Search Results (57)

Titanite is widely used in geochronology and petrogenetic studies, yet its behaviour during fluid-mediated alteration remains insufficiently constrained. This study investigates titanite alteration and element redistribution in the Mesoproterozoic Kabeliai granitoids (southern Lithuania) to evaluate their response to magmatic and hydrothermal processes. Petrography, EPMA, LA-ICP-MS, U-Pb geochronology, and mass balance modeling were combined to characterise titanite textures, chemistry, and isotopic evolution. Three titanite types were distinguished. Type 1 titanite preserves magmatic compositions and yields U-Pb ages of 1508 ± 19 (MSWD = 0.91; 2σ) and 1527 ± 9 Ma (MSWD = 0.54; 2σ), consistent with late magmatic crystallisation. Type 2 titanite represents a transitional fluid-altered stage, characterised by a porous texture. Type 3 titanite is interpreted to record hydrothermal recrystallisation, trace element depletion (Y, REE, Nb, Zr), and U-Pb resetting, with ages of 1454 ± 14 Ma (MSWD = 0.48; 2σ) and 1475 ± 23 Ma (MSWD = 0.63; 2σ) partially overlapping molybdenite mineralisation at ca. 1486 Ma. Mass balance modeling indicates that alteration was dominated by coupled albitisation and chloritisation, and by the redistribution of Ca, Si, and REE. In contrast, Ti remained relatively immobile at the rock scale and was locally redistributed among secondary phases via dissolution–reprecipitation. These results suggest that different titanite domains may preserve distinct stages of magmatic and hydrothermal evolution and highlight the importance of microstructural context when interpreting U-Pb ages in altered granitoid systems. Full article

In many African nations, including Nigeria, groundwater remains the most readily available source of clean water. However, finding and developing these resources in heterogeneous terrain, such as the Federal Capital Territory (FCT), Abuja, is challenging due to the uneven distribution of the aquifers and complex geological settings. Using a GIS-based machine learning approach that incorporates surface and subsurface hydrogeological parameters, this study defines groundwater potential zones (GWPZ). Nine conditioning factors were derived from remote sensing, geophysical and climatic datasets. Aquifer thickness, depth to bedrock, geology, rainfall, slope, LULC, lineament density, drainage density and distance from river were among these variables. Three machine learning models: Extreme Gradient Boosting (XGBoost), Support Vector Machine (SVM) and Random Forest (RF) were trained and validated using 2410 borehole records (productive and abortive). Hold-out validation (80:20), 10-fold cross-validation, ROC-AUC, and confusion matrix were used to assess each model’s performance. The ensemble models outperformed the SVM, achieving higher predictive accuracy and better generalisation (XGBoost: 0.89, RF: 0.88 and SVM: 0.87). The generated maps categorised the study area into five GWPZs: very high, high, moderate, low and very low. These findings provide a scientific foundation for groundwater exploration and sustainable water resource management in the study area. Full article

The Santa Elena Peninsula has experienced local subduction earthquakes in 1901 (7.7 Mw) and 1933 (6.9 Mw), during which local ground conditions, including deposits of longshore-current sediments, paleo-lagoon or marsh, sandspit, and ancient tidal channel sediments, exhibited various coseismic deformation behaviors in Quaternary soils of inferior geotechnical quality. This study shows that geophysical profiles from seismic refraction and shear-wave velocities are correlated with stratigraphic data from sedimentary sequences obtained from slope cutting and geotechnical drilling. This database is used to create a comprehensive map to describe the lithological units of Salinas’ urban geology. The thickness of the Tertiary–Quaternary sedimentary sequences and the depth to the bedrock of the Piñon and Cayo geological formations determine the periods of sites in these stratigraphic sequences, which range from 0.3 to 1.5 s. This study provides the first geotechnical zoning map for the city of Salinas at a scale of 1:25,000, which is a technical requirement of the Ecuadorian construction standard. This geotechnical zoning information is essential for appropriate land management in Salinas and its neighboring cities, La Libertad and Santa Elena, as well as for outlining municipal restrictions on future construction. Full article

Artisanal and small-scale gold mining (ASGM) poses significant environmental challenges globally, particularly due to mercury (Hg) use. As an example, in Ecuador, Hg use still persists, despite its official ban in 2015. This study investigated the geogenic and anthropogenic contributions of potentially toxic elements (PTEs) in the Ponce Enriquez Mining District (PEMD), a region characterized by hydrothermally altered basaltic bedrock and Au-mineralized quartz veins. To assess local baseline values and identify PTE-bearing minerals, a comprehensive geochemical, mineralogical, and petrographic analysis was conducted on bedrock and mineralized veins. These findings reveal distinct origins for the studied PTEs, which include Hg, As, Cu, Ni, Cr, Co, Sb, Zn, and V. Specifically, Hg concentrations in stream sediments downstream (up to 50 ppm) far exceed natural bedrock levels (0.03–0.707 ppm), unequivocally indicating significant anthropogenic input from gold amalgamation. Furthermore, copper shows elevated concentration primarily linked to gold extraction. Conversely, other elements like As, Ni, Cr, Co, Sb, Zn, and V are primarily exhibited to be naturally abundant in basalts due to the presence of primary mafic minerals and to hydrothermal alterations, with elevated concentrations particularly seen in sulfides like pyrite and arsenopyrite. To distinguish natural geochemical anomalies from mining-related contamination, especially in volcanic terrains, this study utilizes Upper Continental Crust (UCC) normalization and local bedrock baselines. This multi-faceted approach effectively helped to differentiate basalt subgroups and assess natural concentrations, thereby avoiding misinterpretations of naturally elevated element concentrations as mining-related pollution. Crucially, this work establishes a robust local geochemical baseline for the PEMD area, providing a critical framework for accurate environmental risk assessments and sustainable mineral resource management, and informing national environmental quality standards and remediation efforts in Ecuador. It underscores the necessity of evaluating local geology, including inherent mineralization, when defining environmental baselines and understanding the fate of PTEs in mining-impacted environments. Full article

The permanently shadowed regions of the lunar South Pole have become a key target for international lunar exploration due to their unique scientific value and engineering challenges. In order to effectively screen suitable landing zones near the lunar South Pole, this research proposes a comprehensive evaluation method based on a self-organizing map (SOM). Using multi-source remote sensing data, the method classifies and analyzes candidate landing zones by combining scientific purposes (such as hydrogen abundance, iron oxide abundance, gravity anomalies, water ice distance analysis, and geological features) and engineering constraints (such as Sun visibility, Earth visibility, slope, and roughness). Through automatic clustering, the SOM model finds the important regions. Subsequently, it integrates with a supervised learning model, a random forest, to determine the feature importance weights in more detail. The results from the research indicate the following: the areas suitable for landing account for 9.05%, 5.95%, and 5.08% in the engineering, scientific, and synthesized perspectives, respectively. In the weighting analysis of the comprehensive data, the weights of Earth visibility, hydrogen abundance, kilometer-scale roughness, and slope data all account for more than 10%, and these are thought to be the four most important factors in the automated site selection process. Furthermore, the kilometer-scale roughness data are more important in the comprehensive weighting, which is in line with the finding that the kilometer-scale roughness data represent both surface roughness from an engineering perspective and bedrock geology from a scientific one. In this study, a local examination of typical impact craters is performed, and it is confirmed that all 10 possible landing sites suggested by earlier authors are within the appropriate landing range. The findings demonstrate that the SOM-model-based analysis approach can successfully assess lunar South Pole landing areas while taking multiple constraints into account, uncovering spatial distribution features of the region, and offering a rationale for choosing desired landing locations. Full article

Accurate, high-resolution maps of bedrock outcrops can be valuable for applications such as models of land–atmosphere interactions, mineral assessments, ecosystem mapping, and hazard mapping. The increasing availability of high-resolution imagery can be coupled with machine learning techniques to improve regional bedrock outcrop maps. In the United States, the existing 30 m U.S. Geological Survey (USGS) National Land Cover Database (NLCD) tends to misestimate extents of barren land, which includes bedrock outcrops. This impacts many calculations beyond bedrock mapping, including soil carbon storage, hydrologic modeling, and erosion susceptibility. Here, we tested if a machine learning (ML) model could more accurately map exposed bedrock than NLCD across the entire Sierra Nevada Mountains (California, USA). The ML model was trained to identify pixels that are likely bedrock from 0.6 m imagery from the National Agriculture Imagery Program (NAIP). First, we labeled exposed bedrock at twenty sites covering more than 83 km² (0.13%) of the Sierra Nevada region. These labels were then used to train and test the model, which gave 83% precision and 78% recall, with a 90% overall accuracy of correctly predicting bedrock. We used the trained model to map bedrock outcrops across the entire Sierra Nevada region and compared the ML map with the NLCD map. At the twenty labeled sites, we found the NLCD barren land class, even though it includes more than just bedrock outcrops, accounted for only 41% and 40% of mapped bedrock from our labels and ML predictions, respectively. This substantial difference illustrates that ML bedrock models can have a role in improving land-cover maps, like NLCD, for a range of science applications. Full article

The Münchberg Gneiss Complex (Central European Variscides, Germany) is separated by a deep-seated lineamentary fault zone, the Franconian Lineamentary Fault Zone, from its Mesozoic foreland. The study area offers insight into a great variety of landforms created by fluvial and mass wasting processes together with their bedrocks, covering the full range from unmetamorphosed sediments to high-grade regionally metamorphic rocks. It renders the region an ideal place to conduct a study of compositional and numerical geomorphology and their landscape-forming indices and parameters. The landforms under consideration are sculpted out of the bedrocks (erosional landforms) and overlain by depositional landforms which are discussed by means of numerical landform indices (LFIs), all of which are coined for the first time in the current paper. They are designed to be suitable for applied geosciences such as extractive/economic geology as well as environmental geology. The erosional landform series are subdivided into three categories: (1) The landscape roughness indices, e.g., VeSi_val (vertical sinuosity—valley of landform series) and the VaSlAn_alti (variation in slope angle altitude), which are used for a first order classification of landscapes into relief generations. The second order classification LFIs are devoted to the material properties of the landforms’ bedrocks, such as the rock strength (VeSi_lith) and the bedrock anisotropy (VaSlAn_norm). The third order scheme describes the hydrography as to its vertical changes by the inclination of the talweg and the different types of knickpoints (IncTal_lith/grad) and horizontal sinuosity (HoSi_lith/grad). The study area is subjected to a tripartite zonation into the headwater zone, synonymous with the paleoplain which undergoes some dissection at its edge, the step-fault plain representative of the track zone which undergoes widespread fluvial piracy, and the foreland plains which act as an intermediate sedimentary trap named the deposition zone. The area can be described in space and time with these landform indices reflecting fluvial and mass wasting processes operative in four different stages (around 17 Ma, 6 to 4 Ma, <1.7 Ma, and <0.4 Ma). The various groups of LFIs are a function of landscape maturity (pre-mature, mature, and super-mature). The depositional landforms are numerically defined in the same way and only differ from each other by their subscripts. Their set of LFIs is a mirror image of the composition of depositional landforms in relation to their grain size. The leading part of the acronym, such as QuantSan_heav and QuantGrav_lith, refers to the process of quantification, the second part to the grain size, such as sand and gravel, and the subscript to the material, such as heavy minerals or lithological fragments. The three numerical indices applicable to depositional landforms are a direct measurement of the hydrodynamic and gravity-driven conditions of the fluvial and mass wasting processes using granulometry, grain morphology, and situmetry (clast orientation). Together with the previous compositional indices, the latter directly translate into the provenance analysis which can be used for environmental analyses and as a tool for mineral exploration. It creates a network between numerical geomorphology, geomorphometry, and the E&E issue disciplines (economic/extractive geology vs. environmental geology). The linguistics of the LFIs adopted in this publication are designed so as to be open for individual amendments by the reader. An easy adaptation to different landform suites worldwide, irrespective of their climatic conditions, geodynamic setting, and age of formation, is feasible due to the use of a software and a database available on a global basis. Full article

The strong multi-stage tectonic movement caused the northwest of the North China Plain to rise and the southeast to fall. The covering layer in the plain area was several kilometers thick. In addition to expensive drilling, it is difficult to obtain deep geological information through traditional geological exploration. In this study, gravity, magnetotelluric (MT) sounding and shallow seismic methods are used to explore the basement relief and stratigraphic structure of the alluvial proluvial area in front of Taihang Mount in the North China Plain so as to understand the geological structure and sedimentary evolution of the area. The gravity anomaly map reveals the basement uplift, depression shape and faults distribution on the horizontal plane in the whole area. The MT profile reflects the geoelectric characteristics of the three-layer distribution in the Cenozoic. The seismic profile deployed on the Daxing Uplift depicts the structural style of the uplift area. The well-to-seismic calibration establishes the relationship between the lithostratigraphic and the wave impedance interface so that we can accurately obtain the shape and depth of the bedrock surface and further subdivide Cenozoic strata. Finally, we have improved the accuracy of interface inversion by using a variable density model based on density logging parameter statistics to constrain the depth of geological interfaces determined through drilling and multi-geophysical methods. Through the combination of geology and comprehensive geophysics, we have obtained the undulating patterns of Paleogene and Quaternary bottom interfaces, the structural styles of the basement and the distribution of faults in the survey area, which provide strong support for the study of neotectonic movement and sedimentary environment evolution since the Cenozoic. The successful application of this pattern proves that geophysical surveys based on prior geological information are an important supplementary tool for geological research in thick coverage areas. Full article

Bedrock geology is crucial in structuring alpine plant communities. Old studies mainly focused on the compositional differences between alpine plant communities on carbonate rocks and crystalline rocks, i.e., calcareous vs. siliceous vegetation. Increasing attention is being paid to bedrock types other than calcareous or siliceous ones, viz. those which have intermediate geochemical characteristics between pure calcareous and pure siliceous ones. Among these types of ‘intermediate’ bedrocks, calc-schists and serpentines are generally characterized by vegetation comprised of a mixture of basiphilous and acidophilous species. We selected several sites in alpine grasslands in the Western Italian Alps, on calc-schist and serpentine bedrocks, located at 2500 ± 100 m above sea level. X-ray fluorescence quantification of major and trace elements, combined with stereomicroscopic examination of bedrock samples with a petrographic approach, revealed a much broader range of bedrock types than recognized by inspection of geological maps. The vegetation investigated in our study was mostly composed of a set of species found more or less frequently in alpine silicicolous or calcicolous plant communities of the Alps and other European mountains. The carbonate content in the bedrock was one of the main drivers of variation in grassland vegetation, not necessarily related to soil pH. There were no distinctive species uniquely characterizing grassland vegetation on serpentines or calc-schists. Full article

In the Baltic States and Belarus, the Middle Devonian period is characterised by an abundant fossil record of invertebrates such as scolecodonts, brachiopods, ostracods, trilobites, bivalves, crinoids, gastropods, and tentaculites. On the other hand, there was limited diversity in the conodont and other vertebrate fauna. In this study, we introduce a newly refined ichthyofaunal assemblage from the Eifelian and Givetian epochs from the present-day regions of Belarus and Lithuania. The isolated scales of Cheirolepis are identified as C. gaugeri, C. cf. gaugeri, C. aleshkai, C. cf. aleshkai, and Cheirolepis sp., while Orvikuina is represented by the isolated scales of O. vardiaensis and Orvikuina sp. The histological analyses for the scales of Orvikuina are provided here. Moreover, Orvikuina and Cheirolepis taxa are now recognised to be widely distributed throughout the Baltic States, especially Lithuania and Belarus, as a result of these findings. Thus, this ichthyofaunal data markedly improved the biostratigraphic correlation within the study region and expanded the paleogeographic distribution of these taxa during the Eifelian and Givetian time in Laurasia. Full article

Elevational climatic heterogeneity, complex terrains, and varying subsurface properties affect the sensitivity of evapotranspiration (ET) in dryland mountain forests to hydrometeorological changes. However, the elevational distribution of ET sensitivity and its major influencing factors remain poorly understood. This study focused on the mid-altitude zone (1000–3500 m) forests in the Chinese Western Tianshan Mountains and assessed ET sensitivity to multiple climate variables, including precipitation (P) and potential evapotranspiration (PET), from 2000 to 2020. To evaluate the multi-year mean and trends in ET sensitivity, multi-source remote sensing data and regional survey data were analyzed using Spearman’s correlation coefficient, the sliding window method, and Kendall’s test. Furthermore, the relative importance of environmental variables (topography, geology, soil, and vegetation) was investigated. P and PET showed no significant trends, while ET exhibited a significant increasing trend (5.81 mm/yr, p < 0.01), particularly at elevations above 2000 m. Most forests (93.5%) showed a positive sensitivity of ET to P, and 70.0% showed a positive sensitivity of ET to PET, mainly at elevations of 1500–2500 m. Additionally, the trend in ET sensitivity to P decreased with an increasing elevation, with 64.5% showing a positive trend. Meanwhile, the trend in ET sensitivity to PET increased with elevation, with 88.1% showing a positive trend. Notably, 53.2% of the forests showed increasing ET sensitivity trends to both P and PET, primarily at elevations of 2000–3000 m with a mean normalized difference vegetation index (NDVI) of 0.56. Geological factors, particularly the hydrological properties of weathered bedrock, contributed the most (~47%) to mean sensitivity. However, geological and vegetative factors, including the NDVI and root zone water availability, were the main contributors (35% each) to the sensitivity. This study highlights the elevation-dependent sensitivity of dryland mountain forests to hydrothermal changes, with higher-elevation forests (>2000 m) being more sensitive to global warming. Full article

The concentric impact rings of the Vredefort Crater contain rocks with elevated uranium concentrations resulting from the geological signature of a meteoric impact. The decay of this uranium was estimated to lead to elevated indoor radon concentrations in the Crater, but such a study has never been carried out. This study explores the relationship between the natural radionuclides found in the geology of the Vredefort Crater and indoor radon concentrations. This was achieved through soil sampling and radionuclide surveys conducted on three impact rings, supplemented by indoor radon measurements in dwellings found in the area. In situ measurements revealed that one impact ring had higher-than-average uranium concentrations at 50 Bq/kg. Surprisingly, the measured indoor radon levels were lower than expected (113 Bq/m³). These measurements were taken during the COVID-19 pandemic and colder months, conditions that would typically result in elevated indoor radon levels. Soil samples indicated uranium activity of 30 Bq/kg, comparable to the world average of 35 Bq/kg. However, defunct mine tunnels in the area exhibited elevated radon concentrations, averaging 364 Bq/m³. The disparity between expected and measured indoor radon levels was attributed to the composition of surficial deposits, bedrock, and architectural features of the dwellings preventing radon accumulation. Full article

The Perrot Spring (1300 m a.s.l.), located to the right of the Chalamy valley in the Monte Avic Natural Park (Valle d’Aosta, Italy), is an important source of drinking water for the municipality of Champdepraz. This spring is located on a large slope characterised by the presence of a Quaternary cover of various origins (glacial, glaciolacustrine, and landslide) above the bedrock (essentially serpentinite referred to the Zermatt–Saas Zone, Penninic Domain). Water emerges at the contact between the landslide bodies and impermeable or semi-permeable glaciolacustrine deposits. The aim of this study is to define the processes and recharge zones of this spring. The analysis of the data revealed the presence of two contributions to the Perrot Spring input: a spring thaw contribution defined by a small increase in flow and an autumn contribution from rainwater infiltration. The low average temperature and low variation of the annual temperature (4.8–6.5 °C) suggest a sufficiently deep flow circuit. Chemical analyses showed a groundwater chemistry consistent with the regional geology: the hydrochemical facies is calcium–magnesium bicarbonate and isotopic analyses (δ²H and δ¹⁸O) of rainfall and spring water suggested a recharge altitude of about 2100 m a.s.l. In conclusion, this study makes it possible to recognize the water inputs to the spring discharge and to delineate its recharge area, which can be proposed to implement strategies to protect the resource. Full article

In the municipality of Enna, 80 HVSR measurements were performed, and some of these were combined with MASW seismic measurements, which made it possible to constrain the data inversion and obtain significant shear wave velocity models. A reconstruction of the depth of the seismic bedrock was performed for the whole territory, showing different depths for the higher and lower areas, as evidenced also by the Vseq parameter map. The frequency peaks identified in the H/V curve were analyzed through a cluster analysis algorithm to evaluate similarities that allow these peaks to be divided according to their stratigraphic origin. A non-hierarchical analysis algorithm modified in such a way as to avoid any a priori choice that could influence the partition has been used. The cluster analysis made it possible to divide the frequency peaks into five groupings, each of which was then associated with a seismic discontinuity, according to the geological contacts expected in the subsoil. Finally, the inversion of the data made it possible to reconstruct the geometries of these geological contact surfaces and to reconstruct a 3D model of the subsoil, which agrees well with the surface geology of the area. Full article

Fuzzy C-Means (FCM) clustering is an unsupervised machine learning algorithm that helps to integrate multiple geophysical datasets and provides automated objective-oriented information. This study analyzed ground-based Bouguer gravity and aeromagnetic datasets using the FCM clustering algorithm to classify lithological units in the western part of the North Singhbhum Mobile Belt, a mineralized belt in the Eastern Indian Craton. The potential field signatures of clusters obtained using FCM correlate remarkably well with the existing surface geology on a broad scale. The cluster associated with the highest gravity signatures corresponds to the metabasic rocks, and the cluster with the highest magnetic response represents the mica schist rocks. The cluster characterized by the lowest gravity and magnetic responses reflects the granite gneiss rocks. However, few geological formations are represented by two or more clusters, probably due to the close association of similar rock types. The fuzzy membership scores for most of the data points in each cluster show above 0.8, indicating a consistent relationship between geophysical signatures and the existing lithological units. Further, the study reveals that integrating multi-scale geophysical data helps to disclose bedrock information and litho-units under the sediment cover. Full article