an asymmetric bilateral event with ruptures mainly propagating to the northeast,while the second one was a unilateral event with ruptures propagating to the west.This information could be useful in locating the meizoseismal areas.Compared with teleseismic models,the strong-motion models showed relatively higher resolution.A noticeable difference was found for the M_(W)7.6 earthquake,for which the strong-motion models shows a bilateral event,rather than a unilateral event,but the dominant rupture direction is still westward.Nevertheless,all strong-motion models are consistent with the teleseismic models in terms of magnitudes,durations,and dominant rupture directions.This suggests that both teleseismic and strong-motion data can be used for fast determination of major source characteristics.In contrast,the strong-motion data would be preferable in future emergency responses since they are recorded earlier and have a better resolution ability on the source ruptures.

Shear wave velocity model using HVSR inversion beneath Bandar Lampung City

The horizontal-to-vertical spectral ratio(HVSR)method has been used to characterize site-effect parameters that are indispensable in seismic hazard and risk-reduction studies in urban areas and rapid land-use planning.This method is widely used because it is the cheapest and simplest geophysical method for the acquisition and processing stages.In subsequent developments,the HVSR method has been widely used to determine elastic rock parameters,particularly shear wave velocity(v_(S)),through the HVSR curve inversion process.Furthermore,the v_(S)structural model can be used to delineate the presence of complex geological structures,particularly faults and sedimentary basins.Bandar Lampung is a city in Lampung Province with many fault structures and groundwater basins to the south.There are 83 HVSR measurement points around Bandar Lampung for delineating the presence of fault structures and groundwater basins.We produced the HVSR curve from the measurement results and then performed an inversion process using the particle swarm optimization algorithm to obtain v_(S)for the depth profile.Subsequently,from this profile,we produced a two-dimensional(2D)lateral and vertical model.The mean v_(S)value was calculated from all the measurement points,and we found stiff soil layers reaching depths of approximately 5 m,with a value of v_(S)<330 m/s.A bedrock layer with a velocity exceeding 1250 m/s was visible at a depth of 100 m.Based on the 2D model,the v_(S)structure shows that the city of Bandar Lampung is divided into two zones,with a NW-SE boundary.The north-middle-eastern part of the city consists of harder rocks.This harder rock is characterized by extremely high v_(S)values,starting from a depth of 50 m.In contrast,the south-middle-west exhibits a low-moderate v_(S)anomaly associated with groundwater basins SW of the city.From the 2D v_(S)structural model,fault structures can be found along the city,characterized by a contrast of v_(S)values from low to medium and from medium to high.

Evaluation of deep learning algorithms for national scale landslide susceptibility mapping of Iran

The identification of landslide-prone areas is an essential step in landslide hazard assessment and mitigation of landslide-related losses.In this study,we applied two novel deep learning algorithms,the recurrent neural network(RNN)and convolutional neural network(CNN),for national-scale landslide susceptibility mapping of Iran.We prepared a dataset comprising 4069 historical landslide locations and 11 conditioning factors(altitude,slope degree,profile curvature,distance to river,aspect,plan curvature,distance to road,distance to fault,rainfall,geology and land-sue)to construct a geospatial database and divided the data into the training and the testing dataset.We then developed RNN and CNN algorithms to generate landslide susceptibility maps of Iran using the training dataset.We calculated the receiver operating characteristic(ROC)curve and used the area under the curve(AUC)for the quantitative evaluation of the landslide susceptibility maps using the testing dataset.Better performance in both the training and testing phases was provided by the RNN algorithm(AUC=0.88)than by the CNN algorithm(AUC=0.85).Finally,we calculated areas of susceptibility for each province and found that 6%and 14%of the land area of Iran is very highly and highly susceptible to future landslide events,respectively,with the highest susceptibility in Chaharmahal and Bakhtiari Province(33.8%).About 31%of cities of Iran are located in areas with high and very high landslide susceptibility.The results of the present study will be useful for the development of landslide hazard mitigation strategies.

Soil characterization of Tinaztepe region(Izmir/Turkey) using surface wave methods and nakamura(HVSR) technique

To determine the shear wave velocity structure and predominant period features of Tmaztepe in izmir, Turkey, where new building sites have been planned, active-passive surface wave methods and single-station microtremor measurements are used, as well as surface acquisition techniques, including the multichannel analysis of surface waves （MASW）, refraction microtremor （ReMi）, and the spatial autocorrelation method （SPAC）, to pinpoint shallow and deep shear wave velocity. For engineering bedrock （V 〉 760 m/s） conditions at a depth of 30 m, an average seismic shear wave velocity in the upper 30 m of soil （AVs30） is not only accepted as an important parameter for defining ground behavior during earthquakes, but a primary parameter in the geotechnical analysis for areas to be classified by V30 according to the National Earthquake Hazards Reduction Program （NEHRP）. It is also determined that Z1.0, which represents a depth to V = 1000 m/s, is used for ground motion prediction and changed from 0 to 54 m. The sediment-engineering bedrock structure for Tmaztepe that was obtained shows engineering bedrock no deeper than 30 m. When compared, the depth of engineering bedrock and dominant period map and geology are generally compatible.

Availability of seismic vulnerability index(K_g) in the assessment of building damage in Van, Eastern Turkey

The seismic vulnerability index(Kg) is a parameter that depends on the dynamic properties of soil. With this parameter, it is possible to evaluate the vulnerability of a point-based site under strong ground motion. Since it is related to the natural vibration period and amplification factor, the parameter can be calculated for both soil and structure. In this study, HVSR microtremor measurements are recorded at more than 200 points in the Van region to generate a seismic vulnerability index map. After generating the map, it is determined that the hazard potential and seismic vulnerability index is high at the sites close to Van Lake and at the densely populated city center. Damage information of the buildings investigated after the 2011 Van earthquakes(Mw = 7.1) are placed on the seismic vulnerability index map and it is realized that there may be a correlation between the damage and the seismic vulnerability index. There is a high correlation, approximately 80 percent, between the damage rate map based on the damaged building data and the K_g values. In addition, vulnerability indexes of buildings are calculated and the effect of local soil conditions and building properties on the damage levels are determined. From the results of this study and the site observations after the 2011 Van earthquakes, it is found that structural damage is not only structure-dependent but is also related to the dynamic behavior of soil layers and local soil conditions.

Spatial prediction of landslide susceptibility in western Serbia using hybrid support vector regression(SVR)with GWO,BAT and COA algorithms

In this study,we developed multiple hybrid machine-learning models to address parameter optimization limitations and enhance the spatial prediction of landslide susceptibility models.We created a geographic information system database,and our analysis results were used to prepare a landslide inventory map containing 359 landslide events identified from Google Earth,aerial photographs,and other validated sources.A support vector regression(SVR)machine-learning model was used to divide the landslide inventory into training(70%)and testing(30%)datasets.The landslide susceptibility map was produced using 14 causative factors.We applied the established gray wolf optimization(GWO)algorithm,bat algorithm(BA),and cuckoo optimization algorithm(COA)to fine-tune the parameters of the SVR model to improve its predictive accuracy.The resultant hybrid models,SVR-GWO,SVR-BA,and SVR-COA,were validated in terms of the area under curve(AUC)and root mean square error(RMSE).The AUC values for the SVR-GWO(0.733),SVR-BA(0.724),and SVR-COA(0.738)models indicate their good prediction rates for landslide susceptibility modeling.SVR-COA had the greatest accuracy,with an RMSE of 0.21687,and SVR-BA had the least accuracy,with an RMSE of 0.23046.The three optimized hybrid models outperformed the SVR model(AUC=0.704,RMSE=0.26689),confirming the ability of metaheuristic algorithms to improve model performance.

Modelling of piping collapses and gully headcut landforms: Evaluating topographic variables from different types of DEM

The geomorphic studies are extremely dependent on the quality and spatial resolution of digital elevation model(DEM)data.The unique terrain characteristics of a particular landscape are derived from DEM,which are responsible for initiation and development of ephemeral gullies.As the topographic features of an area significantly influences on the erosive power of the water flow,it is an important task the extraction of terrain features from DEM to properly research gully erosion.Alongside,topography is highly correlated with other geo-environmental factors i.e.geology,climate,soil types,vegetation density and floristic composition,runoff generation,which ultimately influences on gully occurrences.Therefore,terrain morphometric attributes derived from DEM data are used in spatial prediction of gully erosion susceptibility(GES)mapping.In this study,remote sensing-Geographic information system(GIS)techniques coupled with machine learning(ML)methods has been used for GES mapping in the parts of Semnan province,Iran.Current research focuses on the comparison of predicted GES result by using three types of DEM i.e.Advanced Land Observation satellite(ALOS),ALOS World 3D-30 m(AW3D30)and Advanced Space borne Thermal Emission and Reflection Radiometer(ASTER)in different resolutions.For further progress of our research work,here we have used thirteen suitable geo-environmental gully erosion conditioning factors(GECFs)based on the multi-collinearity analysis.ML methods of conditional inference forests(Cforest),Cubist model and Elastic net model have been chosen for modelling GES accordingly.Variable’s importance of GECFs was measured through sensitivity analysis and result show that elevation is the most important factor for occurrences of gullies in the three aforementioned ML methods(Cforest=21.4,Cubist=19.65 and Elastic net=17.08),followed by lithology and slope.Validation of the model’s result was performed through area under curve(AUC)and other statistical indices.The validation result of AUC has shown that Cforest is the most appropriate model for predicting the GES assessment in three different DEMs(AUC value of Cforest in ALOS DEM is 0.994,AW3D30 DEM is 0.989 and ASTER DEM is 0.982)used in this study,followed by elastic net and cubist model.The output result of GES maps will be used by decision-makers for sustainable development of degraded land in this study area.

Deep learning neural networks for spatially explicit prediction of flash flood probability

Flood probability maps are essential for a range of applications,including land use planning and developing mitigation strategies and early warning systems.This study describes the potential application of two architectures of deep learning neural networks,namely convolutional neural networks(CNN)and recurrent neural networks(RNN),for spatially explicit prediction and mapping of flash flood probability.To develop and validate the predictive models,a geospatial database that contained records for the historical flood events and geo-environmental characteristics of the Golestan Province in northern Iran was constructed.The step-wise weight assessment ratio analysis(SWARA)was employed to investigate the spatial interplay between floods and different influencing factors.The CNN and RNN models were trained using the SWARA weights and validated using the receiver operating characteristics technique.The results showed that the CNN model(AUC=0.832,RMSE=0.144)performed slightly better than the RNN model(AUC=0.814,RMSE=0.181)in predicting future floods.Further,these models demonstrated an improved prediction of floods compared to previous studies that used different models in the same study area.This study showed that the spatially explicit deep learning neural network models are successful in capturing the heterogeneity of spatial patterns of flood probability in the Golestan Province,and the resulting probability maps can be used for the development of mitigation plans in response to the future floods.The general policy implication of our study suggests that design,implementation,and verification of flood early warning systems should be directed to approximately 40%of the land area characterized by high and very susceptibility to flooding.

Comparisons of the suture zones along a geotraverse from the Scythian Platform to the Arabian Platform

The area from the Greater Caucasus to the southeast Turkey is characteri：;.ed and shaped by several major continental blocks. These are Scythian Platform, Pontian-Transcaucasu.,; Continent-Arc System （PTCAS）, the Anatolian-lranian and the Arabian Platforms. The aim of this paper is to define these continental blocks and describe and also compare their boundary relationships along the suture zones. The Scythian Platform displays the evidence of the Hercynian and Alpine orogens. This platform is separated from the PTCAS by the Greater Caucasus Suture Zone. The incipient collision began along this suture zone before middle-late Carboniferous whereas the final collision occurred before Oligocene. The PTCAS can be divided into four structural units： （1） the Georgian Block - northern part of the Pontian-Transcaucasian island-arc, （2） the southern and eastern Black Sea Coast-Adjara-Trialeti Unit, （3） the Artvin-Bolnisi Unit, comprising the northern part of the southern Transcaucasus, and （4） the Imbricated Bayburt-Garabagh Unit. The PTCAS could be separated from the Anatolian Iranian Platform by the North Anatolian-Lesser Caucasus Suture （NALCS） zone. The initial collision was developed in this suture zone during Senonian-early Eocene and final collision before middle Eocene or Oligocene-Miocene. The Anatolian-lranian Platform （AIP） is made up of the Tauride Platform and its metamorphic equivalents together with Iranian Platform. It could be separated from the Arabian Platform by the Southeastern Anatolian Suture （SEAS） zone. The collision ended before late Miocene along this suture zone. The southernmost continental block of the geotraverse is the Arabian Platform, which constitutes the northern part of the Arabian-African Plate. This platform includes a sequence from the Precambrian felsic volcanic and clastic rocks to the Campanian-early Maastrichtian fiyschoidal clastics. All the suture zones include MORB and SSZ-types ophiolites in different ages. However, the ages of the suture zones and the crustal thicknesses along the suture zones are different, as the age becoming younger, the thickness decreasing from north to south. The emplacements of the ophiolites have similar pattern of a flower structure, reflecting both the north- and south-dipping overthrusts along the suture zones.

Implementation of a Petrographical and Petrophysical Workflow Protocol for Studying the Impact of Heterogeneity on the Rock Typing and Reservoir Quality of Reefal Limestone:A Case Study on the Nullipore Carbonates in the Gulf of Suez

This study focuses on the heterogeneity of the middle Miocene syn-rift Belayim nullipore(reefal)marine sequences in the Gulf of Suez and its impacts on reservoir quality.The sequences consist of coralline algal reef limestones with a highly complex dual-porosity system of primary and secondary porosities of widely varying percentages.To achieve a precise mathematical modeling of these reservoir sequences,a workflow protocol was applied to separate these sequences into a number of hydraulic flow units(HFUs)and reservoir rock types(RRTs).This has been achieved by conducting a conventional core analysis on the nullipore marine sequence.To illustrate the heterogeneity of the nullipore reservoir,the Dykstra-Parsons coefficient(V)has been estimated(V=0.91),indicating an extremely heterogeneous reservoir.A slight to high anisotropy(λ_(k))has been assigned for the studied nullipore sequences.A stratigraphic modified Lorenz plot(SMLP)was applied to define the optimum number of HFUs and barriers/baffles in each of the studied wells.Integrating the permeability-porosity,reservoir quality index-normalized porosity index(RQI-NPI)and the RQI-flow zone indicator(RQIFZI)plots,the discrete rock types(DRT)and the R35 techniques enable the discrimination of the reservoir sequences into 4 RRTs/HFUs.The RRT4 packstone samples are characterized by the best reservoir properties(moderate permeability anisotropy,with a good-to-fair reservoir quality index),whereas the RRT1 mudstone samples have the lowest flow and storage capacities,as well as the tightest reservoir quality.

Statistical analysis of geomagnetic field variations during the partial solar eclipse on 2011 January 4 in Turkey

Some geophysical parameters, such as those related to gravitation and the geomagnetic field, could change during solar eclipses. In order to observe geomagnetic fluctuations, geomagnetic measurements were carded out in a limited time frame during the partial solar eclipse that occurred on 2011 January 4 and was observed in Canakkale and Ankara, Turkey. Additionally, records of the geomagnetic field spanning 24 hours, obtained from another observatory （in Iznik, Turkey）, were also analyzed to check for any peculiar variations. In the data processing stage, a polynomial fit, following the application of a running average routine, was applied to the geomagnetic field data sets. Geomagnetic field data sets indicated there was a characteristic decrease at the beginning of the solar eclipse and this decrease can be well-correlated with previous geomagnetic field measurements that were taken during the total solar eclipse that was observed in Turkey on 2006 March 29. The behavior of the geomagnetic field is also consistent with previous observations in the literature. As a result of these analyses, it can be suggested that eclipses can cause a shielding effect on the geomagnetic field of the Earth.

Ground Penetrating Radar Survey of Dam Structures of Kazakhstan on example of Aktobe and Karatomar Water Storage Basins

Ground penetrating radar surveys of technical condition of Karatomar and Aktobe water storage basins on the river Tobol are shown. In this article we have shown that dams have problems with cavities and identified longitudinal dimensions of anomalous zones of decompression.

Geoelectrical survey over perched aquifers in the northern part of Upper Sakarya River Basin,Türkiye

In this study,a groundwater exploration survey was conducted using the DC Resistivity(DCR)method in a hydrogeological setting containing a perched aquifer.DCR data were gathered and an electrical tomography section was recovered using conventional four-electrode instruments with a Schlumberger array and a two-dimensional(2D)inversion scheme.The proposed scheme was tested over a synthetic threedimensional(3D)subsurface model before deploying it in a field situation.The proposed method indicated that gathering data with simple four-electrode instruments at stations along a line and 2D inversion of datasets at multiple stations can recover depth intervals of the studied aquifer in the hydrogeological setting even if it has a 3D structure.In this study,2D inversion of parallel profiles formed a pseudo-3D volume of the subsurface resistivity structures and mapped out multiple resistive(>25 ohm·m)bodies at shallow(between 50-100 m)and deep sections(>150 m).In general,the proposed method is convenient to encounter geological units that have limited vertical and spatial extensions in any direction and presents resistivity contrast from groundwater-bearing geologic materials.

Synthesis and Characterization of Lithium Manganese Oxide with Different Ratio of Mole on Lithium Recovery Process from Ge-othermal Fluid of Lumpur Sidoarjo

Geothermal fluid of Lumpur Sidoarjo (Lusi) with lithium content as high as 5.81 mg/liter has a great potential as the source of lithium. Lithium recovery from geothermal liquid of Lusi is firstly investigated by adsorption methods with Lithium Manganese Oxide (LMO) as absorbent. LMO is considered as a promising candidate of adsorbent material due to non-toxic and low cost production. LMOs with different ratio of mole are prepared by solid state reactions method at temperature 500?C for 5 hrs. XRD peaks of pre- and post-acid treatment LMO 1, 0.8 and 0.5 show a stable spinel crystal structure while LMO 2 has monoclinic structure. The highest lithium adsorption capability is obtained by LMO 1 with 6.6 mg/g.

Geothermal Modeling of Kizilcahamam-Çamlidere Area Using 3D Imaging Technique

Geothermal energy has long been used for various purposes. Geothermal energy was used for bath and health care since ancient times. With the increase in the population, it is being used today for industrial and energy production. This paper examines the geothermal structure of Northern Ankara-NAF (Northern Anatolian Fault Zone) regions to reveal its tectonic features, and the relationships of the region with earthquakes. The 3D geological features of the area are investigated using the resistivity data and tectonic and the quake values. The resistivity data obtained by MTA (Mineral Research and Exploration of Turkey) are reached by geothermal measurements in the area in 1999. In Kizilcahamam town of Ankara Province, geothermal exploration was performed using geoelectrical methods. During the study, electrode measurement scheme was planned according to the Schlumberger expansion. AB/2 spacing is between 1900 m. and 2000 m. Data obtained from geoelectrical methods were processed to delineate the subsurface structure. Also, lithological components were determined and the previously known fault structure was shown. Since the 3D works have been more feasible recently, the received results are transferred into the 3D imaging platform taking advantage of 2D electrical resistivity maps. The low resistivity values obtained in 3D imaging are gathered that the temperature values of the area are high. On the other hand, as the pull-apart between NAF and Kirikkale fault trending NE-SW of the region is in form of basin, the study area is observed to own opening tectonics. Thus, when the seismic activity is considered, it reveals important findings about the presence of geothermal fields in the local.

Assessment and adjustment of sea surface salinity products from Aquarius in the southeast Indian Ocean based on in situ measurement and My Ocean modeled data

The in situ sea surface salinity（SSS） measurements from a scientific cruise to the western zone of the southeast Indian Ocean covering 30°-60°S, 80°-120°E are used to assess the SSS retrieved from Aquarius（Aquarius SSS）.Wind speed and sea surface temperature（SST） affect the SSS estimates based on passive microwave radiation within the mid- to low-latitude southeast Indian Ocean. The relationships among the in situ, Aquarius SSS and wind-SST corrections are used to adjust the Aquarius SSS. The adjusted Aquarius SSS are compared with the SSS data from My Ocean model. Results show that：（1） Before adjustment： compared with My Ocean SSS, the Aquarius SSS in most of the sea areas is higher; but lower in the low-temperature sea areas located at the south of 55°S and west of 98°E. The Aquarius SSS is generally higher by 0.42 on average for the southeast Indian Ocean.（2） After adjustment： the adjustment greatly counteracts the impact of high wind speeds and improves the overall accuracy of the retrieved salinity（the mean absolute error of the Zonal mean is improved by 0.06, and the mean error is-0.05 compared with My Ocean SSS）. Near the latitude 42°S, the adjusted SSS is well consistent with the My Ocean and the difference is approximately 0.004.

Assessment of Vertical Magnetic Gradient Data of Tuzla Fault Using Boundary Analysis and 3-D Inversion Techniques

The magnetic prospection is one of the most useful methods to determine buried geological structures such as shallow fracture zones. The investigation of vertical and horizontal gradient and total magnetic field variations over geological structures, which have been used for many years, may reveal their locations, geometries and physical characteristics. In this study, a proposed iterative 3-D rectangular prismatic model inversion algorithm was modified to interpret vertical magnetic gradient data defining the boundaries and the physical parameters of the anomalous structure. Vertical magnetic gradient measurements were carried out at the Tuzla fault, an active fault system located along NE-SW direction in Izmir (Turkey). Boundary analysis studies were applied to data in order to obtain boundaries of the structures, afterwards the inversion process was carried out considering these geometries. As a result, location, direction and other physical and geometrical features of the fault are achieved.

Calculation of Constitutive Parameters from Electric and Magnetic Field Measurements in an Anisotropic Medium with a Triaxial Instrument

A hypothetical electric and magnetic induction tensor is considered in an anisotropic medium. The sources are magnetic dipoles. In such a medium, constitute parameters can be calculated by combining electric and magnetic field measurements. Constitutive parameters are not a scalar in this case. They are tensors, so parameters have at least both horizontal and vertical components in a uniaxial medium. These calculated parameters from the field measurement are horizontal and vertical conductivity, permittivity, and magnetic permeability. Operating frequency range is also quite large. It is up to 4 GHz. A hypothetical instrument should measure gradient fields both electric and magnetic types as well.