Search Results (1,616)

Lake Faro (Cape Peloro coastal lagoon, NE Sicily, Italy) is a distinctive Mediterranean coastal lake characterized by the coexistence of a shallow platform and a steep-sided deep basin within a very limited area. This study provides a sedimentological and geological characterization of the present-day lake floor based on grain-size, petrographic, statistical, and GIS-based analyses, with the aim of clarifying the relationship between basin morphology and modern depositional processes. The lake floor is subdivided into two main bathymetric domains. The shallow platform (<10 m water depth) is dominated by modern coarse-grained, very poorly sorted sediments, including gravel and very coarse- to medium-grained sand, deposited under high-energy, low-confinement conditions comparable to beach and open-lagoon environments. In contrast, the deep basin (>10 m water depth) is characterized by modern finer, organic-rich sediments with extremely poor sorting, reflecting lower-energy and more confined depositional conditions. A key new finding is the identification of upper Holocene beachrocks beneath the modern unconsolidated sediments of the shallow platform, which likely exert a significant morpho-structural control on platform development. Overall, the results highlight the strong influence of bathymetry on sediment distribution in coastal lake systems and provide a reference framework for comparable Mediterranean lagoon environments. Full article

Selenium (Se) is an essential trace element for humans, and agricultural soils are a major source of dietary Se. Therefore, identifying the key environmental drivers of Se in farmland is crucial for evaluating the resource base for Se-rich agriculture and improving human health. Although soil Se distribution and its controlling factors have been widely investigated, quantitative assessments of soil Se in small-scale farmland systems under humid monsoon conditions remain limited. Sampling sites were designed to represent different geological types, soil types, and topography, and 314 farmland topsoil (0–20 cm) samples were collected. Total Se was determined after complete HNO₃–HClO₄ wet digestion and quantified by HG–AFS (AFS–830), with certified reference materials showing recoveries of 95.3–101.2%. The spatial patterns were mapped using ordinary kriging. Geographically weighted regression (GWR) and Geodetector were used to explore the impact of environmental factors (geological type, precipitation, etc.) on soil Se from both local and overall perspectives. The findings reveal a mean total soil Se of 1.76 mg/kg (95% CI: 1.540–1.974), and 91.40% (n = 287) of soil samples were classified as Se-rich (0.4–3 mg/kg). Organic matter (OM), elevation, slope, and the topographic wetness index (TWI) exhibited non-stationary spatial relationships with Se. The spatial variation trend of precipitation corresponds with the local R² values between Se and elevation, indicating that precipitation may strengthen the association between elevation and Se distribution. Geological type and rainfall were identified as key driving factors affecting soil Se content within the study area, particularly through their interactions with OM. Overall, the synergistic effects of geological type, precipitation, and OM are responsible for the accumulation of Se in the agricultural soils of Xin’an Town. Full article

The Yanchang Formation in the Ordos Basin is a key target for continental shale oil exploration in China. Due to its complex geological background and diversified organic inputs, the hydrocarbon generation and accumulation in the lacustrine basin remain to be fully understood. Unlike marine shales rich in Type I kerogen, this lacustrine system is dominated by Type II and III kerogens. In this study, Rock-Eval pyrolysis was performed on lacustrine shales with Type IIa, IIb, and III kerogens to investigate the effect of kerogen type on their hydrocarbon generation and expulsion characteristics. The results reveal that the hydrocarbon generation potential of the Yangchang Formation shale generally follows the order of Type IIa > Type IIb > Type III. Pyrolysis kinetic calculations of the kerogens demonstrate a clear hierarchy of hydrocarbon generation and expulsion among the kerogen types, of which Type II kerogen has better hydrocarbon generation potential, earlier generation timing, and narrower generation window than Type III kerogen. The discrepancy in hydrocarbon generation potential and pyrolysis kinetic behavior is largely attributed to the kerogen components and types, which manifests as a kerogen-type constraint on the hydrocarbon generation and expulsion of shale. Based on the geological mapping of the lacustrine shales in the study area, we propose a “kerogen type-specific” exploration strategy that prioritizes Type IIa-rich intervals in moderate-maturity areas for shale oil exploration, Type IIb as secondary prospects, and Type III in high-maturity areas for shale gas exploration. This study provides a systematic investigation of pyrolysis simulation and hydrocarbon generation and expulsion kinetics on the Yanchang Formation shale, as well as a practical framework for optimizing exploration in analogous lacustrine basins. Full article

The increasing global demand for energy has accelerated the depletion of identified conventional resources, highlighting the need for sustainable alternatives. Geothermal energy, a renewable resource derived from the Earth’s internal heat, offers a reliable solution for both power generation and direct use applications. We present a comprehensive investigation of medium-enthalpy geothermal reservoirs in the Prinos–Kavala Basin, Northern Aegean, Greece. We firstly integrate geological, geophysical, and geochemical data from 66 wells across Prinos–Kavala basin to analyze the temperature distribution in the reservoir. The methodology includes the correction of bottom-hole temperatures and estimation of the geothermal gradients. A 1-D semi-steady-state well temperature modeling technique was applied to estimate the expected production wellhead temperature and assess its suitability for surface heating applications. Results reveal significant spatial heterogeneity in geothermal gradients and reservoir properties, with overpressured conditions confirmed in key zones. The integration of 3D reservoir model and isothermal mapping (>90 °C) identifies zones with high geothermal potential, supporting optimal exploitation strategies. The estimated production wellhead temperatures support the utilization of the produced brine heat content for various applications, among them the pre-heating of a CO₂ stream to be injected within the CCS framework for wellbore thermal stress management purposes. The findings demonstrate the value of reservoir characterization for sustainable geothermal development in complex tectonic settings. Full article

Hyperspectral images (HSIs) from the lunar polar regions are frequently compromised by low signal-to-noise ratio (SNR) under adverse illumination, limiting their utility for scientific analysis. Existing spectral-only compensation approaches operate without spatial context, leading to speckle-like artifacts that degrade spatial consistency and constrain subsequent applications. To address this limitation, we propose SSF-3DSC, a spatial–spectral fusion 3D signal-compensation framework tailored for lunar HSIs to simultaneously restore spectral fidelity and spatial consistency under extreme low-illumination conditions. To the best of our knowledge, this represents the first deep learning framework specifically engineered for joint spatial–spectral restoration in the photon-starved regime. SSF-3DSC integrates three specialized components: a spectral compensation module (SCM) for restoring spectral fidelity, a multi-scale spatial attention (MSA) module for capturing hierarchical spatial patterns, and a cascaded 3D residual convolutional module (C3D-RCM) for refining spatial–spectral representations. Trained on paired low- and high-SNR Moon Mineralogy Mapper (M3) data cubes from the lunar south polar region, SSF-3DSC employs synergistic spatial–spectral fusion to achieve high-fidelity reconstruction, significantly outperforming a spectral-only lunar baseline (Paired-CycleGAN). Regional-scale experiments demonstrate its ability to recover both spatially coherent geological structures and spectrally reliable mineral abundance maps. By establishing a new benchmark for lunar HSI restoration under low-illumination conditions, this work enhances the scientific utility of low-signal M3 data and enables robust quantitative investigations into the Moon’s challenging polar regions. Full article

Flooding is one of the major natural disasters that have a major impact on urban areas due to the increasing intensity of factors like extreme weather conditions, climate change, and unplanned urbanization. Considering Cook County, Illinois, the rapid development of the region, flat topography, and the induced rainfall extremes from climate change increase the potential risk of flooding when interacting with dense urban exposure and infrastructure. This study employed the Frequency Ratio (FR) model in a GIS environment to create a high-resolution flood susceptibility map of the county. The map was developed using 281 historical flood points collected from several authoritative sources, such as National Oceanic and Atmospheric Administration (NOAA) Storm Events Database records, Federal Emergency Management Agency (FEMA) Flood Insurance Study (FIS) and Flood Insurance Rate Map (FIRM)-based FIRMette products, and U.S. Geological Survey (USGS) flood-inundation studies. Thirteen conditioning factors, including land use, elevation, slope, soil drainage, rainfall, and distance to the stream, were used to calculate FR values and to develop the Flood Susceptibility Index (FSI). The resulting FSI was grouped into four susceptibility zones: low, medium, high, and very high. The findings indicated that more than 64% of Cook County has a high and very high risk of flood susceptibility, particularly in the vicinity of major river corridors. The model was validated using testing data with a 91.4% prediction accuracy, which also demonstrated the reliability and applicability of the FR model in the urban flood susceptibility assessment. The map serves as a valuable tool for risk-based urban planning and design of flood mitigation infrastructure in one of the most populated counties in the United States. Full article

The North China Plain is one of the largest plains in China, where domestic water supply, agricultural irrigation, and industrial production rely on groundwater resources. Groundwater quality is increasingly affected by the combined effects of intense human activity and geological conditions. To ensure sustainable groundwater utilization, it is crucial to investigate the hydrogeochemical processes linked to hydrogeological conditions. In this study, 85 samples were collected from cold wells and 56 samples from geothermal wells in North China. By integrating self-organizing mapping (SOM), hydrochemical and isotopic analysis, nitrate distribution, water quality index (WQI), and human health risk assessment (HHRA) methodologies, we systematically evaluated the spatial variability of groundwater quality and the associated health risks in the region. Hydrochemical analysis indicates that groundwater recharge is primarily driven by atmospheric precipitation. Shallow cold groundwater in Cluster 1 exhibited a mixed phase, whereas geothermal water in Clusters 2 and 3 and cold groundwater in Cluster 4 predominantly displayed a Na-Cl type. Cation exchange processes are the primary factors controlling ion composition. Water quality assessment studies indicate that 75.15% of the groundwater is suitable for drinking. The average water quality index of the geothermal water was higher than that of the cold water. Shallow groundwater in plains is significantly affected by agricultural activities, typically manifested as elevated NO₃⁻ concentrations. Arsenic and boron are the primary non-carcinogenic risk pollutants in geothermal water, and children are more vulnerable than adults. The non-carcinogenic risk zones for cold wells were primarily distributed in Shijiazhuang, Baoding, and the coastal areas downstream of the Yellow River. Tianjin has high-risk geothermal water. Therefore, effective strategies must be implemented to protect this valuable water resource and achieve sustainable development in the region. Full article

The McMurdo Dry Valleys (DVs) of South Victoria Land, Antarctica, constitute the largest ice-free region on the continent and one of Earth’s most Mars-analog environments. Their hyper-arid polar desert conditions offer a unique setting for investigating surface weathering and mineralogical processes under extreme climates. This study presents the first regional-scale mapping of alteration and crystalline weathering minerals across the McMurdo DVs. It uses Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) multispectral data; visible and near-infrared (VNIR) and shortwave infrared (SWIR) bands were analyzed through a Spectral Hourglass Workflow, endmember extraction, and spectral unmixing with Matched Filtering (MF) and Constrained Energy Minimization (CEM). Inter-algorithm consistency analysis between MF and CEM yielded 78.83% overall agreement with a Kappa coefficient of 0.75, indicating strong methodological consistency in mineral discrimination using ASTER VNIR+SWIR data. It should be noted that this agreement reflects internal algorithmic robustness rather than independent geological validation. Geological reliability is instead supported by documented field observations, lithological map comparisons, and spectral correspondence with the USGS spectral library. Validation employed documented field observations, lithological maps, and the USGS spectral library. Results reveal distinct spatial distributions of hematite-limonite/goethite, jarosite, kaolinite/smectite-illite-pyrophyllite-alunite, muscovite, hydrous silica/sericite/jarosite/hematite, epidote/chlorite, and calcite, closely associated with lithological units and unconsolidated deposits in Taylor, Wright, Victoria, and McKelvey Valleys. An inter-algorithm consistency check achieved 78.83% overall accuracy with a Kappa coefficient of 0.75, underscoring the robustness of ASTER VNIR+SWIR data for Antarctic mineral discrimination despite localized spectral mixing. Beyond refining the geological understanding of the McMurdo DVs, these results establish ASTER as an effective tool for regional mineralogical mapping in inaccessible polar terrains. The findings further strengthen the role of the Dry Valleys as a terrestrial analog for Mars, where similar mineralogical assemblages and spectral ambiguities have been observed, thereby contributing to both Antarctic geoscience and planetary exploration frameworks. Full article

Floods are natural disasters that cause significant socioeconomic and environmental losses in both urban and rural areas. Within the framework of spatial planning, precautionary measures against flood hazards can be developed using analytical approaches based on different modeling techniques. In this study, flood-prone areas in the Melen Basin, Türkiye, were identified and mapped using five statistical methods, namely Frequency Ratio (FR), Shannon Entropy (SE), Evidential Belief Function (EBF), and the hybrid models EBF–SE and EBF–FR. The analysis was conducted using a flood inventory and environmental datasets covering the period 2019–2024, including elevation, slope, aspect, land use, plan and profile curvature, drainage density, distance to river, curve number, long-term average precipitation, geological formation, soil depth, topographic wetness index, sediment transport, and stream power index. Model performances were evaluated using the Receiver Operating Characteristic (ROC) curve and the Area Under the Curve (AUC). The results indicate that the SE method achieved the highest predictive performance (AUC = 0.979), followed by FR (0.974), EBF–SE (0.972), EBF–FR (0.968), and EBF (0.966). According to the FR and SE models, elevation, lithology, and slope were identified as the most influential factors in flood occurrence. In the evaluation of the success index of the models, the following values were determined according to their size: EBF–SE (96.0), SE (94.4), EBF (91.8), FR (81.9), and EBF–FR (79.4). In the classification of flood sensitivity maps, Natural Breaks (Jenks) is the most successful method according to the success index. The findings demonstrate that data-driven and hybrid models can effectively support flood risk assessment and provide valuable input for land-use planning and flood risk management. Full article

Impact craters, as key geomorphic features on Mars, provide important insights into surface processes and geological evolution. However, automatic classification of crater morphologies remains challenging due to substantial variations in size, degradation degree, and data quality across different types of Martian craters. This study proposes a multi-modal framework for Martian crater classification by integrating infrared imagery, an optical map, and digital elevation model (DEM) data. Specifically, daytime infrared imagery from THEMIS, a color map from the Tianwen-1 MoRIC instrument, and topographic data derived from combined MOLA–HRSC observations are used to capture complementary thermal, morphological, and elevation-related characteristics. A transformer-based feature extraction and cross-modal fusion strategy is adopted, where infrared imagery guides the interaction among multi-source features. Experiments on a carefully constructed dataset covering four crater categories, i.e., standard craters, layered ejecta craters, degraded craters, and secondary craters, demonstrate that the proposed approach achieves an overall precision of 0.848 and a recall of 0.851, outperforming single-modality baselines. Layered ejecta craters exhibit the highest classification performance, benefiting from their distinctive ejecta morphologies, whereas secondary craters remain more difficult to classify due to their small spatial scales. The results highlight the value of multi-modal data for Martian crater morphology classification. Full article

Rapid urbanization is reshaping thermal environments worldwide, with the strongest impacts occurring at the interface between urban and non-urban areas. Impervious surfaces, as key indicators of urban expansion, are critical for monitoring urban growth and assessing surface urban heat island (SUHI) effects. Land use and land cover change (LULCC) provides an essential link between urban dynamics and their environmental and societal consequences. Here, we integrated the U.S. Geological Survey (USGS) Climate Global Issues (CGI) Land Cover Product with Landsat thermal time-series to investigate SUHI evolution in two contrasting metropolitan regions: Wuhan, China, and Brasília, Brazil. Using data spanning 1986–2023, we analyzed the relationships between land cover, Landsat-based land surface temperature (LST), and SUHI intensity, and identified persistent thermal hotspots. Results demonstrate that the land cover data utilized increases the accuracy of impervious surface mapping along urban–rural gradients. Average SUHI intensities were 3.4 °C in Wuhan and 3.3 °C in Brasília, with statistically significant warming trends of 0.04 °C/year and 0.01 °C/year, respectively. Maximum temperature proved to be a robust indicator of SUHI intensification, capturing long-term upward trends. Our findings highlight the important role of urban land cover dynamics in shaping temporal SUHI variability and hotspot emergence. This prototype framework demonstrates the scientific and policy value of combining long-term land cover monitoring information with satellite thermal monitoring to quantify and track SUHI at city scale, supporting sustainable urban planning and climate adaptation strategies. Full article

With the rapid advancement in information technology, the digital twin and smart assembly process simulation have become an integral part of the design and manufacturing of high-precision products. However, conventional Tunnel Boring Machine (TBM) cutterhead design and on-site assembly planning remain largely experience-driven and fragmented, with limited interoperability between geological characterization, structural verification, and constructability validation. This study proposes a digital twin-driven framework for TBM cutterhead design optimization and assembly process simulation that integrates geology-aware design inputs, BIM-based information modelling, FEM-based structural assessment, and immersive virtual environments within a unified virtual–physical workflow. To ensure consistent data exchange across platforms, an IFC4.3-compliant ontology is established using a non-intrusive property-set (Pset) extension strategy to represent cutterhead components, geological parameters, FEM load cases/results, and assembly tasks. Tunnel-scale stress analysis and cutter–rock interaction modelling are used to define project-representative cutter loading envelopes, which are mapped to a high-fidelity cutterhead FEM model for iterative structural refinement. The optimized configuration is then transferred to a game-engine/VR environment to support full-scale design inspection and assembly rehearsal, followed by manufacturing and field deployment with bidirectional feedback. To validate the proposed framework, an implementation case study of a deep hard-rock tunnelling project is presented where five design iterations were tracked across BIM–FEM–VR and nine constructability issues detected and resolved prior to assembly. The results indicate that the proposed digital twin approach strengthens traceability from geology to loading to structural response, reduces localized stress concentration at critical interfaces, and improves assembly readiness for complex tunnelling projects. Full article

The presence of shallow gas or overlying gas reservoirs often degrades the imaging accuracy of underlying structural formations. To address the “pull-down” effect of deep structural reflectors caused by low-velocity shallow gas anomalies, this study takes the X Gas Field in the Pearl River Mouth Basin as an example. By using spectral attenuation attributes, we finely characterize the planar distribution and temporal thickness of the shallow gas. On this basis, a shallow gas anomaly thickness correction method is established. This approach integrates the temporal thickness of shallow gas (derived from spectral attenuation), characteristics of the seismic velocity field, and velocity differences calibrated by well logs to compute specific depth correction values. Application results, validated through blind well tests, show that the accuracy of the structural map can be improved to within 5 m. This multi-data integration strategy, which combines lateral velocity variation with vertical correction, offers a valuable reference for the detailed characterization of hydrocarbon reservoirs under similar geological conditions. Full article

This study develops a reproducible regional screening workflow to assess geothermal potential in the Cambrian reservoir system of Western Lithuania under conditions of sparse and heterogeneous legacy subsurface data. The approach integrates data compilation, cleaning, and harmonization from archival well materials, ordinary kriging spatialization of key reservoir properties with uncertainty multipliers, standardized doublet simulations to derive comparative thermal performance indicators, and a neural network surrogate to accelerate regional inference. The workflow integrates 12 compiled reservoir control points into a gridded regional representation (25 × 30 cells; ~6750 km²) and evaluates uncertainty through low, mid and high scenarios (±10%). Physics-based simulations were executed for 303 representative grid locations per scenario, yielding cumulative extracted-energy indicators on the order of 10⁵–10⁷ MWh across cases (reported as comparative indicators). The neural network surrogate reproduced simulation outputs with a high predictive agreement (test R² = 0.996; cross-validation mean R² ≈ 0.99), enabling swift prediction across the remaining grid cells after training. Relative potential maps highlight spatially coherent zones of higher prospectivity and provide a transparent basis for prioritizing follow-up investigations and data acquisition. The proposed framework is modular and can be refined as improved geological constraints, thermophysical properties, and operational assumptions become available. Full article

The territory of the Republic of Armenia (RA) lies within the central Arabia–Eurasia collision zone and is characterized by rugged mountain landscapes, complex geology, active faulting, and seismicity. Armenia is highly vulnerable to seismic and landslide hazards, with more than 2504 active landslides mapped in the country. A significant landslide in the Tumanyan Community, Lori Marz, was activated in January 2018 and threatened critical infrastructure, including the railway linking Armenia to Georgia and the M6 interstate highway. The landslide’s activation was driven by groundwater, a nearby water reservoir leak, and adjacent infrastructure. Preliminary hazard analysis revealed that further movement of the landslide could dam the Debed River, leading to potentially catastrophic downstream impacts. In response, the Minister of Emergency Situations of RA requested urgent studies by the Institute of Geological Sciences of NAS RA. Surveys began on 22 January 2018, involving an interdisciplinary approach including geotechnical study, UAV-based digital mapping, and application of geophysical methods, such as MASW, microtremor recordings, GPR, and VES. The combination of these methods provided reliable information on the landslide’s geotechnical structure, identified the sliding plane, and allowed for numerical slope stability modeling, which confirmed the landslide’s unstable condition and susceptibility to reactivation from earthquakes or elevated groundwater. Based on this complex research, protective measures were developed and applied, including, in particular, horizontal drilling to dewater the sliding plane. These emergency measures stabilized the landslide, mitigating immediate threats to infrastructure and ensuring relative safety. Full article