Integrated approach for the evaluation of groundwater quality through hydro geochemistry and human health risk from Shivganga river basin, Pune, Maharashtra, India

Hazard-mapping and health risk analysis of iron and arsenic contamination in the groundwater of Sylhet district

This study investigates groundwater contamination by arsenic and iron and its health implications within the Sylhet district in Bangladesh. Utilizing geographic information system (GIS) and inverse distance weighting (IDW) methods, hazard maps have been developed to evaluate contamination risk across various upazilas. The findings show significant arsenic and iron pollution, particularly in the northwestern part of the district. In about 50% of the area, especially in Jaintiapur, Zakiganj, Companiganj, and Kanaighat where arsenic levels surpass 0.05 mg/L which is the standard limit of Bangladesh. Iron levels peak at 13.83 mg/L, severely impacting 45% of the region, especially in Gowainghat, northeastern Jaintiapur, Zakigonj, and Golabganj. The study employs USEPA health risk assessment methods to calculate the hazard quotient (HQ) and hazard index (HI) for both elements via oral and dermal exposure. Results indicate that children face greater noncarcinogenic and carcinogenic risks than adults, with oral HI showing significant risk in Balagonj and Bishwanath. Dermal adsorption pathways exhibit comparatively lower risks. Cancer risk assessments demonstrate high carcinogenic risks from oral arsenic intake in all areas. This comprehensive analysis highlights the urgent need for effective groundwater management and policy interventions in the Sylhet district to mitigate these health risks and ensure safe drinking water.

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 dissolution is far more common than dolomite.

Spatio-temporal variability of public water supply characteristics and associated health hazards for children and adults in selected locations of Ambala, India

The contamination of public water supply and groundwater resources is a major concern in many parts of developing nations. Polluted water poses serious health risks to humans and the environment. This research was conducted to investigate the seasonal variations of the water quality parameters in the public water supply. To assess the supply water quality in different blocks of Ambala District, hydro-chemical analysis was conducted after a series of systematic sampling in various locations. The statistical tools for water quality indexing including water quality indexing (WQI), heavy metal pollution indexing (HMPI), pollution indexing (PI), overall pollution indexing (OPI), metal indexing (MI), and hazard indexing (HI) were used for data as well as the health hazard analysis through water pathway. Overall, 40 water samples were taken from the public water supply systems covering winter and summer seasons, and the levels of pH, total dissolved solids (TDS), EC, F- , Cl- , NO3 - , SO4 2- , HCO3 - , As, B, Cd, Co, Pb, Zn, Cr, Fe, and Mn were investigated. The weight arithmetic index method was used for WQI, and water pollution indices such as HMPI, PI, OPI, and MI were calculated using different models to check the severity of contamination. The mean hazard quotient and hazard index values calculated using the concentration levels of As, B, Cd, Co, Pb, Cr, Fe, Mn, Zn, F- , and NO3 - reveal that supply water may pose a significant health risk to both adults and children that further varies with temporal and spatial changes. During both seasons, a high carcinogenic risk for both adults and children was observed in the studied area because of high levels of As, Pb, Cd, and NO3 - . PRACTITIONER POINTS: The quality of public supply water was assessed at the selected sites of Ambala, India. High levels of NO3 - , As, Cd, and Pb were observed posing a health risk to adults and children via water pathway. 95% of the samples qualified for the excellent water quality category with respect to the levels of F- , Cl- , NO3 - , SO4 2- , HCO3 - , pH, EC, and TDS. Statistical analysis (HMPI, PI, MI, OPI, HI) using different models revealed water contamination with reference to the levels of NO3 - , As, Pb, Cr, Ni, and Cd. Immediate measures are needed to uphold the safety and health of the natives.

An appraisal to hydrochemical characterization, source identification, and potential health risks of sulfate and nitrate in groundwater of Bemetara district, Central India

Gypsum-enriched aquifers (GEA) and intensive agriculture regions (IAR) in semi-arid regions are responsible for very high amounts of sulfate and nitrate in many groundwater systems of the world, respectively. However, in such regions, the problem of nitrate pollution and its associated health risk has been increasing and emerging as a global issue. However, along with nitrate, sulfate contamination and its potential health risks are often neglected worldwide in these regions. Therefore, considering sulfate along with nitrate as a significant threat to water quality in such regions, this study aimed to characterize hydrochemistry, factors controlling groundwater quality, and assessment of risk to human health. To accomplish this objective, 116 groundwater samples were collected over pre-monsoon (PRM) and post-monsoon (POM) (2019) seasons in Bemetara district. As per Bureau of Indian standards (BIS) for drinking, SO42- (28 and 19%) and NO3- (7 and 35%) exceeded the permissible limits in PRM and POM seasons, respectively; thereby, groundwater was not suitable for drinking. SO42- and NO3- pollution sources were identified and mainly attributed to gypsum dissolution and agricultural activities as well as domestic sewage discharge, respectively. In addition, SO42-and NO3- risk assessment results show that total 20% to 46% of all samples surpassed the permissible limit (HQ = 1) of risk to children and adults, over both seasons. To ensure drinking water security in this region, sustainable management of agricultural activities and treatment should be done to reduce the potential health risks due to SO42- and NO3-.

Spatio-temporal variation of groundwater pollution in urban wetlands and management strategies for zoning

Groundwater is an important resource to maintain the sustainable development of urban wetlands. The Jixi National Wetland Park (JNWP) was studied to realize the refined prevention and control of groundwater. The self-organizing map-K-means algorithm (SOM-KM), improved water quality index (IWQI), health risk assessment model and forward model were used comprehensively to evaluate the groundwater status and solute sources in different periods. The results showed that the groundwater chemical type in most areas was the HCO₃-Ca type. Groundwater chemistry data from different periods were clustered into five groups. Groups 1 and 5 are affected by agricultural and industrial activities, respectively. The IWQI value in the normal period was higher in most areas due to the influence of spring ploughing. The east side of the JNWP was disturbed by human activities, and the quality of drinking water continued to deteriorate from the wet period to the dry period. 64.29% of the monitoring points showed good irrigation suitability. The health risk assessment model showed that the health risk was the largest in the dry period and the smallest in the wet period. The main factors causing health risks in the wet period and other periods were NO₃^- and F^-, respectively. The overall cancer risk was within acceptable limits. The forward model and ion ratio analysis showed that the weathering of carbonate rocks was the main factor affecting the evolution of groundwater chemistry, accounting for 67.16%. The high-risk areas of pollution were mainly concentrated in the east of the JNWP. K⁺ and Cl^- were the key monitoring ions in the risk-free zone and potential risk zone, respectively. The research can be used to help decision-makers carry out fine zoning control of groundwater.

Hydrogeochemical characterisation and geospatial analysis of groundwater for drinking water quality in Ludhiana district of Punjab, India

This study characterises the quality of groundwater for the Ludhiana district of Punjab, India by analysing water samples collected from 152 locations spread across 3767 km². The samples were analysed for 18 parameters consisting of pH, EC, TDS, TA, TH, major anions and cations. The parameter values have been used to calculate the drinking water quality index of the study area which suggests that 2.6, 57.9, 32.9, 4 and 2.6% of the samples fall under the excellent, good, poor, very poor and unsuitable categories, respectively. The sequence of abundance for ions (in meq/l) as revealed from the laboratory tests is Na⁺ (37.1%) > Ca²⁺ (30.8%) > Mg²⁺ (29.1%) > K⁺ (2.8%) for cations and HCO₃^- (80%) > Cl^¯ (8.9%) > CO₃^2- (6.5%) > SO₄^2- (3.9%) > NO₃^-, F^-, PO₄^3- (< 1%) for anions. The spatial variability of these parameters has been depicted through the use of interpolation maps. Evaluation of different ionic ratios indicates that carbonate weathering and silicate weathering are both significantly affecting the groundwater chemistry with a slight dominance of carbonate weathering. Also, the ion exchange process is taking place in the area as confirmed by CAI index values. In terms of saturation index, the groundwater is undersaturated with respect to halite, fluorite and sylvite, whereas it is supersaturated for calcite, dolomite and aragonite minerals. The principal components in PCA explained 75.4% of the total variance with 29.1 and 28.3% contributions from PC1 and PC2. Both of these components indicate towards the geogenic and anthropogenic influence on groundwater mineralization of the area. The analysis suggests that groundwater for the study area is suitable for drinking in most of the region expect in a few places. Such a study could be used to understand the current status of groundwater quality in the area, the results of which can be used to prevent further contamination and sustain the resource for the future.

Hydrogeochemical evaluation, groundwater contamination and associated health risk in southern Tangail, Bangladesh

Water pollution is a worldwide concern that has growing severe in developed and developing nations. Increasing groundwater pollution threatening both the physical and environmental health of billions of people as well as economic progress. Consequently, hydrogeochemistry, water quality and potential health risk assessment is crucial for water resource management. The study area comprises Jamuna Floodplain (Holocene deposit) area in the west and the Madhupur tract (Pleistocene deposit) area in the eastern part. Total 39 groundwater samples were collected from the study area and were analyzed for physicochemical parameters, hydrogeochemical, trace metals, and isotopic composition. The water types are mainly Ca-HCO₃^- to Na-HCO₃^- types. The isotopic compositions (δ¹⁸O and δ²H) analysis traces the recent recharge in Floodplain area from rainwater and no recent recharge in Madhupur tract. The concentration of NO₃^-, As, Cr, Ni, Pb, Fe, and Mn in shallow and intermediate aquifer at the Floodplain area exceed the WHO-2011 permissible limit and is lower at deep Holocene and Madhupur tract aquifer. The integrated weighted water quality index (IWQI) exposed groundwater from shallow and intermediate aquifer are unsuitable for drinking and deep Holocene aquifer and Madhupur tract are suitable for drinking purposes. PCA analysis confirmed that anthropogenic activity is dominant in shallow and intermediate aquifers. The non-carcinogenic and carcinogenic risk for adults and children is due to oral and dermal exposure. The non-carcinogenic risk evaluation revealed that the mean hazard index (HI) values range from 0.009742 to 16.37 for adults and 0.0124-20.83 for children, respectively, and most groundwater samples from shallow and intermediate aquifers exceed the permissible limit (HI > 1). The carcinogenic risk ranges from 2.71 × 10^-6-0.014 for adults and 3.44 × 10^-6-0.017 for children via oral consumption and 7.09 × 10^-11-1.18 × 10^-6 for adults and 1.25 × 10^-10-2.09 × 10^-6 for children via dermal exposure. Spatial distribution shows the presence of trace metal and associated health risk is high in shallow and intermediate aquifer (Holocene) than in the deep (Holocene) Madhupur tract (Pleistocene). The study implies that effective water management will ensure safe drinking water for the future generation of people.

Hydrochemical evaluation of groundwater quality and human health risk assessment of trace elements in the largest mining district of South Khorasan, Eastern Iran

The groundwater resources of mining areas have been in a challenging condition in terms of metal pollution and human health. Therefore, this study investigated the concentration of cobalt (Co), molybdenum (Mo), selenium (Se), tin (Sn), and antimony (Sb) in groundwater samples (wells, qanats, and springs) in a heavily contaminated mining district, South Khorasan, Eastern Iran. Human health risk of the studied metals to target groups was assessed, and water quality of the studied groundwater was investigated in the study area. A total of 367 sampling sites (279 wells, 74 qanats, and 14 springs) in South Khorasan Province were selected to collect the groundwater samples from June to July 2020. Sampling was performed thrice for each sampling point, and hydrochemical parameters were evaluated using a portable multiparameter. Inductively coupled plasma mass spectrometry (ICP-MS) was used to detect the metal concentrations. Results showed an order of Se > Mo > Sn > Co > Sb, and hazard index (HI) demonstrated a warning condition for south of South Khorasan (drinking application), southwest of South Khorasan (Irrigation application), and east and center of South Khorasan (drinking-irrigation application). Hydrochemical parameters showed a classification of "Na + K type" and "Mixed Ca-Mg-Cl type" with an overall group of "Na-Cl-HCO3" for sampled waters. Ficklin-Caboi diagram depicted a classification of "near-neutral low metal," and Schoeller diagram classified studied groundwater as "good" for drinking and irrigation consumptions and "Na-Cl" type based on ion balance diagram. Based on the correlation analysis, positive relationships were recorded among EC, TDS, Cl-, Na+, sulfate, Ca2+, salt, total hardness, Mg2+, ammonia, and K+ measured in the water samples. In essence, arid regions of the world greatly rely upon groundwater resources for drinking and irrigation consumptions, and mining districts with a heavy load of active mines can be a serious threat to the groundwater quality and human health.

Groundwater Quality Assessment in the Northern Part of Changchun City, Northeast China, Using PIG and Two Improved PIG Methods

As a numerical indicator, the pollution index of groundwater (PIG) has gained a great deal of popularity in quantifying groundwater quality for drinking purposes. However, its weight-determination procedure is rather subjective due to the absolute dependence on experts’ experience. To make the evaluation results more accurate and convincing, two improved PIG models (CRITIC-PIG and Entropy-PIG) that integrate subjective weights and objective weights were designed, and they were employed to appraise groundwater suitability for drinking purposes in the northern part of Changchun City. A total of 48 water samples (34 unconfined water samples and 14 confined water samples) with abundances of Ca²⁺ and HCO₃⁻ were collected and tested to obtain the data for the analyses. The results showed that 60.4%, 47.9% and 60.4% of the water samples manifested insignificant pollution and were marginally potable based on the values of the PIG, CRITIC-PIG and Entropy-PIG, respectively. Though 48% of the water samples had different evaluation results, their level difference was mostly 1, which is relatively acceptable. The distribution maps of the three sets of PIG values demonstrated that the quality of groundwater was the best in Dehui City and the worst in Nongan County. Groundwater contamination in the study area was mainly caused by the high concentrations of TDS, TH, Fe³⁺, F⁻ and NO₃⁻, which not only came from geogenic sources but also anthropogenic sources.

Judging the sources of inferior groundwater quality and health risk problems through intake of groundwater nitrate and fluoride from a rural part of Telangana, India

Evaluation of groundwater quality and related health hazards is a prerequisite for taking preventive measures. The rural region of Telangana, India, has been selected for the present study to assess the sources and origins of inferior groundwater quality and to understand the human health risk zones for adults and children due to the consumption of nitrate ([Formula: see text])- and fluoride (F^-)-contaminated groundwater for drinking purposes. Groundwater samples collected from the study region were determined for various chemical parameters. Groundwater quality was dominated by Na⁺ and [Formula: see text] ions. Piper's diagram and bivariate plots indicated the carbonate water type and silicate weathering as a main factor and man-made contamination as a secondary factor controlling groundwater chemistry; hence, the groundwater quality in the study region is low. According to the Groundwater Quality Index (GQI) classification, 48.3% and 51.7% of the total study region are excellent (GQI: < 50) and good (GQI: 50 to 100) water quality types, respectively, for drinking purposes. However, [Formula: see text] ranged from 0.04 to 585 mg/L, exceeding the drinking water quality limit of 45 mg/L in 34% of the groundwater samples due to the effects of nitrogen fertilizers. This was supported by the relationship of [Formula: see text] with TDS, Na⁺, and Cl^-. The F^- content was from 0.22 to 5.41 mg/L, which exceeds the standard drinking water quality limit of 1.5 mg/L in 25% of the groundwater samples. The relationship of F^- with pH, Ca²⁺, Na⁺, and [Formula: see text] supports the weathering and dissolution of fluoride-rich minerals for high F^- content in groundwater. They were further supported by a principal component analysis. The Health Risk Index (HRI) values ranged from 0.20 to 20.10 and 0.36 to 30.90 with a mean of 2.82 and 4.34 for adults and children, respectively. The mean intensity of HRI (> 1.0) was 1.37 times higher in children (5.70) than in adults (4.16) due to the differences in weight size and exposure time. With an acceptable limit of more than 1.0, the study divided the region into Northern Safe Health Zone (33.3% for adults and 28.1% for children) and Southern Unsafe Health Zone (66.7% for adults and 71.9% for children) based on the intensity of agricultural activity. Therefore, effective strategic measures such as safe drinking water, denitrification, defluoridation, rainwater harvesting techniques, sanitary facilities, and chemical fertilizer restrictions are recommended to improve human health and protect groundwater resources.

Data-driven soft computing modeling of groundwater quality parameters in southeast Nigeria: comparing the performances of different algorithms

In recent decades, the simulation and modeling of water quality parameters have been useful for monitoring and assessment of the quality of water resources. Moreover, the use of multiple modeling techniques, rather than a standalone model, tends to provide more robust and reliable insights. In this present paper, several soft computing techniques were integrated and compared for the modeling of groundwater quality parameters (pH, electrical conductivity (EC), total dissolved solids (TDS), total hardness (TH), modified heavy metal index (MHMI), pollution load index (PLI), and synthetic pollution index (SPI)) in Ojoto area, SE Nigeria. Standard methods were employed in the physicochemical analysis of the groundwater resources. It was found that anthropogenic and non-anthropogenic activities influenced the concentrations of the water quality parameters. The PLI, MHMI, and SPI revealed that about 20-25% of the groundwater samples are unsuitable for drinking. Simple linear regression indicated that strong agreements exist between the results of the water quality indices. Principal component and Varimax-rotated factor analyses showed that Pb, Ni, and Zn influenced the judgment of the water quality indices most. Q-mode hierarchical and K-means clustering  algorithms grouped the water samples based on their pH, EC, TDS, TH, MHMI, PLI, and SPI values. Multiple linear regression (MLR) and artificial neural network (ANN) algorithms were used for the simulation and prediction of  the pH, EC, TDS, TH, PLI, MHMI, and SPI. The MLR performed better than the ANN model in predicting EC, TH, and TDS. Nevertheless, the ANN model predicted the pH better than the MLR model. Meanwhile, both MLR and ANN performed equally in the prediction of PLI, MHMI, and SPI.