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Environmental Sustainability

, Volume 1, Issue 2, pp 197–208 | Cite as

Spatio-temporal variations in hydro-geochemistry of groundwater at rural, urban and industrial areas of Kanpur, India

  • Narendra Kumar
  • Dhananjay Kumar
  • Sanjeev Kumar
  • Vertika Shukla
  • Preeti Shukla
  • Beenu Raj
Original Article
  • 304 Downloads

Abstract

Physicochemical characteristics of groundwater provide vital information regarding prevailing geochemical, geomorphological and predominant pollution conditions in an area. In the present work, hydro-geochemical properties of ground water were examined at rural, urban and industrial areas of Kanpur to determine its aptness for drinking and irrigation. Groundwater samples were randomly collected from deep borewell pumps across the city. The samples were examined for pH, electrical conductivity (EC), nitrate, sulphate, chloride, hardness, alkalinity, total dissolved solids, sodium, potassium, calcium, which ranged between 7.10 and 8.60, 140–3990 mS cm−1, 0.02–13.67, 4.67–285.37, 4–747.77, 108–1555.2, 32–532, 89.60–2550, 18–720, 2–19 and 5–290 mg L−1 in pre-monsoon season and 7.1–8.2, 400–5450 mS cm−1, 0.02–24.09, 7.62–258.21, 4–538.84, 122–750, 240–988, 256–3490, 29–730, 3–53 and 10–185 mg L−1 in post-monsoon season respectively. Water Quality Index of groundwater during post-monsoon were recorded to be better than the pre-monsoon season, reason being percolation of water during rainfall in monsoon. The pre and post-monsoon data provided valuable information regarding the suitability of groundwater for various purposes such as drinking and irrigation. Results showed ‘fairly’ and ‘good’ categories of water quality in the pre-monsoon season which further improved in post monsoon season. Results clearly specify that the natural process of groundwater recharge is an important mechanism to maintain the quality of groundwater.

Keywords

Hydro-geochemistry Groundwater Monsoon Pollution Water Quality Index 

Introduction

Being a renewable natural resource, groundwater has always been the largest reserve of drinking water for the human population. Globally, about 33% of the human population use groundwater for drinking (Prasanth et al. 2012; Khan and Jharia 2017). Groundwater is preferred over surface water because it tends to be less polluted by anthropogenic wastes (Belkhiri and Mouni 2012; Kumari et al. 2014; Kumar et al. 2015). However, its quality can be modified by numerous anthropogenic sources such as faulty waste disposal practices, unplanned urbanization, industrial pollution, etc. besides natural geogenic processes (Manorama and Paulsamy 2013; Jhariya et al. 2017; Swartjes and Otte 2017; Selvakumar et al. 2017). The groundwater chemistry is governed not only by the geomorphology, soil type and residence time but also by the atmosphere, soil and weathering of rocks as well as other anthropogenic sources like mining, unplanned urbanization and industrialization (Prasanth et al. 2012; Singh et al. 2015; Srivastava 2007). Metals and other trace elements present in the groundwater can cause considerable health related problems either by deficiency or excessive intake (Frengstad et al. 2001; Kumar and James 2013). Hence, knowledge of hydrochemistry is the pre-requisite in order to assess the aptness of groundwater for irrigation and drinking needs. Classifying the water for specific purposes, on the basis of concentration of individual pollutant limit its suitability for other designated uses (Ravikumar et al. 2011; Tiwari et al. 2017; Khan and Jharia 2017). Better outcomes can be obtained only by studying the combined chemical behaviour of all the pollutants instead of individual pollutant characteristics (Belkhiri and Mouni 2012). Hence, groundwater quality assessment is of immense importance to identify the possible sources of contamination and to evaluate its suitability for specific use (Suthar et al. 2009; Singh et al. 2015).

India’s population is 17% of the total population of the world but have only 4% of the total freshwater resources (Ramesh and Elango 2012). In India, more than 90% population in several states are dependent on groundwater for their daily needs (Srinivasamoorthy et al. 2008; Kumari et al. 2014; Singh et al. 2015). The government of India has established a dense network of hand pumps (India Mark II) to provide the safe drinking water particularly in rural areas. However, the deep-bore wells are regarded as the worst type of groundwater source in terms of physicochemical characteristics due to the non-existence of concrete plinth and poorly planned drainage system (WHO 1997). Urban areas are more prone to the incidence of groundwater pollution due to the generation of large volume of industrial and municipal wastes and their subsequent discharge into comparatively small areas (Rao and Mamatha 2004; Jhariya et al. 2017; Neha et al. 2017). In India, a number of studies have been carried out to examine the groundwater quality (Jeevanandam et al. 2006; Kumar and James 2013). However, the information on the hydro-geochemistry of groundwater in the selected areas is very scanty. Therefore, the present study was piloted with an objective to assess the spatial distribution of hydro-chemical constituents of groundwater determining its suitability for drinking and agriculture purposes at the urban, rural and industrial areas of Kanpur District, Uttar Pradesh, India. Further, temporal variation in groundwater quality have also been recorded in terms of monsoon (rainy season) and post-monsoon.

Materials and methods

Study area: Kanpur, India

The study area; Kanpur is situated in the central region of Uttar Pradesh and commonly known as commercial capital of the State. Kanpur district and its municipality cover an area of 3155.4 and 278 km2 respectively (Fig. 1) and lies between 25°55′ and 27° North latitude and 79°30′ and 80°35′ East longitudes. Geographically major parts are flat plains with slight undulations. The river Ganges and Yamuna along with their tributaries constitute a dendritic type drainage system. According to the census in 2011 the population of the city was 27,67,031. It is the 11th largest town in India (population wise), and 1st in the state of Uttar Pradesh. In 2005–2006 the net sown area was 1,85,667 hectare and net irrigated area was 1,30,333 hectare. The area irrigated by canals was 32,308 hectare, whereas, that by ground water was 96,636 (74%) ha. The total canal length in Kanpur is 822 km. In 2005–2006, the total number of tube wells and bore well were 293 and 54,160 respectively. Climate of the Kanpur is humid and characterised by hot summer having annual precipitation of 821.9 mm. The mean of maximum and minimum temperature ranges between 45 and 8.6 °C. Monthly mean relative humidity of the district is 50% and potential evapotranspiration is 1660.9 mm. Geologically, Kanpur is interfluve of Ganga and Yamuna having clay, silt, gravel and sands in their sedimentary constituents. The older alluviums and alluvial deposits mostly reported in the central parts during lower to Pleistocene period while newer alluvium was encountered during upper Pleistocene to recent period along the river courses. In addition to five ordinance factories of Government of India, Kanpur is also one of the largest textile and leather manufacturer. Besides textile and leather industries, several chemicals, soaps, two-wheelers, hosiery, pan masala and fertilizer manufacturing industries are also running in the district. Being the hub of various industrial set ups, several regions are exerting high pressure on groundwater resources.
Fig. 1

Location map of study area in Kanpur city, India

Sample collection and analysis

In total, 23, 29 and 34 groundwater samples from India Mark II hand pumps were collected in polyethene bottles from sites representing industrial, rural and urban areas respectively during the month of March to May (Pre-monsoon) and October to December (Post monsoon) 2013 (Fig. 1). For hydro-geochemical parameters, collected water samples were brought to the Department of Environmental Science (BBA University, Lucknow) laboratory in sampling kits at 4 °C for further analysis. Hydro-geochemical characteristics viz. pH, electrical conductivity (EC), nitrate, sulphate, chloride, hardness, alkalinity, total dissolved solid (TDS), sodium (Na), potassium (K), calcium (Ca) and magnesium (Mg) of groundwater were analysed following the ‘Standard methods for the examination of water and waste water’ (APHA 2005).

Analytical methods and equipment

The pH, EC and TDS were measured electrometrically by pH meter, conductivity meter and TDS meter respectively. Alkalinity, chloride, hardness, Ca and Mg were analysed titrimetrically with suitable titrant viz. H2SO4, AgNO3 and EDTA respectively, while sulphate by turbidity meter. Nitrate was measured by Double-Beam UV–VIS Spectrophotometer (Systronic 2203), while Na and K with the help of Flame photometer (Systronic 130).

Water Quality Index (WQI)

WQI was calculated by following methods developed by Canadian Council of Ministers of the Environment (CCME, 1997). The WQI includes three elements i.e. F1 (scope), F2 (frequency) and F3 (amplitude) (Marvin et al. 2004).

The F1 and F2 were calculated by following equation:
$$F1 = \frac{{number\;of\;failed\;variables}}{{total\;number\;of\;variables}} \times 100$$
(1)
$$F2 = \frac{{number\;of\;failed\;tests }}{{total\;number\;of\;tests }} \times 100$$
(2)
While calculation of F3 requires three steps.
  1. 1.

    The number of times by which an individual concentration is higher than (or less than when the standard or guidelines level is a minimum) the water quality guideline is labeled as “excursion” and expressed as followed: When the ith test value must not exceed the respective guidelines (guidelinesi):

    $${\text{Excursion}}\;i = \left( {\frac{{{\text{failed test value}}\;i}}{{{\text{guidelines}}\;i}}} \right) - 1$$
    (3a)
    When the ith test value must not fall below respective guidelines:
    $${\text{Excursion}}\;i = \left( {\frac{{{\text{guidelines}}\;i}}{{{\text{failed test value}}\;i}}} \right) - 1$$
    (3b)
     
  2. 2.

    The normalized sum of excursion (NSE) is calculated as follows:

    $$NSE = \frac{{\sum\nolimits_{{i = 1}}^{n} {{excursion}\;i} }}{{total\,number\,of\,tests}}$$
    (4)
    where n is the total number of test.
     
  3. 3.

    F3 is now calculated using the following function that scales the NSE to the range of 1–100:

    $$F3 = \frac{{\text{NSE}}}{{0.01\,{\text{NSE}} + 0.01}}$$
    (5)
    Now WQI can be calculated as follows:
    $${\text{WQI}} = 100 - ~\left( {\frac{{\sqrt {F_1^2 + ~F_2^2 + F_3^2} }}{{1.732}}} \right)$$

    The WQI index produces a number between 0 (worst quality) and 100 (best quality) comprised of 5 categories as presented in Table 5 (CCME 2004; Nikoo et al. 2011).

     

Statistical analysis

Results have been analysed statistically using SPSS (version 20) for the standard error and correlation coefficient (r) by performing Pearson correlation analysis.

Results and discussion

Results of physico-chemical analysis of groundwater of Kanpur are presented in Table 1. pH of all the water samples collected from rural (29), urban (34), and industrial areas (23), was found within the permissible limit prescribed by WHO (2012) (6.5–8.5) during post-monsoon, however, during pre-monsoon it was found beyond the permissible limit at three locations (Table 1). Interestingly, at none of the locations the pH of the water was found acidic i.e. < 7, which clearly indicates that the water of Kanpur is alkaline in nature, irrespective of minor changes in the geographical location. Alkaline pH of groundwater may be observed due to leaching of anions, particularly carbonates and bicarbonates (Belkhiri and Mouni 2012). An alkaline pH enhances the process of dissolution and subsequently the ion concentration in water which may exert adverse effects on human health such as gastrointestinal disorders, ulcers etc. (Pies et al. 2011). Further, a high pH also increases the toxicity due to ammonia (WHO 2012). Similar results with high pH of the hand-dug well were water obtained in Nigeria by Taiwo et al. (2011).
Table 1

Physicochemical characteristics of groundwater during pre and post monsoon season at rural, urban and industrial areas of Kanpur city, India

 

pH

EC (mS cm−1)

Nitrate (mg L−1)

Sulphate (mg L−1)

Chloride (mg L−1)

Hardness (mg L−1)

Alkalinity (mg L−1)

TDS (mg L−1)

Na (mg L−1)

K (mg L−1)

Ca (mg L−1)

Groundwater characteristics during pre-monsoon

 Rural

7.2–8.1

0.39–3.67

0.02–13.02

12.79–285.37

12.79–285.37

302.40–1555.20

32.00–316.00

250.00–2350.00

59.00–720.00

6.00–17.00

14.00–96.00

 Urban

7.1–8.4

0.28–1.68

0.30–12.40

5.13–122.03

3.99–537.83

158.40–1281.60

76.00–468.00

176.00–1730.00

18.00–169.00

5.00–12.00

6.00–35.00

 Industrial

7.1–8.5

0.14–3.25

0.13–13.67

8.95–201.28

3.99–481.85

108.00–3470.40

48.00–452.00

256.00–2550.00

27.00–660.00

2.00–19.00

6.00–290.00

 Avg.

7.86

1.25

4.76

58.54

123.75

621.88

212.74

877.97

174.23

8.94

37.94

 WHO

6.5–8.5

500

50

500

250

150–500

200

500

200

100

 BIS

6.5–8.5

500

45

200

250

300

200

500

 FSA

12

Groundwater characteristics during post–monsoon

 Rural

7.2–8.2

0.62–3.54

0.20–15.77

16.98–188.62

5.0–272.91

260–692

211–746

397–2260

61–730

3–12

16–100

 Urban

7.1–8.1

0.52–2.11

0.11–15.5

7.62–253.73

7.0–538.84

122–680

246–988

275–1350

40–200

6–17

10–300

 Industrial

7.1–8.1

0.4–5.45

0.02–24.09

8.2–258.21

4.0–481.85

138–472

240–756

256–3490

29–625

5–15

17–67

 Avg.

7.75

1.36

6.105

81.81

146.07

380

513

1246.50

150.29

8.45

44

 WHO

6.5–8.5

500

50

500

250

150–500

200

500

200

100

 BIS

6.5–8.5

500

45

200

250

300

200

500

 FSA

12

Where, EC electrical conductivity, WHO World Health Organization, BIS Bureau of Indian Standards, FSA Food Standard Agency)

Approximately 26% (pre-monsoon) and 19% (post-monsoon) of water samples were found to have EC beyond the limits prescribed by WHO (2012) i.e. 1.5 mS cm−1 (Table 1). EC of ground water generally depends upon temperature, concentration and ions present in it (Agbalagba et al. 2011; Benhamiche et al. 2015). A high EC of water shows the occurrence of the high amount of dissolved inorganic ions (Harilal et al. 2004). High EC of water can not only cause adverse ecological effects but also lead to scaling and corrosion of machinery and pipelines and may degrade the quality of industrial product (Fried 1991; Ravikumar et al. 2011). Anthropogenic happenings such as industrial and domestic effluent and agricultural runoff are the prime reasons for the enhanced EC (Pandit 2002; Gupta et al. 2008).

Among all the samples; TDS in 21 and 19 samples of pre and post monsoon seasons respectively, were found to be beyond the permissible limit recommended by WHO (2012) i.e. 1000 mg L−1(Table 1). TDS is the residue of filtered water after evaporation. A high range of TDS in water (195–1100 mg L−1) may be encountered due to the presence of carbonate, sulphate and chlorides of Ca, Mg, Na, P, Si, nitrate and boron (Rainwater and Thatcher 1960; Ravikumar et al. 2013; Selvakumar et al. 2017). Pies et al. (2011) reported that the drinking water containing high level of dissolved solids induce unfavourable physiological reactions and can cause gastrointestinal problems.

Among all the collected samples, hardness in 51 during pre and 13 post-monsoon were recorded beyond the permissible limit as recommended by WHO (2012) i.e. 150–500 mg L−1 (Table 1). Salts of Ca and Mg drive the hardness of water, which in turn is principally governed by the geological characteristics of the area (Kumar and James 2013). Ca and Mg ions may find their way in the groundwater via leaching of limestone, dolomites, gypsum, and anhydrite (Garrels 1976; Thomson et al. 1999). Prolonged use of hard water may cause urolithiasis, anencephaly, prenatal mortality, cardiovascular disorders and malignancy (Agarwal and Jagetai 1997; Kumar et al. 2014).

The concentration of chloride in groundwater exceeded the WHO (2012) limits (250 mg L−1) in 8–9% of samples during both pre as well as post-monsoon seasons (Table 1). It was reported by Beaucaire et al. (1999) that during summer season high temperature of the tropical regions may concentrate chloride present in groundwater (due to evaporation), whereas, during the post-monsoon it may be found high because of dissolution of chloride salts due to percolation of rainwater. Chloride contamination in water is common because it does not gets sorbed by the soil components, resulting in unrestricted movement and enhances bioavailability (Kumar and James 2013; Sadat-Noori et al. 2014). Presence of chloride in groundwater derives from miscellaneous sources such as weathering and leaching of rock and soil, the intrusion of saltwater, windblown salt in rainfall, domestic and industrial effluent discharges etc. (Dhanasekarapandian et al. 2016; Khan and Jharia 2017). Presence of chloride in drinking water gives salty taste and may cause burning and tissue drying of leaves in plants (Ayers and Westcot 1994; Vasanthvigar et al. 2010).

Groundwater alkalinity ranged between 32–316, 76–468 and 48–532 mg L−1 during pre-monsoon and 260–746, 296–988 and 240–756 mg L−1 during post-monsoon season in rural, urban and industrial areas respectively (Table 1). It has been found that about 52% of groundwater samples during pre-monsoon season and 100% of groundwater samples during the post monsoon season failed on the criteria (alkalinity) prescribed by WHO (2012) i.e. 200 mg L−1. It has been reported that the runoff increases the alkalinity of water due to leaching of salts particularly carbonates and silicates (Phiri et al. 2005; Shyamala et al. 2008; Dinka et al. 2015; Bhat et al. 2001). Atmospheric CO2 and that released from the decomposition of organic materials may also contribute towards the building up of alkalinity of the water. The high alkalinity of water gives a soda like taste, which can dry out skin. High alkalinity in water is unsuitable for irrigation as it disturbs the natural soil profile, which reduces soil fertility and the crop yield.

Sulphate concentration was found to be within the prescribed limit (200 mg L−1) of WHO (2012) in all the groundwater samples during the post-monsoon season except at one location, however, during pre-monsoon season it was found to be higher at five locations (Table 1). Both natural and anthropogenic sources contribute the sulphate to water; however, the natural mineral sources, including barite (BeSO4), epsomite (MgSO4·7H2O) and gypsum (CaSO4·2H2O) are the prime contributors (Greenwood and Earnshaw 1984; Manivaskam 2005). Since the above mentioned sulphate minerals have not been reported from Kanpur region (Pal et al. 2012) hence, it implies that the anthropogenic sources are primarily responsible for the presence of sulphate in Kanpur. Application of sulfate fertilizers may also be the possible source for the sulphate contamination in groundwater of Kanpur. Higher concentration of sulphate may cause gastrointestinal problems particularly when Mg and Na are also present in drinking water (Suthar et al. 2009).

Nitrate concentration at all the locations during pre and post-monsoon season were found within the permissible limits given by WHO (2012) (45 mg L−1 Table 1). Use of fertilizers and septic tanks, animal farming, atmospheric deposition, industrial and municipal discharges are the prime sources of nitrate in groundwater (Vidal et al. 2000; Liu et al. 2005; Reddy et al. 2011; Kumar and James 2013; Vystavna et al. 2015). Presence of high level of nitrate in drinking water causes methemoglobinemia (infant cyanosis or blue baby syndrome).

During pre-monsoon season, 20, 26 and 7 samples have been found to be beyond the prescribed limits of Na, K and Ca (200, 10 and 75 mg L−1 respectively), whereas, in the post-monsoon season the corresponding figure were 15, 17 and 3 respectively. Na is an essential element found in the earth’s crust, especially in hard rocks like granites and gneisses in the plagioclase feldspar form (Srinivasamoorthy et al. 2009; Singh et al. 2015). High level of Na in drinking water causes hypertension, congenital heart disease and kidney problems (Raju et al. 2011). K concentration in water is generally very low (Vystavna et al. 2015). Intake of K rich water may have a laxative effect. High K in the drinking water causes hyperkalemia (WHO 2009). The occurrence of silicate minerals from the igneous and metamorphic rocks in the groundwater may increase the level of K contamination (Jameel and Hussain 2011; Vystavna et al. 2015). Permissible limits of K in drinking water have not been established by the public health authorities. Prime sources of Ca in groundwater around basalts are plagioclase and pyroxene (Botsa et al. 2016). The level of Ca in groundwater mainly depends on the solubility of calcium carbonate, sulphide and rarely chloride. The high calcium intake causes adverse effect on the cardiovascular health (Xiao et al. 2013; Kumar et al. 2014).

The negative correlation coefficient of pH with most of the parameter further affirms the alkaline nature of water samples. Remarkable positive correlation of hardness and sulphate with Ca (r = 0.761 and r = 0.867 respectively) indicates that water samples from rural areas are having permanent hardness and require chemical treatment before consumption (Tables 2, 3). EC is significantly correlated with TDS (r = 1.000) indicating the dependence of dissolved ions on the conductivity (Tables 2, 3).
Table 2

Correlation analysis for groundwater samples during pre-monsoon in rural, urban and industrial area of Kanpur city, India

 

pH

EC

Nitrate

Sulphate

Chloride

Hardness

Alkalinity

TDS

Na

K

Ca

Rural area

 pH

1

          

 EC

− 0.115

1

         

 Nitrate

− 0.065

0.192

1

        

 Sulphate

− 0.225

0.861**

0.035

1

       

 Chloride

− 0.241

0.815**

0.139

0.605**

1

      

 Hardness

− 0.097

0.812**

0.118

0.803**

0.584**

1

     

 Alkalinity

− 0.012

0.110

− 0.101

0.182

− 0.006

− 0.109

1

    

 TDS

− 0.114

1.000**

0.192

0.861**

0.815**

0.812**

0.110

1

   

 Na

0.037

0.815**

0.255

0.719**

0.720**

0.672**

− 0.035

0.814**

1

  

 K

− 0.179

0.650**

0.295

0.651**

0.432*

0.727**

− 0.106

0.649**

0.598**

1

 

 Ca

− 0.066

0.947**

0.0.178

0.867**

0.763**

0.761**

0.124

0.947**

0.918**

0.633**

1

Urban area

 pH

1

          

 EC

− 0.227

1

         

 Nitrate

0.159

− 0.068

1

        

 Sulphate

− 0.288

0.296

0.107

1

       

 Chloride

− 0.565**

0.702**

0.032

0.489**

1

      

 Hardness

− 0.629**

0.269

0.228

0.439**

0.666**

1

     

 Alkalinity

0.190

− 0.319

0.233

− 0.006

− 0.412*

− 0.404*

1

    

 TDS

− 0.281

1.000**

− 0.071

0.298

0.706**

0.276

− 0.322

1

   

 Na

0.120

0.451**

0.027

0.356*

0.207

− 0.217

0.180

0.450**

1

  

 K

− 0.261

0.035

0.256

0.105

0.194

0.481**

− 0.093

0.037

− 0.051

1

 

 Ca

− 0.280

0.704**

− 0.170

0.442**

0.636**

0.207

− 0.068

0.706**

0.757**

0.045

1

Industrial area

 pH

1

          

 EC

− 0.321

1

         

 Nitrate

− 0.175

0.796**

1

        

 Sulphate

− 0.238

0.900**

0.724**

1

       

 Chloride

− 0.329

0.919**

0.729**

0.869**

1

      

 Hardness

− 0.060

0.597**

0.590**

0.445*

0.518*

1

     

 Alkalinity

− 0.535**

− 0.067

− 0.319

− 0.057

0.091

− 0.407

1

    

 TDS

− 0.321

1.000**

0.796**

0.900**

0.920**

0.597**

− 0.067

1

   

 Na

− 0.130

0.651**

0.594**

0.765**

0.603**

− 0.090

0.064

0.651**

1

  

 K

− 0.052

0.428*

0.313

0.369

0.496*

0.597**

− 0.072

0.428*

− 0.017

1

 

 Ca

− 0.182

0.844**

0.768**

0.768**

0.752**

0.872**

− 0.247

0.844**

0.357

0.548**

1

** Correlation is significant at the 0.01 level (2-tailed); * correlation is significant at the 0.05 level (2-tailed)

Table 3

Correlation analysis for groundwater samples during post-monsoon in rural, urban and industrial area of Kanpur city, India

 

pH

EC

Nitrate

Sulphate

Chloride

Hardness

Alkalinity

TDS

Na

K

Ca

Rural areas

 pH

1

          

 EC

− 0.48

1

         

 Nitrate

− 0.09

0.363**

1

        

 Sulphate

− 0.38

0.837**

0.262

1

       

 Chloride

− 0.26

0.503

0.075

0.624

1

      

 Hardness

− 0.53

0.786**

0.046

0.588

0.299

1

     

 Alkalinity

− 0.08

0.554

0.353

0.506

0.362

0.225

1

    

 TDS

− 0.47

0.999**

0.363

0.837**

0.502

0.785**

0.554

1

   

 Na

− 0.03

0.155

− 0.027

0.302

0.484

0.078

0.233

0.154

1

  

 K

− 0.04

0.548

0.526

0.257

0.193

0.219

0.436

0.549

− 0.011

1

 

 Ca

0.146

− 0.053

− 0.129

− 0.020

0.181**

− 0.057

0.026

− 0.054

0.150**

− 0.083

1

Urban areas

 pH

1

          

 EC

− 0.654

1

         

 Nitrate

− 0.114

0.406

1

        

 Sulphate

− 0.299

0.546**

0.180

1

       

 Chloride

− 0.254

0.247

0.021

− 0.044

1

      

 Hardness

− 0.524

0.624**

0.146

0.344

0.331

1

     

 Alkalinity

− 0.017

0.272

0.132

0.066

− 0.111

− 0.142

1

    

 TDS

− 0.655

1.000

0.405

0.546

0.248

0.625

0.271

1

   

 Na

− 0.166

0.656**

0.413

0.397

− 0.108

0.083

0.681**

0.655**

1

  

 K

− 0.309

0.510*

0.222

0.348

− 0.041

0.558**

− 0.136

0.511

0.047

1

 

 Ca

− 0.716

0.689

0.262

0.322

0.270

0.462

0.118

0.689

0.221

0.316

1

Industrial area

 pH

1

          

 EC

− 0.31

1

         

 Nitrate

− 0.30

0.695**

1

        

 Sulphate

− 0.32

0.944**

0.494

1

       

 Chloride

− 0.44

0.844**

0.627

0.861**

1

      

 Hardness

− 0.34

0.378

0.093

0.480

0.619

1

     

 Alkalinity

− 0.05

0.327*

0.006

0.313*

0.055

0.023

1

    

 TDS

− 0.28

0.974**

0.688

0.927**

0.840**

0.410

0.280

1

   

 Na

0.092

0.780**

0.266

0.790

0.439

0.110

0.533

0.756

1

  

 K

− 0.62

0.359

0.487*

0.289

0.444*

0.360

0.098

0.298

− 0.07

1

 

 Ca

− 0.55

0.820**

0.806**

0.729**

0.890**

0.449

− 0.001

0.797**

0.292

0.575

1

** Correlation is significant at the 0.01 level (2-tailed); * correlation is significant at the 0.05 level (2-tailed)

WQI of groundwater at Kanpur during post-monsoon was recorded better than the pre-monsoon season (Table 4 and Fig. 2) except for industrial area. Except for one sample of pre-monsoon at the industrial area, all the samples were found to be ‘marginal’ to ‘fair’ water quality (Table 5). WQI showed the high proportion of ‘fair’ quality of groundwater during post-monsoon than pre-monsoon. Results indicate that the scarcity of groundwater and industrial discharges during pre-monsoon season are responsible for the lower WQI. During post-monsoon, the groundwater level increases due to rainfall which dilutes the concentration of contaminants. The value of WQI for rural area reveals that 65% of samples fall in ‘fair’ category in post-monsoon season while in pre-monsoon it was 44.83%. The increase of 20% in ‘fair’ category can be assigned to dilution of contaminants and decreased rate of weathering. The WQI of Industrial area revealed that the 34.78% of the groundwater samples expressed ‘good’ quality in pre-monsoon season while in post monsoon it was 13.03%. Reduction of 21.75% may be due to high rate of leaching, weathering, and seepage (Reza and Singh 2010; Singh et al. 2008). Similarly, water quality of 4.34% samples was found to be ‘poor’ during pre-monsoon season while, in post monsoon none of the samples has fallen in this category (Fig. 2). Overall WQI indicates the fairly good quality of underground water which is suitable for drinking and irrigation purposes.
Table 4

WQI of ground water during pre and post-monsoon season at rural, urban and industrial area of Kanpur, India

Sampling sites

Rural

Urban

Industrial

Pre

Post

Pre

Post

Pre

Post

1

66.6

Fair

65.76

Fair

74.2

Fair

74.9

Fair

52.7

Marginal

66.6

Fair

2

84.9

Good

77.40

Fair

74.5

Fair

68.1

Fair

75.1

Fair

73.7

Fair

3

85.1

Good

76.9

Fair

81.3

Good

75.2

Fair

75.3

Fair

67.4

Fair

4

81.1

Good

91.9

Good

64.1

Fair

58.9

Marginal

59.5

Marginal

59.2

Marginal

5

92.6

Good

84.5

Good

71.4

Fair

75.4

Fair

91.1

Good

92.4

Good

6

92.4

Good

84.3

Good

76.2

Fair

76.3

Fair

84.1

Good

84.5

Good

7

83.5

Good

76.1

Fair

76.9

Fair

80.9

Good

55.6

Marginal

45.7

Marginal

8

59.8

Marginal

76.5

Fair

85.1

Good

76.1

Fair

60.9

Marginal

67.2

Fair

9

65.4

Fair

77.3

Fair

74.2

Fair

76.7

Fair

43.3

Poor

55.2

Marginal

10

85.0

Good

77.3

Fair

76.7

Fair

69.8

Fair

76.6

Fair

90.5

Good

11

77.2

Fair

84.4

Good

84.3

Good

84.5

Good

59.5

Marginal

73.8

Fair

12

85.1

Good

76.9

Fair

76.9

Fair

76.4

Fair

92.2

Good

69.7

Fair

13

54.0

Marginal

61.6

Marginal

84.0

Good

91.7

Good

91.9

Good

77.5

Fair

14

70.0

Fair

69.1

Fair

76.2

Fair

66.3

Fair

84.9

Good

76.9

Fair

15

77.0

Fair

76.5

Fair

76.5

Fair

73.6

Fair

83.2

Good

77.8

Fair

16

69.5

Fair

82.6

Good

68.6

Fair

76.4

Fair

76.1

Fair

60.5

Marginal

17

77.4

Fair

83.8

Good

76.1

Fair

68.3

Fair

82.6

Good

75.7

Fair

18

83.9

Good

77.0

Fair

68.2

Fair

71.8

Fair

55.0

Marginal

46.8

Marginal

19

75.3

Fair

67.8

Fair

77.1

Fair

77.1

Fair

59.2

Marginal

66.4

Fair

20

77.1

Fair

76.3

Fair

67.3

Fair

67.8

Fair

92.1

Fair

77.1

Fair

21

69.1

Fair

75.5

Fair

66.2

Fair

66.6

Fair

76.8

Fair

76.5

Fair

22

61.2

Marginal

67.8

Fair

62.7

Marginal

62.1

Marginal

69.0

Fair

68.2

Fair

23

48.0

Marginal

57.6

Marginal

74.1

Fair

76.1

Fair

84.8

Good

69.5

Fair

24

69.3

Fair

76.9

Fair

74.6

Fair

74.4

Fair

    

25

85.03

Good

81.4

Good

73.6

Fair

75.1

Fair

    

26

69.8

Fair

74.6

Fair

61.5

Marginal

74.1

Fair

    

27

60.4

Marginal

66.0

Fair

68.1

Fair

68.9

Fair

    

28

68.0

Fair

67.5

Fair

72.8

Fair

58.1

Marginal

    

29

58.0

Marginal

58.8

Marginal

75.2

Fair

68.0

Fair

    
     

60.0

Marginal

68.1

Fair

    
     

76.2

Fair

76.7

Fair

    
     

74.3

Fair

76.3

Fair

    
     

82.6

Good

82.5

Good

    
     

75.5

Fair

92.3

Good

    
Fig. 2

WQI categories of samples (%) in pre and post monsoon season

Table 5

Water quality ranking on the basis of WQI Value (CCME 2001, 2004)

Category

WQI value

Remarks

Excellent

95–100

Water quality is protected with a virtual absence of threat or impairment; situations very close to natural or pristine levels

Good

80–94

Water quality is protected with only a minor degree of threat or impairment; conditions rarely depart from natural or desirable levels

Fair

65–79

Water quality is usually protected but occasionally threatened or impaired; conditions sometimes depart from natural or desirable levels

Marginal

45–64

Water quality is frequently threatened or impaired; conditions often depart from natural or desirable levels

Poor

0–44

Water quality is almost always threatened or impaired; conditions usually depart from natural or desirable levels

Piper (1944) developed a form of tri-linear diagram known as piper diagram; a combination of anions and cations triangles that lie on a common baseline. A piper diagram of the groundwater of Kanpur was created by using the analytical data obtained from the hydro-chemical analysis (Fig. 3). The diamond part of a Piper diagram may be used for characterization of different qualities of water. Piper segregated location based on water quality into four different zones. Location lying at the top corner of the diamond is high in Ca2+ + Mg2+ and Cl + SO 4 2− indicating the zone of permanent hardness while location lying near the left corner is also high in Ca2+ + Mg2+ and HCO3 which indicates the zone of temporary hardness. Location lying at the lower corner is mainly composed of alkali carbonate (Na+ + K+ and HCO3 + CO 3 2− ) and location lying adjacent to the right-hand side may be considered as saline (Na+ + K+ and Cl + SO 4 2− ). Vystavna et al. (2015) have also observed high Na + K at sites adjacent to urban areas and downstream sites.
Fig. 3

Piper diagram showing hydro geochemical characteristics of ground water at rural, urban and industrial areas of Kanpur city

Piper diagram further validates the finding that most of the water samples are prone to permanent hardness due to the presence of MgSO4 and CaSO4 as the concentration of Mg2+ and Ca2+ increases with increase in the sulphate (SO42−) content, while Na and K occur as bicarbonate. The findings further provide evidence about the geochemistry of the underground water and its influence on the prevailing water quality of the area. The results obtained from the present study provide information about the groundwater quality which will not only assist the judicious use of groundwater but also help to sustain the availability of water over a longer period of time. Findings may also be helpful to prevent cases of epidemiological issues caused by contaminated groundwater.

Conclusions

The physico-chemical characteristics of pre-monsoon and post-monsoon groundwater of Kanpur provided valuable information on the influence of geochemistry, anthropogenic pressure and groundwater extraction on the water quality of rural, urban and industrial areas. Values of various physicochemical parameters viz. nitrate, chloride, hardness, Na and K were found low during post-monsoon period, reason being a dilution of contamination of groundwater due to rainfall. WQI of groundwater at Kanpur during post-monsoon was found be better than the pre-monsoon season. Further, the proportion of ‘fair’ category of water was higher than other categories indicating that ground water was suitable for drinking purpose. Results provided evidence on the alkaline nature of groundwater and presence of permanent hardness in most of the water samples indicating the influence of the mineral composition of water table on water quality. Results clearly indicate that groundwater recharging is an important mechanism to maintain the quality of underground water.

Notes

Acknowledgements

Dr. Narendra Kumar would like to thank to University Grant Commission, New Delhi, India for providing financial assistance extended in the form of Major Research Project (Grant No. F.No.-41-1101/2012 (SR)).

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Copyright information

© Society for Environmental Sustainability 2018

Authors and Affiliations

  • Narendra Kumar
    • 1
  • Dhananjay Kumar
    • 1
  • Sanjeev Kumar
    • 1
  • Vertika Shukla
    • 1
  • Preeti Shukla
    • 1
  • Beenu Raj
    • 1
  1. 1.Department of Environmental ScienceBabasaheb Bhimrao Ambedkar UniversityLucknowIndia

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