Search Results (206)

The groundwater resources are increasingly stressed in the Islamabad–Rawalpindi metropolitan area of Pakistan due to unplanned urbanization, growth of industries, and inadequate waste management. In this study, the aquifer vulnerability was evaluated in the productive alluvial zone of Islamabad Watershed using a Geographic Information System (GIS)-based DRASTIC model and critically comparing it with independent measured contamination of groundwater, which is a common weakness in many machine-learning-based DRASTIC studies considering the vulnerability index as the model input. The data from 21 boreholes supplied by the Capital Development Authority (CDA) were used to map seven hydrogeological parameters in ArcGIS Pro at a 30 m resolution. The DRASTIC Index values ranged from 69 to 188, with 12.9% of the mapped watershed (209.3 km²) being rated as Very High vulnerability, mainly in the shallow western urban alluvium where water tables are below 5 m. Single-parameter sensitivity analysis showed that the most influential factors of the index were impact of the vadose zone (S_i = 1.14) and depth to water table (S_i = 1.09). A Random Forest model was trained on independently measured nitrate instead of the DRASTIC Index, but had a poor predictive skill (cross-validated R² = 0.08), and the SHapley Additive exPlanations (SHAP) analysis suggested that increased vulnerability (shallow water table and high recharge) was correlated with lower nitrate concentrations. The inverse relationship between groundwater intrinsic vulnerability and measured nitrate was statistically significant when compared to 233 groundwater samples collected at the same locations during two different campaigns (2018 and 2024) (pooled Pearson r = −0.27, p < 0.001; Spearman ρ = −0.19, p = 0.007; Kruskal–Wallis H = 14.10, p = 0.003). Levels of nitrate in both Low and Moderate vulnerability zones (6.0 and 7.7 mg/L, respectively) were higher than in Very High zones (3.4 mg/L). The inverse direction was consistent across both campaigns and robustly significant in the 2024 dataset (ρ = −0.33, p < 0.001), which covered a wider contamination gradient; in the 2018 dataset, only the parametric test was significant. Nitrate showed no significant difference between land-use classes (H = 7.23, p = 0.065) and was found as a few individual high concentrations, suggesting that these were not diffuse loading issues or intrinsic susceptibility, but were likely influenced by point sources. These results show that intrinsic DRASTIC vulnerability is useful to identify areas vulnerable to potential future contamination, but does not explain the current distribution of contamination in this aquifer, which is influenced by point-source loading and residence-time effects. To provide effective groundwater protection, intrinsic vulnerability assessment must be complemented with specific monitoring of point sources. Full article

Assessing nitrate sensitivity to hydroclimatic variability is important for evaluating water-quality vulnerability under hydroclimatic variations in coupled surface-water and groundwater systems. This study applies a hybrid, scenario-based projection framework combining a Long Short-Term Memory (LSTM) model and Weighted Regression on Time, Discharge, and Season with Projections (WRTDS-P) to examine nitrate plus nitrite responses under idealized wet and dry conditions across seven U.S. river basins and three associated groundwater wells. LSTM projections evaluate conditional sensitivity to altered precipitation forcing, while WRTDS-P projections assess discharge-conditioned responses based on empirically derived concentration–discharge relationships. Results show strong basin-scale heterogeneity in nitrate sensitivity. Agriculturally dominated Midwestern and central U.S. basins generally exhibit higher nitrate concentrations under the idealized wet scenarios, whereas basins influenced by groundwater buffering, flow regulation, or managed hydrology show weak or slightly negative wet–dry responses. For the three evaluated wells, groundwater projections show site-specific damped or delayed responses relative to nearby surface-water systems, reflecting aquifer storage and legacy nitrogen effects, although the Illinois well shows a larger projected wet–dry amplitude than the associated river. Cross-framework comparison reveals moderate agreement in response direction but notable differences in magnitude, highlighting sensitivity to model structure and forcing assumptions. These findings emphasize the value of hybrid projection frameworks for cross-framework sensitivity analysis and for interpreting nitrate vulnerability under hydroclimatic variation while accounting for uncertainty across surface-water and groundwater systems. Full article

Occlusal pits and fissures remain the most vulnerable tooth surfaces for caries initiation, and selecting a sealant that seals these areas reliably is a clinically meaningful question. We investigated the internal adaptation of four pit and fissure sealants—two resin-based and two glass ionomer-based—applied to permanent premolar teeth. Forty extracted premolars were randomly assigned to four groups (n = 10): Group 1, BeautiSealant (BS); Group 2, 3M Clinpro Sealant; Group 3, GC Fuji IX without surface coating; and Group 4, GC Fuji IX with G-Coat Plus. Following 15,000 thermal cycles, internal adaptation was assessed by X-ray microtomography (micro-CT) using silver nitrate as a tracer. No statistically significant difference was found in the overall mean gap volumes between groups (p = 0.774). The 3M™ Clinpro™ Sealant group exhibited the lowest mean gap value (3.45 ± 1.71), followed by BeautiSealant (3.89 ± 1.34) and GC Fuji IX GP^® with G-Coat Plus™ (4.93 ± 4.09), whereas the GC Fuji IX GP^® without coating group showed the highest mean value (5.56 ± 5.35). Resin-based sealants achieved better fissure penetration and marginal adaptation than the glass ionomer formulations tested, though the differences did not reach statistical significance under the conditions of this study. Full article

Groundwater resources in semi-arid regions are increasingly threatened by agricultural intensification, irrigation expansion, and climate variability. This study investigates the influence of irrigation practices on groundwater recharge and quality degradation in the semi-arid Regueb Basin, Central Tunisia, using an integrated framework combining hydrochemical analysis, irrigation water quality indices, GIS-based spatial modeling, and explainable machine learning (XAI). Thirty groundwater samples were analyzed for major physicochemical parameters and irrigation suitability indicators, including Electrical Conductivity (EC), Total Dissolved Solids (TDS), Sodium Adsorption Ratio (SAR), sodium percentage (%Na), and Irrigation Water Quality Index (IWQI). Hydrochemical facies are dominated by Ca–Mg–Cl, Na–Cl, and Ca–Mg–SO₄ water types, reflecting the combined effects of evaporite dissolution, water–rock interaction, evaporation, and irrigation return flow. Groundwater salinity is generally high, with EC values ranging from 1490 to 8710 µS/cm, while nitrate concentrations frequently exceed the World Health Organization guideline value of 50 mg/L in intensively cultivated zones, indicating significant anthropogenic contamination linked to fertilizer leaching and irrigation practices. GIS-based recharge assessment indicates that irrigation return flow may represent an important component of effective recharge in cultivated areas under semi-arid conditions while simultaneously contributing to salinization and nutrient accumulation within the aquifer system. However, quantitative partitioning of recharge sources requires further investigation using tracer-based approaches and numerical modeling. More than 40% of groundwater samples were classified as unsuitable for irrigation because of elevated salinity and sodicity hazards. To explore the relationships among irrigation water quality indicators, several machine-learning algorithms were evaluated for IWQI estimation and interpretation. Linear Regression achieved the highest performance for IWQI estimation (R² = 0.9839), reflecting the strong internal relationships among irrigation water quality indicators. SHapley Additive exPlanations (SHAP) analysis identified Residual Sodium Carbonate (RSC) as the most influential parameter controlling irrigation water quality. The results highlight the dual role of irrigation as both a recharge-enhancing mechanism and a driver of groundwater degradation. This study provides an integrated hydrochemical–GIS–XAI framework for identifying vulnerable zones and supporting sustainable groundwater management strategies in semi-arid agricultural regions. Full article

Agricultural karst watersheds are highly vulnerable to nutrient loss because strong surface water–groundwater (SW–GW) connectivity can rapidly transfer nitrogen and sulfur species from soils, agricultural activities, and human settlements into aquatic systems. However, the coupled behavior and contrasting controls of nitrate (NO₃⁻) and sulfate (SO₄²⁻) in such agroecosystems remain insufficiently understood, limiting effective nutrient and groundwater-quality management. In this study, a typical karst agricultural watershed in Southwest China was selected to investigate the sources, transformation processes, and transport pathways of NO₃⁻ and SO₄²⁻ under strong SW–GW interactions. During the rainy season, 44 groundwater and 40 surface water samples were collected for major hydrochemical and nitrate–sulfate stable isotope analyses. An integrated framework combining hydrochemical analysis, self-organizing maps (SOM), positive matrix factorization (PMF), and MixSIAR were used to identify dominant sources, quantify source contributions, and clarify controlling processes. The results showed that groundwater was mainly characterized by carbonate-controlled Ca-HCO₃ facies, whereas surface water exhibited higher mineralization and a shift toward Ca-SO₄ facies, indicating stronger external inputs and rapid hydrological responses. Nitrate was primarily controlled by external nitrogen inputs, with manure and sewage and soil nitrogen contributing 39–62% and 16–33%, respectively. Nitrate was also regulated by nitrification under oxic conditions, while denitrification was negligible. In contrast, sulfate was predominantly governed by geogenic processes, with sulfide oxidation contributing 63–83%, while other sources were minor. These contrasting controls resulted in distinct spatial and process behaviors: nitrate showed source-driven variability associated with agricultural and domestic inputs, whereas sulfate displayed process-driven accumulation mainly controlled by water–rock interactions. Strong SW–GW connectivity enhanced the transfer of anthropogenic nutrient signals, while subsurface mixing and buffering regulated their expression in groundwater and surface water. These findings demonstrate a clear decoupling between nitrate and sulfate controls in agricultural karst systems and provide a scientific basis for nutrient pollution control, groundwater protection, and sustainable agricultural water management in vulnerable karst regions. Full article

This study represents the first comprehensive characterization of fish biodiversity in the Sonche Canyon (northeastern Peru) using environmental DNA (eDNA), revealing a community of 19 taxa whose detection depended critically on a multi-marker approach. The analysis demonstrated that the use of both Metafish and Mifish-U PCR primer pairs generated a high complementarity index (0.53), allowing the capture of divergent biological signals; Metafish was essential for identifying characiformes; while Mifish-U revealed the presence of specific gymnotiformes and loricariids. The findings, supported by rarification curves confirming sampling saturation. Principal Component Analysis (PCA) revealed co-variation between the biodiversity “hotspot” in Tingorbamba and elevated nitrate concentration (6.1 mg/L), as well as the ubiquitous presence of the invasive species Oncorhynchus mykiss. In conclusion, the utility of the molecular markers and the observed co-variation between physicochemical variables and species distributions underscore the need for standardized protocols for the monitoring and conservation of fauna in the vulnerable lotic systems of the Peruvian Andes. Full article

Overexploitation of groundwater resources poses a critical challenge in major agricultural regions worldwide, yet how confined and unconfined aquifers respond differentially to governance interventions remains poorly understood. This study presents a comparative assessment of hydrochemical evolution and nitrate contamination dynamics in the Weishan Irrigation District, Shandong Province, China, contrasting pre-governance conditions (2011) with post-governance status (2022–2023) following comprehensive overexploitation control. By integrating hydrochemical characterization with stable isotope tracers (δ¹⁸O, δD, δ¹⁵N-NO₃⁻, δ¹⁸O-NO₃⁻) and Bayesian mixing models (MixSIAR), we reveal fundamentally contrasting aquifer responses to regulation. The unconfined aquifer exhibited continued degradation under persistent agricultural influence, characterized by elevated sodium, nitrate, and bicarbonate concentrations. In sharp contrast, the confined aquifer demonstrated substantial recovery, with major ion concentrations declining markedly, hydrochemical facies restored toward a pristine state, and overall water quality improving significantly to achieve full compliance with the highest-quality standards by 2023. These divergent trajectories indicate that regulatory interventions effectively restored aquitard barrier integrity, thereby shielding the confined aquifer from surface contamination, whereas the unconfined aquifer remained vulnerable to agricultural pollution. Isotope-constrained Bayesian modeling identified soil organic nitrogen, chemical fertilizers, manure/sewage, and industrial wastewater as dominant nitrate sources, with isotopic evidence confirming that the unconfined aquifer receives mixed recharge from Yellow River water and precipitation under contemporary contamination, while the confined aquifer maintains independent, pollution-free recharge. These findings demonstrate that overexploitation control can effectively rehabilitate confined aquifer systems by reestablishing natural hydrogeological barriers, but unconfined aquifers require targeted agricultural pollution mitigation. The contrasting responses highlight the necessity of aquifer-specific management strategies in irrigation-dependent regions, advancing theoretical understanding of how regulatory measures differentially affect multi-layered groundwater systems and providing a scientific basis for precision groundwater governance. Full article

Shallow groundwater systems of rural municipalities are highly vulnerable to long-term contamination from former on-site sanitation systems, while the hydrochemical response of the aquifer after sewerage network development may be delayed by several factors. In the present study, a total of 147 shallow groundwater samples collected during the summer sampling campaigns of 2018, 2019, 2023, and 2024 were analyzed for general water-quality parameters including pH, EC, NH₄⁺, NO₂⁻, NO₃⁻, PO₄⁻, Cl⁻, SO₄²⁻, microelements, and potentially toxic elements, including As, Pb, Cd, Ni, Cu, Zn, Fe, and Mn. The dataset was evaluated using descriptive statistics, Piper, Wilcox, and Gibbs diagrams, hierarchical cluster analysis, principal component analysis, and GIS-based spatial interpolation. The results indicate that, more than ten years after sewerage network development (2014), shallow groundwater in the study area still shows considerable contamination, primarily characterized by elevated mean concentrations of ammonium (0.836 mg/L), nitrate (177.43 mg/L), and chloride (313.26 mg/L), accompanied by high electrical conductivity (3115 µS/cm) and sodium enrichment (378.12 mg/L). Spatial and boxplot analyses of SAR further indicated increasing sodium-related heterogeneity after 2018, with higher local SAR values in 2023–2024. Hydrochemical diagrams revealed a shift towards Ca-Cl type to Na–Cl types, while multivariate analyses confirmed that salinity enrichment, nitrate contamination, water–rock interaction and redox-sensitive trace element mobilization act as overlapping but partly separable controls. The nitrate–chloride source plot indicated mixed contamination origins, dominated by residual sewage influence and manure-related inputs, with diffuse agricultural nitrogen leaching. Arsenic was used as a supporting indicator of mixing with wastewater; however, As was no longer detectable in most of the investigated wells, suggesting a marked reduction in the former wastewater leakage. These results support the slow attenuation of contamination in the shallow groundwater system affected by former wastewater infiltration and highlight the need for continuous monitoring. Full article

Background: Access to safe drinking water remains a critical public health concern in rural Ghana, particularly in climatically vulnerable and underserved settings. This study assessed the microbiological and chemical quality of drinking water and evaluated nitrate-related health risks in the North Gonja and North-East Gonja Districts of the Savannah Region. Methods: A cross-sectional study was conducted between January and March 2025. A total of 460 water samples were collected from groundwater sources and household storage containers. Microbial analyses targeted total coliforms and Escherichia coli. Physicochemical and chemical parameters included nitrate-nitrogen, pH, residual chlorine, major ions, and trace metals. Data was analyzed using descriptive statistics, chi-square tests, spatial interpolation, and non-carcinogenic health risk assessment based on the hazard quotient (HQ) approach. Results: Widespread microbial contamination was observed, with 91.5% of household water samples positive for total coliforms and 46.6% for E. coli. Contamination of source water was significantly higher in North Gonja than in North-East Gonja. Overall, 49.1% (n = 55) of groundwater sources exceeded the World Health Organization guideline value for nitrate-nitrogen, with exceedances predominantly occurring in North Gonja. Additionally, 67.0% (n = 75) of samples were outside the acceptable pH range (6.5–8.5), including 74 samples below 6.5 and one above 8.5. Residual chlorine was not detected in any of the samples. Health risk assessment indicated potential non-carcinogenic risks associated with nitrate exposure, particularly among infants and children. Conclusions: The study demonstrates significant microbial contamination and nitrate-related health risks in the study area, particularly in North Gonja. Interventions such as improved source protection, routine water quality monitoring, chlorination, household water treatment, and implementation of Water Safety Plans are recommended to enhance drinking water safety and reduce associated public health risks. Full article

Groundwater nitrate (NO₃⁻) pollution is a critical environmental challenge with direct implications for human health. In this work, we propose a comprehensive analytical framework that integrates multi-model intercomparison, interpretable machine learning techniques, and quantitative health risk evaluation to tackle the pressing groundwater nitrate governance dilemmas in Handan City, a representative urban area in North China. Based on 157 groundwater samples and 17 hydrochemical parameters, comparative analysis of three state-of-the-art machine learning algorithms showed that the Light Gradient Boosting Machine (LightGBM) algorithm outperformed all counterparts, delivering the optimal predictive performance (R² = 0.753, RMSE = 3.67). SHapley Additive exPlanations (SHAP) analysis identified F⁻, Ca²⁺, Cl⁻, K⁺, total hardness, and Mg²⁺ as dominant factors influencing groundwater NO₃⁻ concentrations, reflecting the combined effects of carbonate dissolution, nitrification, and anthropogenic inputs. Subsequently, we performed a health risk assessment based on the standard methodological framework issued by the United States Environmental Protection Agency (USEPA), and the results indicated that children were the most vulnerable group, with hazard quotient (HQ, a non-carcinogenic risk indicator) values reaching 1.07 in the western mountainous region, exceeding the safety threshold (HQ > 1). These findings clarify the pollution mechanisms and spatial heterogeneity, and provide targeted policy guidance for groundwater protection as well as the safeguarding of public health. Full article

Physicochemical and microbiological parameters are important indicators of drinking water quality. This study assessed the quality of groundwater used for drinking in four regions of Kosovo at 16 locations using an integrated assessment framework that combined physicochemical, microbiological, and Water Quality Index (WQI) approaches. The results reveal substantial spatial variability in water quality. While most physicochemical parameters remained within recommended limits, elevated values of total dissolved solids (up to 2792.5 mg/L), electrical conductivity (up to 2768.5 µS/cm), nitrate (up to 60.75 mg/L), and phosphate (up to 0.875 mg/L) were observed at several locations, indicating localized hydrogeochemical and anthropogenic influences. Dissolved oxygen levels were generally low (0.68–5.49 mg/L), reflecting limited aeration conditions in groundwater systems. Microbiological analysis revealed critical contamination, with Escherichia coli concentrations up to 299.9 CFU/100 mL, and all sampling sites exceeded permissible limits, indicating widespread fecal pollution and rendering the groundwater unsafe for direct consumption. WQI assessment further confirmed this condition, where 93.75% of locations were classified as medium quality using the NSF-WQI method, whereas the WA-WQI method categorized 68.75% of samples as poor and 6.25% as very poor. The novelty of this study lies in the integrated evaluation of hydrogeochemical processes and microbiological contamination using dual WQI methods and multivariate statistical analysis, providing a comprehensive understanding of groundwater degradation pathways. The findings are significant for policymakers, environmental managers, and public health authorities, highlighting the urgent need for groundwater treatment, improved sanitation infrastructure, and sustainable water resource management strategies in vulnerable regions. Full article

Surface water systems are increasingly exposed to multiple pressures generated by climate variability, intensified water resource exploitation, and evolving geopolitical dynamics. This study provides a novel contribution by identifying critical threshold effects and non-linear interactions that influence nitrate concentrations through an integrated information systems framework. It develops an integrated information-system-based analytical framework that combines hydrological, climatic, geopolitical, and strategic indicators to shape the broader contextual framework within which hydrological and climatic pressures operate, rather than serving as direct predictors. Considering the nitrate concentration in rivers as a key parameter of water quality, the paper goes beyond univariate analysis of nitrite concentration, examining its relationship with four explanatory variables: the Water Exploitation Index Plus (WEI+), the number of heat stress days (Heat_Stress), the Geopolitical Risk Index (GPR), and a proxy variable representing the presence of strategic infrastructure (Nuclear_State) using a Reduced Error Pruning Tree (REPTree) decision tree algorithm with 10-fold cross-validation. The results indicate that climatic stress emerges as the primary predictor, with a critical threshold of approximately 7.83 heat stress days, beyond which nitrate concentrations increase significantly. Under conditions of high climatic stress and intensive water exploitation (WEI+ ≥ 67.39), predicted nitrate levels exceed 20 mg/L and can reach extreme values of up to 58.82 mg/L. In contrast, low hydrological pressure (WEI+ < 0.39) combined with moderate climatic stress is associated with very low nitrate concentrations, around 2.75 mg/L. The model demonstrates strong predictive performance, with a correlation coefficient of 0.976, a Mean Absolute Error (MAE) of 0.593, a Root Mean Squared Error (RMSE) of 2.046, and a Receiver Operating Characteristic (ROC) area exceeding 0.94 for classification tasks. While geopolitical and strategic variables do not act as direct predictors, they contribute to shaping the contextual framework influencing water resource management and environmental vulnerability. Overall, the study highlights the non-linear and systemic nature of water quality dynamics and demonstrates the effectiveness of decision tree-based models within integrated information systems for supporting environmental monitoring and decision-making under conditions of climate stress and geopolitical uncertainty. Full article

We examined neocortical pathology and interneuron degeneration in neonatal hypoxia-ischemic encephalopathy (HIE). Piglets in two age groups (2–3 or 7–10 days old, n = 4–12/group) underwent global cerebral hypoxia–ischemia (HI) or sham treatment. Piglets (2–3 days old) had epidural electrodes for continuous electroencephalography (cEEG) and were treated with hypothermia (HT) or remained at normothermia (NT). Older piglets, all NT, had scalp EEG. Piglets at both ages had seizures and survived for 1–7 days. Cortical damage was assessed by hematoxylin & eosin staining and immunohistochemistry; calretinin (CR), parvalbumin (PV), and vasoactive intestinal peptide (VIP) interneurons (INs) were counted. Cell injury was assessed by DNA fragmentation and protein nitration. TAR DNA binding protein-43 (TDP43) and the DNA repair scaffold protein X-ray repair cross complementing-1 (XRCC1) were examined for degeneration mechanisms. Cortical layers 3 and 4 showed high vulnerability; damage emerged as isolated cells, focal and laminar, and distributed as panlaminar throughout different cortical regions that correlated with seizure burden. HT protected strongly against cortical damage. CR- and PV-INs were severely depleted in HI-NT piglets compared to sham. VIP INs appeared invulnerable. HT partially rescued the loss of INs. CR and PV formed nuclear and cytoplasmic inclusions that colocalized with TDP43 and XRCC1; co-immunoprecipitation identified interactions among these proteins, and tyrosine nitration of CR. CR and PV INs accumulated DNA single- and double-strand breaks and appeared as attritional apoptosis variants with proteinopathy. This cell death is identified as aggreosis. IN loss correlated with seizure presence. Postmortem human neonatal HIE cases had a similar loss of CR and PV INs and nuclear depletion of TDP43 in the neocortex. Thus, neonatal HIE causes the loss of neocortical inhibitory IN subtypes with vulnerabilities instructed by their intrinsic calcium-binding protein signature and by mechanisms consistent with toxic sequestration and the nuclear depletion of XRCC1 and TDP43 underlying DNA damage accumulation. Early inhibitory IN deletion could drive seizure evolution in HIE; TDP43 and XRCC1 could be therapeutic targets for neonatal HIE. Full article

Rapid urbanisation and intensified agriculture are major drivers of groundwater contamination in peri-urban agricultural aquifers worldwide. Contaminants including nitrates and phosphates accumulate through fertilizer use, wastewater infiltration, and groundwater overextraction, creating complex spatial and temporal patterns. Quantifying these impacts under multiple anthropogenic pressures remains a key challenge for effective water resource management. This study develops a Geo-AI ensemble modeling framework that integrates grid-based spatial analysis with advanced machine learning to assess groundwater contamination dynamics. A composite contamination index (CCI) was constructed to synthesize hydrochemical indicators into a unified measure of aquifer degradation. The AI framework uses Graph Neural Networks (GNNs), Light Gradient Boosting Machine (LightGBM), and Deep Long Short-Term Memory Networks (LSTM). Anthropogenic drivers include population growth, infrastructure density, agricultural intensity, groundwater abstraction, and hydroclimatic variability, providing a comprehensive understanding of contamination sources. The methodology was applied to the urbanised aquifer of Manouba, western suburban Tunis (Tunisia), using 295 samples collected from 85 monitoring wells between 2005 and 2025. Validation results show strong predictive performance, with LightGBM achieving R² = 0.986, RMSE = 13.14, and MAE = 1.72, outperforming GNNs (R² = 0.972) and LSTM (R² = 0.943). The spatial analysis reveals a major shift in contamination patterns, with severe contamination expanding to 55% of the study area in 2025, compared with 7% in 2005, while low and slight contamination declined from 45% to 20%. The results highlight how urban expansion reduces recharge, increases pollutant loading, and amplifies aquifer vulnerability, while agricultural intensification further accelerates contaminant accumulation and degradation processes. This framework provides a transferable, data-driven tool for mapping contamination hotspots and supporting targeted, sustainable groundwater management in peri-urban agricultural aquifers under increasing anthropogenic pressures worldwide. Full article

Degraded groundwater quality, characterized by elevated salinity and nitrate concentrations, poses significant public health concerns, particularly for vulnerable populations such as children. High content of nitrate in drinking water may lead to non-carcinogenic health risks, highlighting the urgent need for sustainable groundwater management strategies to protect both human health and environmental integrity. This study assesses the suitability of groundwater resources in the Regueb Basin for irrigation and drinking purposes, with particular attention paid to nitrate contamination. The Irrigation Water Quality Index (IWQI) indicates considerable spatial variability in groundwater quality, with values varying between 15.86 and 89.55 and a median of 41.69, reflecting differing levels of suitability for irrigation across the basin. Similarly, the Drinking Water Quality Index (DWQI) ranges from 149.16 to 982.42, with a median value of 445.71, suggesting significant concerns regarding groundwater suitability for drinking purposes. The health risk assessment (HHRA) based on the Nitrate Pollution Index (NPI) and the nitrate hazard quotient (HQ__nitrate) reveal substantial risks to human health. NPI values vary between 0.45 and 5.5, with a median of 1.65 indicating varying levels of nitrate pollution. The HQ__nitrate results show that all groundwater samples (100%) pose health risks for children (HQ > 1). For women, 75.61% of HQ values exceed the safe threshold, affecting approximately 80% of the study area, whereas for men, 48.48% of HQ values exceed 1, impacting about 36.67% of the area. Overall, these findings highlight the urgent need for effective groundwater management strategies to mitigate nitrate contamination and ensure the safe and sustainable use of the groundwater resources in the Regueb Basin. Full article