Geological Information Research Articles

From rockfall source area identification to susceptibility zonation: a proposed workflow tested on El Hierro (Canary Islands, Spain)

Abstract. Rockfall modelling is a common topic in the landslide literature, but a comprehensive workflow for rockfall susceptibility zonation remains a challenge. Several aspects of the modelling, such as rockfall runout simulation, are consolidated, but others still show inconsistencies and ambiguities, such as the source area identification or the criteria to obtain probabilistic susceptibility zonation. This study proposes a workflow for rockfall susceptibility zonation at the regional scale that integrates (i) source area identification criteria, (ii) deterministic runout modelling, (iii) approaches for the runout classification, and (iv) robust procedures for validation and comparison. The workflow is tested on El Hierro Island (Canary Islands, Spain) and considers the effect of different methods to identify the rockfall source areas that are used as input data for rockfall runout modelling. The runout outputs are classified to derive rockfall susceptibility zonation considering different types of classification (i.e. supervised versus unsupervised methods). The source area identification reflects situations with limited data availability and scenarios with a large amount of topographic, geological, and geomorphological information. The first approach is based on slope angle thresholding, the second uses a statistical method based on empirical cumulative distribution functions (ECDFs) of slope angle values, and the third involves the combination of multiple multivariate statistical classification models where the source area is the dependent variable and thematic information is the independent variables. The source area maps obtained from the three methods are utilized as inputs for a rockfall runout model (STONE) to derive rockfall trajectory count maps. Two classification approaches are applied to generate probabilistic susceptibility maps from the trajectory counts: unsupervised and supervised statistical methods using distribution functions. The unsupervised classification employs only the rockfall trajectory counts as input, whereas the supervised classification requires additional data on the areas already affected by rockfalls. To complement the workflow, statistical methods and metrics are proposed to verify, validate, and compare the susceptibility zonation.

Geology in renewable energy development in Ethiopia: potentials, challenges, and future directions

Ethiopia possesses vast geological resources that present significant opportunities for renewable energy development, particularly in geothermal, hydropower, and wind energy. This review explores the role of geology in harnessing these resources, evaluating geological conditions, resource availability, and the feasibility of scaling up renewable energy projects. Ethiopia’s geothermal potential is largely attributed to its location within the tectonically active East African Rift System, which provides abundant geothermal anomalies. Similarly, the country’s river systems, shaped by geological formations, offer extensive hydropower capacity, while its wind corridors, particularly in the Somali and Afar regions, hold promise for wind energy generation. Despite these opportunities, geological factors pose notable challenges to renewable energy development. Seismic activity, sedimentation, and site accessibility can complicate exploration and infrastructure development. Furthermore, gaps in geological data, limited investment, and inadequate policy frameworks hinder effective resource utilization. Addressing these challenges requires integrated geological surveys, enhanced research, and coordinated policy efforts. The review highlights key barriers, including technical constraints, financial limitations, and regulatory hurdles that impede the expansion of renewable energy projects. Successful case studies demonstrate that overcoming these obstacles necessitates strategic public-private partnerships, improved policy support, and advancements in geological research. The role of geology extends beyond resource identification to influencing the sustainability and efficiency of renewable energy projects, underscoring the importance of comprehensive geological assessments in decision-making processes. Future efforts should focus on improving geological research, expanding data availability, and implementing robust policies that support sustainable energy development. Strengthening public-private collaboration and investing in capacity-building initiatives will be essential in addressing technical and financial limitations. By leveraging its geological advantages, Ethiopia can advance its renewable energy agenda, enhance energy security, and contribute to economic growth. This review provides insights for policymakers, industry stakeholders, and researchers seeking to optimize Ethiopia’s renewable energy potential in alignment with national development objectives. The findings emphasize the need for a holistic approach that integrates geology with technological and economic considerations to ensure the long-term sustainability of Ethiopia’s renewable energy sector.

Soil Classification Maps for the Lower Tagus Valley Area, Portugal, Using Seismic, Geological, and Remote Sensing Data

The Lower Tagus Valley (LTV) region has the highest population density in Portugal, with over 3.7 million people living in the region. It has been struck in the past by several historical earthquakes, which caused significant economic and human losses. For a proper seismic hazard evaluation, the area needs detailed Vs30 and soil classification maps. Previously available maps are based on proxies, or an insufficient number of velocity measurements followed by coarse geological generalizations. The focus of this work is to significantly improve the available maps. For this purpose, more than 90 new S-wave seismic velocities measurements obtained from seismic refraction and seismic noise measurements, doubling the number used in previously available maps, are used to update available Vs30 and soil classification maps. The data points are also generalized to the available geological maps using local lithostratigraphic studies and, for the first time, satellite images of this area. The results indicate that lithological and thickness changes within each geological formation prevent a simple generalization of geophysical data interpretation based solely on geological mapping. The maps presented here are the first attempt to produce maps at a scale larger than 1:1,000,000 in Portugal, with direct shear wave velocity measurements. A tentative approach to produce more detailed maps using machine learning was also carried out, presenting promising results. This approach may be used in the future to reduce the number of shear wave measurements necessary to produce detailed maps at a finer scale.

Kriging-interpolated mapping and predictive modeling of groundwater F- and NO3- contamination with chemometric and health risk assessments in Ghana's Birimian Province.

Increasing global reports of fluoride (F-) and nitrate (NO3-) contamination in groundwater highlight the urgency of identifying pollution hotspots to safeguard public health. This study investigates groundwater quality in two agricultural regions of Ghana's Birimian province, filling a vital research gap. This study utilized a diverse set of tools, including physicochemical analyses, violin plot visualizations, the Pollution Index of Groundwater (PIG), the Water Pollution Index (WPI), health risk assessments, Pearson's correlation analysis, and artificial neural network modeling. These approaches evaluated the key factors affecting groundwater quality, identified contamination sources and hotspots, and assessed associated human health risks. Results revealed predominantly alkaline groundwater (pH 7-9), with F- ranging from 0.0 to 1.5mg/L and NO3- exceeding 500mg/L in some areas. The PIG and WPI rated 81.94-94.44% of samples suitable for consumption, with mean scores of 0.54 and 0.51, respectively, highlighting NO3-, pH, and K+ as primary quality influencers. Violin plots showed multimodal distributions in TDS, NO3-, Ca2+, and Mg2+, suggesting complex hydrogeochemical dynamics. Health risk assessments indicated oral exposure risks ranging from low to very high, with NO3- posing a sixfold greater threat than F-. Spatial analysis tied F- contamination in central and southern areas to geological formations, while higher NO3- in the northern part aligned with agricultural activities. Correlation analysis and neural network modeling confirmed the geogenic origin of F- whereas the mixed sources of NO3- strongly tied to anthropogenic inputs. These insights urge targeted remediation and offer a scalable framework for global groundwater challenges.

Application and validation of the surface-to-underground transient electromagnetic method for detecting deep water-rich area affected by shallow aquifers: a case study of the Ningdong mining area

Water-rich area present underground in coal mines pose a serious threat to the safety of coal mining operations. Electrical methods are commonly used for the detection of subsurface water-rich area, but the presence of shallow aquifers can significantly affect the accuracy of deep water-rich zone detection. In this study, surface-to-underground transient electromagnetic (SUTEM) technology and the finite-difference time-domain (FDTD) method was employed to investigate the detection of deep water-rich areas under the low-resistivity shielding of shallow aquifers. On the basis of the theoretical analysis, numerical simulation, and practical application results, it was concluded that variations in the thickness and depth of shallow aquifers have a certain effect on the transient electromagnetic (TEM) response. Compared with surface TEM, SUTEM can obtain more geological information about deep water-rich area when affected by shallow aquifers, allowing for a more accurate delineation of low-resistivity anomaly area. Therefore, SUTEM can serve as a method for the detection of deep water-rich area in coal mines under similar geological conditions.

Composition and Potential Industrial Uses of Upper Cretaceous Carbonates of the Wadi Sir Limestone (WSL) and the Amman Silicified Limestone (ASL) Formations, North Jordan

Upper Cretaceous carbonate rocks in Jordan are the main resources for construction and paint-related industrial applications. This study evaluates the elemental composition, mineralogy, and petrography of two main geological formations from two localities in northern Jordan (Hallabat, Turonian age, and Ajlun, Santonian–Campanian age) to shed light on their composition, depositional environments, and potential industrial end uses. The elemental composition of the Hallabat Wadi Sir Limestone (WSL) Formation indicates notable variability between the middle and upper parts of the WSL carbonates in the area, with higher CaO content in the middle part (mean 55 wt.%) and higher silica content observed in the upper part (mean 2 wt.%) compared with the middle part (mean 0.9 wt.%). Meanwhile, analysis of the elemental composition of the Ajlun Amman Silicified Limestone (ASL) Formation indicates that the CaO content is relatively higher in the upper part (mean 56 wt.%). In addition, the lower part is more influenced by detrital input when compared with the upper part of the studied section, in contrast to the Hallabat WSL Formation. Petrographic analysis demonstrates that the WSL and ASL samples are predominantly micritic limestone. The XRD results for the Hallabat WSL and Ajlun ASL show that the mineralogical composition is dominated by calcite (CaCO3). Statistical and PCA analyses also confirm these variabilities between the two sites, indicating that all samples from both sites were deposited under variable hydrodynamic and environmental conditions that affected their physical and chemical composition. The results show that all studied samples are in the range of pure limestone and can be used for specific industrial applications in addition to their current uses, including those in the pottery and porcelain ware, soda ash and caustic soda, steel industry, sugar, and textile production industries, thus contributing to the economic resources in Jordan.

Research on the Optimized Design of Medium and Deep Ground-Source Heat Pump Systems Considering End-Load Variation

Ground-source heat pump (GSHP) systems with medium-depth and deeply buried pipes in cold regions are highly important for addressing global climate change and the energy crisis because of their efficient, clean, and sustainable energy characteristics. However, unique geological conditions in cold climates pose serious challenges to the heat transfer efficiency, long-term stability, and adaptability of systems. This study comprehensively analyses the effects of various factors, including well depth, inner-to-outer tube diameter ratios, cementing material, the thermal conductivity of the inner tube, the flow rate, and the start–stop ratio, on the performance of a medium-depth coaxial borehole heat exchanger. Field tests, numerical simulations, and sensitivity analyses are combined to determine the full-cycle thermal performance and heat-transfer properties of medium-depth geological formations and their relationships with system performance. The results show that the source water temperature increases by approximately 4 °C and that the heat transfer increases by 50 kW for every 500 m increase in well depth. The optimization of the inner and outer pipe diameter ratios effectively improves the heat-exchange efficiency, and a larger pipe diameter ratio design can significantly reduce the flow resistance and improve system stability. When the thermal conductivity of the cementing cement increases from 1 W/(m·K) to 2 W/(m·K), the outlet water temperature at the source side increases by approximately 1 °C, and the heat transfer increases by 13 kW. However, the improvement effect of further increasing the thermal conductivity on the heat-exchange efficiency gradually decreases. When the flow rate is 0.7 m/s, the heat transfer is stable at approximately 250 kW, and the system economy and heat-transfer efficiency reach a balance. These findings provide a robust scientific basis for promoting medium-deep geothermal energy heating systems in cold regions and offer valuable references for the green and low-carbon transition in building heating systems.

From shallow to deep: Enhancing seismic resolution with weak supervision

High-resolution (HR) seismic data are crucial for accurately identifying subsurface geologic formations and reservoir properties. However, as widely observed in prestack and poststack data, seismic wave attenuation often leads to a gradual decrease in resolution with depth. This degradation leads to resolution differences between data from shallow and deep layers, characterized by high-frequency energy loss in deeper target layers. The latter could complicate the extraction of crucial deep-layer structure information, leading to increased uncertainty in reservoir modeling and significant economic losses due to our inability to image deep targets with sufficient resolution. Traditional methods with simplified assumptions about this nonlinear attenuation hinder modeling geologic complexity and variability. Deep-learning methods excel at capturing complex, nonlinear relationships but often rely heavily on scarce and costly paired labels for supervised learning. As a result, deep learning without requiring paired labels for seismic resolution enhancement has become a key research focus. This study explores a method to enhance 3D seismic data resolution using weakly supervised learning, leveraging the inherent similarity of sedimentary structures across depths. Specifically, our approach uses a relatively shallow, HR data window to transfer and extrapolate learned high-frequency information to a deeper window containing attenuated responses from deeper layers. Thereby, we achieve enhanced resolution in the target region. A tailored 3D convolutional neural network with a bidirectional cycle structure, custom-designed loss functions, and data preprocessing techniques specifically addresses the challenge of resolution differences caused by seismic wave attenuation. The effectiveness of our method is validated with synthetic and real 3D poststack migration data, demonstrating its robustness for regions near the target layer. Compared with conventional spectral whitening, our approach leverages intrinsic data characteristics more adaptively and robustly, making geologic structures more discernible.

Performance evaluation of a novel environmentally friendly lubricants for water-based drilling fluids

The continuous depletion of shallow oil and gas reserves, the exploration focus has shifted to deeper geological formations. This transition has led to significantly higher demands on the lubricity of drilling fluids. Traditional lubricants, which often contain harmful elements, are increasingly facing regulatory restrictions due to environmental and safety concerns. Consequently, the development of new, environmentally friendly lubricants has emerged as a prominent area of research in the oil and gas industry. In this study, choline chloride and 1,3-butanediol were selected as raw materials to synthesize a deep eutectic solvent, designated as HTG-1, which serves as a novel environmentally friendly drilling fluid lubricant. A series of experimental tests were carried out to comprehensively evaluate the performance of HTG-1. At temperatures below 180 °C, HTG-1 demonstrated a remarkable enhancement in the lubricating properties of both drilling fluids and filter cakes. The adhesion coefficient was effectively maintained within the range of 0.1, resulting in a reduction rate exceeding 50%. As the concentration of HTG-1 increased, the filter cakes consistently maintained a low adhesion coefficient, ranging from 0.0761 to 0.1157 at 160 °C and from 0.0642 to 0.1053 at 180 °C. Moreover, it exhibited higher reduction rate values, indicating its superior performance in reducing friction and enhancing overall drilling efficiency. HTG-1 exhibited remarkable salt resistance. The lubricating mechanism of HTG-1 involves the adsorption of choline chloride and the formation of numerous hydrogen bonds. This mechanism contributes to its excellent lubricating properties and ability to reduce friction in drilling operations.

Simulation and Modeling of Convective Mixing of Carbon Dioxide in Geological Formations

AbstractWe perform large‐scale numerical simulations of convection in 3D porous media at Rayleigh‐Darcy numbers up to . To investigate the convective mixing of carbon dioxide () in geological formations, we consider a semi‐infinite domain, where the concentration is constant at the top and no flux is prescribed at bottom. Convection begins with a diffusion‐dominated phase, transitions to convection‐driven solute finger growth, and ends with a shutdown stage as fingers reach the bottom boundary and the concentration in the system increases. For , we observe a constant‐flux regime with dissolution flux stabilizing at 0.019, approximately 13% higher than in 2D estimates. Finally, we provide a simple and yet accurate physical model describing the mass of solute entering the system throughout the whole mixing process. These findings extend solutal convection insights to 3D and high‐, improving the reliability of tools predicting the long‐term dynamics in the subsurface.

A comprehensive review on compressed air energy storage in geological formation: Experiments, simulations, and field applications

A comprehensive review on compressed air energy storage in geological formation: Experiments, simulations, and field applications

Determination of sampling points in rice fields and rainfed rice fields based on characteristics of land resources using GIS and K-mean cluster

Abstract Sample points were usually determined based on land map units (LMU) which were carried out manually so that the level of accuracy and validation is difficult to identify, and a lot of the area size eliminated was dependent on the scale of the map to be produced. However, with a combination of GIS techniques and the K-mean cluster method, the accuracy level of sample points can be optimized and LMU could be identified to less than 0,5 ha. This research was conducted using land resource data such as geological formations (Alluvium and Coastal Deposits, Argapuro Volcanics, Bagor Formation, Lahar of Old Raung, Menuran Formation, Old Ijen volcanic rock, Raung-Pendil volcanic Rock, Ringgit Formation, Volcanic Rock of Kemuning), soil type (Lithic Hapludands, Typic Dystrudepts, Typic Eutrudepts, Typic Hapludands), slope (0-8, 8-15, 15-25%), altitude (0- 300, 300-700, 700-1,000, >1,000 m above sea level), and land use that clipped to the territorial boundaries of Bondowoso Regency, East Java Province, Indonesia on Juni 2023 to February 2024. Overlaying various land resource characteristics resulted in 5,553 Land map unit (LMU) which was then selected to become 801 LMU for use of paddy fields (irrigated and rain-fed rice fields). Cluster analysis using the K-mean cluster method was carried out from 3 to 300 clusters. The optimum cluster were shown on a cluster number of 39 with consideration of Variance Decomposition (VD) as 68.23% and the most statistically and economical analysis costs. Meanwhile, the best results were obtained at the number of clusters 276 with VD 90.075% even though it was economically inefficient.

Underground hydrogen storage in geological formations: A review

Underground hydrogen storage in geological formations: A review

An Integrated Deep Learning and Physics-Constrained Upscaling Workflow for Robust Permeability Prediction in Digital Rock Physics

Summary Research on rock permeability plays a crucial role in understanding fluid flow in geological formations, which contributes significantly to addressing challenges in sustainable energy production and CO2 sequestration. Currently, numerous advanced techniques are used for predicting permeability in porous media, including experimental methods, numerical simulations, and deep learning approaches. However, existing methods often face difficulties in accurately predicting properties across multiple scales. In this study, we propose an integrated workflow that combines deep learning and physical constraints to achieve accurate and multiscale permeability prediction. The workflow begins with a 3D pore-segmentation stage, where a novel architecture is developed, achieving a segmentation accuracy exceeding 0.99. We then introduce a progressive transfer learning approach to directly predict permeability at varying scales. This method achieves R² scores of 0.94, 0.83, and 0.84 for subvolumes of 150³ voxels, 300³ voxels, and 600³ voxels (2.25 µm/voxel), respectively. To address reduced accuracy for larger volumes, we further develop a physics-constrained upscaling method. This approach enhances predictive performance, achieving R² scores of 0.98 for transitions from subvolumes of 150³ voxels to 300³ voxels and 0.99 for transitions from 300³ voxels to 600³ voxels. This research underscores the potential of integrating advanced deep learning with physics-informed constraints, providing a robust framework for accurate and scalable permeability prediction in digital rock physics and paving the way for core-scale applications and future studies.

Mitigating Leachate Contamination: Geological Investigations at Alue Lim Landfill Area, Lhokseumawe City

Abstract Geological studies are essential for identifying potential pollution in the Alue Lim Landfill Area, Lhokseumawe City. This research focuses on the physical properties of rocks, soil structure, and specific geological layers that influence water movement. The permeability and porosity of rocks are critical factors determining the ease with which leachate penetrates and migrates through geological formations. The study area encompasses the Idi formation sandstone unit (Qpi) and alluvium deposits (Qh). The Idi formation sandstone unit is characterized by fine to medium grain sizes (0.125 - 0.25 mm), interbedded with coarse sand, and exhibits a range from well to poorly sorted, moderately rounded grains with good porosity and permeability. Conversely, the alluvium deposit unit consists of clay, sand, and gravel, where the clay deposits are well-sorted with grain sizes >1/256mm, displaying poor porosity and permeability (range from 35% to 80%), and a clastic texture. The interaction between the permeable sandstone layer of the Idi Formation (aquifer) and the impermeable clay deposits in the alluvium unit (aquiclude) significantly affects leachate movement through the subsurface. Leachate rapidly migrates through the porous materials such as sand and gravel in the sandstone layers, potentially spreading contamination. In contrast, the clay layers act as barriers, limiting and redirecting leachate flow within the alluvium deposits (to the west and south). This research provides crucial insights for recommending management and mitigation strategies to address groundwater pollution in the Alue Lim Landfill Area.

Development and application of coal rock permeability test system

Permeability is one of the most important reservoir properties in coalbed methane (CBM) production, with the accurate measurement of its value being crucial for improving the efficiency of CBM extraction. For this reason, this paper independently designs and develops a coal rock permeability test system that can select the measurement methods (the steady state method and the pressure pulse decay method). In this paper, in order to fully and accurately evaluate the reliability level of the system, the variable pressure under constant external stress is tested, and the results show that the device has high measurement accuracy and convenient operation. The test results are consistent with the existing results with a classical V-shaped trend being observed, which reflected how permeability varied under gas pressure. In addition, it was found that the system could simulate the effect of differences in boundary conditions relating to seepage under different geological formations, which would provide technical support for understanding the change law concerning permeability in complex geological environments.

Evaluation of tectonic trends affecting hydrocarbon accumulation of El-Obaiyed Field, Bir Fouad area, Egypt, using gravity and dipmeter data

Bir Fouad is a significant region in the Western Desert of Egypt. It includes El-Obaiyed Field, which is considered the main Jurassic gas and condensate asset for the Shell-BAPETCO organization in the north part of the Western Desert. This field is strategically important due to its major contribution to Egypt's oil production. The purpose of the gravity data is to use disturbances in earth's gravitational field at the surface to outline the subsurface structures (faults) and determine the depth of the basement as the base of the planning area. The Bouguer gravity anomaly map was separated into regional (deep sources) and residual (shallow sources). Additionally, mathematical edge enhancement filters such as total horizontal derivative, tilt angle, and analytic signal were applied to the Bouguer data utilizing the vertical and horizontal derivatives to delineate the structural framework. Euler deconvolution and source parameter imaging methods were employed to estimate the depth of gravity sources and trends of structural elements. The gravity interpretation indicates that the main tectonics affecting the study area have east–west, east-northeast–west-southwest, west-northwest–east-southeast, northeast–southwest, and northwest–southeast trends, whereas the minor structures are aligned in north–south, north-northeast–south-southwest, and north-northwest–south-southeast trends. The results of depth estimation from applying 2D and 3D modeling, along with the available geologic information (the total depth and density logs for the available wells) illustrate a detailed basement structure map showing the basement configuration. The map reveals that the central and northwestern parts of the investigated area have shallower basement rock depths (3100 m), while the eastern and southwestern parts exhibit a deep basement structure, reaching more than 7000 m. The interpretation of advanced well-log data (the OMRI dipmeter) confirmed the resultant structural trends from the Bouguer gravity map that influence production of the Upper Safa and Lower Safa reservoirs in El-Obaiyed Field.

Tectonical-pattern of Basement Aquifers: New Insight from Combined Analysis of Wells and Electrical Resistivity Data of Bertoua Area, East Cameroon

ABSTRACT Groundwater is the main source of water for the population of the town of Bertoua (East Cameroon). However, most of the waterworks that have been built are characterized by low flow rates, which generally lead to dewatering. The aim of this study is to identify and locate the different types of aquifer in the Bertoua region and determine the influence of tectonics on their characteristics. To achieve this, satellite images and vertical electrical soundings (VES) were used. The major orientations of the lineaments highlighted are N030-060 (NE-SSW), N105-135 (ESE-WSW), and N345-10 (N-S). These directions represent 27, 12, and 9%, respectively, of the lineaments interpreted. The vertical electrical boreholes are characterized by four types of curves: KH, AK, HA, and A. The aquifer levels have resistivities between 86 and 1540 Ω m. These levels are located at a depth of 4.50–45 m. The thickness of the water table varies from 5 to 42 m. Flow rates range from 0.54 to 9.80 m3/h. The correlation between the borehole data, the geoelectric data, and the characteristics of the existing boreholes shows that the KH and AK type curves have the best hydrogeological potential. These are characterized by the presence of alterite aquifers and fracture aquifers. Those of type A have the lowest potential and are not very recommendable. The nature of the geological formations seems to play less of a role in borehole productivity. The direction of the lineaments, on the other hand, plays a key role in the productivity of these boreholes. The NE-SW direction, perpendicular to the flow of the watercourses, is the most productive, while those parallel (N-S) present less interesting potential. The model presented here is characterized by the variation in the number of terrains within the same direction. It can only be applied to areas with same geological and tectonic context and which have been affected by the same external geodynamic processes.

Radiological environmental monitoring of groundwater around phosphate deposits in North Africa-Southern Tunisia: geochemical, environmental and health factors

Groundwater contamination is a global problem that has a significant impact on human health and environmental/biota services. Southern Tunisia’s atmospheric, sediments and deep hydrothermal naturally contain radioactive isotopes originating primarily from Eocene/Ypresian phosphate deposits and extracted from the great hydrothermal reservoir of North Africa (North Western Sahara Aquifer System). These apatite deposits can be enriched in Uranium-238 and its daughter isotopes. This can have harmful effects on both the human life and the environment. The changing climate amplifies the devastating impacts of nuclear radiation resulting from phosphate mining and industry sectors particularly in Southern Tunisia. The phosphate nodules carrying radioactive elements from the Eocene have been redistributed into more recent geological formations. This has led to their widespread distribution throughout the Tunisian southern region. The results of measurements relating to natural radioactivity in southern Tunisia demonstrate that the various components’ values (238U, 232Th, 226Ra, and 40K) show significant variations depending on the location (0.05 mSv/h < gamma radiation dose < 0.36 mSv/h in the air, 0.06 mSv/h < gamma radiation dose < 0.36 mSv/h in the soil and between 0.18-0.24 mSv/y in groundwater). However, the gamma radiation levels and the overall radioactivity are high in the vicinity of phosphate deposits exceeding the standards set by the International Atomic Energy Agency of 0.3 mSv/h. This is due to the persistent presence of a dusty cloud containing metallurgical and radioactive pollutants above the phosphate mines and the hydrothermal groundwater. Influenced by meteorological parameters such as wind velocity, temperature, fog, and precipitation, groundwater hydrodynamic circulation, such pollutants are transported to neighboring regions. Mining of the Eocene deposits and related activities caused rising levels of air, soil and groundwater radioactivity on the western side. Intensified contamination can manifest in various ways and may have severe impacts on the human health and the environment.

Landslide susceptibility mapping for hazard management along Pakistan’s Balakot-Naran Route

Landslides represent a significant hazard worldwide, leading to substantial loss of life and property. In Pakistan’s Balakot Valley, severe landslides frequently disrupt key roadways, particularly along the Balakot-Naran route, which serves as a crucial artery for tourism—the region’s primary economic activity. This study aimed to create a high-resolution landslide susceptibility map for a 457 km² area along this road, where landslides are driven by factors such as intense rainfall, weak geological formations, seismic activity, and slope destabilization due to road construction. Using Geographic Information Systems (GIS) and remote sensing, we analyzed nine critical landslide-predictive factors: slope, aspect, lithology, land cover/land use, plan curvature, profile curvature, and proximity to faults, roads, and streams. Our methodology applied the frequency ratio (FR) model to 80% of the landslide inventory data for model construction, while 20% of the inventory was reserved for validation. The resulting susceptibility map, classified into low, moderate, high, and very high-risk zones using the natural breaks method in ArcGIS, indicates that slope gradient, lithology, land cover, and stream proximity are the primary contributors to landslide occurrence in this area. Model performance metrics demonstrate high predictive accuracy, with a success rate of 0.93 and a prediction rate of 0.96. The generated susceptibility map provides a robust tool for hazard management, offering valuable insights for targeted mitigation strategies and sustainable infrastructure development in this landslide-prone region. This study advanced landslide susceptibility mapping by integrating high-impact geospatial factors with an innovative, validated FR approach, supporting safer, data-driven land use planning and disaster preparedness.