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.

  • Groundwater quality was evaluated using the pollution index of groundwater.

  • The health risks for humans were calculated using the model suggested by the United States Environmental Protection Agency (USEPA).

  • The health risk was higher in children as compared to women and men in the study area.

  • Findings from this study will provide an important understanding of the health risk of nitrate present in groundwater.

Groundwater plays an essential role in providing a major drinking water sources in arid and semi-arid areas worldwide. About 2.5 billion people worldwide fulfill their drinking needs using groundwater as the only source (UNESCO 2012; Aasif et al. 2023). Many studies have indicated that the quality of groundwater has been deteriorating over time due to various factors such as rapid industrialization, population growth, anthropogenic and geogenic activities, excessive exploitation, the intensive use of fertilizers and pesticides in agriculture, and the discharge of untreated municipal and industrial effluents into water sources (Gao et al. 2020; Adimalla & Qian 2022). Consumption of contaminated drinking water poses a threat to human health, resulting in various health issues in many regions around the world (Adimalla et al. 2020; Rajmohan et al. 2021). Over the past few decades, extensive research is reported about the geochemistry of groundwater, groundwater quality, sources of groundwater pollution, and the interrelated health risks. For example, Adimalla et al. (2020) evaluated the groundwater quality in the Nalgonda district, Telangana state, India. They found that health risk was higher in infants and children as compared to adults. However, while evaluating the comprehensive chemical quality of groundwater, Krishan et al. (2023) employed an integrated approach for studying groundwater quality for drinking through hydrochemistry and water quality index in the Mewat district, northern India. (Subba Rao 2012; Rao et al. 2018; Adimalla et al. 2020; Raheja et al. 2024) employed the pollution index of groundwater (PIG) to estimate the relative influence of each physicochemical parameter on the overall chemical quality of groundwater. Their results showed that hydrogen ion concentration (pH), electrical conductivity (EC), total dissolved solids (TDS), total hardness (TH), calcium (Ca2+), magnesium (Mg2+), bicarbonate (HCO3), chloride (Cl), sodium (Na+), potassium (K+), sulfate (SO42−), nitrate (NO3), and fluoride (F) were used as pollution indicators to estimate groundwater quality for drinking. Raheja et al. (2023a) investigated the groundwater quality in Kurukshetra, India, using multivariate approaches (Irrigation Water Quality Index (IWQI), Wilcox diagram, and principal component analysis (PCA)). PCA is an effective tool that divides various hydrochemical parameters into distinct principal components (PCs) based on the relations among different variables. These components represent the basic factors influencing groundwater chemistry (Lanjwani et al. 2020; Zhang et al. 2022).

Several studies have highlighted the significance of employing various methods not just for measuring groundwater quality but also for evaluating pollution sources and identifying susceptible distribution patterns (Najafzadeh et al. 2021; Sunitha & Reddy 2022; Zhang et al. 2022; Raheja et al. 2023c). Kumar et al. (2019) applied various techniques to identify the origin of nitrate contamination in the groundwater of the middle Gangetic plain, India, and suggest that nitrate pollution in groundwater is primarily caused by human activities, including the application of fertilizers, livestock practices, the presence of wastewater ponds, and seepage from septic tanks. For example, the study by Bazeli et al. (2022) in rural areas of Khaf County, Iran, assessed non-carcinogenic human health risks and revealed that the hazard quotient (HQ) values of nitrate for infants, children, teenagers, and adults in 32, 32, 14, 10, and 7% of the groundwater samples were higher than the desired limit. Another study carried out by Singh et al. (2020) in the alluvial plains of Punjab, northern India, found that children are more exposed through direct ingestion compared to other age groups. Prolonged ingestion of high nitrate levels can pose instantaneous health hazards, including the risk of methemoglobinemia (commonly known as blue baby syndrome) in newborn babies and a sensitive potential for stomach cancer in men and women (WHO 2017; Karnena et al. 2022; Sun et al. 2023). The World Health Organization (WHO 2017) has set a maximum allowable nitrate concentration in drinking water of 50 mg/L. In India, the Bureau of Indian Standards (BIS 2015) recommends a permissible nitrate level in drinking water of 45 mg/L. The issue of high salinity in groundwater affects the northwestern regions of India, including Haryana, Delhi, Punjab, and Rajasthan, where these problems originated from terrestrial sources (Krishan et al. 2023). In recent years, several studies on groundwater have focused on issues such as monitoring pollution sources, examining geochemistry, and assessing the quality of water for both drinking and irrigation uses (Howladar et al. 2018; Toure et al. 2019; Adimalla 2020; Aouiti et al. 2021; Patel et al. 2022; Dey & Raju 2023; Raheja et al. 2023b). Factually, this research primarily highlighted a particular problem-solving approach within specific regions. Consequently, there exists a research gap that can be addressed by presenting a novel combined approach. This study reveals the effectiveness of such an innovative integrated method.

An extensive literature review suggests that so far no research study has evaluated the groundwater quality of Rohtak district (Haryana, India) based on PIG and human health risk from nitrate pollution using an integrated approach. Hence, there is a need to understand the groundwater quality and assess the human health risk in the study area. Keeping this in view, the present study is carried out (a) to assess the chemical characterization of groundwater in the Rohtak district, (b) to evaluate groundwater quality for drinking purpose using PIG and their spatial distribution, (c) to recognize the hydrogeochemistry of groundwater by using multivariate techniques (PCA, correlation), and (d) to estimate the concentration of nitrate and its potential non-carcinogenic health risk for children, women, and men. The results of this research will offer valuable scientific insights into the health risks associated with nitrate present in groundwater, contributing to the maintenance of water quality standards in this region.

Study area

The Rohtak district in Haryana, India, is located between 28°40.46′ and 29°06.08′ North latitude and 76°12.40′ and 76°52.00′ East longitude. The district covers an area of 1,745 km2 and has an elevation range varying from 216 to 275 m above sea level. The average temperature in the area varies from 7 °C in January to 40.5 °C in May and June, and the annual average rainfall is about 592 mm. The study area falls within a subtropical semi-arid region, which is known for its hot summers and cold winters. The depth of groundwater levels fluctuates between the range of less than 1.72–10.75 m below ground level (BGL) during the pre-monsoon period and 1.46–9.07 m BGL during the post-monsoon period (CGWB 2019).

Land use land cover

Land use and land cover (LULC) data are as crucial inputs for any region to track the evolving changes in their soil and land use over time (Tavares et al. 2019; Elmahdy et al. 2020). In this present study, an LULC map of the study area is created and is represented in Figure 1(a). For this, the Landsat 8 data of 5 September 2023 and having 0% cloud cover was acquired. The area was classified into five classes. Irrigation serves as the principal occupation of the people in the study area, as evident from land use data revealing that 62.7% of the land is area that covers vegetation and agricultural activities, 10.5% fall under water bodies, 18.5% built-up area, and 8.3% barren land (Figure 1(b)). The major crops of the study area are wheat, rice, jowar, bajra, mustard, and sugarcane (CGWB 2019). The presence of agriculture and vegetation in about two-third of the study area indicates the excessive use of groundwater, leading to deterioration in its quality.
Figure 1

(a) LULC classification map of the study area. (b) LULC distribution map of the study area.

Figure 1

(a) LULC classification map of the study area. (b) LULC distribution map of the study area.

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Collection of groundwater samples and analytical techniques

Groundwater samples were collected from 47 locations through tube wells and hand pumps exclusively used for drinking during December 2022. The precise locations of the tube wells and hand pumps in the study area were obtained using a portable GPS device (Figure 2). Groundwater samples were collected using pre-cleaned 1-L high-density polyethylene bottles rinsed with the groundwater samples three to four times. The standard procedures outlined by the American Public Health Association (APHA 2012) were strictly followed for the collection, storage, transportation, and analysis of groundwater samples. The pH, EC, and TDS were measured at each sampling site using a portable digital pH/EC/TDS meter. The concentration of TH, Ca2+, Mg2+, HCO3, and Cl were estimated using the titration method (APHA 2012). The concentration of Na+ and K+ were calculated using a flame photometer. The concentration of SO42−, NO3, and F were estimated using a spectrophotometer. To check the reliability of the groundwater quality dataset, an ion balance error (IBE) test was also carried out using Equation (1), as given below:
formula
(1)
Figure 2

Location map of the study area with groundwater sample positions.

Figure 2

Location map of the study area with groundwater sample positions.

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All the cation and anion concentrations are in mg/L, and all groundwater samples fall within the acceptable limit of ±10%.

Pollution index of groundwater

The PIG, initially proposed by Subba Rao (2012), is an effective tool for evaluating the overall water quality pollution based on hydrochemical data and water quality criteria. PIG calculation involves five different steps, which are explained below:

Step 1: Calculate the relative weight () of each groundwater quality parameter. The varies from 1 to 5 and is assigned to each chemical parameter, depending on the level of importance of groundwater for drinking purposes, as shown in Table 1.

Table 1

Relative weight of groundwater quality parameters

Sr. No.Name of parametersRelative weight ()
pH 0.0652 
TDS 0.0870 
EC 0.0870 
TH 0.0652 
Ca2+ 0.0435 
Mg2+ 0.0870 
HCO3 0.0217 
Na+ 0.0652 
K+ 0.0652 
10 Cl 0.0870 
11 SO42− 0.1087 
12 NO3 0.1087 
13 F 0.1087 
= 46    
Sr. No.Name of parametersRelative weight ()
pH 0.0652 
TDS 0.0870 
EC 0.0870 
TH 0.0652 
Ca2+ 0.0435 
Mg2+ 0.0870 
HCO3 0.0217 
Na+ 0.0652 
K+ 0.0652 
10 Cl 0.0870 
11 SO42− 0.1087 
12 NO3 0.1087 
13 F 0.1087 
= 46    

Step 2: Weight parameter , which is the ratio of the relative weight of the parameter to the sum of all relative weights is calculated. The is calculated using Equation (2):
formula
(2)
Step 3: The concentration status is calculated by dividing each chemical concentration of each groundwater sample by its relevant drinking standards limits (BIS 2015; WHO 2017) using Equation (3):
formula
(3)
Step 4: Overall groundwater quality for drinking is calculated using Equation (4):
formula
(4)
Step 5: The is computed by taking the sum of all values (Equation (5)):
formula
(5)

PIG value can be classified into five categories (Subba Rao 2012). If PIG value is less than 1.0, it falls in the insignificant pollution class. If PIG values lie between 1.0 and 1.5, then it falls in the low pollution class. If PIG values lie between 1.5 and 2.0, then it falls in the moderate groundwater pollution class. If PIG values lie between 2.0 and 2.5, then there is high pollution, and if the PIG value exceeds 2.5, groundwater has very high pollution, which means that the groundwater in a specific region is at a higher risk of contamination (Subba Rao 2012; Adimalla et al. 2020).

Human health risk assessment

The human health risk assessment was introduced by the United States Environmental Protection Agency (USEPA), and it evaluates the possible health impacts on humans resulting from consuming contaminated water (USEPA 1989). In general, consuming contaminated drinking water poses a substantial risk to humans, mainly through two-way exposure: through oral drinking water and through the dermal or skin contact. This research calculates the health risks associated with oral and skin contact exposures separately for both children and adults (women and men). The non-carcinogenic risk from oral contact was calculated using Equations (6) and (7):
formula
(6)
formula
(7)
where is the daily intake through oral way [mg/(kg × day)], C represents the contamination of the nitrate content in groundwater of the study area (mg/L), is the ingestion rate in L/day (IR = 1 L/day for children and 2.5 L/day for adults), is exposure duration in year (12 years for children, 67 years for women, and 64 years for men) (Adimalla et al. 2020), represents the exposure frequency (days/year, 365 days/year for children, women, and men), and is the hazard quotient. is average body weight in kg (15 kg for children, 55 kg for women, and 65 kg for men), represents the average exposure time in days (4,380 days for children, 24,455 days for women, and 23,360 days for men), and is the reference dose of nitrate contaminant, which is 1.6 mg/kg/day (USEPA 1989, 2002).
Non-carcinogenic risk from dermal/skin contact is calculated using Equations (8) and (9):
formula
(8)
formula
(9)
formula
(10)
where represents the dermal absorbed dose (mg/kg × day), represents the contact time (0.4 h/day), is the dermal adsorption parameters (0.001 cm/h), represents the conversion factor (0.001) based on the USEPA (USEPA 1989, 2002), is the bathing frequency (times/day, one time in a day), represents the skin surface area in cm2 (12,000 cm2 for children and 16,600 cm2 for adults). The non-carcinogenic health risk is given by the hazard index (HI). The value of HI >1 expresses a potential health risk to humans, and HI <1 means no health risk (USEPA 1989).

Geospatial and statistical analysis

Inverse distance weighting (IDW) and Kriging are the primary interpolation methods for creating spatial representations of water quality assessments across different locations (Kumar & Sangeetha 2020; Fatima et al. 2022; Azhari et al. 2023). However, IDW can also detect parameters that are potentially not distributed in normal ways, while Kriging is only capable to perform well with normally distributed samples (Kamaraj et al. 2021; Raheja et al. 2022). For this study, IDW is used to prepare the spatial distribution maps. In addition, PCA is also used to identify the correlations among various physicochemical parameters in the study area. Its aims are to moderate the complexity of a multivariate dataset by capturing its information through a limited set of PCs, thereby preserving the essential characteristics of the environment. This reduction in information allows for the extraction of primary factors containing the necessary information. Therefore, to monitor the groundwater quality of the study area and to observe the major influencing factors, PCA is applied on the obtained results of physicochemical parameters.

Hydrochemistry of the groundwater

Table 2 provides a comprehensive statistical summary of the analysis of 13 physicochemical parameters (including pH, EC, TDS, Ca2+, Mg2+, HCO3, Na+, K+, Cl, SO42−, NO3, and F) across 47 groundwater samples. Moreover, these results are compared with the drinking water quality standards recommended by the Bureau of Indian Standards (BIS 2015) and the World Health Organization (WHO 2017) to estimate their suitability for drinking purposes in the study region. The standard deviation (SD) values vary from 0.33 to 3,717.13, and this considerable difference in SD may stem from various hydrogeochemical reactions and substantial differences in the distribution of salts within the groundwater. The coefficient of variation (CV) ranges from 4.92 to 107.42%, and the highest value of CV is of Mg2+ (107.42%) followed by EC (87.39%), Ca2+ (70.66%), TDS (68.41%), SO42− (50.04%), Cl (48.93%), Na+ (40.24%), K+ (40.19%), NO3 (37.86%), F (37.35%), HCO3 (34.69%), and pH (4.92%). This observation recommends that Mg2+, EC, Ca2+, and TDS might be the primary key factors that naturally govern the groundwater chemistry in the study area.

Table 2

Statistical summary of the measured water parameters compared to BIS (2015) and WHO (2017) limits for drinking water

Name of parametersMinimumMaximumMeanSDCVBIS (2015) WHO (2017) 
Acceptable-permissible limitAcceptable-permissible limit
pH 7.05 8.7 7.72 0.38 4.92% 6.5–8.5 6.5–8.5 
TDS 229 8,544 2,681.89 1,834.68 68.41% 500–2,000 500–1,500 
EC 329 18,400 4,253.70 3,717.13 87.39% a a 
TH 110 3,660 794.38 714.31 89.92% 200–600 100–500 
Ca2+ 60 1,060 294.33 207.97 70.66% 75–200 75–200 
Mg2+ 50 2,900 500.05 537.18 107.42% 30–100 30–150 
HCO3 1.8 14.9 7.65 2.66 34.69% a 50–200 
Na+ 115 636 301.96 121.51 40.24% a 200 
K+ 29 163 90.94 36.55 40.19% a 300–600 
Cl 85 921 462.30 226.21 48.93% 250–1,000 250–600 
SO42− 75 965 448.26 224.32 50.04% 200–400 200–600 
NO3 15 85 49.43 18.71 37.86% 10–45 50 
F 0.25 1.65 0.87 0.33 37.35% 1.0–1.5 1.0–1.5 
Name of parametersMinimumMaximumMeanSDCVBIS (2015) WHO (2017) 
Acceptable-permissible limitAcceptable-permissible limit
pH 7.05 8.7 7.72 0.38 4.92% 6.5–8.5 6.5–8.5 
TDS 229 8,544 2,681.89 1,834.68 68.41% 500–2,000 500–1,500 
EC 329 18,400 4,253.70 3,717.13 87.39% a a 
TH 110 3,660 794.38 714.31 89.92% 200–600 100–500 
Ca2+ 60 1,060 294.33 207.97 70.66% 75–200 75–200 
Mg2+ 50 2,900 500.05 537.18 107.42% 30–100 30–150 
HCO3 1.8 14.9 7.65 2.66 34.69% a 50–200 
Na+ 115 636 301.96 121.51 40.24% a 200 
K+ 29 163 90.94 36.55 40.19% a 300–600 
Cl 85 921 462.30 226.21 48.93% 250–1,000 250–600 
SO42− 75 965 448.26 224.32 50.04% 200–400 200–600 
NO3 15 85 49.43 18.71 37.86% 10–45 50 
F 0.25 1.65 0.87 0.33 37.35% 1.0–1.5 1.0–1.5 

Note: All parameters are shown in mg/L, except for pH (pH on a scale) and EC (μS/cm). SD, standard deviation; CV, coefficient of variation

aNot available.

The pH value in the study area lies between 7.05 and 8.7, with a mean of 7.66, suggesting that the study area's groundwater is neutral to slightly alkaline. The value of pH is mainly within the permissible limit (6.5–8.5) recommended by BIS (2015) and WHO (2017) for drinking (Table 2). TDS concentration ranges between 229 and 8,544 mg/L with a mean of 2,681.89 mg/L. The maximum permissible limit is 2,000 mg/L, as suggested by BIS (2015). The value of TDS in about 51.06% of groundwater samples exceeded this permissible limit (BIS 2015). EC measures a material's capacity to enable the flow of electric current through the dissolved salts in water. EC can be classified as follows: low salt enrichment if EC value is less than 1,500 μS/cm, medium salt enrichment if EC falls in between 1,500 and 3,000 μS/cm, and high salt enrichment if EC is more than 3,000 μS/cm. In the present study, EC value of the study area ranges from 329 to 18,400 μS/cm with a mean of 3,717.13 μS/cm. However, only 8.5% of groundwater samples fall under the Class I type, and 40.4 and 51.1% are found in the Class II and Class III types, respectively. This observation strongly suggests that interactions between rocks and water, geochemical reactions, and anthropogenic influences are the predominant factors influencing groundwater chemistry in the study area. The TH value was found to vary from 110 to 3,360 mg/L with a mean of 794.38 mg/L. The TH is divided into four different classes: TH <75 mg/L indicates soft water; when the TH value lies between 75 and 150 mg/L, moderately hard water; between 150 and 300 mg/L, hard water; and more than 300 mg/L, very hard water (Sawyer & McCarty 1978). According to this classification, no groundwater samples fall under soft water, and 14.89 and 80.85% fall under the hard and very hard water category. About 48.93% of groundwater samples have exceeded the maximum permissible limit of 600 mg/L, which is unsuitable for drinking purposes (BIS 2015). The predominant of cations and anions based on their mean values are in the following order: Mg2+ > Ca2+ > Na+ > K+, and Cl > SO42− > NO3 > HCO3 > F. The concentration of Ca2+ varied from 60 to 1,060 mg/L with a mean of 294.33 mg/L. Of the groundwater samples, 60% have a higher value than the recommended limit of 200 mg/L (BIS 2015; WHO 2017). The Mg2+ value was found to vary from 50 to 2,900 mg/L with a mean of 500.1 mg/L. The HCO3 concentration ranged from 1.8 to 14.9 with a mean of 7.65 mg/L. A comparison with the permissible limit of HCO3 for drinking water mentions that all the groundwater samples are within acceptable limits (WHO 2017). The concentration of Na+ ranges from 115 to 636 mg/L for all samples collected in the study area. This study found that 68.08% of groundwater samples exceeded the permissible drinking limit recommended by WHO (2017). The value of K+ ranges from 29 to 163 mg/L, with a mean value of 90.94 mg/L. Keeping in view of the excess amount of both Na+ and K+ in the study region, it is recommended that groundwater should be treated before using it for drinking purposes. The Cl concentration was found to vary from 85 to 921 mg/L with a mean of 462.30 mg/L (Table 2). Results suggest that 76.5% of the total groundwater samples have a higher value of Cl content than the recommended limit of 250 mg/L for drinking water (BIS 2015). The SO42− concentration in the study area was between 75 and 965 mg/L, and about 50% of the groundwater samples exceed permissible limits (BIS 2015). The F concentration ranges between 0.25 and 1.65 mg/L with a mean of 0.87 mg/L (Table 2). In this study, only 6.3% of the samples exceeded the maximum permissible limit (1.5 mg/L) for drinking purposes (BIS 2015).

Concentration and distribution of NO3

NO3 is the predominant pollutant found in groundwater across arid and semi-arid areas worldwide. In this study, NO3 concentration ranges from 15 to 85 mg/L with a mean value of 49.43 mg/L (Figure 3(a)). The BIS (2015) and the WHO (2017) established a public health standard for NO3 in drinking water, with a limit of 45 mg/L. The findings from this study demonstrate that 48.93% of groundwater samples had NO3 concentrations exceeding the BIS (2015) and WHO (2017) limits of 45 mg/L, which are not recommended for drinking uses. The high concentration of NO3 in drinking water can lead to health issues such as methemoglobinemia or blue baby syndrome in infants as well as an increased risk of gastric cancer, central nervous system congenital disabilities, and hypertension in adults (Karnena et al. 2022; Raheja et al. 2023c). Usually, higher NO3 concentration in groundwater originates from human activities, including agricultural practices (such as extreme fertilizer use), improper disposal of domestic sewage, animal waste, and septic tank leaks (Adimalla et al. 2020; Singh et al. 2020). The spatial distribution map of NO3 in groundwater of the study area is represented in Figure 3(b). The highest NO3 concentration (85 mg/L) was found in groundwater sample S46, which is located in the northern part of the study region and marked in red color, and the lowest value (15 mg/L) was found in groundwater sample S3, which is situated in the western part of the study area.
Figure 3

(a) Scatter plot of NO3 concentration in all collected groundwater samples. (b) Spatial distribution map of health risk zones concerning NO3 in groundwater.

Figure 3

(a) Scatter plot of NO3 concentration in all collected groundwater samples. (b) Spatial distribution map of health risk zones concerning NO3 in groundwater.

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Evaluation of PIG

The PIG method is highly valuable for evaluating water quality, including surface and groundwater (Subba Rao & Chaudhary 2019; Adimalla et al. 2020; Egbueri 2020). In this study, the PIG concentration ranges from 0.99 to 3.85, with an average of 1.98 (Figure 4(a)). Based on the PIG classification, 2.21% of groundwater samples fall in insignificant pollution; 23.4% of samples fall in low pollution; and 42.55%, 14.89%, and 17.02% of the samples fall under moderate, high, and very high pollution zones, respectively. Figure 4(b) shows the spatial distribution map of the PIG classification of the study area. Most of the study area is occupied by moderate to high pollution regions in yellow and golden colors in the PIG spatial map. Moreover, very high pollution was observed in the western part of the study area.
Figure 4

(a) Scatter plot PIG concentration in all collected groundwater samples. (b) Spatial distribution map of PIG classification in groundwater.

Figure 4

(a) Scatter plot PIG concentration in all collected groundwater samples. (b) Spatial distribution map of PIG classification in groundwater.

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Principal component analysis

PCA is widely used to study the correlations between water quality parameters and the sources responsible for these variations. In this study, five PCs were observed with eigenvalues of more than 1 with a cumulative variance of 77.36%. The relationship between water quality parameters and the sample locations within the study area is shown in Figure 5. Figure 5 also represents a variation of each groundwater quality parameter concerning PC1 (34.54%) and PC2 (14.07%). PC1 involves positive loadings of TDS (0.428), TH (0.451), Mg2+ (0.451), Ca2+ (0384), and EC (0.380). The findings suggest that groundwater chemistry primarily reflects the influence of natural sources, rock and mineral weathering, and human activities (Zhang et al. 2020). PC2 has positive loadings with NO3 (0.435) and F (0.502), indicating that the source of nitrate in the groundwater of the study area was different from that of other significant cations and anions. These ions are primarily associated with inputs from human activities, with domestic sewage infiltration, unexpected irrigation practices, industrial wastewater, septic tanks, animal waste, and landfill leachate being potential primary sources of nitrate pollution (Zhang et al. 2020). PC3 has positive loadings with K+ (0.521) and Cl (0.626) (Table 3). PC4 explained 9.94% of the total variance with 1.292 of the total loading, and PC5 explained 8.04% of the total variance with 1.045 of the total loading. The correlation matrix of all 13 groundwater quality parameters was created and analyzed (Table 4). The TDS has a significant positive correlation with EC (0.851), TH (0.803), Ca2+ (0.593), and Mg2+ (0.832), as demonstrated by the correlation matrix of the quality parameters (Table 4).
Table 3

PC loadings for groundwater quality parameters of the study area

ComponentEigenvalue
Component
Total% of varianceCumulative %ParametersPC1PC2PC3PC4PC5
pH− 0.211− 0.0800.0590.3200.674
PC1 4.491 34.54 34.54 TDS 0.428 0.212 −0.052 −0.0001 0.118 
PC2 1.829 14.07 48.61 EC 0.380 0.119 −0.067 −0.025 0.419 
PC3 1.401 10.78 59.39 TH 0.451 0.094 0.015 0.169 −0.024 
PC4 1.292 9.94 69.32 Ca2+ 0.384 0.158 0.113 0.220 −0.200 
PC5 1.045 8.04 77.36 Mg2+ 0.451 0.064 −0.024 0.139 0.045 
PC6 0.853 6.56 83.92 HCO3 0.157 −0.519 −0.003 −0.373 −0.172 
PC7 0.730 5.62 89.54 Na+ 0.049 0.142 −0.143 −0.576 0.097 
PC8 0.563 4.33 93.87 K+ 0.081 −0.008 0.521 0.250 0.423 
PC9 0.360 2.77 96.64 Cl −0.080 0.274 0.626 0.054 −0.097 
PC10 0.265 2.04 98.68 SO42− −0.089 −0.300 −0.146 0.506 0.067 
PC11 0.097 0.75 99.43 NO3 −0.045 0.435 0.520 −0.082 0.263 
PC12 0.074 0.57 100 F 0.154 0.502 0.003 0.044 −0.095 
ComponentEigenvalue
Component
Total% of varianceCumulative %ParametersPC1PC2PC3PC4PC5
pH− 0.211− 0.0800.0590.3200.674
PC1 4.491 34.54 34.54 TDS 0.428 0.212 −0.052 −0.0001 0.118 
PC2 1.829 14.07 48.61 EC 0.380 0.119 −0.067 −0.025 0.419 
PC3 1.401 10.78 59.39 TH 0.451 0.094 0.015 0.169 −0.024 
PC4 1.292 9.94 69.32 Ca2+ 0.384 0.158 0.113 0.220 −0.200 
PC5 1.045 8.04 77.36 Mg2+ 0.451 0.064 −0.024 0.139 0.045 
PC6 0.853 6.56 83.92 HCO3 0.157 −0.519 −0.003 −0.373 −0.172 
PC7 0.730 5.62 89.54 Na+ 0.049 0.142 −0.143 −0.576 0.097 
PC8 0.563 4.33 93.87 K+ 0.081 −0.008 0.521 0.250 0.423 
PC9 0.360 2.77 96.64 Cl −0.080 0.274 0.626 0.054 −0.097 
PC10 0.265 2.04 98.68 SO42− −0.089 −0.300 −0.146 0.506 0.067 
PC11 0.097 0.75 99.43 NO3 −0.045 0.435 0.520 −0.082 0.263 
PC12 0.074 0.57 100 F 0.154 0.502 0.003 0.044 −0.095 
Table 4

Correlation among groundwater quality parameters of the study area

pHTDSECTHCa2+Mg2+HCO3Na+K+ClSO42−NO3F
pH             
TDS −0.291            
EC −0.110 0.851           
TH −0.35 0.803 0.693          
Ca2+ −0.411 0.593 0.451 0.891         
Mg2+ −0.308 0.832 0.747 0.984 0.798        
HCO3 −0.266 0.474 0.297 0.150 0.026 0.190       
Na+ −0.168 0.073 0.139 0.026 −0.042 0.052 0.054      
K+ −0.006 0.124 0.223 0.083 0.102 0.071 0.066 0.028     
Cl 0.102 −0.265 −0.217 −0.079 0.036 −0.119 −0.272 0.013 0.158    
SO42− 0.183 −0.048 −0.080 −0.150 −0.125 −0.151 −0.059 −0.156 −0.190 −0.152   
NO3 0.024 −0.192 −0.016 −0.048 −0.067 −0.038 −0.374 0.144 −0.186 −0.204 −0.208  
F −0.242 0.116 0.135 0.342 0.288 0.343 −0.264 0.104 0.056 0.127 −0.173 0.228 
pHTDSECTHCa2+Mg2+HCO3Na+K+ClSO42−NO3F
pH             
TDS −0.291            
EC −0.110 0.851           
TH −0.35 0.803 0.693          
Ca2+ −0.411 0.593 0.451 0.891         
Mg2+ −0.308 0.832 0.747 0.984 0.798        
HCO3 −0.266 0.474 0.297 0.150 0.026 0.190       
Na+ −0.168 0.073 0.139 0.026 −0.042 0.052 0.054      
K+ −0.006 0.124 0.223 0.083 0.102 0.071 0.066 0.028     
Cl 0.102 −0.265 −0.217 −0.079 0.036 −0.119 −0.272 0.013 0.158    
SO42− 0.183 −0.048 −0.080 −0.150 −0.125 −0.151 −0.059 −0.156 −0.190 −0.152   
NO3 0.024 −0.192 −0.016 −0.048 −0.067 −0.038 −0.374 0.144 −0.186 −0.204 −0.208  
F −0.242 0.116 0.135 0.342 0.288 0.343 −0.264 0.104 0.056 0.127 −0.173 0.228 

Note: Units of all groundwater quality parameters are in mg/L except pH (on a scale) and EC (μs/cm). Bold values ≥0.5 reflect significant correlation among the correlated groundwater quality parameters.

Figure 5

Biplot of the groundwater quality parameters (denoted by blue points) and sample points (denoted by red points) in the study area.

Figure 5

Biplot of the groundwater quality parameters (denoted by blue points) and sample points (denoted by red points) in the study area.

Close modal

Non-carcinogenic health risk assessment

This study shows the health risk assessment of children, women, and men as per the USEPA (2002). Most of the population in the study area depended on untreated groundwater for their drinking water requirements, so the health risk assessment for various groups (children, women, and men) is necessary for this region. The detailed results of non-carcinogenic health risks are presented in Table 5. Figure 6 shows the spatial distribution maps of health risk for children, women, and men. HQOral results range from 0.625 to 3.542 with an average of 2.059 for children, from 0.426 to 2.415 with an average 1.404 for women, and from 0.361 to 2.043 with an average of 1.188 for men (Table 5). It is observed that HQDermal values were much lower than zero for all three age groups. The HITotal values range from 0.628 to 3.559 with an average of 2.069 for children, from 0.427 to 2.421 with an average of 1.408 for women, and from 0.362 to 2.049 with an average of 1.191 for men. As per the USEPA guidelines, the acceptable limit of HI value is ≤ 1. When the Hazard Index (HI) is greater than 1, there are significant adverse human health risks from exposure (USEPA 2002). Table 5 shows that among the 47 groundwater samples in this region, the nitrate contamination level in drinking water exposes children in 45 communities, women in 38 communities, and men in 27 communities to the risk of acute nitrate poisoning. More precisely, the findings strongly suggest that children in the study area face a higher risk of non-carcinogenic health effects due to the consumption of high nitrate level in their drinking water.
Table 5

Results of non-carcinogenic risk through drinking water intake and dermal contact

Non-carcinogenic risk
SamplesHQOral
HQDermal
HITotal
ChildrenWomenMenChildrenWomenMenChildrenWomenMen
S1 3.125 2.131 1.803 0.015 0.006 0.005 3.140 2.136 1.808 
S2 1.083 0.739 0.625 0.005 0.002 0.002 1.089 0.741 0.627 
S3 3.542 2.415 2.043 0.017 0.006 0.005 3.559 2.421 2.049 
S4 1.000 0.682 0.577 0.005 0.002 0.002 1.005 0.684 0.578 
S5 0.625 0.426 0.361 0.003 0.001 0.001 0.628 0.427 0.362 
S6 2.708 1.847 1.563 0.013 0.005 0.004 2.721 1.851 1.567 
S7 1.500 1.023 0.865 0.007 0.003 0.002 1.507 1.025 0.868 
S8 1.583 1.080 0.913 0.008 0.003 0.002 1.591 1.082 0.916 
S9 1.875 1.278 1.082 0.009 0.003 0.003 1.884 1.282 1.085 
S10 2.750 1.875 1.587 0.013 0.005 0.004 2.763 1.880 1.591 
S11 1.417 0.966 0.817 0.007 0.003 0.002 1.423 0.968 0.819 
S12 1.625 1.108 0.938 0.008 0.003 0.002 1.633 1.111 0.940 
S13 3.250 2.216 1.875 0.016 0.006 0.005 3.266 2.222 1.880 
S14 2.000 1.364 1.154 0.010 0.004 0.003 2.010 1.367 1.157 
S15 2.875 1.960 1.659 0.014 0.005 0.004 2.889 1.965 1.663 
S16 1.583 1.080 0.913 0.008 0.003 0.002 1.591 1.082 0.916 
S17 1.542 1.051 0.889 0.007 0.003 0.002 1.549 1.054 0.892 
S18 2.000 1.364 1.154 0.010 0.004 0.003 2.010 1.367 1.157 
S19 3.125 2.131 1.803 0.015 0.006 0.005 3.140 2.136 1.808 
S20 1.458 0.994 0.841 0.007 0.003 0.002 1.465 0.997 0.844 
S21 2.708 1.847 1.563 0.013 0.005 0.004 2.721 1.851 1.567 
S22 2.792 1.903 1.611 0.013 0.005 0.004 2.805 1.908 1.615 
S23 2.667 1.818 1.538 0.013 0.005 0.004 2.679 1.823 1.543 
S24 1.958 1.335 1.130 0.009 0.004 0.003 1.968 1.339 1.133 
S25 2.875 1.960 1.659 0.014 0.005 0.004 2.889 1.965 1.663 
S26 1.417 0.966 0.817 0.007 0.003 0.002 1.423 0.968 0.819 
S27 1.875 1.278 1.082 0.009 0.003 0.003 1.884 1.282 1.085 
S28 1.583 1.080 0.913 0.008 0.003 0.002 1.591 1.082 0.916 
S29 3.083 2.102 1.779 0.015 0.006 0.005 3.098 2.108 1.784 
S30 0.750 0.511 0.433 0.004 0.001 0.001 0.754 0.513 0.434 
S31 2.792 1.903 1.611 0.013 0.005 0.004 2.805 1.908 1.615 
S32 3.125 2.131 1.803 0.015 0.006 0.005 3.140 2.136 1.808 
S33 2.833 1.932 1.635 0.014 0.005 0.004 2.847 1.937 1.639 
S34 2.417 1.648 1.394 0.012 0.004 0.004 2.428 1.652 1.398 
S35 1.333 0.909 0.769 0.006 0.002 0.002 1.340 0.912 0.771 
S36 1.875 1.278 1.082 0.009 0.003 0.003 1.884 1.282 1.085 
S37 1.625 1.108 0.938 0.008 0.003 0.002 1.633 1.111 0.940 
S38 1.042 0.710 0.601 0.005 0.002 0.002 1.047 0.712 0.603 
S39 1.458 0.994 0.841 0.007 0.003 0.002 1.465 0.997 0.844 
S40 1.958 1.335 1.130 0.009 0.004 0.003 1.968 1.339 1.133 
S41 1.208 0.824 0.697 0.006 0.002 0.002 1.214 0.826 0.699 
S42 1.875 1.278 1.082 0.009 0.003 0.003 1.884 1.282 1.085 
S43 2.833 1.932 1.635 0.014 0.005 0.004 2.847 1.937 1.639 
S44 1.000 0.682 0.577 0.005 0.002 0.002 1.005 0.684 0.578 
S45 1.542 1.051 0.889 0.007 0.003 0.002 1.549 1.054 0.892 
S46 3.542 2.415 2.043 0.017 0.006 0.005 3.559 2.421 2.049 
S47 1.958 1.335 1.130 0.009 0.004 0.003 1.968 1.339 1.133 
Minimum 0.625 0.426 0.361 0.003 0.001 0.001 0.628 0.427 0.362 
Maximum 3.542 2.415 2.043 0.017 0.006 0.005 3.559 2.421 2.049 
Mean 2.059 1.404 1.188 0.010 0.004 0.003 2.069 1.408 1.191 
Non-carcinogenic risk
SamplesHQOral
HQDermal
HITotal
ChildrenWomenMenChildrenWomenMenChildrenWomenMen
S1 3.125 2.131 1.803 0.015 0.006 0.005 3.140 2.136 1.808 
S2 1.083 0.739 0.625 0.005 0.002 0.002 1.089 0.741 0.627 
S3 3.542 2.415 2.043 0.017 0.006 0.005 3.559 2.421 2.049 
S4 1.000 0.682 0.577 0.005 0.002 0.002 1.005 0.684 0.578 
S5 0.625 0.426 0.361 0.003 0.001 0.001 0.628 0.427 0.362 
S6 2.708 1.847 1.563 0.013 0.005 0.004 2.721 1.851 1.567 
S7 1.500 1.023 0.865 0.007 0.003 0.002 1.507 1.025 0.868 
S8 1.583 1.080 0.913 0.008 0.003 0.002 1.591 1.082 0.916 
S9 1.875 1.278 1.082 0.009 0.003 0.003 1.884 1.282 1.085 
S10 2.750 1.875 1.587 0.013 0.005 0.004 2.763 1.880 1.591 
S11 1.417 0.966 0.817 0.007 0.003 0.002 1.423 0.968 0.819 
S12 1.625 1.108 0.938 0.008 0.003 0.002 1.633 1.111 0.940 
S13 3.250 2.216 1.875 0.016 0.006 0.005 3.266 2.222 1.880 
S14 2.000 1.364 1.154 0.010 0.004 0.003 2.010 1.367 1.157 
S15 2.875 1.960 1.659 0.014 0.005 0.004 2.889 1.965 1.663 
S16 1.583 1.080 0.913 0.008 0.003 0.002 1.591 1.082 0.916 
S17 1.542 1.051 0.889 0.007 0.003 0.002 1.549 1.054 0.892 
S18 2.000 1.364 1.154 0.010 0.004 0.003 2.010 1.367 1.157 
S19 3.125 2.131 1.803 0.015 0.006 0.005 3.140 2.136 1.808 
S20 1.458 0.994 0.841 0.007 0.003 0.002 1.465 0.997 0.844 
S21 2.708 1.847 1.563 0.013 0.005 0.004 2.721 1.851 1.567 
S22 2.792 1.903 1.611 0.013 0.005 0.004 2.805 1.908 1.615 
S23 2.667 1.818 1.538 0.013 0.005 0.004 2.679 1.823 1.543 
S24 1.958 1.335 1.130 0.009 0.004 0.003 1.968 1.339 1.133 
S25 2.875 1.960 1.659 0.014 0.005 0.004 2.889 1.965 1.663 
S26 1.417 0.966 0.817 0.007 0.003 0.002 1.423 0.968 0.819 
S27 1.875 1.278 1.082 0.009 0.003 0.003 1.884 1.282 1.085 
S28 1.583 1.080 0.913 0.008 0.003 0.002 1.591 1.082 0.916 
S29 3.083 2.102 1.779 0.015 0.006 0.005 3.098 2.108 1.784 
S30 0.750 0.511 0.433 0.004 0.001 0.001 0.754 0.513 0.434 
S31 2.792 1.903 1.611 0.013 0.005 0.004 2.805 1.908 1.615 
S32 3.125 2.131 1.803 0.015 0.006 0.005 3.140 2.136 1.808 
S33 2.833 1.932 1.635 0.014 0.005 0.004 2.847 1.937 1.639 
S34 2.417 1.648 1.394 0.012 0.004 0.004 2.428 1.652 1.398 
S35 1.333 0.909 0.769 0.006 0.002 0.002 1.340 0.912 0.771 
S36 1.875 1.278 1.082 0.009 0.003 0.003 1.884 1.282 1.085 
S37 1.625 1.108 0.938 0.008 0.003 0.002 1.633 1.111 0.940 
S38 1.042 0.710 0.601 0.005 0.002 0.002 1.047 0.712 0.603 
S39 1.458 0.994 0.841 0.007 0.003 0.002 1.465 0.997 0.844 
S40 1.958 1.335 1.130 0.009 0.004 0.003 1.968 1.339 1.133 
S41 1.208 0.824 0.697 0.006 0.002 0.002 1.214 0.826 0.699 
S42 1.875 1.278 1.082 0.009 0.003 0.003 1.884 1.282 1.085 
S43 2.833 1.932 1.635 0.014 0.005 0.004 2.847 1.937 1.639 
S44 1.000 0.682 0.577 0.005 0.002 0.002 1.005 0.684 0.578 
S45 1.542 1.051 0.889 0.007 0.003 0.002 1.549 1.054 0.892 
S46 3.542 2.415 2.043 0.017 0.006 0.005 3.559 2.421 2.049 
S47 1.958 1.335 1.130 0.009 0.004 0.003 1.968 1.339 1.133 
Minimum 0.625 0.426 0.361 0.003 0.001 0.001 0.628 0.427 0.362 
Maximum 3.542 2.415 2.043 0.017 0.006 0.005 3.559 2.421 2.049 
Mean 2.059 1.404 1.188 0.010 0.004 0.003 2.069 1.408 1.191 

Values in italics indicate minimum, maximum, and mean values.

Figure 6

(a) Spatial distribution map of HI for children. (b) Spatial distribution map of HI for women. (c) Spatial distribution map of HI for men. (d) Box plot of HI for children, women, and men.

Figure 6

(a) Spatial distribution map of HI for children. (b) Spatial distribution map of HI for women. (c) Spatial distribution map of HI for men. (d) Box plot of HI for children, women, and men.

Close modal

The spatial distribution of non-carcinogenic risk (HI) suggests that approximately 80% of the study region's population, including children, women, and men, face a higher health risk. As evident from Figure 6, the prominently green areas in the spatial map of HI across the study area specify no significant non-carcinogenic health risk. However, the yellow and red zones highlight areas where people may potentially face health risks in this area. The yellow and red regions shown in Figure 6 specify that the groundwater samples from these areas were unsuitable for direct consumption due to their intolerable non-carcinogenic values. Consuming an excessive amount of nitrate in drinking water can result in adverse health effects (Singh et al. 2020; Adimalla et al. 2021). Even so, the non-carcinogenic risk of nitrate contamination in drinking water has become a big concern in several areas globally, particularly in areas where a large population depends on groundwater for drinking without prior quality assessment (Adimalla et al. 2020; Singh et al. 2020; Verma et al. 2023). However, the results of this study demonstrate that the health risks of nitrate are most severe for children. Nevertheless, the current study's findings clearly suggest that the state government should promptly implement plans to reduce nitrate contamination in groundwater as well as ensure the provision of safe drinking water in the affected areas.

In this research, the nitrate concentration in groundwater was measured, and a PIG and human health risk assessment for nitrate exposure was conducted. Furthermore, spatial distribution maps were generated, and PCA was conducted to identify contamination zones and potential sources of pollution. Groundwater generally exhibits a neutral to slightly alkaline nature. The cations and anions based on their average values are in the following order: Mg2+ > Ca2+ > Na+ > K+, and Cl > SO42− > NO3 > HCO3 > F. The spatial maps demonstrate that a higher nitrate contamination is observed in the northern part, while the lowest value is observed in the western part of the study region. However, the PIG values specify that most of the study area is occupied by moderate to high pollution zones. PC1 has positive loadings of TDS, TH, Mg2+, Ca2+, and EC and suggests that groundwater chemistry primarily replicates the influence of natural sources, rock and mineral weathering, and anthropological activities. PC2 has positive loadings with NO3 and F, indicating ions are primarily associated with human inputs, domestic sewage infiltration, unexpected irrigation practices, industrial wastewater, septic tanks, animal waste, and landfill leachate. The mean value of non-carcinogenic risk is 1.191 for men, 1.408 for women, and 2.069 for children, respectively. The health risk assessment specified that children in the study area face a higher susceptibility to health risks compared to women and men.

HR is grateful to the Ministry of Education, Government of India (Grant No. 2K19/NITK/PHD/61900011), for funding this study. The authors acknowledge the National Institute of Technology, Kurukshetra, for providing various research facilities.

HR was responsible for sample collection and assessment, data processing, writing the original draft, methodology, conceptualization, analysis, editing, and funding acquisition. AG was responsible for the visualization, conceptualization, and supervision of the whole research work. MP was responsible for visualization, conceptualization, data processing, and reviewing and editing the writing of the entire research work.

The authors declare there is not conflict.

All relevant data are included in the paper or its Supplementary Information.

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