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/).

On 1 September 2022, a giant loess landslide occurred in Huzhu Tu Autonomous County, Qinghai Province, China. This catastrophic event brought to light a unique loess fluidisation phenomenon. In specific parts of the landslide, the loess completely transformed into a viscous, fluid-like state, whereas other parts showed a deepseated slide that retained their structural integrity. In this case, loess with different sliding patterns exhibited varying levels of mobility and destructive potential. Based on the field investigation, electrical resistivity tomography was employed to investigate the groundwater condition of the slope. Subsequently, ring-shear tests were carried out to examine the mechanical properties of the sliding zone loess under different saturation degrees and its response to rainfall as a triggering factor. The results indicate that the natural water content in the original slope was unevenly distributed, influenced by local terrain and groundwater runoff. Following the initial slide caused by cumulative rainfall, the overlying sliding material with high degree of saturation was likely to fluidise due to the increase in excess porewater pressure caused by continued shearing, ultimately resulting in flow-like movement features. In contrast, in areas with a deeper groundwater table, the initial shear could only be sustained over a short distance. This study reveals a mechanism of multiple movement patterns that may coexist in giant loess landslides.

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.

Infrastructure development into peat necessitates geotechnical engineers to find a better profiling method. The conventional profiling carried out by either a localized peat augering or a borehole drilling is often subjective, lacking of details, time consuming and high cost. This paper presents results and analysis of in-situ tests that combines Electrical Resistivity Tomography (ERT) and Multichannel Analysis of Surface Wave (MASW) methods. The results show that ERT method is a good tool for delineating the boundary between peat and underlying mineral soil using their large contrast in electrical resistivity values. The ERT enables the peat thickness to be determined accurately, but lacks of information regarding peat mechanical properties. On the other hand, the MASW provides a lower contrast between the peat and the mineral soil layers compared to the ERT, but it can provide the mechanical properties of the two layers based on shear wave velocity measurements. Hence, the combination of these two methods were found to be improving the peat profiling for engineering application. The results correlate well with the existing peat auger and borehole records in the study area. The combined ERT and MASW methods is recommended to be practically used by engineers as the current best solution for peat profiling.

Slope failures are an ongoing global threat leading to significant numbers of fatalities and infrastructure damage. Landslide impact on communities can be reduced using efficient early warning systems to plan mitigation measures and protect elements at risk. This manuscript presents an innovative geophysical approach to monitoring landslide dynamics, which combines electrical resistivity tomography (ERT) and low-frequency distributed acoustic sensing (DAS), and was deployed on a slope representative of many landslides in clay rich lowland slopes. ERT is used to create detailed, dynamic moisture maps that highlight zones of moisture accumulation leading to slope instability. The link between ERT derived soil moisture and the subsequent initiation of slope deformation is confirmed by low-frequency DAS measurements, which were collocated with the ERT measurements and provide changes in strain at unprecedented spatiotemporal resolution. Auxiliary hydrological and slope displacement data support the geophysical interpretation. By revealing critical zones prone to failure, this combined ERT and DAS monitoring approach sheds new light on landslide mechanisms. This study demonstrates the advantage of including subsurface geophysical monitoring techniques to improve landslide early warning approaches, and highlights the importance of relying on observations from different sources to build effective landslide risk management strategies.

Permafrost is a widespread phenomenon in the cold regions of the globe and is under-represented in global monitoring networks. This study presents a novel low-cost, low-power, and robust Autonomous Electrical Resistivity Tomography (A-ERT) monitoring system and open-source processing tools for permafrost monitoring. The processing workflow incorporates diagnostic and filtering tools and utilizes open-source software, ResIPy, for data inversion. The workflow facilitates quick and efficient extraction of key information from large data sets. Field experiments conducted in Antarctica demonstrated the system's capability to operate in harsh and remote environments and provided high-temporal-resolution imaging of ground freezing and thawing dynamics. This data set and processing workflow allow for a detailed investigation of how meteorological conditions impact subsurface processes. The A-ERT setup can complement existing monitoring networks on permafrost and is suitable for continuous monitoring in polar and mountainous regions, contributing to cryosphere research and gaining deeper insights into permafrost and active layer dynamics. Permafrost, frozen ground in cold regions, has significant impacts on the global environment. Monitoring of permafrost is crucial because it influences the global carbon cycle, hydrology, contaminant movement, and ecosystem stability. However, current monitoring systems have limitations, particularly in remote regions like Antarctica. To tackle this challenge, a new monitoring system, Autonomous Electrical Resistivity Tomography (A-ERT), was introduced. A-ERT is a geophysical technique that employs electrical signals to study ground freezes and thaws with high precision over time. Alongside this, open-source processing tools were developed to process obtained A-ERT data and efficiently extract essential information from large data sets. The developed A-ERT system is robust, low-cost, low-power, and designed to operate in harsh conditions. Tested in Antarctica, our findings show that A-ERT data combined with processing pipelines offers a valuable tool for examining freezing and thawing processes in extreme environments. The proposed setup can contribute to a network of autonomous permafrost monitoring systems, important for cryosphere research and advancing our understanding of climate change's impact on permafrost dynamics. We present a robust low-cost Autonomous Electrical Resistivity Tomography system for permafrost monitoring in polar and mountainous regions We introduce an open-source tool for processing and inverting large data sets, enabling quick and efficient extraction of key information Field experiments conducted in Antarctica show high-temporal-resolution imaging of ground freezing and thawing dynamics

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.

This study aims to investigate the quantitative relationship between resistivity and the physical and mechanical properties of soil in different types of herbaceous slopes in the alpine arid and semi-arid loess area. The research is conducted in the self-built test area of Changlinggou Basin in Xining Basin. Five types of slopes, including Elymus nutans Griseb., Elymus sibiricus Linn., Agropyron trachycaulum Linn. Gaertn., Festuca arundinacea Schreb., and bare slopes are selected as the research objects. These slopes have been planted for 3 years. The study compares the effects of different herbaceous roots on the physical and mechanical properties of the soil by conducting tests of soil density and water content, and direct shear test on the soils with and without root systems. Based on these tests, a quantitative relationship between the physical and mechanical properties of different slope soils and resistivity data is established using 2D electrical resistivity tomography. The results show that: (1) Compared with the bare slope without planting, the maximum increase of soil moisture content in the upper layer (0-10 cm) of the Elymus sibiricus Linn. slope is 26.53%. The average soil density of the upper layer (0-10 cm) of the Festuca arundinacea Schreb. slope was 18.30% lower than that of the bare slope. The maximum added value of soil cohesion in the upper layer (0-10 cm) of the Elymus nutans Griseb. slope is 2.75 times that of the bare slope. (2) The resistivity characteristics of five types of slopes are affected by root distribution and slope position factors, and the resistivity value decreases with the increase of depth. The soil resistivity value of the four herbaceous slopes is larger than that of the bare slope at 0-20 cm, which is the approximately range of root distribution. (3) There are fitting equations between the physical and mechanical properties and resistivity data of five kinds of slope soils (with correlation coefficients R-2 ranging from 0.48 to 0.77), and the Pearson correlation analysis shows that the cohesion c value of the slope soil has the highest correlation with resistivity, with an R-2 value of 0.765. The results of this study demonstrate that 2D resistivity tomography technology can reflect the physical and mechanical properties of slope soil, as well as the distribution characteristics of plant roots. This provides a theoretical basis and practical guidance for effectively preventing and controlling soil erosion, shallow landslides, and other disasters in the study area and its surrounding areas.

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.