This study employed geo-electrostratigraphic and hydrogeological information to model and assess subsurface structure and hydrogeological properties within a major coastal environment in Nigeria's Niger Delta region, offering a high-resolution approach to groundwater resource management. The selection of the study area was predicated on its critical residential, agricultural, and economic significance, as well as its susceptibility to hydrogeological challenges arising from rapid urbanization and industrial activities. Unlike previous studies that utilized these methods independently, this research combined different geoelectrical technologies to enhance the accuracy of subsurface characterization. The results delineated four distinct geo-layers characterized by specific resistivity values, thicknesses, and depths, providing crucial insights into groundwater infiltration, storage potential, and contamination risks. The first geo-layer (motley topsoil) had resistivity values ranging from 95.2 to 1463.7 Qm. The second layer (sandy clay) exhibited resistivity values ranging from 8.8 to 2485.1 Qm. The third layer, identified as fine sand, exhibited resistivity values ranging from 72.5 to 1332.7 Qm. The fourth layer comprised coarse sands and it exhibited a mean resistivity of 525.98 Qm, indicating a well-drained permeable formation that could serve as an additional aquifer unit. A key innovation of this study was the quantitative assessment of hydrogeological parameters, including anisotropic coefficient, transverse resistance, longitudinal conductance, and groundwater yield potential index. The anisotropic coefficient ranged from 1.0 to 1.78 (mean: 1.17), revealing minimal sediment invasion and confirming the dominance of arenaceous sediments in the Benin Formation. The groundwater yield potential index varied from 3.14 x 102 to 8.1465 x 104 Qm2, highlighting areas of significant aquifer potential. The longitudinal conductance analysis revealed that 69 % of the study area has low aquifer protectivity, underscoring the region's vulnerability to contamination. Another novel contribution was the evaluation of soil corrosivity, which has direct implications for infrastructure longevity. Results indicate that 86 % of the study area is non-corrosive, making it suitable for long-term pipeline installation, a factor rarely integrated into groundwater assessments. The study alsoadvances understanding of the Benin Formation by linking resistivity variations to arenaceous-argillitic intercalations, and this significantly influences groundwater movement and contaminant transport. By synthesizing resistivity models, hydrogeological parameters, and contamination risk assessments, this research provides a more holistic framework for sustainable groundwater management. Furthermore, this research offers a robust framework for similar hydrogeophysical assessments in other regions with comparable geological and hydrological settings. (c) 2025 Guangzhou Institute of Geochemistry, CAS. Published by Elsevier BV. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Permafrost, a major component of the cryosphere, is undergoing rapid degradation due to climate change, human activities, and other external disturbances, profoundly impacting ecosystems, hydroclimate, engineering geological stability, and infrastructure. In Northeast China, the thermal dynamics of Xing'an permafrost (XAP) are particularly complex, complicating the accurate assessment of its spatial extent. Many earlier mapping efforts, despite significant progress, fall short in accounting for some key local geo-environmental factors. Thus, this study introduces a new approach that incorporates four key driving factors-biotic, climatic, physiographic, and anthropogenic-by integrating multisource datasets and in situ observations. Four machine learning (ML) models [random forest (RF), support vector machine (SVM), logistic regression (LR), and extreme gradient boosting (XGB)] are applied to simulate permafrost distribution and probability, as well as to evaluate their performance. The results indicate that models' accuracy, ranked from highest to lowest, is as follows: RF (area under the curve (AUC) =0.88 and accuracy =0.81), XGB (0.86 and 0.77), LR (0.81 and 0.73), and SVM (0.76 and 0.66), with RF emerging as the most effective model for permafrost mapping in Northeast China. Analysis of the relationships between predictors and permafrost occurrence probability (POP) indicates that vegetation and snow cover exert nonlinear effects on permafrost, while human activities significantly reduce POP. Additionally, finer soil textures and higher soil organic matter content are positively correlated with increased POP. The modeling results, combined with field survey data, also show that permafrost is more prevalent in lowlands than in uplands, confirming the symbiotic relationship between permafrost and wetlands in Northeast China. This spatial variation is influenced by local microclimates, runoff patterns, and soil thermal properties. The primary sources of model error are uncertainties in the accuracy of multisource datasets at different scales and the reliability of observational data. Overall, ML models demonstrate great potential for mapping permafrost in Northeast China.

Subsurface processes significantly influence surface dynamics in permafrost regions, necessitating utilizing diverse geophysical methods to reliably constrain permafrost characteristics. This research uses multiple geophysical techniques to explore the spatial variability of permafrost in undisturbed tundra and its degradation in disturbed tundra in Utqia & gdot;vik, Alaska. Here, we integrate multiple quantitative techniques, including multichannel analysis of surface waves (MASW), electrical resistivity tomography (ERT), and ground temperature sensing, to study heterogeneity in permafrost's geophysical characteristics. MASW results reveal active layer shear wave velocities (Vs) between 240 and 370 m/s, and permafrost Vs between 450 and 1,700 m/s, typically showing a low-high-low velocity pattern. Additionally, we find an inverse relationship between in situ Vs and ground temperature measurements. The Vs profiles along with electrical resistivity profiles reveal cryostructures such as cryopeg and ice-rich zones in the permafrost layer. The integrated results of MASW and ERT provide valuable information for characterizing permafrost heterogeneity and cryostructure. Corroboration of these geophysical observations with permafrost core samples' stratigraphies and salinity measurements further validates these findings. This combination of geophysical and temperature sensing methods along with permafrost core sampling confirms a robust approach for assessing permafrost's spatial variability in coastal environments. Our results also indicate that civil infrastructure systems such as gravel roads and pile foundations affect permafrost by thickening the active layer, lowering the Vs, and reducing heterogeneity. We show how the resulting Vs profiles can be used to estimate key parameters for designing buildings in permafrost regions and maintaining existing infrastructure in polar regions.

Effective engineering design of structures requires a thorough understanding of the groundwater conditions of the substrate. In some situations, a three-dimensional survey is necessary. Landslides are examples of such cases. They are complex phenomena, and the main factors significantly influencing their behaviour over time are changes in slope geometry, inclination and water conditions. The article discusses the reconnaissance of the substrate structure in an area threatened by mass movements along a modernized of a railway line. The analysed area is located in the marginal zone of the North Polish glacial moraine. The geological structure of the substrate consists of: glacial tills, glaciofluvial sands, lacustrine clays, and organic soils found in periodically waterlogged areas and depressions in the terrain. Colluvial deposits, mainly consisting of clayey formations, occur on the slope of the escarpment. Surface geomorphology was interpreted using LIDAR data and field observations. Two-dimensional and three-dimensional electrical resistivity tomography (ERT) was used to obtain a detailed subsurface image, which was verified by borehole drilling and laboratory analysis of soil samples for physical properties, including grain size distribution and plasticity, as well as mechanical properties of soils. This research enabled the creation of a three-dimensional substrate model, showing the spatial distribution of colluvium and areas at risk of active landslides. The results indicate that an integrated approach, combining geophysical imaging and geotechnical reconnaissance, allows for a detailed understanding of the structure and lithology of landslide areas.

Landslides, one of the natural disaster problems, occur due to slope stability triggered by natural or human activities. Once such mass movements have begun, they are challenging to stop and, in some cases, almost impossible. Geophysical methods are very effective in determining the character and mechanical properties of landslides with a high resolution before or after mass movement. This study aims identifying the landslide that tends to continue in the & Ccedil;aml & imath;ca neighborhood of the Hendek district of Sakarya province by electrical resistivity (ERT), surface waves analysis (MASW-ReMi), and mechanical soil drilling. The low resistivity and low shear wave velocity (Vs) unit in the geophysical sections was determined as a saturated clayey thick cover layer from the borehole log. This clayey unit causes mass movement on the slip surface. Andesite-basalt-containing bedrock unit under the slip surface has been identified as having high resistivity and high velocity in geophysical sections. The integrated use of geophysical methods in this landslide, determined as the progressive mechanism, contributed significantly to the realistic modeling of the landslide internal structure.

Permafrost in the NE European Russian Arctic is suffering from some of the highest degradation rates in the world. The rising mean annual air temperature causes warming permafrost, the increase in the active layer thickness (ALT), and the reduction of the permafrost extent. These phenomena represent a serious risk for infrastructures and human activities. ALT characterization is important to estimate the degree of permafrost degradation. We used a multidisciplinary approach to investigate the ALT distribution in the Khanovey railway station area (close to Vorkuta, Arctic Russia), where thaw subsidence leads to railroad vertical deformations up to 2.5 cm/year. Geocryological surveys, including vegetation analysis and underground temperature measurements, together with the faster and less invasive electrical resistivity tomography (ERT) geophysical method, were used to investigate the frozen/unfrozen ground settings between the railroad and the Vorkuta River. Borehole stratigraphy and landscape microzonation indicated a massive prevalence of clay and silty clay sediments at shallow depths in this area. The complex refractive index method (CRIM) was used to integrate and quantitatively validate the results. The data analysis showed landscape heterogeneity and maximum ALT and permafrost thickness values of about 7 and 50 m, respectively. The active layer was characterized by resistivity values ranging from about 30 to 100 omega m, whereas the underlying permafrost resistivity exceeded 200 omega m, up to a maximum of about 10 k omega m. In the active layer, there was a coexistence of frozen and unfrozen unconsolidated sediments, where the ice content estimated using the CRIM ranged from about 0.3 - 0.4 to 0.9. Moreover, the transition zone between the active layer base and the permafrost table, whose resistivity values ranged from 100 to 200 omega m for this kind of sediments, showed ice contents ranging from 0.9 to 1.0. Taliks were present in some depressions of the study area, characterized by minimum resistivity values lower than 10 omega m. This thermokarst activity was more active close to the railroad because of the absence of insulating vegetation. This study contributes to better understanding of the spatial variability of cryological conditions, and the result is helpful in addressing engineering solutions for the stability of the railway.

An increase in air temperature leads to a significant transformation of the relief and landscapes of the Arctic. The rate of permafrost degradation, posing a profound change in the Arctic landscape, depends on air temperature, vegetation cover, type of soils, surface and ground waters. The existing international circumpolar programs dedicated to monitoring the temperature state of permafrost TSP (Thermal State Permafrost) and active layer thickness CALM (Circumpolar Active Layer Monitoring) are not sufficient for a comprehensive characterization of geocryological conditions. Yet, no standardized protocol exists for permafrost monitoring and related processes. Here, we propose a novel multi-parameter monitoring protocol and implement it for two sites in the European part of the Russian Arctic: the Yary site along the coast of the Baydaratskaya Bay in the Kara Sea (68.9 degrees N) within the continuous permafrost area and the Hanovey site in the Komi Republic (67.3 degrees N) within the discontinuous permafrost area. The protocol includes drilling boreholes, determining the composition and properties (vegetation cover and soils), snow cover measurement, geophysical imaging, active layer estimation and continuous ground temperature measurements. Ground temperature measured in 2014-2020 revealed that amplitudes of surface temperature fluctuations had no significant differences between the Yary and Hanovey sites, while that the mean annual temperatures between the areas had a considerable difference of greater than 3.0 degrees C. The period of the presence of the active layer changed with the year (e.g., ranging between 135 and 174 days in the Yary site), showing longer when the air temperatures in summer and the preceding winter were higher. Electrical resistivity tomography (ERT) allowed determining the permafrost distribution and active layer thicknesses. Thermometry results were consistent with our geophysical data. Analyzing the composition and properties of frozen soils helped better interpret the data of geophysical and temperature measurements. By integrating the study of the soil properties, ground temperatures, and ERT, our work allowed us to fully characterize these sites, suggesting that it helps better understand the thermal state at any other research sites in the European north of Russia. Our suggested monitoring protocol enables calibrating and verifying the numerical and analytical models of the heat transfer through the earth's surface.