Assessment of coastal river water quality in Bangladesh: Implications for drinking and irrigation purposes.

Saltwater intrusion in the coastal areas of Bangladesh is a prevalent phenomenon. However, it is not conducive to activities such as irrigation, navigation, fish spawning and shelter, and industrial usage. The present study analyzed 45 water samples collected from 15 locations in coastal areas during three seasons: monsoon, pre-monsoon, and post-monsoon. The aim was to comprehend the seasonal variation in physicochemical parameters, including water temperature, pH, electrical conductivity (EC), salinity, total dissolved solids (TDS), hardness, and concentrations of Na+, K+, Mg2+, Ca2+, Fe2+, HCO3-, PO43-, SO42-, and Cl-. Additionally, parameters essential for agriculture, such as soluble sodium percentage (SSP), sodium absorption ratio (SAR), magnesium absorption ratio (MAR), residual sodium carbonate (RSC), Kelly's ratio (KR), and permeability index (PI), were examined. Their respective values were found to be 63%, 16.83 mg/L, 34.92 mg/L, 145.44 mg/L, 1.28 mg/L, and 89.29%. The integrated water quality index was determined using entropy theory and principal component analysis (PCA). The resulting entropy water quality index (EWQI) and SAR of 49.56% and 63%, respectively, indicated that the samples are suitable for drinking but unsuitable for irrigation. These findings can assist policymakers in implementing the Bangladesh Deltaplan-2100, focusing on sustainable land management, fish cultivation, agricultural production, environmental preservation, water resource management, and environmental protection in the deltaic areas of Bangladesh. This research contributes to a deeper understanding of seasonal variations in the hydrochemistry and water quality of coastal rivers, aiding in the comprehension of salinity intrusion origins, mechanisms, and causes.

Pollution characteristics and source apportionment of heavy metal(loid)s in soil and groundwater of a retired industrial park.

Heavy metal(loid)s (HMs) pollution has become a common and complex problem in industrial parks due to rapid industrialization and urbanization. Here, soil and groundwater were sampled from a retired industrial park to investigate the pollution characteristics of HMs. Results show that Ni, Pb, Cr, Zn, Cd, and Cu were the typical HMs in the soil. Source analysis with the positive matrix factorization model indicates that HMs in the topsoil stemmed from industrial activities, traffic emission, and natural source, and the groundwater HMs originated from industrial activities, groundwater-soil interaction, groundwater-rock interaction, and atmosphere deposition. The sequential extraction of soil HMs reveals that As and Hg were mainly distributed in the residue fraction, while Ni, Pb, Cr, Zn, Cd, and Cu mainly existed in the mobile fraction. Most HMs either in the total concentration or in the bioavailable fraction preferred to retain in soil as indicated by their high soil-water partitioning coefficients (Kd), and the Kd values were correlated with soil pH, groundwater redox potential, and dissolved oxygen. The relative stable soil-groundwater circumstance and the low active fraction contents limited the vertical migration of soil HMs and their release to groundwater. These findings increase our knowledge about HMs pollution characteristics of traditional industrial parks and provide a protocol for HMs pollution scrutinizing in large zones.

Geographical distribution of radon and associated health risks in drinking water samples collected from the Mulazai area of Peshawar, Pakistan.

Geospatial methods, such as GIS and remote sensing, map radon levels, pinpoint high-risk areas and connect geological traits to radon presence. These findings direct health planning, focusing tests, mitigation, and policies where radon levels are high. Overall, geospatial analyses offer vital insights, shaping interventions and policies to reduce health risks from radon exposure. There is a formidable threat to human well-being posed by the naturally occurring carcinogenic radon (222Rn) gas due to high solubility in water. Under the current scenario, it is crucial to assess the extent of 222Rn pollution in our drinking water sources across various regions and thoroughly investigate the potential health hazards it poses. In this regard, the present study was conducted to investigate the concentration of 222Rn in groundwater samples collected from handpumps and wells and to estimate health risks associated with the consumption of 222Rn-contaminated water. For this purpose, groundwater samples (n = 30) were collected from handpumps, and wells located in the Mulazai area, District Peshawar. The RAD7 radon detector was used as per international standards to assess the concentration of 222Rn in the collected water samples. The results unveiled that the levels of 222Rn in the collected samples exceeded the acceptable thresholds set by the US Environmental Protection Agency (US-EPA) of 11.1 Bq L-1. Nevertheless, it was determined that the average annual dose was below the recommended limit of 0.1 mSv per year, as advised by both the European Union Council and the World Health Organization. In order to avoid the harmful effects of such excessive 222Rn concentrations on human health, proper ventilation and storage of water in storage reservoirs for a long time before use is recommended to lower the 222Rn concentration.

Analysis of the chemical characteristics and causes of high total hardness of groundwater in Jianghan Plain, China.

Familiarity with the chemical characteristics of regional groundwater can provide important guidance and reference for the development of regional groundwater exploitation. Jianghan Plain has been reported to have high groundwater total hardness (TH), resulting in the inability of local groundwater to be directly used as drinking water. In order to explore the causes of high TH, the paper analyzed the hydrochemical characteristics of shallow groundwater in Jianghan Plain combined with software of SPSS, JMP, and PHEEQC. The results showed that the cations in the groundwater in the area were mainly Ca2+, while the anions were mainly HCO3-. 20% of groundwater exceed the China national guideline for TH (i.e., 450 mg/L). The groundwater chemistry in the study area was controlled by three main factors of dissolution of carbonate rocks, human activities, and redox conditions, among which the interaction between water and rock had the greatest impact. The water carbonate rock interaction within Jianghan Plain was affected by various factors such as water flow and aquifers and showed a gradually weakening trend from west to east. This work not only strengthened the understanding of the causes of the high TH of groundwater in the region, but also provided reference value for regional groundwater environmental management.

Integrated assessment of pollution status of MSW sites: a case study of Uyo, Ikot Ekpene and Oron, Akwa Ibom State, southern Nigeria.

One of the main causes of contaminated groundwater in emerging nations is improper trash disposal in urban areas, which affects the level of groundwater contamination caused by contaminants of municipal solid waste (MSW) origin within the three local government headquarters in Akwa Ibom State, southeastern Nigeria. The main thrust of this research survey is to assess the level of groundwater contaminations and their consequences. The research used statistical data generated from the Electrical Resistivity Survey (ERS) in combination with hydrogeochemical investigations. Analysis of variance of resistivity between Uyo, Ikot Ekpene and Oron was carried out. The test result indicated significant difference in contamination among the three cities. This was followed by a t-test between each pair of dump and control sites in the three cities. The test results showed significant difference between each control and dumpsite. The results showed that leachate layer conductivity is always higher than that of the layer above it. All water samples from boreholes close to the dumpsites were identified by hydrogeochemical analysis to exhibit pH (3.70-4.15) lower than the permissible limit of the WHO; few water samples exhibit increased electrical conductivity (EC), cadmium and total dissolved solids (TDS). Similarly, the bacteriological analyses indicated a high level of microbial load due to the waste dump. Formations found in boreholes close to the dumpsite have litho-correlations which depict intercalations of comparatively impermeable and porous materials. The findings reveal that leachate (contaminate) travels slowly downward, allowing for physical, chemical and biological processes to filter out impurities before they get to the aquifer. It is recommended that no new water supply wells should be placed in areas of abnormally low resistivity and physicochemical and bacteriological parameters, until the reasons for these values are properly assessed.

Identification of groundwater pollution sources and health risk assessment in the Fengshui mining area of Central Shandong, China.

The crux of groundwater protection lies in a profound understanding of the sources of pollutants and their impacts on human health. This study selected 47 groundwater samples from the Fengshui mining area in central Shandong Province, China, employing advanced hydrogeochemical techniques, positive matrix factorization (PMF), and Monte Carlo analysis methods, aimed at unveiling the characteristics, origins, and health risks of water pollutants. The results indicated that the majority of samples exhibited a slightly alkaline nature. Notably, the concentrations of fluoride (F-) and nitrate (NO3-) exceeded China's safety standards in 40.43% and 23.40% of the samples, respectively. Moreover, a water quality index (WQI) below 50 was observed in approximately 68.09% of the sites, suggesting that the water quality in these areas generally met acceptable levels. However, regions with higher WQI values were predominantly located in the northern and southern parts of the mining area. PMF analysis revealed that regional geological and industrial activities were the primary factors affecting water quality, followed by mining discharges, fundamental geological and agricultural processes, and leachate enrichment activities. The health risk assessment highlighted the heightened sensitivity of the youth demographic to fluoride, with a more pronounced non-carcinogenic risk compared to nitrate, affecting about 31.89% of the youth population. Hence, it is imperative for local authorities and relevant departments to take prompt actions to remediate groundwater contamination to minimize public health risks.

Groundwater microbial communities reflect geothermal activity on volcanic island.

Studies of the effects of volcanic activity on the Hawaiian Islands are extremely relevant due to the past and current co-eruptions at both Mauna Loa and Kilauea. The Big Island of Hawai'i is one of the most seismically monitored volcanic systems in the world, and recent investigations of the Big Island suggest a widespread subsurface connectivity between volcanoes. Volcanic activity has the potential to add mineral contaminants into groundwater ecosystems, thus affecting water quality, and making inhabitants of volcanic islands particularly vulnerable due to dependence on groundwater aquifers. As part of an interdisciplinary study on groundwater aquifers in Kona, Hawai'i, over 40 groundwater wells were sampled quarterly from August 2017 through March 2019, before and after the destructive eruption of the Kilauea East Rift Zone in May 2018. Sample sites occurred at great distance (~80 km) from Kilauea, allowing us to pose questions of how volcanic groundwater aquifers might be influenced by volcanic subsurface activity. Approximately 400 water samples were analyzed and temporally split by pre-eruption and post-eruption for biogeochemical analysis. While most geochemical constituents did not differ across quarterly sampling, microbial communities varied temporally (pre- and post-eruption). When a salinity threshold amongst samples was set, the greatest microbial community differences were observed in the freshest groundwater samples. Differential analysis indicated bacterial families with sulfur (S) metabolisms (sulfate reducers, sulfide oxidation, and disproportionation of S-intermediates) were enriched post-eruption. The diversity in S-cyclers without a corresponding change in sulfate geochemistry suggests cryptic cycling may occur in groundwater aquifers as a result of distant volcanic subsurface activity. Microbial communities, including taxa that cycle S, may be superior tracers to changes in groundwater quality, especially from direct inputs of subsurface volcanic activity.

Groundwater quality characterization using an integrated water quality index and multivariate statistical techniques.

This study attempts to characterize and interpret the groundwater quality (GWQ) using a GIS environment and multivariate statistical approach (MSA) for the Jakham River Basin (JRB) in Southern Rajasthan. In this paper, analysis of various statistical indicators such as the Water Quality Index (WQI) and multivariate statistical methods, i.e., principal component analysis and correspondence analysis (PCA and CA), were implemented on the pre and post-monsoon water quality datasets. All these methods help identify the most critical factor in controlling GWQ for potable water. In pre-monsoon (PRM) and post-monsoon (POM) seasons, the computed value of WQI has ranged between 28.28 to 116.74 and from 29.49 to 111.98, respectively. As per the GIS-based WQI findings, 63.42 percent of the groundwater samples during the PRM season and 42.02 percent during the POM were classed as 'good' and could be consumed for drinking. The Principal component analysis (PCA) is a suitable tool for simplification of the evaluation process in water quality analysis. The PCA correlation matrix defines the relation among the water quality parameters, which helps to detect the natural or anthropogenic influence on sub-surface water. The finding of PCA's factor analysis shows the impact of geological and human intervention, as increased levels of EC, TDS, Na+, Cl-, HCO3-, F-, and SO42- on potable water. In this study, hierarchical cluster analysis (HCA) was used to categories the WQ parameters for PRM and POR seasons using the Ward technique. The research outcomes of this study can be used as baseline data for GWQ development activities and protect human health from water-borne diseases in the southern region of Rajasthan.

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.

Evaluating health risks from the release of trace elements to groundwater by rock-water interaction in a weathered gneissic aquifer.

High concentration of trace elements in groundwater poses more health risks to humans by drinking groundwater and dermal contact. This work aimed to assess the trace element concentration in groundwater, water quality for drinking purposes, and its effect on human health upon prolonged consumption. The study was carried out in the gneissic terrain of Perambalur District, Tamil Nadu, India, where groundwater is used mainly for drinking, agricultural, and domestic purposes. Hydrochemistry, water quality, and health risk assessments of trace elements from 44 groundwater samples for pre- and post-monsoon were determined by drinking water quality, hazard quotient, hazard index, and carcinogenic risk. The dominance of trace elements in groundwater was in the order of Zn > Fe > Cu > Ni > Te > Pb > Co. Ni and Co are released more during the post-monsoon, and Zn, Fe, Cu, and Pb concentration during the pre-monsoon. The dominant type of groundwater was Ca-HCO3 and mixed Ca-Mg-Cl type. The dissolution of fissile hornblende biotite gneissic rock dissolves more trace elements to groundwater than charnockite rock. The correlation matrix indicates that major ion and trace elements were positively good in groundwater during the pre-monsoon and post-monsoon 2018. The principal component analysis suggests that the weathering of rocks, rainwater recharge, and evaporation processes controlled the hydrochemistry of trace and major ions. The concentration of Pb, Ni, and Cd elements exceeded the permissible limit of BIS and WHO; these elements are unsuitable for drinking. The trace element concentration in groundwater was good for drinking and irrigation in the study area, except in a few wells. The hazard quotient and hazard index were computed, which revealed that non-carcinogenic risk to human health by drinking groundwater was more of a problem for children than adults. This study will help prevent children from health risks of trace elements.

Enhancing groundwater vulnerability assessment for improved environmental management: addressing a critical environmental concern.

Groundwater serves as a primary water source for various purposes. Therefore, aquifer pollution poses a critical threat to human health and the environment. Identifying the aquifer's highly vulnerable areas to pollution is necessary to implement appropriate remedial measures, thus ensuring groundwater sustainability. This paper aims to enhance groundwater vulnerability assessment (GWVA) to manage aquifer quality effectively. The study focuses on the El Orjane Aquifer in the Moulouya basin, Morocco, which is facing significant degradation due to olive mill wastewater. Groundwater vulnerability maps (GVMs) were generated using the DRASTIC, Pesticide DRASTIC, SINTACS, and SI methods. To assess the effectiveness of the proposed improvements, 24 piezometers were installed to measure nitrate concentrations, a common indicator of groundwater contamination. This study aimed to enhance GWVA by incorporating new layers, such as land use, and adjusting parameter rates based on a comprehensive sensitivity analysis. The results demonstrate a significant increase in Pearson correlation values (PCV) between the produced GVMs and measured nitrate concentrations. For instance, the PCV for the DRASTIC method improved from 0.42 to 0.75 after adding the land use layer and adjusting parameter rates using the Wilcoxon method. These findings offer valuable insights for accurately assessing groundwater vulnerability in areas with similar hazards and hydrological conditions, particularly in semi-arid and arid regions. They contribute to improving groundwater and environmental management practices, ensuring the long-term sustainability of aquifers.

Source identification and potential health risks from elevated groundwater nitrate contamination in Sundarbans coastal aquifers, India.

In recent years groundwater contamination through nitrate contamination has increased rapidly in the managementof water research. In our study, fourteen nitrate conditioning factors were used, and multi-collinearity analysis is done. Among all variables, pH is crucial and ranked one, with a value of 0.77, which controls the nitrate concentration in the coastal aquifer in South 24 Parganas. The second important factor is Cl-, the value of which is 0.71. Other factors like-As, F-, EC and Mg2+ ranked third, fourth and fifth position, and their value are 0.69, 0.69, 0.67 and 0.55, respectively. Due to contaminated water, people of this district are suffering from several diseases like kidney damage (around 60%), liver (about 40%), low pressure due to salinity, fever, and headache. The applied method is for other regions to determine the nitrate concentration predictions and for the justifiable alterationof some management strategies.

Groundwater chlorinated solvent plumes remediation from the past to the future: a scientometric and visualization analysis.

Contamination of groundwater with chlorinated hydrocarbons has serious adverse effects on human health. As research efforts in this area have expanded, a large body of literature has accumulated. However, traditional review writing suffers from limitations regarding efficiency, quantity, and timeliness, making it difficult to achieve a comprehensive and up-to-date understanding of developments in the field. There is a critical need for new tools to address emerging research challenges. This study evaluated 1619 publications related to this field using VOSviewer and CiteSpace visual tools. An extensive quantitative analysis and global overview of current research hotspots, as well as potential future research directions, were performed by reviewing publications from 2000 to 2022. Over the last 22 years, the USA has produced the most articles, making it the central country in the international collaboration network, with active cooperation with the other 7 most productive countries. Additionally, institutions have played a positive role in promoting the publication of science and technology research. In analyzing the distribution of institutions, it was found that the University of Waterloo conducted the majority of research in this field. This paper also identified the most productive journals, Environmental Science & Technology and Applied and Environmental Microbiology, which published 11,988 and 3253 scientific articles over the past 22 years, respectively. The main technologies are bioremediation and chemical reduction, which have garnered growing attention in academic publishing. Our findings offer a useful resource and a worldwide perspective for scientists engaged in this field, highlighting both the challenges and the possibilities associated with addressing groundwater chlorinated solvent plumes remediation.

Assessing water quality index and health risk using deterministic and probabilistic approaches in Darab County, Iran; A machine learning for fluoride prediction.

The present study employed deterministic and probabilistic approaches to determine the Water Quality Index (WQI) and assess health risks associated with water consumption in Darab County, Iran. Additionally, pollution levels were predicted using a machine-learning algorithm. The study's findings indicate that certain physicochemical parameters of water in some locations exceeded permissible limits (WHO or EPA), with 79.00 % of total hardness (TH) and 21.74 % of Total dissolved solids (TDS) levels exceeding standard values. The WQI for drinking water was determined to be 94.56 % using the deterministic approach, and 98.4 % of samples included the excellent and good categories according to the WQI classification system using the probabilistic approach. Fluoride (F) exhibited the most substantial impact on WQI values. The Artificial Neural Network (ANN) analysis findings suggest that the pH, nitrate (NO3), and TDS are the most significant factors affecting the prediction of F concentration in water. Multivariate analysis demonstrated that anthropogenic, especially agriculture and geogenic factors, contributed to the water quality in this area. The health risk assessment (HRA) using deterministic methods revealed that water consumption posed a relatively high risk in certain areas. However, Monte Carlo simulation demonstrated that the 5th and 95th percentiles of Hazard Index (HI) for children, teenagers, and adults were within limits of (0.14-2.38), (0.09-1.29), and (0.10-1.00) respectively, with a certainty level of 70 %, 91 %, and 95 %. Interactive indices revealed that the intake of IR and NO3-IR in children, BW and F-BW in teenagers, and NO3 and NO3-IR in adults significantly impacted health risks. Based on these findings, augmenting water treatment processes, regulating fluoride concentrations, and advocating for sustainable agricultural practices complemented by continuous monitoring is imperative.

Temporal variation of water quality parameters in the lacustrine of the Thrace Region, Northwest Türkiye.

Thrace is a part of the Marmara Region northwest of Türkiye. This region hosts several lentic ecosystems used for irrigation and drinking water supply. The present study was conducted to analyze the temporal distributions of water quality parameters (WQPs) of lentic ecosystems (lacustrine habitats), including lakes (L1-L2), reservoirs (R1-R12), and ponds (P1-P19) of the Thrace Region. Thirty-three lacustrine habitats were identified in the region. Freshwaters were collected in the wet (end of winter) and dry (end of summer) seasons of 2021-2022 and tested for 12 WQPs. Data was evaluated for the water quality index (WQI) and nutrient pollution index (NPI) and their overall quality level. For the evaluation of non-carcinogenic health risk indices of WQPs, the chronic daily index (CDI), hazard quotient (HQ), and hazard index (HI) were applied. Cluster analysis (CA), Pearson correlation index (PCI), and principal component analysis (PCA) were used to classify the lacustrine habitats and identify the source of WQPs. The average values were as follows: 9.28 mg/L for dissolved oxygen (DO), 94.6% for oxygen (O2) saturation, 9.29 for pH, 613 µS/cm for electrical conductivity (EC), 3.96 NTU for turbidity, 358 mg/L for total dissolved solids (TDS), 3.17 mg/L for nitrate (NO3), 0.05 mg/L for nitrite (NO2), 1.01 mg/L for phosphate (PO4), 78.5 mg/L for sulfate (SO4), and 102 mg/L for chloride (Cl). Results showed a significant increase in WQPs, including NO3, NO2, and PO4, in the wet season, while the salinity decreased from the dry to wet season. Results revealed that HI values of water contaminants in lacustrine habitats were noted to be less than one. Based on determined WQPs, the present study recommends using lacustrine water habitats for irrigation, drinking, and other domestic and industrial purposes.

Utilizing machine learning for reactive material selection and width design in permeable reactive barrier (PRB).

Permeable reactive barrier (PRB) is an important groundwater treatment technology. However, selecting the optimal reactive material and estimating the width remain critical and challenging problems in PRB design. Machine learning (ML) has advantages in predicting evolution and tracing contaminants in temporal and spatial distribution. In this study, ML was developed to design PRB, and its feasibility was validated through experiments and a case study. ML algorithm showed a good prediction about the Freundlich equilibrium parameter (R2 0.94 for KF, R2 0.96 for n). After SHapley Additive exPlanation (SHAP) analysis, redefining the range of the significant impact factors (initial concentration and pH) can further improve the prediction accuracy (R2 0.99 for KF, R2 0.99 for n). To mitigate model bias and ensure comprehensiveness, evaluation index with expert opinions was used to determine the optimal material from candidate materials. Meanwhile, the ML algorithm was also applied to predict the width of the mass transport zone in the adsorption column. This procedure showed excellent accuracy with R2 and root-mean-square-error (RMSE) of 0.98 and 1.2, respectively. Compared with the traditional width design methodology, ML can enhance design efficiency and save experiment time. The novel approach is based on traditional design principles, and the limitations and challenges are highlighted. After further expanding the data set and optimizing the algorithm, the accuracy of ML can make up for the existing limitations and obtain wider applications.

Evaluation of groundwater quality by adopting a multivariate statistical approach and indexing of water quality in Sagar Island, West Bengal, India.

In the vicinity of the coast, predominantly groundwater is the sole reliable resource for potable purposes as the surface water sources are highly saline and unfit for human consumption. However, the groundwater in Sagar Island is highly vulnerable to saltwater intrusion. The majority of drinking water comes from government-owned hand pump-equipped tube wells. But during the summer season, many of these tube wells yield significantly less water. Hence, in the current scenario, water quality assessment has become important to the quantity available. Total of 31 samples of deep tube wells (groundwater) are collected at variegated locations during pre-monsoon season throughout Sagar, and then, the physical and chemical quality parameters of these water samples are analysed. Furthermore, a multivariate statistical technique is executed with the aid of the SPSS program. The hydro-chemical parameters that are taken into account for the quality analysis are pH, salinity, electrical conductivity (EC), total dissolved solids (TDS), total hardness, aluminium, arsenic, bi-carbonate, cadmium, iron, chloride, copper, chromium, cobalt, lead, magnesium, manganese, nickel, potassium, sulphate, zinc, and sodium. Then, the analysed data evaluates the water quality index (WQI). Five components are identified through the principal component analysis (PCA) technique, and 82.642% total variance is found. The outcomes of the quality assessment study illustrate that about 54.84% of collected samples come in the "excellent" water quality class when calculated by the "weighted arithmetic WQI method," and 90.32% of collected groundwater samples come in the "good" water quality class when computed using the "modified weighted arithmetic WQI method." This study helps for the interpretation of WQI to assess groundwater quality.

Evaluation of spatial and temporal dynamics of seawater intrusion in coastal aquifers of southeast India: insights from hydrochemical facies analysis.

This study aims to investigate and understand the temporal and spatial movement of seawater intrusion into the coastal aquifers. Groundwater salinity increase has affected the entire eastern part of the study area and is primarily influenced by direct and reverse ion exchange reactions associated with intrusion and freshwater influx phases, which alternate over monsoons. To gain insights into the spatiotemporal dynamics of the seawater intrusion process, hydrochemical facies analysis utilizing the HFE-Diagram was employed. Additionally, the study considered the major ionic changes during both the monsoons. The HFE-Diagram analysis of hydrochemical facies revealed distinctions in the behaviour of each coastal aquifer concerning seawater intrusion-induced salinization. In PRM 2020, the data shows that approximately 65% of the samples fall under the freshening phase, while the remaining 35% were categorized as intrusion phase. Within the freshening phase, seven different hydrochemical facies were identified, including Na-Cl, Na-MixCl, MixNa-MixCl, Na-MixHCO3/MixSO4, MixNa-MixSO4, Na-HCO3, and MixCa-HCO3. In contrast, the intrusion phase had four facies: MixCaMixHCO3, MixNa-Cl, Ca-Cl, and Na-Cl. Especially, the Na-Cl facies (f1) within the freshening phase attributed for the largest percentage, contributing 30% of the samples. In POM 2021, the distribution of samples shifted slightly, with approximately 72.5% belonging to the freshening phase and 27.5% to the intrusion phase. Within the freshening phase of POM 2021, five hydrochemical facies were identified: Na-Cl, Na-MixCl, Na-MixHCO3/MixSO4, MixNa-MixSO4, and Na-HCO3. The intrusion phase of POM 2021 had three facies: MixNa-Cl, Na-Cl, and MixCa-Cl. Similar to PRM 2020, the Na-Cl facies (f1) remained the most predominant in the freshening phase, comprising 30% of the samples. The relation between total dissolved solids (TDS) and various ionic ratios, such as HCO3-/Cl-, Na+/Cl-, Ca2+/Cl-, Mg2+/Cl-, K+/Cl-, and SO42-/Cl-, clearly demonstrates the presence of seawater influence within the coastal aquifers of the study area.

Groundwater quality assessment for drinking purpose using traditional and fuzzy-GIS-based water quality index in Gurugram District of Haryana, India.

Primarily groundwater is consumed for the drinking and irrigation purpose. However, due to increasing anthropogenic activities, its quality and quantity have substantially declined over time. The focus of this study is to evaluate the pre-monsoonal groundwater quality and its spatial variability for drinking purposes in the Gurugram, Haryana, India. Ground Water quality index (GWQI) developed on the basis of the Geographical Information System is effective in the assessment of groundwater quality and its spatial variability, but it is unable to account for uncertainties related to environmental problems. Thus, a Hybrid Fuzzy-GIS-based Water Quality Index (FGQI) has been proposed for the assessment of groundwater quality. The study conducted factor analysis to identify the prime factors responsible for groundwater contamination and collected pre-monsoonal groundwater samples through primary sampling. The groundwater quality was assessed based on eight hydro geochemical parameters (pH, TDS, Calcium, Chloride, Sulfate, Fluoride, Potassium, and Sodium). The spatial interpolation of each parameter was performed using appropriate techniques, selected based on a normality test. The guidelines of the World Health Organization and Bureau of Indian Standard were incorporated in the development of GWQI and FGQI, respectively. Correlation analysis was performed to determine the best fuzzy overlay technique for FGQI, and the Fuzzy GAMMA technique with gamma equal to 0.9 was selected. Finally, the GWQI and FGQI were classified into three classes: unsuitable, moderate suitable, and suitable using "natural break". A higher index indicates a higher water quality. The results show that the groundwater in the central part of Gurugram is suitable for drinking, while it is not suitable in the extreme north, south-east, and western regions. In conclusion, this study finds that FGQI effectively assesses the groundwater quality in the region better than GWQI.