Abstract
This study reported the results of groundwater quality for drinking and irrigation purposes in Kurukshetra district, Haryana, India. Twelve parameters, namely pH, TDS, TH, sodium (Na+), magnesium (Mg2+), calcium (Ca2+), potassium (K+), chloride (Cl−), sulfate (SO42−), bicarbonate (HCO3−), nitrate (NO3−), and fluoride (F−) were evaluated and the Water Quality Index (WQI) was calculated. Based on the WQI, 31.57% and 68.43% of samples fall in excellent and good drinking water quality. The sodium adsorption ratio (SAR: 5.75–33.8), magnesium hazard ratio (MHR: 0.21–0.75), percent sodium (%Na: 31.34–72.84), residual sodium carbonate (RSC: 139–770), potential salinity (PS: 18.5–90), and Kelley Ratio (KR: 0.9–3.13) were calculated. The SAR, %Na, MHR, and KR indicated that most of the groundwater is suitable for irrigation. In addition, the inverse distance weighted (IDW) interpolation method was also employed to determine the spatial distribution of groundwater quality in the form of maps using ArcGIS software. The Pearson correlation matrix has been calculated to analyze the relationship between the water quality parameters. Gibbs plots have shown that evaporation and rock weathering are primary processes responsible for affecting the hydrochemistry of groundwater. Piper plots suggested that maximum groundwater samples are (HCO3−–Na+), (Na+), and (HCO3−) types.
HIGHLIGHTS
The groundwater quality for drinking was compared with the BIS and WHO by evaluating the WQI in the Kurukshetra district of Haryana, India.
To analyze groundwater for irrigation, SAR, MHR, %Na, RSC, PS, and KR were calculated.
Piper trilinear, Gibbs diagrams, and spatial distribution maps were plotted to monitor groundwater's hydrochemistry.
The groundwater of the Kurukshetra can be used for drinking and irrigation after some primary treatments.
Graphical Abstract
INTRODUCTION
Groundwater is being used as a primary source for industrial, irrigation, and drinking purposes in many parts of the world. Worldwide, 15% of groundwater is used for industrial work, 20% for irrigation purposes, and 65% for drinking purposes. About one-third population of the world depends upon groundwater for drinking purposes. Due to the excessive use of fertilizers and chemicals in agriculture, groundwater quality is being degraded continuously leading to an impact on human health (Rango et al. 2012; Zhang et al. 2020). In the past, several studies have been conducted around the world to assess the quality of groundwater and its suitability for drinking and irrigation purposes (Chung et al. 2015; Al-Barakah et al. 2017; Raza et al. 2017; Sheikh et al. 2017; Wu et al. 2018; Chaudhry & Sachdeva 2020; Adimalla 2021). Groundwater may contain harmful chemicals that affect human health seriously when consumed (Appelo & Postma 2004). A proper understanding of the science of groundwater geochemistry which uncovers the processes that influence the chemical configuration of groundwater is essential to monitor the water quality for drinking and irrigation purposes (Dassargues 2018). Therefore, it is strongly suggested to regularly evaluate groundwater quality to assess its fitness for irrigation and drinking purposes.
In the past few decades, groundwater contamination has been a severe problem worldwide. Rapid industrial growth, intensive urbanization, over usage of fertilizers in irrigation sectors, animal and human wastage, etc., are significant reasons for the deterioration of the groundwater quality. Therefore, several studies have been focused on groundwater quality studies for several usages (Amiri et al. 2015; Narsimha & Sudarshan 2018; Gharbi et al. 2019; Sood & Sharma 2020; Raheja et al. 2022; Wang et al. 2022). A study by Shan et al. (2021) evaluated the water quality using the Water Quality Index (WQI) in Bhindawas bird sanctuary, Haryana, India. Paul et al. (2019) studied groundwater quality in Tripura, Northeast India, using a Geographical Information System (GIS). Simsek & Gunduz (2007) studied the GIS-based irrigation water quality index (IWQI) using hydrochemical parameters like magnesium hazard ratio (MHR), infiltration hazard, electrical conductivity (EC), salinity hazard, sodium adsorption ratio (SAR), and others of the Simav Plain in Turkey. Gao et al. (2020) worked on the integrated weight WQI for evaluating groundwater quality in Xi'an, China. Karnena et al. (2022) investigated the suitability of groundwater using the WQI in the GIS environment covering a coastal region of Andhra Pradesh, India. They observed that groundwater quality varied from good to poor for drinking purposes and was free from fluoride content. Ram et al. (2021) studied groundwater quality by using the WQI under the GIS framework in Mahoba District, Uttar Pradesh, India, and found that the groundwater is safe for drinking purposes except at a few locations. The GIS-based inverse distance weighted (IDW) interpolation method is commonly used to obtain spatial distribution maps of groundwater quality (Şener et al. 2017; Balamurugan et al. 2020; Fang et al. 2020; Soujanya Kamble et al. 2020; Ram et al. 2021). It is a time-efficient and cost-effective technique to create various spatial distribution maps and projections. A GIS-based study is used for the spatial evaluation of various groundwater quality parameters. The literature review concluded that the assessment of groundwater quality is essential and offers basic information on groundwater for the sustainable development of any region. Most of the land in the Kurukshetra district of Haryana (state) is being used for agriculture. Further, this region is considered quite important for good-quality rice crops in the country. Therefore, it is very important to ascertain whether groundwater is suitable for irrigation or not. In addition to this, the groundwater of this study area is also frequently used for drinking purposes. As a result, the main aim of this study was to analyze the suitability of groundwater quality for drinking and irrigation purposes.
In the present study, multivariate statistical plots and spatial distribution maps developed in the GIS have been used to analyze physicochemical information of the groundwater of the Kurukshetra district of Haryana state, India. The groundwater quality was compared with guidelines laid down by the Bureau of Indian Standards (BIS 2015) and the World Health Organization (WHO 2011) by calculating the WQI as proposed in the literature. On the other hand, the suitability of groundwater for irrigation purposes was evaluated by computing indices such as SAR, MHR, percent sodium (%Na) or sodium hazard, residual sodium carbonate (RSC), potential salinity (PS), and Kelley Ratio (KR). Furthermore, Piper trilinear and Gibbs diagrams were also plotted for the classification of hydrochemistry of groundwater.
STUDY AREA
For all agricultural and drinking purposes, groundwater is being utilized as the main source of water in the entire district. The groundwater level lies between 20.18 and 32.64 m below ground level (bgl) in pre-monsoon and 21.80 and 34.41 m bgl in post-monsoon (CGWB 2013) and is being depleted at a rate of more than 1 m/year due to excessive water use for rice crop. As per CGWB (2013), the groundwater level is in the dark zone and groundwater depletion is a significant problem in the area. Moreover, the average groundwater level depth is more than 30 m. Therefore, it is essential to study the groundwater quality of aquifers in the Kurukshetra district.
METHODOLOGY
Sampling and analysis
The observed CBE is within the suggested limit of ±5% (Zhang et al. 2018), where all the anions (Cl−, SO42−, HCO3−, NO3−, and F−) and cations (Na+, Mg2+, Ca2+, and K+) are in milligrams per liter (mg/L).
Water quality index
The Bureau of Indian Standards (BIS 2015) suggested the use of the WQI for drinking water quality standards. To calculate the WQI, the following steps are followed:
In the first step, 12 chemical parameters were assigned weights () as in Table 1 (Ramakrishnaiah et al. 2009).
Sr. No. . | Name of parameters . | Weight () . | Relative weight = . | Permissible limits (BIS 2015) . |
---|---|---|---|---|
1 | pH | 4 | 0.091 | 6.5–8.5 |
2 | TDS | 4 | 0.091 | 500 |
3 | TH | 4 | 0.091 | 200 |
4 | Ca2+ | 3 | 0.068 | 200 |
5 | Mg2+ | 3 | 0.068 | 30 |
6 | Na+ | 4 | 0.091 | 200 |
7 | K+ | 1 | 0.023 | 12 |
8 | HCO3− | 1 | 0.023 | 120 |
9 | Cl− | 5 | 0.11 | 250 |
10 | SO42− | 5 | 0.11 | 200 |
11 | NO3− | 5 | 0.11 | 45 |
12 | F− | 5 | 0.11 | 1.5 |
= 44 |
Sr. No. . | Name of parameters . | Weight () . | Relative weight = . | Permissible limits (BIS 2015) . |
---|---|---|---|---|
1 | pH | 4 | 0.091 | 6.5–8.5 |
2 | TDS | 4 | 0.091 | 500 |
3 | TH | 4 | 0.091 | 200 |
4 | Ca2+ | 3 | 0.068 | 200 |
5 | Mg2+ | 3 | 0.068 | 30 |
6 | Na+ | 4 | 0.091 | 200 |
7 | K+ | 1 | 0.023 | 12 |
8 | HCO3− | 1 | 0.023 | 120 |
9 | Cl− | 5 | 0.11 | 250 |
10 | SO42− | 5 | 0.11 | 200 |
11 | NO3− | 5 | 0.11 | 45 |
12 | F− | 5 | 0.11 | 1.5 |
= 44 |
Sr. No. . | Name of parameter . | Minimum value . | Maximum value . | Mean value . | WHO limits . | Number of Samples . | ||
---|---|---|---|---|---|---|---|---|
Desirable limit . | Maximum allowable limit . | Within desirable limit . | Out of maximum allowable limit . | |||||
1 | pH | 7.85 | 8.96 | 8.48 | 6.5–8.5 | 9.5 | 12 | – |
2 | TDS (mg/L) | 403 | 1,400 | 713.53 | 500 | 1,500 | 4 | – |
3 | TH (mg/L) | 177 | 276 | 235.80 | 200 | 600 | 4 | – |
4 | Ca2+ (mg/L) | 10 | 45 | 28.52 | 75 | 200 | 19 | – |
5 | Mg2+ (mg/L) | 14 | 45 | 25.79 | 50 | 150 | 19 | – |
6 | Na+ (mg/L) | 34 | 187 | 83.74 | – | 200 | – | – |
7 | K+ (mg/L) | 3.4 | 14.5 | 7.81 | – | 12 | – | 3 |
8 | CO32− (mg/L) | 23 | 86 | 44.63 | – | – | – | – |
9 | HCO3− (mg/L) | 155 | 745 | 294.74 | – | – | – | – |
10 | NO3− (mg/L) | 1.5 | 22.6 | 6.08 | 10 | 45 | 15 | – |
11 | Cl− (mg/L) | 12 | 75 | 37 | 250 | 1,000 | 19 | – |
12 | SO42− (mg/L) | 10 | 65 | 37.21 | 200 | 400 | 19 | – |
13 | F− (mg/L) | 0.35 | 0.98 | 0.61 | 1.0 | 1.5 | 19 | – |
Sr. No. . | Name of parameter . | Minimum value . | Maximum value . | Mean value . | WHO limits . | Number of Samples . | ||
---|---|---|---|---|---|---|---|---|
Desirable limit . | Maximum allowable limit . | Within desirable limit . | Out of maximum allowable limit . | |||||
1 | pH | 7.85 | 8.96 | 8.48 | 6.5–8.5 | 9.5 | 12 | – |
2 | TDS (mg/L) | 403 | 1,400 | 713.53 | 500 | 1,500 | 4 | – |
3 | TH (mg/L) | 177 | 276 | 235.80 | 200 | 600 | 4 | – |
4 | Ca2+ (mg/L) | 10 | 45 | 28.52 | 75 | 200 | 19 | – |
5 | Mg2+ (mg/L) | 14 | 45 | 25.79 | 50 | 150 | 19 | – |
6 | Na+ (mg/L) | 34 | 187 | 83.74 | – | 200 | – | – |
7 | K+ (mg/L) | 3.4 | 14.5 | 7.81 | – | 12 | – | 3 |
8 | CO32− (mg/L) | 23 | 86 | 44.63 | – | – | – | – |
9 | HCO3− (mg/L) | 155 | 745 | 294.74 | – | – | – | – |
10 | NO3− (mg/L) | 1.5 | 22.6 | 6.08 | 10 | 45 | 15 | – |
11 | Cl− (mg/L) | 12 | 75 | 37 | 250 | 1,000 | 19 | – |
12 | SO42− (mg/L) | 10 | 65 | 37.21 | 200 | 400 | 19 | – |
13 | F− (mg/L) | 0.35 | 0.98 | 0.61 | 1.0 | 1.5 | 19 | – |
Irrigation groundwater quality evaluation
RSC, SAR, MHR, percent sodium (%Na) or sodium hazard, PS, and KR were calculated for assessing the groundwater quality for irrigation purposes. To calculate these chemical indices, the following equations were used (Richards 1954; Wilcox 1955; Kelley 1963; Doneen 1964; Ragunath 1987; Gharbi et al. 2019; Gugulothu et al. 2022).
Sodium adsorption ratio
Magnesium hazard ratio
Percent sodium (%Na)
Residual sodium carbonate
If the RSC value <1.25, then water is useful for irrigation; if the RSC lies between 1.25 and 2.25, then the condition is doubtful, if the value exceeds 2.25, then groundwater is unfit for irrigation.
Potential salinity
If the PS value <3, then it can be used for irrigation; otherwise, it remains unsuitable.
Kelley ratio
If the KR value <1, then groundwater can be used for irrigation. If the KR value >1, groundwater is not used for irrigation.
RESULTS AND DISCUSSION
Hydrogeochemistry
A summary of 19 groundwater samples in terms of various parameters is provided in Table 2. The pH or hydrogen ion plays an important role in assessing groundwater quality. The value of pH ion value ranges from 7.85 to 8.96 in the study areas with a mean of 8.48, signifying a mildly alkaline nature of groundwater (Table 2). The TDS lies between 403 and 1,400 mg/L with an average of 713.53 mg/L. If the value of TDS is below <500 mg/L, then it is considered potable and freshwater (BIS 2015). A higher value of TDS might contribute to bad taste in groundwater (Monteiro De Oliveira et al. 2021). This classification indicates that 86% of groundwater samples are suitable for drinking purposes (<1,000 mg/L). Davis & De (1966) proposed to divide TH into four different groups. If TH is below 75 mg/L, water will be considered slightly hard; moderately hard if it is between 75 and 150 mg/L; hard if the value is between 150 and 300 mg/L, and very hard if its value exceeds 300 mg/L. The TH concentration variation suggests that 100% of the study area falls under 150–300 mg/L (hard water) as per these classifications.
Cation chemistry
In the cation compositions of groundwater (Ca2+, Mg2+, Na+, and K+), calcium (Ca2+) ions range from 10 to 45 mg/L with a mean value equal to 28.52 mg/L. Due to agricultural drainage, a higher amount of Ca2+ was observed in Baronda village of Kurukshetra district. The desirable and allowable limit of Ca2+ for drinking purposes is 75 and 200 mg/L. In the case of magnesium (Mg2+) ion, the desirable and allowable limits as per drinking purposes are 50 and 150 mg/L. Analysis of the results (Table 2) suggested that 100% of groundwater samples in the study area fall under desirable limits. The concentration of Na+ ion lies between 34 and 187 mg/L, indicating that 100% of groundwater samples lie within maximum allowable limits (WHO 2011). Moreover, a higher amount of Na+ intake will cause hypertension and osteoporosis problems. The level of potassium (K+) ion is relatively high in the Kurukshetra district as its value lies between 3.4 and 14.5 mg/L with a mean value of 7.81 mg/L. A few groundwater samples, i.e., 16%, falls under the maximum allowable limits of K+ ion (Table 2).
Anion chemistry
Chloride (Cl−) is considered the most essential anion present in groundwater for irrigation. As per WHO (2011), a maximum allowable limit of Cl− is 1,000 mg/L as suggested for drinking purposes. A high intake of Cl− anion in drinking water can cause heart and kidney problems (Patel et al. 2022). The Cl− content of the Kurukshetra district ranged from 12 to 75 mg/L with an average of 37 mg/L. A higher level of Cl− ion was found in the Samalkhi village of the study area. Sulfate (SO42−) is an important anion occurring in groundwater. It may enter groundwater through the seepage of industrial effluents (APHA 2005). The SO42− ion in the study area ranges from 10 to 65 mg/L with a mean of 37.21 mg/L (Table 2). If the concentration of SO42− lies between 300 and 400 mg/L, it causes a bitter taste in groundwater, and if it is more than 1,000 mg/L, it can cause stomach disorders (Patel et al. 2022). However, a high intake of SO42− ion in water may cause probable dehydration and laxative effects (Li et al. 2019). The carbonate (CO32−) ion range varies from 23 to 86 mg/L with an average of 44.63 mg/L. The value of bicarbonate (HCO3−) ion lies in a range from 155 to 745 mg/L. Neither BIS nor WHO has recommended any limits (both desirable and allowable) for drinking purposes for CO32− and HCO3− ions. The F− anion values ranged from 0.35 to 0.98 mg/L with a mean of 0.61 mg/L. The F− anion is categorized into three different classifications. If the F− value is below 1 mg/L, it is most suitable. If the range is between 1 and 1.5 mg/L, it is not fit for drinking (WHO 2011). Continuous consumption of higher F− concentration may cause teeth problems and skeletal fluorosis. The nitrate (NO3−) is formed by domestic and industrial discharge, biochemical, and fertilizer plants. The NO32− anion values ranged from 1.5 to 22.6 mg/L with a mean of 6.08 mg/L. As per BIS (2015), the maximum allowable limit of NO3− is 45 mg/L, and all the groundwater samples were are falling within the allowable limit.
Classification of groundwater quality for drinking purpose
Sample No. . | Sampling location . | Latitude . | Longitude . | WQI value . | WQI range . | Type of groundwater . | % of samples . |
---|---|---|---|---|---|---|---|
S1 | Baronda | 29.9556 | 77.0522 | 48.25 | < 50 | Excellent | 31.57 |
S2 | Berthala | 30.1292 | 76.9833 | 46.75 | |||
S3 | Ishaq | 30.0167 | 76.4917 | 49.17 | |||
S4 | Ram Sharan Majra | 30.0017 | 77.0003 | 49.92 | |||
S5 | Shahbad | 30.1667 | 76.8667 | 48.41 | |||
S6 | Dabkhera | 30.0006 | 76.7536 | 49.6 | |||
S7 | Jogna Khera | 29.9736 | 76.8278 | 50.36 | 50–100 | Good | 68.43 |
S8 | Kaulapur | 30.025 | 76.8958 | 60.02 | |||
S9 | Pehowa | 29.9792 | 76.5833 | 53.53 | |||
S10 | Hatira | 29.95 | 76.7625 | 52.3 | |||
S11 | Bateri | 29.9208 | 76.6083 | 51.15 | |||
S12 | Samalkhi | 30.235 | 76.8278 | 58.19 | |||
S13 | Sirsala | 30.0003 | 76.5019 | 59.95 | |||
S14 | Jandaula | 29.8889 | 76.5728 | 60.48 | |||
S15 | Santokhpur | 30.0292 | 76.725 | 61.46 | |||
S16 | Bachki | 30.0394 | 76.7556 | 60.67 | |||
S17 | Bodhni | 30.0542 | 76.5583 | 60.57 | |||
S18 | Malikpur-Singhpura | 30.00 | 76.7514 | 53.34 | |||
S19 | Thana | 29.9083 | 76.5083 | 77.31 | |||
– | – | – | – | 100–200 | Poor | 0 | |
– | – | – | 200–300 | Very poor | 0 | ||
– | – | – | – | >300 | Not suitable | 0 |
Sample No. . | Sampling location . | Latitude . | Longitude . | WQI value . | WQI range . | Type of groundwater . | % of samples . |
---|---|---|---|---|---|---|---|
S1 | Baronda | 29.9556 | 77.0522 | 48.25 | < 50 | Excellent | 31.57 |
S2 | Berthala | 30.1292 | 76.9833 | 46.75 | |||
S3 | Ishaq | 30.0167 | 76.4917 | 49.17 | |||
S4 | Ram Sharan Majra | 30.0017 | 77.0003 | 49.92 | |||
S5 | Shahbad | 30.1667 | 76.8667 | 48.41 | |||
S6 | Dabkhera | 30.0006 | 76.7536 | 49.6 | |||
S7 | Jogna Khera | 29.9736 | 76.8278 | 50.36 | 50–100 | Good | 68.43 |
S8 | Kaulapur | 30.025 | 76.8958 | 60.02 | |||
S9 | Pehowa | 29.9792 | 76.5833 | 53.53 | |||
S10 | Hatira | 29.95 | 76.7625 | 52.3 | |||
S11 | Bateri | 29.9208 | 76.6083 | 51.15 | |||
S12 | Samalkhi | 30.235 | 76.8278 | 58.19 | |||
S13 | Sirsala | 30.0003 | 76.5019 | 59.95 | |||
S14 | Jandaula | 29.8889 | 76.5728 | 60.48 | |||
S15 | Santokhpur | 30.0292 | 76.725 | 61.46 | |||
S16 | Bachki | 30.0394 | 76.7556 | 60.67 | |||
S17 | Bodhni | 30.0542 | 76.5583 | 60.57 | |||
S18 | Malikpur-Singhpura | 30.00 | 76.7514 | 53.34 | |||
S19 | Thana | 29.9083 | 76.5083 | 77.31 | |||
– | – | – | – | 100–200 | Poor | 0 | |
– | – | – | 200–300 | Very poor | 0 | ||
– | – | – | – | >300 | Not suitable | 0 |
Classification of groundwater quality for irrigation purposes
Agriculture is the prime occupation in the study area, with extensive rice, wheat, and sugarcane farming. Keeping in view of extensive use of groundwater for water-intensive crops like rice and sugarcane, the estimation of groundwater quality is necessary. To assess the groundwater quality for irrigation uses, chemical indices like SAR, MHR, %Na, PS, and RSC were used in this study.
Name of parameter . | Water type . | Range . | Number of samples . | % of samples . |
---|---|---|---|---|
SAR | Low sodium | <10 | 6 | 31.58 |
Medium sodium | 10–18 | 7 | 36.84 | |
High sodium | 18–26 | 5 | 26.32 | |
Very high sodium | >26 | 1 | 5.26 | |
EC | Low saline | <250 | 0 | 0 |
Medium saline | 250–750 | 16 | 84.21 | |
High saline | 750–2,250 | 3 | 15.79 | |
Very high saline | >2,250 | 0 | 0 |
Name of parameter . | Water type . | Range . | Number of samples . | % of samples . |
---|---|---|---|---|
SAR | Low sodium | <10 | 6 | 31.58 |
Medium sodium | 10–18 | 7 | 36.84 | |
High sodium | 18–26 | 5 | 26.32 | |
Very high sodium | >26 | 1 | 5.26 | |
EC | Low saline | <250 | 0 | 0 |
Medium saline | 250–750 | 16 | 84.21 | |
High saline | 750–2,250 | 3 | 15.79 | |
Very high saline | >2,250 | 0 | 0 |
Statistical analysis of hydrochemical parameters
Pearson, Kendall, and Spearman are the three essential methods for correlation. The Kendall method is used to measure either nonlinear or linear correlation, the Pearson method measures linear correlation, and Spearman measures nonlinear correlation. The Pearson correlation matrix has been used in this study to establish a relation between groundwater quality parameters. The values of the Pearson correlation coefficient range from −1 to +1. When the value is 0, there is no correlation between the two parameters. When the coefficient is +1, there is a perfect positive linear correlation. When the coefficient is −1, there is a perfect negative linear correlation. Overall, when the correlated value lies between 0.50 and 0.70, it specifies a moderate correlation. When the coefficient value >0.7, it indicates a strongly correlated (Giridharan et al. 2008). Table 6 presents the Pearson correlation matrix of groundwater concentration of 13 hydrochemical parameters. It can be observed from Table 6 that TDS has a strong positive correlation with CO32−, Na+, and HCO3− ions, whereas Na+ is well correlated with CO32− and HCO3− (Table 6).
Parameters . | Values . | Water type . | Number of samples . | % of samples . |
---|---|---|---|---|
%Na (Wilcox 1955) | <20 | Excellent | 0 | 0 |
20–40 | Good | 2 | 10.53 | |
40–60 | Permissible | 13 | 67.90 | |
60–80 | Doubtful | 3 | 21.57 | |
>80 | Unsuitable | 0 | 0 | |
PS (Doneen 1964) | <3 | Suitable | 0 | 0 |
>3 | Unsuitable | 19 | 100 | |
MHR (Ragunath 1987) | <50 | Suitable | 12 | 62.63 |
>50 | Unsuitable | 7 | 37.37 | |
RSC (Ragunath 1987) | <1.25 | Good | 0 | 0 |
1.25–2.25 | Doubtful | 0 | 0 | |
>2.25 | Unsuitable | 19 | 100 | |
KR (Kelley 1963) | <1 | Suitable | 15 | 78.95 |
>1 | Unsuitable | 4 | 21.05 |
Parameters . | Values . | Water type . | Number of samples . | % of samples . |
---|---|---|---|---|
%Na (Wilcox 1955) | <20 | Excellent | 0 | 0 |
20–40 | Good | 2 | 10.53 | |
40–60 | Permissible | 13 | 67.90 | |
60–80 | Doubtful | 3 | 21.57 | |
>80 | Unsuitable | 0 | 0 | |
PS (Doneen 1964) | <3 | Suitable | 0 | 0 |
>3 | Unsuitable | 19 | 100 | |
MHR (Ragunath 1987) | <50 | Suitable | 12 | 62.63 |
>50 | Unsuitable | 7 | 37.37 | |
RSC (Ragunath 1987) | <1.25 | Good | 0 | 0 |
1.25–2.25 | Doubtful | 0 | 0 | |
>2.25 | Unsuitable | 19 | 100 | |
KR (Kelley 1963) | <1 | Suitable | 15 | 78.95 |
>1 | Unsuitable | 4 | 21.05 |
Hydrochemical classification of groundwater
(a) Piper trilinear diagram
(b) Gibbs diagram
CONCLUSIONS
This work is based on the hydrochemistry of significant anions and cations of groundwater of the Kurukshetra district of Haryana state in India. The main objective is to better understand groundwater chemical composition to estimate its suitability for drinking and irrigation uses. The conclusions drawn from this work are as follows:
The groundwater of Kurukshetra district, Haryana state, is found to be mildly alkaline and hard. The ions, namely Ca2+, Mg2+, Cl−, SO42−, and F− ions are within desirable limits (WHO 2011). However, HCO3− anion and Na+ cation are most dominant in the groundwater. It is observed that the K+ ion is relatively higher and is laying between 3.4 and 14.5 mg/L. A total of 16% of groundwater samples exceeded limits for K+ ions as per the recommendation of WHO (2011).
The calculated values of WQI lie between 46.75 and 77.31. The value of the WQI for drinking purposes revealed that 31.57% of groundwater samples belong to excellent water quality and 68.43% of groundwater samples are in a good category.
On the basis of values of groundwater salinity, SAR, RSC, MHR, sodium hazard, PS, and KR, it can be concluded that 15.79, 31.58, 100, 37.37, 21.57, 100, and 21.05% of the study area are not suitable for irrigation uses.
Piper plots exhibited that maximum groundwater samples are HCO3− -Na+, Na+, and HCO3− types. Gibbs plots revealed that evaporation and rock weathering are the major techniques influencing the hydrochemistry of groundwater.
In India, approximately 85% of groundwater is used for drinking and irrigation purposes and is the biggest user of groundwater around the Globe. This is a severe insinuation to the sustainability of living beings, irrigation, and commercial growth. The approach used in this work can be efficiently helpful to other areas having similar conditions and is beneficial for groundwater management authorities in ensuring safe water for the stakeholders.
ACKNOWLEDGEMENTS
H.R. is grateful to the Ministry of Education, Government of India, for providing the fellowship to do this research. The author conveys his gratitude to the National Institute of Technology, Kurukshetra, for giving research facilities in completing this work.
DATA AVAILABILITY STATEMENT
All relevant data are included in the paper or its Supplementary Information.
CONFLICT OF INTEREST
The authors declare there is no conflict.