Contaminant transport from solid waste dumps: Implications for environmental degradation with a focus on capital territory regions.

Open dumping of Municipal solid waste is the main method of solid waste management in Pakistan. To investigate the impacts of leachate transportation from these waste dumps on groundwater quality, two sites were selected (I-12 in Islamabad and Lohsar in Rawalpindi), water samples were collected from existing wells during summer, winter, and rainy seasons and were analyzed for physiochemical parameters using standard methods. Most groundwater samples showed contamination and values of various parameters exceeded the desired limits set by the World Health Organization (WHO) and the National Standard for Drinking Water Quality (NSDWQ), especially during the rainy season, whereas the least contamination in groundwater samples was observed during the winter season. The results obtained were, pH: 5.75-7.87, Electrical Conductivity (EC): 103-3460 µS cm-1, Total Dissolved Solids (TDS): 436-4425 mg L-1, Total Alkalinity (TA): 190-1330 mg L-1, Total Hardness (TH): 128-676 mg L-1, Chlorides (Cl⁻): 56.7-893.3 mg L-1, Nitrates (NO3⁻): 7.8-19.9 mg L-1, Dissolved Oxygen (DO): 6.1-20.8 mg L-1, Biological Oxygen Demand (BOD): 1.0-44.0 mg L-1 and Chemical Oxygen Demand (COD): 56-272 mg L-1. The findings suggest that the magnitude of groundwater contamination from leachate transportation is intricately influenced by factors such as leachate composition, seasonal variations and distance from the dumpsite. The contamination level reduced along the distance from the dumps. Except Copper (Cu) and Zinc (Zn), the concentration of all other heavy metals including, Iron (Fe), Chromium (Cr), Nickel (Ni), Lead (Pb), Cadmium (Cd) was found above standard appreciable limits. The t-test showed a significant difference in parameter concentrations for all seasons except for Cd and Zn. The calculation of water quality index through CCME (Canadian Council of Ministers of Environment) model revealed that all the groundwater samples around both the dump sites were of poor and marginal quality. In general, the groundwater quality of both study areas is not suitable for the drinking purpose. The study suggests regular testing and treating groundwater before use, use of engineered landfills, covering landfills with clay and vegetation and use of alternative strategies like composting and recycling for waste management.

Integrating machine learning models with cross-validation and bootstrapping for evaluating groundwater quality in Kanchanaburi province, Thailand.

Exploring the potential of new models for mapping groundwater quality presents a major challenge in water resource management, particularly in Kanchanaburi Province, Thailand, where groundwater faces contamination risks. This study aimed to explore the applicability of random forest (RF) and artificial neural networks (ANN) models to predict groundwater quality. Particularly, these two models were integrated into cross-validation (CV) and bootstrapping (B) techniques to build predictive models, including RF-CV, RF-B, ANN-CV, and ANN-B. Entropy groundwater quality index (EWQI) was converted to normalized EWQI which was then classified into five levels from very poor to very good. A total of twelve physicochemical parameters from 180 groundwater wells, including potassium, sodium, calcium, magnesium, chloride, sulfate, bicarbonate, nitrate, pH, electrical conductivity, total dissolved solids, and total hardness, were investigated to decipher groundwater quality in the eastern part of Kanchanaburi Province, Thailand. Our results indicated that groundwater quality in the study area was primarily polluted by calcium, magnesium, and bicarbonate and that the RF-CV model (RMSE = 0.06, R2 = 0.87, MAE = 0.04) outperformed the RF-B (RMSE = 0.07, R2 = 0.80, MAE = 0.04), ANN-CV (RMSE = 0.09, R2 = 0.70, MAE = 0.06), and ANN-B (RMSE = 0.10, R2 = 0.67, MAE = 0.06). Our findings highlight the superiority of the RF models over the ANN models based on the CV and B techniques. In addition, the role of groundwater parameters to the normalized EWQI in various machine learning models was found. The groundwater quality map created by the RF-CV model can be applied to orient groundwater use.

Analysing agricultural plant protection product concentrations in groundwater in Germany: Nationwide database with site and compound insights.

Pesticides from agricultural practices are among the most pressing reasons why groundwater sources do not reach the good chemical status standards as required by the European Water Framework directive. Complementary to previous federal pesticide reports, we analysed groundwater-monitoring data from 13 German Länder assembled in a database consisting of 26.192 groundwater measuring sites sampled between 1973 and 2021 of in total 521 parent compounds and metabolites. This study focuses on agricultural plant protection products. The monitored substance spectrum and site density developed over time and differs between Länder. More than 95 % of all samples lie below the respective (multiple) limits of quantification (LOQ). We thus report the frequency of exceedance above concentration thresholds, which allows to compare measurements temporally and spatially. Pesticide detections were found in all aquifer types, land uses and well screen depths. Most detections of higher concentrations were found in agricultural areas, at shallow screen depth in porous aquifers. Karst aquifers showed also a higher percentage of samples in higher concentration classes. Metabolites with high mobility and persistence were found in higher concentration ranges. Herbicides and metabolites thereof dominate the top 20 of pesticides that most frequently exceed 0.1 µg L-1. The ranking for 2010-2019 includes both authorised and banned compounds and their occurrence is discussed in the context of their mobility, persistence and underlying monitoring density. Yearly exceedance frequencies above 0.05, 0.1 µg L-1 and higher thresholds of metazachlor and its esa-metabolite, and national sales data of the parent compound did not show a temporal correlation in subsequent years. This study stresses the need for the harmonisation of heterogeneous pesticide data. Further, a characterisation of the groundwater data used to analyse pesticide occurrence in selected concentration ranges for relevant site factors and compound properties and provides a pesticide ranking based on exceedance frequencies is provided.

Delineation of groundwater potential zones and its extent of contamination from the hard rock aquifers in west-Bengal, India.

This study evaluates the groundwater potential and quality in the parts of Chhotanagpur Gneissic Complex situated in the East Indian Shield. The region has faced groundwater development challenges for several decades. Therefore, in the study area, it is crucial to address the depletion of both groundwater quality and quantity, as this facilitates the identification of potential uncontaminated groundwater zones. The present study interprets the groundwater potential zones (GWPZ) utilizing an analytical hierarchical process (AHP) integrated with hydrogeochemical analysis. Several thematic maps were prepared to delineate the GPWZ. It has been found that ∼0.6% of the study area has a very good potential zone, 14.4% has good, 52% has moderate, and approximately 32% and 0.9% have low to very low prospective groundwater resources, respectively. The authentication of results was found to be excellent (91.4%) with the Area Under Curve (AUC). Analysis of hydrogeochemical data suggests that Mixed Ca-Na-HCO3, Mixed Ca-Mg-Cl, Ca-HCO3, and Na-Cl are the dominant water types in the study area. The principal component analysis suggests that Na+, Mg2+, Cl-, NO3-, and SO42- significantly contribute to groundwater chemistry. The K-means clustering and hierarchical cluster analysis classified groundwater samples into three clusters based on the hydrogeochemical characteristics. It is inferred that silicate weathering and reverse ion reactions through rock-water interaction control geogenic processes for groundwater chemistry. It is also inferred that regions with poor to unsuitable water quality indexes also have low GWPZ. Further, groundwater for irrigation is also accessed and found unsuitable at some locations. This research contributes to comprehending groundwater characteristics in analogous geological regions globally. Additionally, it assists in implementing preventive actions to mitigate groundwater contamination, consequently lowering health risks and formulating sustainable plans for the future.

Assessing groundwater quality dynamics in Madhya Pradesh: Chemical contaminants and their temporal patterns.

Groundwater is essential for maintaining ecosystem health and overall well-being as a pivotal resource for plants and animals. The increasing public consciousness of the deterioration of groundwater quality has emphasized the significance of undertaking extended evaluations of groundwater water quality, particularly in regions undergoing substantial hydrological alterations. This study primarily aims to investigate the spatio-temporal variations in groundwater quality and evaluate its suitability for potable purposes in the region of Madhya Pradesh. The study combines the Mann-Kendall (MK) test and Sen's Slope (SS) to analyze the changes in groundwater quality of all 51 districts of Madhya Pradesh, India, utilizing 12 water quality indices using MATLAB. Data was sourced from the Central Ground Water Board (CGWB) in India from the year 2001-2021. The data was then tested for homogeneity at all 1154 sampling stations using the software XLSTAT. Piper plot clustering characterized the state's groundwater as bicarbonate-calcium-magnesium (HCO3--Ca2+-Mg2+) type. The study found that the groundwater in the area is heavily impacted by high levels of nitrate and hardness, which is caused by an increase in multivalent cations. The water was classified as ranging from hard to extremely hard, and approximately 25.49% of the state's groundwater has nitrate levels that exceed the acceptable limits. The MK test showed a significant increasing correlation in trends for parameters such as nitrate, sulfate, fluoride, chloride, bicarbonate, total hardness, and electrical conductivity. It also showed a significant decreasing correlation for calcium, magnesium, potassium, and sodium. These results were observed at a confidence level of 95%. The analysis of trends has shown that human-related factors have a considerable effect on the characteristics of groundwater quality. It is therefore recommended that such human-related factors be taken into consideration when developing policies for managing groundwater resources. Consequently, these policies should emphasize the strict enforcement of rules and standards that limit the overuse of fertilizers, ensure the appropriate disposal of municipal solid and liquid wastes, and regulate industrial pollutants.

Public data from three US states provide new insights into well integrity.

Oil and gas wells with compromised integrity are a concern because they can potentially leak hydrocarbons or other fluids into groundwater and/or the atmosphere. Most states in the United States require some form of integrity testing, but few jurisdictions mandate widespread testing and open reporting on a scale informative for leakage risk assessment. In this study, we searched 33 US state oil and gas regulatory agency databases and identified records useful for evaluating well integrity in Colorado, New Mexico, and Pennsylvania. In total, we compiled 474,621 testing records from 105,031 wells across these states into a uniform dataset. We found that 14.1% of wells tested prior to 2018 in Pennsylvania exhibited sustained casing pressure (SCP) or casing vent flow (CVF)-two indicators of compromised well integrity. Data from different hydrocarbon-producing regions within Colorado and New Mexico revealed a wider range (0.3 to 26.5%) of SCP and/or CVF occurrence than previously reported, highlighting the need to better understand regional trends in well integrity. Directional wells were more likely to exhibit SCP and/or CVF than vertical wells in Colorado and Pennsylvania, and their installation corresponded with statewide increases in SCP and/or CVF occurrence in Colorado (2005 to 2009) and Pennsylvania (2007 to 2011). Testing the ground around wells for indicators of gas leakage is not a widespread practice in the states considered. However, 3.0% of Colorado wells tested and 0.1% of New Mexico wells tested exhibited a degree of SCP sufficient to potentially induce leakage outside the well.

Investigating the effects of surface water recharge on groundwater quality using hydrochemistry and ANFIS model: A case study Minia Governorate, Egypt.

Monitoring and assessing groundwater quality and quantity lays the basis for sustainable management. Therefore, this research aims to investigate various factors that affect groundwater quality, emphasizing its distance to the primary source of recharge, the Nile River. To this end, two separate study areas have been considered, including the West and West-West of Minia, Egypt, located around 30 and 80 km from the Nile River. The chosen areas rely on the same aquifer as groundwater source (Eocene aquifer). Groundwater quality has been assessed in the two studied regions to investigate the difference in quality parameters due to the river's distance. The power of machine learning to associate different variables and generate beneficial relationships has been utilized to mitigate the cost consumed in chemical analysis and alleviate the calculation complexity. Two adaptive neuro-fuzzy inference system (ANFIS) models were developed to predict the water quality index (WQI) and the irrigation water quality index (IWQI) using EC and the distance to the river. The findings of the assessment of groundwater quality revealed that the groundwater in the west of Minia exhibits suitability for agricultural utilization and partially meets the criteria for potable drinking water. Conversely, the findings strongly recommend the implementation of treatment processes for groundwater sourced from the West-West of Minia before its usage for various purposes. These outcomes underscore the significant influence of surface water recharge on the overall quality of groundwater. Also, the results revealed the uncertainty of using sodium adsorption ratio (SAR), Sodium Percentage (Na%), and Permeability Index (PI) techniques in assessing groundwater for irrigation and recommended using IWQI. The developed ANFIS models depicted perfect accuracy during the training and validation stages, reporting a coefficient of correlation (R) equal to 0.97 and 0.99 in the case of WQI and 0.96 and 0.98 in the case of IWQI. The research findings could incentivize decision-makers to monitor, manage, and sustain groundwater.

Using numerical methods for map the spatiotemporal geogenic and anthropogenic influences on the groundwater in a detrital aquifer in south Spain.

The presence of trace elements in water for domestic supply or irrigation could pose a significant toxic risk for health, due to direct consumption or bioaccumulation through the ingestion of vegetables irrigated with this water. This paper studies the presence of 41 trace elements plus nitrate and bromate in groundwater, using a multivariate statistical tool based on Principal Component Analysis and a geostatistical Kriging method to map the results. Principal Component Analysis revealed 11 significant principal components, which account for 82% and 81% of the total variance (information) respectively for the two dates analysed. Ordinary Kriging was applied to draw maps of the trace elements and PC scores. This research breaks new ground in terms of the large number of parameters used and in terms of the analysis of spatiotemporal variations in these parameters. The results obtained indicate that PC1 represents the natural quality of the aquifer (geogenic) and that there is little change in the average PC1 value between the two dates studied (June near the peak recharge point and November at the end of summer). Agriculture is the human activity that causes the greatest variations in the quality of the groundwater due to the use of fertilizers and due to watering crops with wastewater (PC7_J and PC5_N, June and November, respectively). Other elements of industrial origin, which are dangerous for human health, such as Pb, Cu and Cd, are grouped together in other principal components. The results show that the decline, or even complete absence, of natural recharge during the summer months leads to an increase in the TEs produced by human activity. This indicates that a temporary reduction in the natural recharge could worsen the quality of water resources. Based on the interpretation of the estimated maps, a synthetic map was created to show the spatial distribution of the areas affected by geogenic and anthropogenic factors. Studies with a global approach like this one are necessary in that the possible sources of pollution that could alter the quality of the groundwater and the amount of trace elements and other potentially harmful substances could increase as time goes by. The main advantage of the methodology proposed here is that it reduces the number of parameters, so simplifying the results. This makes it easier to interpret the results and manage the quality of the water.

Improving multidimensional normal cloud model to evaluate groundwater quality with grey wolf optimization algorithm and projection pursuit method.

Groundwater quality is related to several uncertain factors. Using multidimensional normal cloud model to reduce the randomness and ambiguity of the integrated groundwater quality evaluation is important in environmental research. Previous optimizations of multidimensional normal cloud models have focused on improving the affiliation criteria of the evaluation results, neglecting the weighting scheme of multiple indicators. In this study, a new multidimensional normal cloud model was constructed for the existing one-dimensional normal cloud model (ONCM) by combining the projection-pursuit (PP) method and the Grey Wolf Optimization (GWO) algorithm. The effectiveness and robustness of the model were analyzed. The results showed that compared with ONCM, the new multidimensional normal cloud model (GWOPPC model) integrated multiple evaluation parameters, simplified the modeling process, and reduced the number of calculations for the affiliation degree. Compared with other metaheuristic optimization algorithms, the GWO algorithms converged within 20 iterations during 20 simulations showing faster convergence speed, and the convergence results of all objective functions satisfy the iteration accuracy of 0.001, which indicates that the algorithm is more stable. Compared to the traditional entropy weights (0.27, 0.23, 0.47, 0.44, 0.29, 0.59, 0.12) or principal component weights (0.38, 0.33, 0.42, 0.34, 0.47, 0.29, 0.38), the weight allocation scheme provided by the GWOPP method (0.50, 0.48, 0.05, 0.38, 0.02. 0.51 and 0.32) considers the density of the distribution of all samples in the data set space. Among all 55 groundwater samples, the GWOPPC model has 21 samples with lower evaluation ratings than the fuzzy evaluation method, and 28 samples lower than the Random Forest method or the WQI method, indicating that the GWOPPC model is more conservative under the conditions of considering fuzziness and randomness. This method can be used to evaluate groundwater quality in other areas to provide a basis for the planning and management of groundwater resources.

Setting goals for agricultural nitrogen emission reduction to ensure safe air and groundwater quality: A case study of Quzhou, the North China Plain.

Setting nitrogen (N) emission targets for agricultural systems is crucial to prevent to air and groundwater pollution, yet such targets are rarely defined at the county level. In this study, we employed a forecasting-and-back casting approach to establish human health-based nitrogen targets for air and groundwater quality in Quzhou county, located in the North China Plain. By adopting the World Health Organization (WHO) phase I standard for PM2.5 concentration (35 µg m-3) and a standard of 11.3 mg NO3--N L-1 for nitrate in drinking water, we found that ammonia (NH3) emissions from the entire county must be reduced by at least 3.2 kilotons year-1 in 2050 to meet the WHO's PM2.5 phase I standard. Additionally, controlling other pollutants such as sulfur dioxide (SO2) and nitrogen oxides (NOx) is necessary, with required reductions ranging from 16% to 64% during 2017-2050. Furthermore, to meet the groundwater quality standard, nitrate nitrogen (NO3--N) leaching to groundwater should not exceed 0.8 kilotons year-1 by 2050. Achieving this target would require a 50% reduction in NH3 emissions and a 21% reduction in NO3--N leaching from agriculture in Quzhou in 2050 compared to their respective levels in 2017 (5.0 and 2.1 kilotons, respectively). Our developed method and the resulting N emission targets can support the development of environmentally-friendly agriculture by facilitating the design of control strategies to minimize agricultural N losses.

Hydrogeochemical characteristics of groundwater contamination in Guwahati city, Assam, India: Tracing the elemental Threads.

Groundwater serves as an important resource for drinking and agriculture in many countries, including India. Assessing the quality of groundwater is essential for understanding its chemical characteristics and suitability for consumption. This study aims to explore the factors affecting the hydrogeochemical changes in groundwater within Guwahati City, Assam, India. Groundwater samples were collected and analyzed for major and trace elements, as well as anion concentrations. Concentrations of As, Al, Ba, Cu, F-, Fe, Mn, and Pb exceeded the permissible limits set by both World Health Organization (WHO) and Bureau of Indian Standards (BIS), indicating serious health concerns for the local inhabitants. The distribution pattern of trace elements exceeding the guideline values is intricate, suggesting widespread contamination of groundwater throughout the study area. The Heavy Metal Pollution Index (HPI) and Water Quality Index (WQI) revealed that, except for the central zone, groundwater across the entire study area requires intervention. Piper plot illustrated that the groundwater is predominantly of Ca-HCO3 type, indicating the dominance of alkaline earth and weak acids. Groundwater hydrogeochemistry is mainly controlled by rock-water interaction and evolves through silicate weathering, carbonate weathering, and cation exchange processes. Multivariate statistical analysis identified distinct groups of groundwater based on chemical characteristics, emphasizing the role of both natural processes and anthropogenic activities in influencing groundwater quality. Regular monitoring, management, and intervention of groundwater sources throughout the study area are crucial for long-term use. The findings of this study will assist stakeholders, regulators, and policymakers in formulating strategies for the sustainable use of groundwater.

Groundwater for drinking and industrial purposes: A study of water stability and human health risk assessment from black sand mineral rich coastal region of Kerala, India.

Tempero-spatial analysis of groundwater to disseminate the level of drinking water quality and industrial suitability to meet the developmental requirement of a region is a significant area of research. Accordingly, groundwater quality and geochemical interactions prevailed in a black sand mineral rich coastal village is systematically presented in appraisal of drinking and industrial uses for economic engineering purposes. The study area focused is Alappad village, Kollam, Kerala, India has numerous ecological features in a sustainable perspective. The region is unique with placer deposits where an alluvial soil aquifer-saline water-freshwater interaction occurs. This dynamics decides the pertinent hydro geochemistry, potable and designated uses of ground water in season wise. Coastal area is hereby presented based on water quality parameters predicted with the health risk assessment model with a view on human health and cancer risk due to ions (Pb, Ni, Cu, Ba, Fe, Al, Mn, Zn) in groundwater.. To ascertain industrial usage, ground water is evaluated by Langelier saturation index (LSI), Ryznar stability index (RSI), Aggressive index (AI), Larson-Skold index (LS) and Puckorius scaling index (PSI) and inferences are complemented. Chemical weathering and evaporation processes are the natural factors controlling hydrochemistry of this aquifer. This complex coastal system has Nemerow pollution index (NPI) of moderate pollution for total dissolved ions of Fe and lesser for Cu, and Cr present in groundwater. LSI indicates, water is scale forming but non corrosive (46% in PRM, 20% in MON and 47% in POM). Water quality index (WQI) in POM (ranged 28.7-79.9) was excellent for drinking, followed by PRM (23.6-218.2) and MON (33.4-202.7) seasons. This groundwater bears temporary hardness with the dominance of Ca-Mg-HCO3 water type. Health risk assessment of non-carcinogenic risk index of trace metals (Fe, Zn, Mn, and Pb) revealed, children are at 'low risk' and 'medium' risk with Ni and Cu. The carcinogenic risk index indicated 93% of samples were high Ni induced cancer risk for children, and 87% for adults due to long term ingestion (drinking water intake) pathway. Studies specific on placer mineral deposited coastal region of India are not sufficiently reported with a focus on the above perspectives. Growing need of rare earths for material, device and energy applications, placer mineral explorations can destabilise the coastal hydrosphere. Interrelations of mineral soil - water chemistry prevailed and health hazard predicted would kindle a set of sustainable deliberations. This study summarises the drinking and industrial use of coastal groundwater for future development and human well-being on the basis of quality criteria, corrosion proneness, water stability and health risk factors.

Interplay of natural and anthropogenic inputs on the groundwater contamination of Beenaganj-Chachura block.

The present research work investigates the impact of natural and anthropogenic inputs on the chemistry and quality of the groundwater in the Beenaganj-Chachura block of Madhya Pradesh, India. A total of 50 groundwater samples were examined for nitrates, fluoride, chlorides, total dissolved solids, calcium, magnesium, pH, total hardness, and conductivity, and their impact on entropy-weighted water quality index and pollution index of groundwater (PIG) was investigated via the response surface methodology (RSM) using the central composite design. According to analytical findings, Ca, Mg, Cl-, SO42-, and NO3- exceed the desired limit and permitted limit set by the Bureau of Indian Standards (BIS) and the World Health Organization (WHO). According to PIG findings, 76, 16, and 8% of groundwater samples, respectively, fell into the insignificant, low, and moderate pollution categories. The regression coefficients of the quadratic RSM models for the experimental data provided excellent results. Thus, RSM provides an excellent means to obtain the optimized values of input parameters to minimize the PIG values.

A GIS approach for groundwater quality evaluation with entropy method and fluoride exposure with health risk assessment.

This study used the entropy water quality index to analyse the suitability of groundwater for human consumption as well as the hazard index to identify the probable non-carcinogenic dangers among children, women, and men in Nawada, Bihar (India). A total of 75 groundwater samples were taken from hand pumps and tube/bore wells in the pre-monsoon of 2017, and they were evaluated for various physicochemical characteristics. The region's groundwater major cations and anions are dominated by Ca2+ > Mg2+ and [Formula: see text] > Cl- > [Formula: see text] > NO3- > F > [Formula: see text]. Fluoride, chloride, and hardness exceeded WHO and BIS safe standards. Calcium, sodium, magnesium, sulphate, and chloride showed positive correlations, indicating water-rock interactions and mineral leaching and dissolution. Ionic cross-plots reveal that the dissolution of carbonate minerals was the primary source of calcium and magnesium in the groundwater. Also, silicate weathering contributed to these ions in the groundwater. The entropy water quality index (EWQI) found that 79% of groundwater samples were drinkable, whereas 21% were not consumable. The eastern, western, and some southern study areas have the worst drinking water quality. The main source of fluoride toxicity in people is groundwater. For all sampling locations, the HQ fluoride was calculated to be in the ranges of 0.04-3.69 (male), 0.04-3.27 (female), and 0.05-4 (children), indicating a considerably greater risk than the permissible levels (> 1). The fluoride-based non-carcinogenic risks are 27%, 20%, and 21% for children, women, and men, respectively. Children have higher risks from polluted water than adults, according to the non-carcinogenic health risk assessment. This study establishes a standard for regional and global scientific studies that help decision-makers and planners determine the quality of groundwater and fluoride risk and management.

Identification of hydrochemical fingerprints, quality and formation dynamics of groundwater in western high Himalayas.

Identifying hydrochemical fingerprints of groundwater is a challenge in areas with complex geological settings. This study takes the Gilgit-Baltistan, a complex geological area in west high Himalayas, Pakistan, as the study area to get insights into the hydrochemcial genesis and quality of groundwater in complex geological mountainous regions. A total of 53 samples were collected across the area to determine the hydrochemical characteristics and formation of groundwater. Results revealed groundwater there is characterized by slightly alkaline and soft fresh feature. Groundwater is dominated by the hydrochemical facies of HCO3·SO4-Ca·Mg type. The factor method yields three components (PCs) of principal component analysis, which together explain 75.71% of the total variances. The positive correlation of EC, TDS, Ca2+, SO42-, K+ in PC1, and NO3-, Cl- in PC2 indicate that a combination of natural and anthropogenic activities influences groundwater hydrochemistry. Water-rock interaction is the main mechanism governing the natural hydrochemistry of groundwater. The negative correlation of Cl-, SO42-, Ca2+, and Na+ with NDVI attributes to inorganic salt uptake by plant roots. Groundwater chemical composition is also affected by the type of land use. Groundwater is characterized as excellent and good water quality based on the entropy-weighted water quality index assessment, and is suitable for drinking purposes except for very few samples, while aqueous fluoride would pose potential health threats to water consumers in western high Himalayas, and infants are most at risk compared to other populations. This study will help to deepen the hydrochemial formation mechanism and exploitation suitability of groundwater resources in the mountainous areas that undergone the combined actions of nature and human activities, and provide insights into the characteristics of water environmental quality in western Himalayas area.

Groundwater Quality and Health: Making the Invisible Visible.

Linking groundwater quality to health will make the invisible groundwater visible, but there are knowledge gaps to understand the linkage which requires cross-disciplinary convergent research. The substances in groundwater that are critical to health can be classified into five types according to the sources and characteristics: geogenic substances, biogenic elements, anthropogenic contaminants, emerging contaminants, and pathogens. The most intriguing questions are related to quantitative assessment of human health and ecological risks of exposure to the critical substances via natural or induced artificial groundwater discharge: What is the list of critical substances released from discharging groundwater, and what are the pathways of the receptors' exposure to the critical substances? How to quantify the flux of critical substances during groundwater discharge? What procedures can we follow to assess human health and ecological risks of groundwater discharge? Answering these questions is fundamental for humans to deal with the challenges of water security and health risks related to groundwater quality. This perspective provides recent progresses, knowledge gaps, and future trends in understanding the linkage between groundwater quality and health.

Arsenic and fluoride exposure in drinking water caused human health risk in coastal groundwater aquifers.

Groundwater (GW) is a precious resource for human beings as we depend on it as a source of fresh drinking water, agricultural practices, industrial and domestic uses, etc. Extreme exposure of arsenic (As) and fluoride (F-) concentrations along the coastal GW aquifers of "South 24 Parganas and East Medinipur" diluted the quality of GW and created serious health issues. Various chronic health disorders such as - black foot disease, fluorosis skin cancer, cardiac problems, and other water borne diseases have been noticed in these two coastal districts. The comprehensive entropy-weighted water quality index (EWQI) and health risk assessment (HRA) were applied to evaluate the quality of GW and probable health risks in the coastal districts. Monte Carlo simulation and sensitivity analysis methods were simultaneously adopted to identify the non-carcinogenic health risk assessment due to regular ingestion of contaminated GW. As the study region is densely populated and part of the Sundarbans Ramsar site, it has greater importance at the international level along with regional importance to address the GWQ of this region. The major findings of the present study highlight that almost 55% of the study area is confronting serious GW quality issues and associated probable health risk (HR) due to the intense accumulation of As and F- in the GW aquifers of the study area. Children's health is more vulnerable due to the consumption of As containing GW, and adults are highly affected due to the intake of F- bearing GW in the coastal districts. The findings of the current study will draw the attention of hydrologists, groundwater management authorities, government bodies, and NGOs to regulate and monitor the GW aquifers routinely, enhance GW quality, minimizing the health hazards and sustainable water management in a more scientific and sustainable way which must be advantageous for coastal people.

Distribution characteristics, source identification and health risk assessment of trace metals in the coastal groundwater of Taizhou City, China.

This study was carried out to evaluate and analyze the fluctuations in groundwater for certain trace metals (Fe, Mn, Cu, Zn, Al, Cd, Cr, Pb, As, and Se) in Taizhou City over three years (2020-2022), evaluate the potential human health risks due to the consumption of groundwater. To quantify the spatiotemporal changes in groundwater trace metals, the heavy metal pollution index (HPI) and heavy metal evaluation index (HEI) were utilized. Furthermore, multivariate statistical methods were utilized to distinguish the sources of trace elements. Deterministic health risk assessment and Monte Carlo health risk simulation methods were employed to evaluate human health risks associated with exposure to trace metals. The results indicate that areas with higher pollution are in the south-central region, with low HPI increasing from 50% to 75% and low HEI from 68.75% to 81.25%, reflecting improved water quality. Correlation matrix analysis and principal component analysis (PCA) pinpointed anthropogenic sources as major trace metal contributors. Cr and As concentrations were associated with farming activities, Cd and Pb concentrations showed links to local industries such as e-waste recycling and shipbuilding. Furthermore, Cu levels in groundwater was influenced by the combined effects of industry, agriculture, and urban sewage discharge. Based on the hazard quotient (HQ) and hazard index (HI) calculations, the majority of groundwater samples did not exceed the reference values, indicating acceptable noncarcinogenic risks for both adults and children. However, the analysis of carcinogenic risk (CR) and uncertainty revealed an overall decreasing trend in carcinogenic risk, with Cr and Cd possessing the highest potential for causing carcinogenic risks. The sensitivities were 46.3%, 53.3%, and 70.3% for Cr, and 18.8%, 27.6%, and 9.3% for Cd.

Hydrogeological characteristics and water availability in the mountainous aquifer systems of Italian Central Alps: A regional scale approach.

Groundwater resources in mountain areas are strategically important to maintain adequate water supply for domestic uses, farming, industrial activities, and energy production, also considering the expected growing demand due to ongoing climate changes. Within this framework, the objective of the study is to develop a regional approach, compliant with the European requirements of the Water Framework Directive 2000/60/EC and Groundwater Directive 2006/118/EC, that could support public agencies and water companies to efficiently manage and protect the available water resources in mountainous environments. The proposed approach identifies and delineates groundwater bodies by coupling a 3D hydro-stratigraphic model with the definition of the water budget and water hydrochemical fingerprints in a geologically complex Alpine environment in Northern Italy. Sixteen groundwater bodies (GWBs) have been identified all over the 10.290 km2 area, showing an average storage capacity of more than 500 Mm³ y-1 (about 3% of the average total inflow from precipitation and snowmelt), with differences up to four times between GWBs mainly constituted of carbonate rocks and those prevalently composed of crystalline or terrigenous rocks. Groundwater quality in the study domain is generally excellent, with few exceptions due to geogenic (i.e., natural) or anthropogenic sources of contamination. The results of this study show the advantages of coupling 3D hydro-stratigraphic modelling combined with meteorological, hydrological and hydrogeological information, which consist in: i) identifying the most Strategic Storage Reservoir both in terms of quality and storage capacity; ii) evaluating the present ground- and surface water availability; iii) detecting areas of specific interest for implementing groundwater monitoring networks; iv) recognising recharge areas of the most relevant springs, to implement protection strategies of the resource.

Evaluation of groundwater for drinking and irrigation applications concerning physicochemical and ionic parameters through multiple indexing approach: a case study around the industrial zone, Punjab, India.

The seasonal quality of groundwater and its appropriateness for drinking and irrigation were assessed using a multiple indexing approach in this study. Physicochemical and ionic parameters were examined in groundwater samples near the industrial zone of Rupnagar, Punjab. To assess groundwater quality, water quality index (WQI) and pollution index were used. The Durov's, piper, wilcox and stiff diagrams were plotted to understand the hydro-chemistry. Similarly, the irrigation indices, i.e., salinity hazard, sodium adsorption ratio, soluble sodium percentage (Na%), magnesium adsorption ratio, residual sodium carbonate, permeability index and Kelley's ratio were applied to ascertain the water quality for agricultural purposes. As a result, total hardness, calcium (Ca2+), magnesium (Mg2+) and fluoride (F-) were found above the standard permissible limits. WQI analysis showed 12% samples of pre-monsoon (PRE-M) and 28% samples of post-monsoon (POS-M) were of poor quality, which may pose health risks. Hydrochemistry revealed the predominance of Ca2+, Na+, Mg2+ and HCO3- ions in the groundwater attributed to natural and anthropogenic sources. Piper diagram revealed Ca2+-Mg2+-Cl-, Na+-Cl-, Ca2+-Na+- HCO3-, Ca2+- HCO3- and Ca2+-Cl, Ca2+-HCO3- water types exist in the study area. USSL diagram showed that the samples from both seasons come under the low salinity hazard. In addition, total dissolved solids and electrical conductivity showed a strong positive association, indicating the saline nature of groundwater. Furthermore, hierarchical clustering classified groundwater into three groups (I, II and III), revealing that groundwater quality varies due to natural and anthropogenic effects. Based on the findings, the groundwater was found marginally suitable for drinking and irrigation purposes. It is therefore recommended that the groundwater is examined on a regular basis in order to maintain its quality.