Groundwater in the Algerian Sahara is an important source of water for various uses. Despite its abundance compared to surface water, it is still confronted to many problems, in terms of overexploitation and quality. Excessive mineralization of this groundwater is a major issue in the Wadi Righ region in northeastern Algerian Sahara. In this paper, we attempt to examine the groundwater mineralization source of the Terminal Complex aquifer and analyze its spatiotemporal trends by combining tools from Geographic Information Systems (GIS) with hydrogeochemical analysis of results from 117 wells between a period of four years (1995, 2012, 2015 and 2017), and 613 groundwater measurements for six years (1998, 2005, 2010, 2013, 2015 and 2017). The groundwater exhibits electrical conductivity values ranging from 2760 to 11200 μS/cm and TDS concentrations between 1934 and 8318 mg/L, indicating strong mineralization gradients from south to north. The dominant hydrochemical facies are SO₄–Cl–Mg–Ca and SO₄–Cl–Na . Hydrogeochemical diagrams reveal that water–rock interaction and evaporite dissolution are the main processes controlling salinity. Spatial mapping of EC, groundwater levels, and saturation indices (SI) indicates a progressive increase in salinity toward Chott Merouane, with an inverse correlation between groundwater level and mineralization. This study provides the first integrated spatiotemporal assessment combining hydrogeochemical and GIS-based approaches to characterize the evolution of groundwater salinity in the Wadi Righ basin, contributing new insight into the link between aquifer depletion and mineralization in the Algerian Sahara.

Tight carbonate reservoirs represent a key target for hydrocarbon exploration in structurally complex foreland basins such as the Potwar Basin of northern Pakistan. This study aims to characterize fracture networks and in-situ stress fields within the Eocene Sakesar Limestone and Chorgali Formation. A multidisciplinary approach was adopted, integrating high-resolution Formation MicroImager (FMI) logs, core observations, borehole breakout analysis, and regional structural data. Results show that the fracture network is dominated by high-angle NE-SW trending sets, with secondary NW-SE orientations reflecting local structural complexities. Fracture densities range from 3 to 12 fractures per meter, with the highest intensities occurring near fault-bounded structural highs. Stress analysis indicates a strike-slip to transpressional regime, with maximum horizontal stress (Shmax) oriented NE-SW (~045°). Estimated magnitudes are Sv = 22-24 MPa/km, Shmin = 18-20 MPa/km, and Shmax = 26-30 MPa/km. These findings identify favorable zones for horizontal well placement and hydraulic fracturing, reducing drilling risks and improving completion design. The study provides a novel, integrated framework for optimizing the development of tight carbonate reservoirs in the Potwar Basin and offers insights applicable to similar foreland fold-and-thrust belt settings.

Mediante el análisis de anomalías de temperatura superficial del mar (SSTA) en el extremo nororiental del Pacífico tropical (0°–10°N, 80°W–100°W), frente a las costas de Centroamérica, utilizando datos de reanálisis para el período 1982–2018 y aplicando técnicas de correlación lineal, se evidencian episodios de calentamiento anómalo no asociados al fenómeno El Niño en la franja ecuatorial (5°S–5°N). El evento de 2014 confirma que estos calentamientos generan efectos climáticos similares a los producidos por El Niño, sin embargo se dificulta su diferenciación. Los eventos identificados presentan características comparables al denominado El Niño costero observado frente a Perú. Para distinguirlos, se propone la clasificación El Niño costero-inca y El Niño costero-maya, debido al ámbito geográfico de ocurrencia. Se plantea la hipótesis de que estos calentamientos podrían tener un origen extratropical y estar vinculados a fluctuaciones en el Giro del Pacífico Norte. Estos hallazgos abren una nueva línea de investigación sobre fenómenos océano-atmosféricos regionales y contribuyen a mejorar la comprensión de los procesos que fortalecen el diagnóstico y la predicción climática en región.

Forest fires represent a significant and escalating environmental threat in Northern Algeria, impacting biodiversity, ecosystem services, regional climate stability, and socioeconomic systems. In recent years, the frequency and intensity of wildfires have increased due to prolonged droughts, rising temperatures, and intensified human activities. This study aims to model and assess wildfire risk by integrating Geographic Information Systems (GIS) with the Analytic Hierarchy Process (AHP), thereby providing a robust spatial decision-support framework for wildfire management. Ten environmental and anthropogenic factors were evaluated: wind speed, temperature, proximity to rivers, solar radiation, proximity to buildings, precipitation, Land Cover/Land Use (LCLU), elevation, proximity to roads, and the Normalized Difference Vegetation Index (NDVI). Each factor was assigned a weight using the AHP method to quantify its influence, and spatial overlay analysis in ArcGIS was applied to generate a comprehensive forest fire risk map. The study area was classified into three risk zones: low (34%), medium (46%), and high (20%), emphasizing the need for targeted interventions in vulnerable regions. Wind speed (0.244) and temperature (0.152) were identified as the most influential factors, while NDVI (0.037) and proximity to roads (0.054) had minimal impact. Despite its relatively low weight, NDVI remains ecologically significant due to its role in influencing vegetation density and fire propagation. The findings highlight the necessity for site-specific prevention strategies, enhanced vegetation management, and continuous monitoring. Furthermore, the study recommends extending the GIS–AHP framework to other regions of Algeria and integrating machine learning techniques to improve predictive accuracy and adaptive wildfire risk management.

This study assesses the effectiveness of satellite gravity methods in disaster risk mapping for the West Coast of Aceh, focusing on fault detection through variations in rock density. The collected data were processed to determine the complete Bouguer anomaly, with terrain corrections using an assumed density of 2.67 g/cm³. Local anomaly values ranged from -32.2 mGal to 27.2 mGal, with higher values in the northeast and lower values in the southwestern coastal areas. Spectral analysis was employed to separate regional and residual anomalies, enhancing the identification of local faults and deeper tectonic features. Gradient analysis was used to delineate geological boundaries, which were validated using geological maps. Horizontal derivatives revealed strong correlations with fault structures, while vertical derivatives highlighted major fault boundaries but were less effective at detecting smaller-scale features. The findings are expected to contribute to disaster risk reduction efforts and support sustainable development planning in West Coast of Aceh. Additionally, these results offer valuable insights for future research and decision-making in disaster mitigation.

Flood frequency analysis is an essential hydrological method for determining the size and recurrence intervals of flood events, especially in areas vulnerable to flooding. One such area where frequent flooding has a major effect on the environment, the economy, and local inhabitants is Khagaria in Bihar, India. This study uses the Log-Pearson Type III Distribution and the Gumbel Extreme Value Distribution to analyze historical discharge data spanning 40 years (1985–2024) from the Bagmati River Basin in Khagaria District. Important statistical measures, including the mean, standard deviation, and skewness, are used to predict catastrophic hydrological events and to assess flood magnitudes for various return periods. The findings show that while both methods effectively model catastrophic floods, the Log-Pearson Type III Distribution more accurately captures variability at longer return periods. The results indicate the highest recorded flood discharge of 30734.001 m³/s in 2023 and the lowest discharge of 884.77 m³/s in 2011. The analysis calculates the anticipated inundation for the return periods of 2, 10, 25, 50, 100, and 1000 years. The expected flood for the two-year return period is 2833.731 cumecs according to the Gumbel distribution, while the Log-Pearson III distribution predicts a flood of 1169.9 cumecs. It has been noted that Gumbel estimated higher values for all of the aforementioned return periods, except for 1000 years, where Log Pearson III predicted significantly higher values. The 2-year flood event has a 50% possibility of occurrence in any year with average impacts, while severe flooding events are predicted at longer return periods, with discharge values exceeding the river’s carrying capacity. The results highlight the urgent need for proactive floodplain management, infrastructure planning, and risk reduction strategies by illustrating the region's increasing flood frequency and severity. This study provides valuable information for sustainable flood management, hydrological modelling, and infrastructure design in the area under study.

The fan delta in the steep slope zone of a rift lake basin is an important oil and gas reservoir unit. The development of vertical multi-stage fan deltas has certain inheritance and vertical non-overlapping characteristics. The driving mechanism of the overall lateral migration of such multi-stage fan deltas is currently not completely clear. Taking the fan delta in the Paleogene steep slope zone of Block G in the Wenchang Sag in the northern South China Sea as the research object, based on core, logging, drilling data and high-precision 3D seismic data, using seismic facies analysis and fault displacement-rate analysis techniques to analyze the driving effect of fault segmentation activities on the lateral migration of the fan delta. The results show that: (1) The vertical multi-stage fan deltas show inherited development characteristics, and the plane shows lateral migration characteristics, with a migration rate of 0.1-0.5 km/Ma; (2) The center position of the fan delta is highly correlated with the low-velocity zone of fault activity, and 80% of the research samples are distributed in the low-velocity zone of fault activity; (3) The migration of the fan delta shows a two-stage driving characteristic of "fault-dominated positioning - geomorphic dynamic regulation". In the early stage, the segmented activity of the fault controls the injection position of the detritus in the uplift area into the lake basin. After the detritus enters the lake, it locally transforms the accommodation space in the basin, dynamically adjusts the sedimentary geomorphology, and then reshapes the sedimentary path and drives the lateral migration of the fan body.

One of the major challenges facing many nations is the lack of reliable access to an adequate water supply, particularly in areas where people struggle to obtain water for domestic use, agriculture, and industry. Because of this, it is essential to develop dependable methods that can accurately identify and allocate groundwater resources. In this study, we used integrated approaches to map the groundwater prospect zones in the Ibadan metropolis of Oyo State, Nigeria. Eleven distinct thematic parameters were formulated to demarcate areas with groundwater potential: slope (S), proximity to the water table (PSWT), geomorphology (G), drainage density (DD), landuse/landcover (LU/LC), elevation (E), lineament density (LD), soil types (ST), land-surface temperature (LST), geology (GE), and rainfall (R). Each of these eleven layers was assigned a weight through Saaty’s Analytical Hierarchy Process (AHP) before being combined and processed within the ArcGIS platform to produce a comprehensive groundwater potential zoning model. The groundwater potential map that was produced was divided into five distinct recharge zones. Areas classified as “very high” and “high” potential were found primarily in the southwestern, northwestern, and part of the northern sections of Ibadan. A “moderate” potential zone stretched across the study area from the southeastern corner up to the northeastern side. The southeastern and northeastern portions of the investigated region exhibited “low” and “very low” potential, respectively. Because the underlying bedrock lacks primary porosity, overall groundwater occurrence in the study area tends to be limited. Nonetheless, the zones identified as having very high to moderate potential can serve as valuable guides for individuals, institutions, governments, and policymakers as they plan sustainable groundwater exploration and management strategies.

Soil erosion directly affects agricultural productivity and water resource quality, but estimating soil loss is complex and costly. This study proposes a machine learning (ML) approach to predict soil loss using selected factors from the Universal Soil Loss Equation (USLE) and the Normalized Difference Vegetation Index (NDVI). We applied the Random Forest (RF) algorithm to train and validate two models using different combinations of predictors: (1) NDVI, topographic factor (LS), and land cover/management factor (CP); and (2) NDVI, LS, and soil erodibility factor (K). These variables represent land use, conservation practices, and topographic conditions in the Sorocabuçu River Basin (SRB), part of Brazil’s Atlantic Forest biome with high environmental and socioeconomic value. Soil loss was classified into three classes (in ton/ha): low (0–10.0), moderate (10.1–50.0), and high (≥50.1). A total of 3348 samples were randomly selected and proportionally distributed to reflect class representation across the study area. We used a 70/30 train-test split and standardized parameters (50 trees and four variables per node) to enable reproducibility. The model using NDVI, LS, and CP achieved 93.43% accuracy with a kappa index of 0.90. The performance was especially strong for the low-loss class, the most prevalent in the area. The second model using NDVI, LS, and K achieved 97.14% accuracy with a kappa index of 0.90, showing excellent results, particularly for the high-loss class, which poses the greatest environmental risk. These models prove effective in identifying areas at risk of severe erosion using fewer, more accessible parameters. The approach offers a scalable and practical tool for decision-makers, environmental managers, and public agencies to monitor and mitigate soil degradation, particularly in sensitive and ecologically important regions.

The Sumochagan Obo fluorite deposit, located in the northern part of Siziwangqi, Inner Mongolia, is recognized as a world-class fluorite-only deposit. However, research on the mineralogical characteristics and genesis of fluorite in this area remains relatively limited. To further elucidate the coloring and formation mechanisms of fluorite in this region, this study investigates the mineralogical and spectral characteristics of green and purple fluorite using Diamond View, infrared spectroscopy, ultraviolet-visible absorption spectroscopy, and laser Raman spectroscopy. Geochemical analysis was conducted using energy dispersive X-ray fluorescence spectrometry, wavelength dispersive X-ray fluorescence spectrometry, and inductively coupled plasma mass spectrometry (ICP-MS). In the ultraviolet-visible absorption spectrum, green fluorite samples exhibit absorption peaks at 223 nm, associated with Y and F centers. Absorption peaks at 693, 440, 360, and 276 nm are attributed to the presence of Sm²⁺, while peaks at 587 and 591 nm are caused by calcium colloidal color centers. The purple color of fluorite is likely due to YO₂ centers, as indicated by absorption peaks at 276 and 261 nm in the ultraviolet-visible absorption spectrum of purple samples. Through the Tb/Ca-Tb/La plot, it is observed that most fluorite samples from this mining area fall within the hydrothermal zone, which aligns with geological observations. The measured total rare earth elements (∑REE) of fluorite in this deposit fall between magmatic-hydrothermal fluids and meteoric water, indicating that the deposit was formed by the mixing of magmatic-hydrothermal processes with meteoric water involvement.