Assessment Of Groundwater Quality Research Articles

Multi-dimensional Assessment of Groundwater Quality Correlating with Textile Mills in Faisalabad City, Pakistan

Multi-dimensional Assessment of Groundwater Quality Correlating with Textile Mills in Faisalabad City, Pakistan

Hydrogeochemical characterization for groundwater quality and risk assessment in part of central gangetic alluvium, India

An exponential growth in groundwater extraction will greatly concern the Varuna River basin of Central Ganga alluvium. This complex issue requires proper systematic evaluations to advocate various opportunities for management strategies for groundwater sustainability. The present study aims to convey scientific assessments of the groundwater using different soft-computing techniques to determine its hydrogeochemistry and quality for averting future risk and envisaging suitable management policies. SOM (Self-Organizing Map) model involves characterizing the spatial clusters of regional hydrogeochemistry and reported a gradual increase in salinity from the northwestern to the southeastern part of the area. PCA (Principal Component Analysis) provides evidence of rock-water interactions and anthropogenic activities as responsible factors in determining hydrogeochemistry. Quality assurance is judged by various systematic chemometric indices. CCMEWQI (Canadian Council of Ministers of the Environment Water Quality Index) and IWQI (Irrigation Water Quality Index) reveal that the groundwater is suitable for drinking/domestic and irrigation use. Continuous fluxes of freshwater nourish Gangetic alluvium and generally provide excellent quality. In contrast, the analysis results notice the degradation of drinking quality from the excellent to good category (CCMEWQI) and moderate to low restriction (IWQI) for irrigation suitability. Further study of potential health risks represents the presence of carcinogenic and non-carcinogenic risks for the exposure of NO3−, F−, Pb, and Cr elements. However, the heavy metal pollution and ecological risks are low. Based on the study's findings, the estimates will support initiatives and activities at the local, regional, and national levels, as nations like India need basin-level studies. It is also recommended to consider depth-wise geochemical and temporal chemical variation for further improved studies towards risk assessment.

Hydrochemical assessment of groundwater using multivariate statistical methods and water quality indices (WQIs)

Groundwater quality assessment is crucial for the sustainable management of water resources in arid regions, where groundwater is the primary source of water supply and increasing demand raises concerns. The study area in Southwest Algeria relies heavily on groundwater as a source of water supply, and the increasing demand for freshwater raises concerns about the quality of groundwater. To assess the hydrochemical characteristics and water quality of groundwater in the Ain Sefra region, multivariate statistical methods, geochemical modeling and water quality indices were employed. The study revealed that the groundwater samples could be classified into four water groups using hierarchical cluster analysis Q mode (HCA), namely Ca–Mg–HCO3, Ca–Mg–Cl–SO4, Ca–SO4 and Na–Cl. Factor analysis was used to identify the main factors controlling the study area’s hydrochemical processes. The results indicated that water–rock interaction, reverse ion exchange and anthropogenic pollution were the main hydrochemical processes affecting groundwater chemistry. The water quality index indicated that the groundwater was suitable for human consumption, with only 2.32% of the samples being unsuitable. Additionally, the groundwater was suitable for agricultural use, but salinity control was necessary. The saturation index values showed that the groundwater was supersaturated with aragonite, calcite, dolomite, anhydrite and gypsum, and undersaturated with halite. Ca-smectite, Mg-smectite and kaolinite were identified as the primary processes controlling the chemical composition of groundwater. The application of multivariate statistical methods, geochemical modeling and water quality indices provided a comprehensive understanding of the hydrochemical characteristics and water quality of groundwater in the Ain Sefra region. The findings of the study can serve as a useful basis for future studies on groundwater quality assessment in the region.

Multi-model exploration of groundwater quality and potential health risk assessment in Jajpur district, Eastern India.

The presence of fluoride and nitrate is a serious groundwater quality issue in India impacting human health. In the present study, 14 different hydrochemical parameters for 76 groundwater samples collected from the Jajpur district of Odisha, India, were evaluated. Entropy-weighted water quality index (EWQI), fixed-weight groundwater quality index (GWQI), principal component analysis (PCA), and rotated factor loading-based water quality index (PCWQI) were employed to assess groundwater quality. About 65.79 ± 4.68%, 33.55 ± 3.95%, and 0.66 ± 0.76% of the samples were rated as "excellent," "good," or "medium" quality, respectively, across the four different water quality indices, with a nominal rating discrepancy of 13.15%. Though 86% of samples consistently received excellent or good ratings across all WQI frameworks, concentrations of F- and NO3- in 36.8% and 11.84% of the samples exceeded the WHO permissible limit. In health risk assessment, about 38.15% of samples surpassed the F- hazard quotient (HQ > 1) posing non-carcinogenic health risks for children. The non-carcinogenic health risks due to NO3- were evident in 55.26% and 11.84% of samples for children and adults, respectively. The higher concentration of NO3- in some of the water samples, together with its positive correlation with HCO3-, may worsen groundwater pollution. The moderate correlation between Ca2+ and HCO3- (r = 0.410) and the insignificant correlation between Mg2+ and HCO3- (r = 0.234) suggests calcite dissolutionis far more common than dolomite.

Index-Based Groundwater Quality Assessment of Nestos River Deltaic Aquifer System, Northeastern Greece

The Nestos River delta is one of the most important and sensitive basins in Greece and Europe due to its ecosystem functions, combining intensive agricultural production with low-enthalpy geothermal energy and important ecotopes. High water quality is of paramount importance to the sustainability of the system. Systematic and continuous assessment of water quality needs to be carried out in a way that is easy and quick for decision makers and non-expert societal partners to comprehend. In this way, decisions may be made more rapidly, and involved water users may be sensitized to rational water use. To this end, this paper presents the assessment of groundwater quality in the Nestos River’s western delta with the use of Poseidon (PoS), a versatile, index-based method. Groundwater samples collected from 24 and 22 wells tapping the unconfined and the confined aquifers, respectively, in four time periods (May and October 2019 and 2020) were analyzed. Using the PoS index, groundwater samples were classified according to their quality status, highlighting the parameters driving quality degradation issues, thus assisting water managers in obtaining an overview of quality status and evolution through datasets that were often large. PoS index is applied in the study area for the first time and provides a groundwater quality assessment through a unique score representative of the overall water quality status regardless of processes (anthropogenic or natural) or any kind of pressures.

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.

Ground Water Quality Assessment Using the Water Quality Index, Iraq

Water Quality Index (WQI) has been applying in the present study to assess suitability of groundwater quality for drinking purposes in Amara city, southern Iraq. This was carried out by subjecting twelve groundwater samples, collected from different sites to comprehensive physic-chemical analysis. Ten parameters have been considered for calculating the WQI such as; pH, electrical conductivity, total dissolved solids, sodium, potassium, calcium, magnesium, chloride, sulphate and nitrate. The WQI values shows that 16.66% of water samples falls in good water categories and the others (83.66%) ranged from poor water to unsuitable for drinking purposes under normal conditions and further action for salinity control is required. The high value of WQI at this study has been found to be mainly due to the higher values of EC, TDS, SO4-2, Ca+2, Mg+2 and Cl- where it was found that there is a very high correlation coefficient between them.

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.

Assessing groundwater quality, health risks, and policy implications: A case study of West Medinipur District, West Bengal, India

AbstractGroundwater is a vital freshwater resource for various uses, including drinking, irrigation, and industry needs. The increasing dependence of India on groundwater due to dwindling surface water sources and climate extremes has led to concerns about its availability and quality. This study focuses on the groundwater quality and associated human health risks in the West Medinipur district of West Bengal, India. The region, situated between the Kangsabati and Subarnarekha rivers, faces challenges from anthropogenic activities such as agricultural practices and industrial pollution. A comprehensive analysis of physicochemical parameters was conducted on well water samples collected during the monsoon and post‐monsoon periods. The study examined the suitability of groundwater for drinking and irrigation purposes. Water quality indices were calculated to assess its fitness for human consumption. Despite several parameters meeting the water quality standards, elevated iron (Fe) and ammonia (NH4+) levels were observed, potentially impacting groundwater use for drinking. Similarly, groundwater's suitability for irrigation was evaluated based on parameters like sodium adsorption ratio (SAR) and sodium percentage (Na%). The groundwater types dominated by magnesium bicarbonate and the quality could affect soil structure and crop productivity in certain areas. The elevated levels of Fe and NH4+ showed potential human health risks, indicating the need to mitigate adverse effects on human well‐being through appropriate policy and other interventions. The study highlights the complexity of groundwater quality in the study area. It underscores the necessity for comprehensive water policy and management strategies to safeguard water resources and human health in rural India. The findings emphasize the importance of ongoing monitoring and intervention measures to ensure the sustainability and safety of groundwater for present and future generations.

Geoelectrical and Geochemical Approaches for Groundwater Quality Assessment in the Equatorial Region

Geoelectrical and Geochemical Approaches for Groundwater Quality Assessment in the Equatorial Region

Groundwater Quality Assessment in the Area of the Zinc Smelter in Miasteczko Śląskie (Poland) Using Selected Metal Indices

Groundwater quality assessment in the region of potential pollution sources can be performed through the use of index-based methods. The aim of this paper was to present the results of the groundwater quality assessment in the region of the zinc smelter in Miasteczko Śląskie (southern Poland) for the Quaternary aquifer based on monitoring data from 2000, 2011, and 2022. The following parameters were used in the analysis: Pb, Cd, Ni, Cu, Fe, Mn, and Zn. Three indices were calculated, i.e., the landfill water pollution index (LWPI), heavy metal pollution index (HPI), and metal index (MI). The values of the indicators suggest that in the described study area, there are waters that are under the strong influence of the zinc smelter infrastructure and landfills. The highest values obtained are about 17 for LWPI, about 66 for HPI, and about 133 for MI. These values indicate significant anthropogenic pollution of the groundwater of the Quaternary aquifer in the study area. Taking into account the values obtained for all three indices, it can be concluded that the HPI indicator is the least reliable due to the need to select two limit values (background and ideal content in waters for each of the parameters), which would suggest that in some cases, waters are not very contaminated. The other two indices show similarities (mainly in their spatial distribution), and only the choice of parameters determines which of the indices should be used. A comparison of the results of local groundwater quality monitoring with the results of the calculated indices indicate that the values of the calculated MI indices are closest to the actual water quality status.

Groundwater Quality Assessment and Irrigation Water Quality Index Prediction Using Machine Learning Algorithms

The evaluation of groundwater quality is crucial for irrigation purposes; however, due to financial constraints in developing countries, such evaluations suffer from insufficient sampling frequency, hindering comprehensive assessments. Therefore, associated with machine learning approaches and the irrigation water quality index (IWQI), this research aims to evaluate the groundwater quality in Naama, a region in southwest Algeria. Hydrochemical parameters (cations, anions, pH, and EC), qualitative indices (SAR,RSC,Na%,MH,and PI), as well as geospatial representations were used to determine the groundwater’s suitability for irrigation in the study area. In addition, efficient machine learning approaches for forecasting IWQI utilizing Extreme Gradient Boosting (XGBoost), Support vector regression (SVR), and K-Nearest Neighbours (KNN) models were implemented. In this research, 166 groundwater samples were used to calculate the irrigation index. The results showed that 42.18% of them were of excellent quality, 34.34% were of very good quality, 6.63% were good quality, 9.64% were satisfactory, and 4.21% were considered unsuitable for irrigation. On the other hand, results indicate that XGBoost excels in accuracy and stability, with a low RMSE (of 2.8272 and a high R of 0.9834. SVR with only four inputs (Ca2+, Mg2+, Na+, and K) demonstrates a notable predictive capability with a low RMSE of 2.6925 and a high R of 0.98738, while KNN showcases robust performance. The distinctions between these models have important implications for making informed decisions in agricultural water management and resource allocation within the region.

Hydrochemical Characteristics and Suitability Assessment of Groundwater Quality for Irrigation

The hydrochemical properties of groundwater play a crucial role in crop growth and soil health, as well as the maintenance of irrigation equipment. To ensure suitable water quality for irrigation, the present study was conducted to evaluate the hydrochemical properties of irrigation groundwater in a typical agricultural region of Serbia. Groundwater was sampled at three monitoring locations in the Srem region in Republic of Serbia between 2011 and 2020. Examined parameters included electrical conductivity (EC), total dissolved salts (TDS), pH values, and the concentrations of cations (sodium (Na+), calcium (Ca2+), magnesium (Mg2+) and potassium (K+)) and anions (bicarbonate (HCO3−), chloride (Cl−), sulfate (SO42−), and nitrate (NO3−)). Further assessment was done using three classification systems; Nejgebauer’s, the US USSL, and the FAO classification. To obtain a more detailed assessment, additional indices were included, such as Soluble Sodium Percentage (SSP), Sodium Adsorption Ratio (SAR), Residual Sodium Carbonate (RSC), Permeability Index (PI), Kelly’s Ratio (KR), Magnesium Adsorption Ratio (MAR), and Total Hardness (TH). The PCA analysis detected that the concentration of K+, Ca2+, and Na+ in the irrigation water were lower in recent years, while the concentration of Cl− was higher. The cluster analysis grouped the parameters into three clusters; I—electroconductivity, II—dry residue and HCO3−, and III—other water parameters for all three monitoring localities. According to the applied classifications, the majority of underground water samples were suitable for irrigation. However, some samples fell out of the range of the first class, indicating the need for regular water quality monitoring. In light of climate changes that influence water deficiency, the urgent need for wise and sustainable water use implies the application of a comprehensive approach to irrigation water quality assessment, as shown in this study.

Assessment of groundwater quality and human health risk from nitrate contamination using a multivariate statistical analysis.

The present study explores the suitability of groundwater for drinking purpose and evaluates non-carcinogenic health risks for children, women, and men. For this purpose, 47 groundwater samples were collected and analyzed for physicochemical parameters, including nitrate concentration. The results revealed that nitrate concentration varied from 15 to 85 mg/L and that 48.93% of the groundwater samples exceeded the Bureau of Indian Standards' limits of 45 mg/L. The spatial map of the pollution index of groundwater specifies that most of the study area lies in moderate to high pollution zones. Principal component analysis was also applied, and five principal components achieving eigenvalues more than 1 with a cumulative variance of 77.36% were found to be sufficient. The findings of non-carcinogenic risk rates range from 0.628 to 3.559 (average of 2.069) for children, 0.427 to 2.421 (average of 1.408) for women, and 0.362 to 2.049 (average of 1.191) for men, and approximately 80% of the population in the study region is exposed to high health risks. The health risk assessment specified that children in the study area are more susceptible than women and men. The findings of this study suggest that groundwater quality in the region has deteriorated, emphasizing the need for treatment before drinking.

Distribution of Groundwater Hydrochemistry and Quality Assessment in Hutuo River Drinking Water Source Area of Shijiazhuang (North China Plain)

The Hutuo River Drinking Water Source Area is an important water source of Shijiazhuang (North China Plain). Knowing the characteristics of groundwater chemistry/quality is essential for the protection and management of water resources. However, there are few studies focused on the groundwater chemistry evolution over the drinking water area. In this study, total of 160 groundwater samples were collected in November 2021, and the spatial distribution of groundwater chemistry and related controlling factors were analyzed using hydrological and multivariate analysis. The entropy-weighted water quality index (EWQI) was introduced to assess the groundwater quality. The results show that the hydrogeochemical types of groundwater are Ca-HCO3 (78.1%), mixed Ca-Mg-Cl (20%), and Ca-Cl (1.9%) in the area. Graphical and binary diagrams indicate that groundwater hydrochemistry is mainly controlled by water–rock interaction (i.e., rock weathering, mineral dissolution, and ion exchange). Five principal components separated from the principal component analysis represent the rock–water interaction and agricultural return, redox environment, geogenic sources, the utilization of agricultural fertilizer, the weathering of aluminum silicates, and dissolution of carbonates, respectively. More than 70% of the samples are not recommended for irrigation due to the presence of high salt content in groundwater. EWQI assessment demonstrates that the quality of the groundwater is good. The outcomes of this study are significant for understanding the geochemical status of the groundwater in the Hutuo River Drinking Water Source Area, and helping policymakers to protect and manage the groundwater.

Groundwater quality assessment using water quality and heavy metal indices in the West-Assiut combined-cycle power plant’s area, Egypt

Groundwater quality assessment using water quality and heavy metal indices in the West-Assiut combined-cycle power plant’s area, Egypt

Assessment of groundwater quality in the region of Hjar Nhal for safe drinking water purposes

This study assesses the groundwater quality in the vicinity of the newly established landfill site in the city of Tangier. A total of 8 wells and 2 water sources within a 2-kilometer radius of the landfill were sampled for analysis. The selection of sampling sites was carefully executed, taking into consideration the flow direction and elevation in the study area to ensure representative results. The study focused on the analysis of 11 physicochemical parameters to evaluate the suitability of the groundwater for drinking and irrigation purposes. Notably, the pH measurements at various points (S1, S2, P4, P7, P8) consistently fell within the WHO's recommended range of 6.5-8.5 for safe drinking water. Conductivity values (μS/cm) were well below the limit of 1000 μS/cm at each location, indicating low levels of dissolved ions. Additionally, the TDS levels (ppm) did not exceed the WHO limit of 500 ppm, further confirming water quality that meets international standards. These findings provide valuable insights into the groundwater quality for safe drinking water and irrigation purposes in the area. The results contribute to informed decision-making and sustainable water resource management practices, ensuring the preservation of local water resources in the context of the landfill's environmental impact.

Groundwater Quality Assessment in the Coastal Mediterranean Aquifer of Northeastern Morocco - A GIS-Based Approach

Groundwater Quality Assessment in the Coastal Mediterranean Aquifer of Northeastern Morocco - A GIS-Based Approach

Surface water and groundwater quality assessment using the WQI method and human health risk assessment (HHR) in the lower seybouse (Annaba Plain), northeast Algeria

Surface water and groundwater quality assessment using the WQI method and human health risk assessment (HHR) in the lower seybouse (Annaba Plain), northeast Algeria

Studies on groundwater quality index around industrial areas of low hills in Himachal Pradesh

The present study emphasizes on groundwater quality assessment and working out the interrelationship between various physico-chemical parameters and potentially toxic elements in low-hills of Himachal Pradesh. The study was conducted in industrial areas of two districts and a total of 240 groundwater samples were collected during 2020-2022 from borewells and handpumps and analyzed 21 parameters such as temperature, turbidity, TDS, EC, pH, DO, BOD, alkalinity, sulphate, nitrate, sodium, calcium, total hardness, chloride, magnesium, manganese, iron, zinc, copper, chromium, and lead. The study area was divided into five locations in both the districts and samples were taken during pre-monsoon and postmonsoon to check the seasonal variation. The estimated values were then compared with drinking water quality standards prescribed by BIS and location-wise WQI value was calculated. The results showed that in both the districts, the physico-chemical parameters under study were within the permissible limits. The WQI values range from 43.85 to 25.85 in district Sirmaur and 39.18 to 25.60 in district Una. In both the districts, the WQI lies under the good to excellent category and were suitable for human consumption. Location-wise, the highest WQI value was highest around the industries followed by samples within the industry > along the main highway > residential areas, and the lowest value was in the control which was the samples taken from the Department of Irrigation and Public Health supply. Seasonal-wise, the concentration of the physico-chemical parameters as well as the WQI was higher during post-monsoon than pre-monsoon.