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The focus on exploiting natural gas resources has been increased in the recent years since it was characterized as the transitional fuel to a net-zero era. Consequently, a reevaluation of the gas resources under a new perspective seems to be logical. Within this context, the gas-bearing Miocene sediments of the Messara basin in Crete (Greece) are discussed in this paper. The gas shows have been first reported during the 1990’s, without being thoroughly evaluated. This paper presents the interpretation of eight legacy onshore seismic reflection lines, which led to the construction of the 3D subsurface structural model of the Neogene Messara basin. The seismic data reveals the basin depocenter which accommodates approximately 1500 m of the Miocene sediments. The relationship of the Miocene deposits with the existence of shallow gas is also examined and discussed. New organic geochemical results combined with the published geochemical data are used to discuss the gas generation potential of the Miocene sediments. The porosity and permeability measurements on surface samples are also presented to describe the reservoir characteristics. The integration of the data mentioned above suggests that the Miocene sediments of the Messara basin comprise intervals with adequate organic matter to generate the observed gasses and good reservoir sandstones to accumulate the generated gas. The gas might have been trapped by lateral and vertical facies changes which provide efficient stratigraphic trapping mechanisms.

Fluid imaging technologies are used in a wide range of E&P applications. Among geophysical methods, electromagnetics (EM) determines subsurface resistivities and thus responds to fluid changes. On the path to zero carbon footprint, the most significant potential for EM lies in monitoring geothermal, carbon capture, utilization and storage (CCUS), and enhancing oil recovery (EOR). To optimize reservoir fluid monitoring, we calibrate surface measurements to well logs resulting in a 3D anisotropic model consistent with borehole data. This is done before and after depletion or injection to estimate a time-lapse reservoir response. As part of a carbon capture and storage project, we carried out baseline measurements and validated the surface EM data to the 3D anisotropic borehole model. The monitoring workflow for this project can easily be adapted for other applications to support the energy transition. From this, we learned that measurement accuracy requirements higher than 1 % because we are often imaging small anomalies. While there are always limits in acquisition set by industrial noise, we derived two ways of increasing the anomaly. One is by using, similar to a borehole focused logs, focusing methods in the acquisition setup. This is still subject to measurement accuracy limitations and limited to electric fields only. Another way is to add borehole sensors that increase the sensitivity by around a factor of 10. While shallow (around 50 m) is sufficient, they can be extended to deeper borehole sensors, bringing the measurements close to the anomaly and is thus the preferred approach. This, in combination with calibration back to the 3D anisotropic borehole log allows you to certify the data for its information content. This will give you quantifiable ways to derive risk values and significantly reduce acquisition and monitoring operations cost.

Groundwater is considered as the primary source of drinking water in many countries around the world. For maintaining resource sustainability, clean and safe groundwater is a priority for water authorities worldwide. Unfortunately, groundwater resources are susceptible to various types of pollution, with arsenic (As) being a major pollutant in certain areas due to natural or anthropogenic activities. Due to its adverse health effects, As, a class-1 carcinogen, has been a topic of intense research. The technical difficulty and high cost incurred by conventional treatment systems for As removal have led many researchers to work on developing efficient, eco-friendly, and cost-effective technologies for the treatment of groundwater sources. Biochar has been widely used as an adsorbent for the decontamination of groundwater. High As removal rates have been achieved following metal (Fe, Zn, Mn) impregnation and magnetic modification to biochar. Despite numerous researches on biochar for As removal, very limited efforts have been made for upscaling to a convenient treatment system. Thus, this review highlights key findings of previous studies required for pragmatic applications. Following up with future trends, an overview is given on real-time monitoring techniques that can be combined with biochar for evaluating adsorption studies. Furthermore, research opportunities that exist in biochar adsorption studies have also been identified. This technical review is aimed for scientists, scholars and researchers as a supplementary guide for understanding As decontamination processes, highlighting the role of biochar as an adsorbent and conceptualizing the prospects of integration of real-time monitoring techniques.

Geophysical inversion is usually carried out to quantitatively analyze the earth model and estimate its physical properties. Successful delineation of these properties such as layer boundaries, or other near-surface structures are crucial to understand the near-surface inhomogeneity. In this study, we focus on the use of joint inversion of seismic refraction and geoelectrical resistivity datasets using local and global optimization methods. The idea is to integrate the two optimization techniques to minimize the challenges faced by each algorithm when applied alone. This hybrid algorithm (local and global) is applied on synthetic data representing simple resistivity and velocity models. About 70% of the anomalies in both seismic and DC resistivity methods were reconstructed in terms of amplitude and geometry using the local optimization algorithm, while the global optimization algorithm shows improved results as it reconstructed about 80% of the amplitude and geometry of the anomalies in both geophysical methods. The result of the synthetic application shows that the hybrid algorithm provides promising outputs in terms of resolution, geometry and amplitude of the anomalies, and computation run time.

The aim of this paper is the creation of an integrated and free-access web platform for parcel irrigation water management on a large spatial scale (Water District of Crete, in Greece) in order to: a) accurately determine the irrigation needs of the main crops for Crete such as olives, citrus, avocados and vineyards, b) design strategies, for optimal adaptation of the agricultural sector in the context of climate change, and c) incorporate the dynamic integration of the above information through the creation of a digital platform. In the proposed decision-making system, essential factors are taken into account, such as real-time meteorological data, information about the type and spatial distribution of the agricultural parcels in Crete, algorithms for calculation crop evapotranspiration per development stage and age of the crops, satellite remote sensing techniques in combination with field surveys to depict accurate soil texture map for the whole island of Crete as well as sustainable cultivation practices for saving water per crop and parcel geomorphology. Based on the proposed decision-making system, users will have the opportunity in any specific location/farm in Crete to know the irrigation needs of the crops in real-time and obtain information about proper climate-water adaptation practices. The main novelty points of the proposed platform include the derivation of parcel-level soil texture data from Sentinel-2 satellite imagery and field samples, the comprehensiveness of the irrigation management information, the relatively low data requirements and the application interface simplicity provided to the end-user.

In this work, we explore the use of biochar as a remediation agent, and the sensitivity of the spectral‐induced polarization method as a remediation monitoring aid. Biochar amended columns were fully saturated with industrial wastewater (olive oil mill waste) with very high concentration of phenols (∼2485 mg/L) and other substances. The biochar‐amended columns achieved very high removal rates of phenols compared to the control (sand only). Geophysical monitoring over the duration of the experiment (10 days) showed changes in the spectral‐induced polarization signal (imaginary conductivity) consistent with phenol removal as confirmed by geochemical monitoring. This experiment confirmed the utility of biochar as a remediation agent. Furthermore, spectral‐induced polarization can serve as long‐term, high resolution, monitoring aid in organic contaminant degradation processes.

The study area is a part of Dammam Dome that is situated at King Fahd University of Petroleum & Minerals (KFUPM) campus, Dhahran, Kingdom of Saudi Arabia. The gravity survey was conducted as a pilot case study to explore part of Dammam Dome in greater detail. Gravity data were collected solely during night hours due to low noise levels. A significant part of the survey was conducted during the summer holiday period, , when there was no student are on campus. A total of 235 gravity measurements were made using a Scintrex CG5 gravitometer, while a Trimble R10+ differential GPS (DGPS) was used to measure the stations’ location and elevation with the highest accuracy. All gravity data were reduced using several algorithms, and their outcomes were cross-compared. The Complete Bouguer anomaly map for the campus was then generated. Several enhancement filters including edged detection and shallow to deeper source separation were applied. Data were inverted, and 2.5D and 3D models were created to image the subsurface conditions. The main purpose of this study is to better understand the subsurface geology, tectonic settings of the Dammam Dome by applying the high-resolution gravity method before carrying out any comprehensive geophysical (seismic) 3D survey.

Summarization: This study develops a comprehensive seismic risk model for the city of Chania, in Greece, which is located ina highly seismic-prone region due to the occurrenceof moderate to large earthquakes because of the nearby major subduction zone between African and Eurasian tectonic plates. The main aim is to reduce the seismic risk for the study area by incorporating the spatial distribution of the near-surface shear wave velocity model and the soil classification, along with all possible seismic sources, taking into account historical events. The study incorporates and correlates various ground motion scenarios and geological fault zones as well as information on existing buildings to develop a seismic risk model using QuakeIST software, and then the seismic hazard and a realistic prediction of resulting future adverse effects are assessed. The developed model can assist the municipal authorities of Chania to be prepared for potential seismic events, as well as city planners and decisionmakers, who can use the model as an effective decision-making tool to identify the seismic vulnerability of the city buildings and infrastructure. Thus, this study enables the implementation of an appropriate and viable earthquake-related hazards strategy to mitigate damage and losses in future earthquakes. Παρουσιάστηκε στο: Applied Sciences

Interest in impact craters on the earth's surface has increased worldwide and is being investigated by using remote sensing, geological, boreholes, geophysical, and laboratory measurements. These measurements are used to build dynamic models to study crater formation. In this work, the near‐crater sediments at the young Wabar crater field in Saudi Arabia have been investigated using magnetic, transient electromagnetic (TEM), seismic, and ground‐penetrating radar (GPR) methods. The main objectives of this research were to (a) explore the possibility of any remnant major pieces of the meteorite, (b) investigate the meteoroid direction, and (c) map the deformational structures associated with the meteorite impact. Our results show five different magnetic anomaly types and three layers in the subsurface. The maximum depth of deformation due to the impact of the meteorite is about 25 m as shown by the seismic travel time tomogram, the quasi‐2D TEM, and the 3D GPR model. TEM survey confirmed the geometrical characteristics of the major crater and located another small crater (known as Philby‐A). The magnetic survey shows no evidence of any remnant major pieces of the meteorite; however, it was used to trace ejecta material containing highly dilute magnetic material. The magnetic carrier is most likely spheres of metal incorporated in the black/green glasses. During the expedition, many small pieces of the meteoroid were found and collected for further geochemical analysis. Based on the geophysical findings, the meteorite direction was found to be from north to south.

The onshore and offshore clastic deposits of the Argive Basin and the Argolic Gulf, respectively, in Peloponnese, Greece, form a Late Neogene–Quaternary half-graben that connects with the Aegean Sea. The onshore Late Neogene–Quaternary sequence, comprised of chaotically intercalated cohesive and granular clastic deposits, is in angular unconformity with bedrock comprised of Triassic–Upper Cretaceous strongly-weathered, highly-fractured karstic limestones thrusted against Paleogene flysch deposits. While the surface geology of the Argive Basin is well-known, the subsurface geology remains both poorly mapped and understood. We utilized transient electromagnetic (TEM) soundings coupled with 185 vintage stratigraphic logs, current surface geology knowledge, and insights from available geophysical surveys to characterize the subsurface conditions of this sedimentary basin. We estimated the thickness of the young deposits (the depth to bedrock) and detected potential subsurface tectonic structures. The TEM-FAST 48HPC data acquisition system with integrated inversion and visualization software package was used with a single-loop dimension of 50 m × 50 m to collect a total of 329 TEM soundings at 151 stations scattered throughout the basin. The TEM station spacing varied from 200 to 750 m allowing the mapping of 80 km2. The total depth of investigation with the inverted TEM data and the lithology logs was 130 m and 183 m, respectively. The joint interpretation produced several quasi-two-dimensional electrical resistivity profiles that traverse the sedimentary basin in various azimuths and depth slices of average electrical resistivity covering the basin. The depth slices and the vintage stratigraphic logs revealed an uneven bedrock topography overlain by an irregularly thick (over 180 m) Late Neogene–Quaternary heterolithic sediment cover.

Due to high oil and gas production and consumption, unconventional reservoirs attracted significant interest. Total organic carbon (TOC) is a significant measure of the quality of unconventional resources. Conventionally, TOC is measured experimentally; however, continuous information about TOC is hard to obtain due to the samples’ limitations, while the developed empirical correlations for TOC were found to have modest accuracy when applied in different datasets. In this paper, data from Devonian Duvernay shale were used to develop an optimized empirical correlation to predict TOC based on an artificial neural network (ANN). Three wells’ datasets were used to build and validate the model containing over 1250 data points, and each data point includes values for TOC, density, porosity, resistivity, gamma ray and sonic transient time, and spectral gamma ray. The three datasets were used separately for training, testing, and validation. The results of the developed correlation were compared with three available models. A sensitivity and optimization test was performed to reach the best model in terms of average absolute percentage error (AAPE) and correlation coefficient (R) between the actual and predicted TOC. The new correlation yielded an excellent match with the actual TOC values with R values above 0.93 and AAPE values lower than 14%. In the validation dataset, the correlation outperformed the other empirical correlations and resulted in less than 10% AAPE, in comparison with over 20% AAPE in other models. These results imply the applicability of this correlation; therefore, all the correlation’s parameters are reported to allow its use on different datasets.

Groundwater resources in Mediterranean coastal aquifers are under threat due to overexploitation and climate change impacts, resulting in saltwater intrusion. This situation is deteriorated by the absence of sustainable groundwater resources management plans. Efficient management and monitoring of groundwater systems requires interpreting all sources of available data. This work aims at the development of a set of plausible 3D geological models combining 2D geophysical profiles, spatial data analytics and geostatistical simulation techniques. The resulting set of models represents possible scenarios of the structure of the coastal aquifer system under investigation. Inverted resistivity profiles, along with borehole data, are explored using spatial data science techniques to identify regions associated with higher uncertainty. Relevant parts of the profiles will be used to generate 3D models after detailed Anisotropy and variogram analysis. Multidimensional statistical techniques are then used to select representative models of the true subsurface while exploring the uncertainty space. The resulting models will help to identify primary gaps in existing knowledge about the groundwater system and to optimize the groundwater monitoring network. A comparison with a numerical groundwater flow model will identify similarities and differences and it will be used to develop a typical hydrogeological model, which will aid the management and monitoring of the area's groundwater resources. This work will help the development of a reliable groundwater flow model to investigate future groundwater level fluctuations at the study area under climate change scenarios.

Complex interactions among organic contaminant, soil and water change the electrical properties of the subsurface often causing strong self-potential (SP) anomalies, whose monitoring is proposed as a useful tool to determine the temporal evolution of the contaminant plumes. In the present study, we focus on the problem of organic contaminant transport related to olive oil mill wastes (OOMWs), which represent an important environmental problem in Mediterranean countries. The diffusion of the contaminants into the subsurface is studied by using a global optimization procedure on SP data measured, at different times, in a well-studied contaminated pilot area located next to the Keritis river in western Crete island (Greece). Despite the complex hydrogeological conditions related to the proximity to both the Keritis river and a small seasonal stream, the analysis of five SP datasets acquired along the same profile shows that the proposed hybrid Genetic-Price algorithm is able to reproduce the main features of the SP signals, thus identifying probable multiple SP anomaly sources and their changes over time. In particular, preferential horizontal pathways of OOMW and their migration in the vadose zone during the summer season were identified, providing some useful insights for future planning of remediation actions.

Cultural heritage is a key element of history as the ancient monuments and archaeological sites enrich today’s societies and help connect us to our cultural origins. The project entitled ''SpaCeborne SAR Interferometry as a Nonivasive tool to assess the vulnerability over Cultural hEritage sites (SCIENCE)'' has as ultimate objective to predict the vulnerability of the archaeological sites to ground deformation in time and space and protect them against natural/man-made damage. The SCIENCE project aims to develop, demonstrate, and validate, in terms of geotechnical local conditions and monuments’ structural health, SAR interferometric techniques to monitor potential ground deformation affecting the archaeological sites and monuments of great importance. During the last few years, spaceborne Synthetic Aperture Radar (SAR) interferometry has proven to be a powerful remote sensing tool for detecting and measuring ground deformation and studying the deformation’s impact on man-made structures. It provides centimeter to millimeter resolution and even single buildings/monuments can be mapped from space. Considering the limitations of conventional MT-InSAR techniques, such as Persistent Scatterers Interferometry (PSI), in this project a two-step Tomography-based Persistent Scatterers (PS) Interferometry (Tomo-PSInSAR) approach is proposed for monitoring ground deformation and structural instabilities over the Ancient City Walls (Ming Dynasty) in Nanjing city, China and in the Great Wall in Zhangjiakou, China. The Tomo-PSInSAR is capable of separating overlaid PS in the same location, minimizing the unfavorable layover effects of slant-range imaging in SAR data. Moreover, the demonstrations are performed on well-known test sites in China and in Greece, such as: a) Ming Dynasty City Walls in Nanjing, b) Great Wall in Zhangjiakou, c) Acropolis complex of Athens and d) Heraklion walls (Crete Island), respectively.In particular, in the framework of SCIENCE project are processed several radar datasets such as Sentinel 1 A & B data of Copernicus program and the high resolution TerraSAR-X data. The products of Persistent Scatterers Interferometry (PSI) are exported in various formats for the identification of the persistent scatterers using high resolution optical images, aerial photographs and fusing with high accuracy Digital Surface Models (DSM). In addition, the validation of the results is taking place through in-situ measurements (geological, geothechnical e.t.c) and data for the cultural heritage sites conditions.SCIENCE project’s final goal is the risk assessment analysis of the cultural heritage monuments and their surrounding areas aiming to benefit institutions, organizations, stakeholders and private agencies in the cultural heritage domain through the creation of a validated pre-operation non-invasive system and service based on earth observation data supporting end-user needs by the provision knowledge about cultural heritage protection. In conclusion, SCIENCE project is composed by a bilateral consortium of the Greek delegation of Harokopio University of Athens, National Technical University of Athens, Terra Spatium S.A, Ephorate of Antiquities of Heraklion (Crete), Acropolis Restoration Service (Athens) of Ministry of Culture and Sports and by the Chinese delegation of Science Academy of China (Institute of Remote Sensing and Digital Earth) and International Centre on Space Technologies for Natural and Cultural Heritage (HIST) under the auspices of UNESCO (HIST-UNESCO).

Groundwater resources in Mediterranean coastal aquifers are under threat due to overexploitation and climate change impacts, resulting in saltwater intrusion. This situation is deteriorated by the absence of sustainable groundwater resources management plans. Efficient management and monitoring of groundwater systems requires interpreting all sources of available data. This work aims at the development of a set of plausible 3D geological models combining 2D geophysical profiles, spatial data analytics and geostatistical simulation techniques. The resulting set of models represents possible scenarios of the structure of the coastal aquifer system under investigation. Inverted resistivity profiles, along with borehole data, are explored using spatial data science techniques to identify regions associated with higher uncertainty. Relevant parts of the profiles will be used to generate 3D models after detailed Anisotropy and variogram analysis. Multidimensional statistical techniques are then used to select representative models of the true subsurface while exploring the uncertainty space. The resulting models will help to identify primary gaps in existing knowledge about the groundwater system and to optimize the groundwater monitoring network. A comparison with a numerical groundwater flow model will identify similarities and differences and it will be used to develop a typical hydrogeological model, which will aid the management and monitoring of the area's groundwater resources. This work will help the development of a reliable groundwater flow model to investigate future groundwater level fluctuations at the study area under climate change scenarios. This work was developed under the scope of the InTheMED project. InTheMED is part of the PRIMA programme supported by the European Union’s Horizon 2020 research and innovation programme under grant agreement No 1923.

In a column set-up, Fe modified biochar produced from date palm leaves was used to remove As (1 mg L−1) from a laboratory-prepared wastewater. The wastewater treatment process was monitored in real-time by spectral induced polarization (SIP), over a wide range of frequencies (0.01–1000 Hz). Both 5 and 10% biochar-amended columns achieved As removal exceeding 98%. The SIP parameters appear to be sensitive on As removal processes, with the recorded trend following the conventional geochemical monitoring, while offering higher temporal resolution.

Geomorphic indices can be used to examine the geomorphological and tectonic processes responsible for the development of the drainage basins. Such indices can be dependent on tectonics, erosional processes and other factors that control the morphology of the landforms. The inter-relationships between geomorphic indices can determine the influence of regional tectonic activity in the shape development of drainage basins. A Multi-Criteria Decision Analysis (MCDA) procedure has been used to perform an integrated cluster analysis that highlights information associated with the dominant regional tectonic activity. Factor Analysis (FA) and Analytical Hierarchy Process (AHP) were considered within that procedure, producing a representation of the distributed regional tectonic activity of the drainage basins studied. The study area is western Crete, located in the outer fore-arc of the Hellenic subduction zone, one of the world's most tectonically active regions. The results indicate that in the landscape evolution of the study area (especially the western basins) tectonic controls dominate over lithological controls.

This review specifically deals with the latest advances in the application of nanotechnologies and nanocomposites for remediation of arsenic (As)-contaminated water and soil. Remediation mechanisms generally include physicochemical adsorption and (photo)chemical redox reactions and filtration. Recently, various types of engineered organic/inorganic nanocomposites have been designed in membrane forms, embedded structures, or composites with extraordinary physical-chemical properties, and outstanding capacity for removal or immobilization of As in contaminated sites. In the present article, we give an overview of engineered nanomaterials developed recently (2017–2021) and their interaction mechanisms with As in contaminated water and soil. Emerging approaches include the development of bio-nanocomposites and nanomaterials that show both oxidative and adsorptive capacities. For the first time, we set out to perform a comprehensive assessment of the advantages of nanomaterials in As-contaminated soils with the focus on the mechanisms of decreasing bioavailability and leaching of As. Although great researches have been developed, serious study gaps and a new direction to future researches have been identified.

Characterizing subsurface site conditions and understanding main geological features are critical components of any safety assessment for any construction, particularly defining subsurface flow paths and weakness (i.e. fracture and fault) zones. Poor definition of flow paths and weakness zones may lead to serious hazards during construction. This study, integrating geophysical and geological investigations, is undertaken to enhance the understanding of both surface and subsurface complexities of an engineering site characterization located in western Saudi Arabia near Red Sea. Two geophysical investigations, Electrical Resistivity Tomography (ERT) and Transient Electromagnetic (TEM), were carried out to characterize the subsurface of the study area. A total of three ERT profiles and sixteen TEM sounding measurements was conducted in the study area. Geological investigation was mainly focused to understanding geological features and bedrock conditions of the two opposite river's abutments at the study site. Geophysical results show NNE-SSW and NNW-SSE fault zones which were confirmed by in-situ geological inspections and by satellite images. The results also reveal the presence of geothermal fluids validated by the observation of hot water flowing in the river along the measurements. This study demonstrates that the integrated geophysical and geological investigations provide means to infer geothermal fluids, locate fractures, and fault zones. This study enabled us to characterize and locate the geological structural framework as well as possible geothermal fluids existence in the study area.

Direct current resistivity, radio-magnetotelluric and seismic refraction methods are widely used in the identification of near surface structures with collected data generally being interpreted separately. In recent decades, the use of joint inversion algorithms in geosciences has become widespread to identify near surface structures. However, there is no developed joint inversion algorithm using direct current resistivity, radio-magnetotelluric and seismic refraction methods. In this study, we developed a new two-dimensional joint inversion algorithm for direct current resistivity, radio-magnetotelluric and seismic refraction data based on a cross gradient approach. In addition, we proposed a new data weighting matrix to stabilize the convergence behavior of the joint inversion algorithms. We used synthetic data to show the advantage of the algorithm. The developed joint inversion algorithm found resistivity and velocity models that are better than the individual inversion of each data set. We also tested an algorithm with the field data collected in the Bafra Plain (Samsun, Turkey) to investigate saltwater intrusion. In comparing the field data inversion results with the sounding log, it can be seen that the developed joint inversion algorithm with the proposed data weighting matrix recovered the resistivity and velocity model better than the individual inversion and classical joint inversion of each data set. Our results showed that a more unique hydrogeological scenario might be obtained, especially in highly conductive media, with the joint usage of these methods. (C) 2017 Elsevier B.V. All rights reserved.

We performed 2D resistivity and IP measurements over a known olive oil mill waste plume at a site in western Crete, Greece. The objectives of the survey were: (1) to determine whether IP is more diagnostic in delineating the spatial extent of the plume relative to resistivity measurements alone; (2) to evaluate whether the additional information content obtained from IP is worth the effort given longer data acquisition times and higher measurement errors that inevitably characterize field IP data acquisition. Complex conductivity inversion of the field IP dataset revealed that the organic plume is characterized as a region of high electrical conductivity (real part of complex conductivity) consistent with the conceptual model for the electrical structure of a biodegraded LNAPL contaminant plume. The plume is also characterized by a region of high polarizability (imaginary part of complex conductivity) that is more localized to the known plume location (based on conventional monitoring) relative to the high conductivity region in the electrical conductivity image. This observation is attributed to the fact that electrical conductivity is more strongly controlled by hydrogeological and geological characteristics of the site that mask the response from the biodegraded plume. This result encourages the use of field IP to improve the spatial delineation of organic contamination in the subsurface. However, more laborious field procedures are required to acquire reliable field IP data and the inversion of field IP data remains more challenging than resistivity data alone.

We present a novel approach where time-domain electromagnetic (TEM) data are transformed and subsequently used in two-dimensional (2-D) magnetotelluric inversion of the determinant of the impedance tensor. The main idea is to integrate TEM with magnetotelluric (MT) data to produce subsurface electrical resistivity models. Specifically, we show that 2-D MT data inversion of the determinant of the impedance tensor supported by inclusion of TEM–MT-transformed data has superior resolution at the near surface and at the same time static shift afflicting the MT data can be addressed. Thus, the approach allows for practical express integration of TEM data with MT measurements as opposed to a full combined 3-D inversion, which requires significant resources. The approach is successfully applied in the Mygdonian sedimentary basin located in Northern Greece. In addition to TEM and MT data, also controlled source — and radiomagnetotelluric data are available from the Mygdonian basin, which have been subjected to 2-D analysis previously. We have extended the analysis to a full 3-D inversion using ModEM code. All obtained models are analysed and are in a good agreement.

The electrical resistivity tomography method has been widely used in geophysics for many purposes such as determining geological structures, water movement, saltwater intrusion, and tectonic regime modeling. Karstic springs are important for water basin management since the karst systems are highly complex and vulnerable to exploitation and contamination. An accurate geophysical model of the subsurface is needed to reveal the spring structure. In this study, several karst springs in the G&ouml, kova Bay (SW, Turkey) were investigated to create a 3D subsurface model of the nearby karstic cavities utilizing electrical resistivity measurements. For this approach, 2D resistivity profiles were acquired and interpreted. Stratigraphically, colluvium, conglomerate, and dolomitic-limestone units were located in the field. The resistivity values of these formations were determined considering both the literature and field survey. Then, 2D profiles were interpolated to create a 3D resistivity model of the study area. Medium-large sized cavities were identified as well as their locations relative to the springs. The measured resistivities were also correlated with the corresponding geological units. The results were then used to construct a 3D model that aids to reveal the cavity geometry in the subsurface. Additionally, several faults are detected and their effect on the cavities is interpreted.

Olive oil mill wastes OOMW constitute a major pollution factor in olive-growing regions and an important problem to be solved for the agricultural industry. Olive oil mill wastes are normally deposited in tanks, or directly into the soil or even on adjacent torrents, rivers, and lakes, posing a high risk of environmental pollution in regard to public health. This study aims to develop integrated satellite remote sensing, geographical information systems GIS, and ground spectroscopy methodologies to detect and monitor OOMW disposal areas on the island of Crete, Greece in the Southeastern Mediterranean. More than 1000 disposal tanks were mapped through an extended global positioning system GPS survey that took place throughout the island. Satellite images of both high IKONOS and medium Landsat 8 OLI Operational Land Imager resolution were preprocessed and analysed by applying geometric, radiometric, and atmospheric corrections. A library with a spectral signature of OOMW including both different time periods and satellite sensors was developed. At the same time, ground spectroscopy campaigns were carried out and a complementary spectral signature library was developed. The narrow band reflectance of ground measurements was recalculated using the relative response filters of the corresponding satellite sensors. Both libraries were compared for their accuracy through statistical approaches and the optimum spectral range for detecting OOMW areas was estimated. Subsequently, further auxiliary image-processing techniques such as image fusion, linear spectral unmixing LSU, false-colour composites FCCs, image classification, and principal component analysis PCA were applied to satellite images to enhance OOMW patterns, and an innovative OOMW detection index for Landsat 8 was developed. In addition, several vegetation indices were applied and compared in regard to their efficiency in detecting waste ponds. Finally an integrated, semi-automatic methodology was developed in the GIS environment employing classification algorithms for the detection of waste ponds. This study highlights the potential of satellite remote sensing, GIS, and ground spectroscopy in the semi–automatic detection of OOMW disposal areas in the context of the Mediterranean landscape.

This study aims to define the geotectonic characteristics of the Mygdonia basin by using 3D Transient Electromagnetic (TEM) technology. The Mygdonian basin is located between Volvi and Langada lakes around 45 km North-East of Thessaloniki city in northern Greece and presents very high seismicity. To define the tectonic regime of the area, a detailed electromagnetic survey was performed along with the geological and lithological study of the area. The TEM data were acquired using the TEM-FAST 48 instrument for 485 soundings in 159 locations. The 1-D and 2-D interpretation of the TEM data indicate the tectonic characteristics of the area. 3D modeling applied to TEM data highlighted the fracture zone in the investigated area. The geothermal field of Apollonia is also depicted. The results are validated with the previous EM (AMT, RMT, and MT) data acquired in the study area studies.

In this work, two multi-criteria methods, an expert-based, semi-quantitative, relative weighting – rating approach, the weighted linear combination (WLC) and a quantitative, statistical method, the weights of evidence (WoE) approach were applied for landslide susceptibility zonation mapping in the Chania Prefecture of Crete Island, Greece. Several thematic maps representing various landslide casual factors, such as geological formations, faults proximity, elevation, slope gradient, aspect and curvature, rivers proximity, precipitation, roads proximity and land use types; have been generated in a GIS environment. Two landslide susceptibility maps were created; one for each method. The maps were compared and validated using the success rate curve (SRC) analysis. The resulting landslide susceptibility maps have uncertainties introduced due to the subjective knowledge of experts in the case of WLC method and to the quality of the recorded landslides sample in the case of the WoE method. Both approaches produced almost equally accurate maps with the WoE method to produce slightly superior predictions.