ORIGINAL ARTICLE

Geochemical characterization and heavy metal contaminationof groundwater in Satluj River Basin

Chander Kumar Singh • Kumari Rina •

Ravi Prakash Singh • Saumitra Mukherjee

Received: 15 October 2012 / Accepted: 16 March 2013

� Springer-Verlag Berlin Heidelberg 2013

Abstract Groundwater, a renewable and finite natural

resource, vital for man’s life, social and economic devel-

opment and a valuable component of the ecosystem, is

vulnerable to natural and human impacts. The aim of

present study is to evaluate hydrogeochemical parameters

and heavy metals in groundwater and to study their spatial

distribution in the Rupnagar District of Punjab. The spatial

distribution of physico-chemical parameters were studied

using Arc GIS 9.2. It was observed that the concentration

of parameters, such as NO3, Cd, Cr, Mn and Pb was above

permissible limit (World Health Organization, WHO) in

southern part of the study area. The heavy metal pollution

index (HPI) was calculated for all sampling locations and it

was found much above the critical limit of pollution.

Geochemical reaction models of selected water groups

were constructed using Phreeqc. Geochemical modeling

suggests that sodium has source other than halite-albite and

calcium has alternate source other than gypsum-carbonate

or silicates. It also suggests that evaporites, ion exchange,

dissolution along with anthropogenic activities are con-

trolling the hydro-geochemistry of groundwater in the

region. Various indices, such as heavy metal pollution

index, permeability index, sodium adsorption ratio, were

studied to verify suitability of groundwater for drinking

and irrigation.

Keywords GIS � Groundwater quality � Phreeqc � Satluj

River � Saturation index � HPI

Introduction

Groundwater is the water found in spaces between soil

particles and rocks, and within cracks of the bedrock. It

forms one of the important sources of potable water. The

hydrogeochemistry of groundwater determines its potabil-

ity for domestic and agricultural use. The rate of with-

drawal of groundwater is increasing continuously due to

faster pace of population growth accompanied by agricul-

tural and industrial development. This has increased the

concern on groundwater resource evaluation and its man-

agement for sustainable development. Groundwater has

become an essential commodity in recent decades due to

industrialization and unplanned urbanization (Kumari et al.

2012). However, rapid expansion of industries and infra-

structure has become hostile, posing a risk to the health and

welfare of the people due to release of pollutants from

industries and urban sewage (Ntengwe 2006). The effluents

discharged from industries and urban sewage finds their

way into surface water bodies. These water bodies which in

turn also act as recharge source for groundwater thus

making it vulnerable. Few of the heavy metals considered

as micronutrients become detrimental to human health

when its concentration exceeds the permissible limits.

Thus, its monitoring in ground water used for drinking

purpose assumes great significance for human health. The

occurrence and movement of groundwater in an area is

governed by several factors, such as topography, hydrog-

eomorphology, geology, drainage pattern, land use, cli-

matic conditions and inter relationships among these

factors. The quality of groundwater is equally important as

C. K. Singh (&)

Department of Natural Resources, TERI University,

New Delhi 110070, India

e-mail: chanderkumarsingh@gmail.com

C. K. Singh � K. Rina � R. P. Singh � S. Mukherjee

School of Environmental Sciences, Jawaharlal Nehru University,

New Delhi 110067, India

123

Environ Earth Sci

DOI 10.1007/s12665-013-2424-x

its quantity owing to the suitability of water for various

purposes (Yidana and Yidana 2010). Variation of ground-

water quality in an area is a function of physical and

chemical parameters that are greatly influenced by geo-

logical formations and anthropogenic activities (Subramani

et al. 2005; Vijith and Satheesh 2007; Nas and Berktay

2010; Singh et al. 2011a). The quality of surface water and

soil characteristics determines the composition and quality

of the groundwater (Atapour 2012; Singh et al. 2011b, c).

The chemical properties of groundwater also depend upon

the chemistry of water in the recharge area as well as on the

different geochemical processes that are occurring in the

subsurface. These geochemical processes are responsible

for the seasonal and spatial variations in groundwater

chemistry (Matthess 1982). To assess the fate and impact

of the chemical discharge on to the soil, it is important to

understand the hydro-geochemistry of the soil–groundwa-

ter interactions (Miller 1985). Generally, groundwater at

the discharge zones tend to have higher mineral concen-

tration as compared to that at the recharge zones due to the

longer residence time and prolonged contact with the

aquifer matrix (Freeze and Cherry 1979). Inverse geo-

chemical modeling in Phreeqc is based on a geochemical

mole-balance model, which computes the phase mole

transfers (the moles of minerals and gases that move in or

leave the solution) to comprise the differences in an initial

and a final composition of groundwater system along the

flow path (Parkhurst and Appelo 1999). This mass balance

approach has been used in recent times to quantify reac-

tions controlling water chemistry along groundwater flow

paths (Hidalgo and Cruz-Sanjulian 2001) and quantify

mixing of end-member components in a flow system

(Kuells et al. 2000).

With the above background, the present study tries to

get insight of hydrogeochemical processes occurring in the

study area and it also tries to quantify the heavy metal

pollution along with its suitability for drinking and irriga-

tion purpose.

Study area

Location and climate

Rupnagar District (formerly known as Ropar), included in

the Patiala division of Punjab falls between latitude 30�320

and 31�240 and longitude 76�180 and 76�550 (Fig. 1). The

Satluj River passes close (2–5 km) to the towns of Nangal,

Rupnagar and Anandpur Sahib. The climate is character-

ized by its general dryness (except in the south-west

monsoon season), a hot summer and a bracing cold winter.

The south-west monsoon season commences late in June

and continues up to about middle of September. The

temperature ranges from minimum of 4 �C in winter to

45 �C in summer. May and June are generally hottest

months and December and January are the coldest months.

Relative humidity is high, averaging about 70 % during

monsoon. The average annual rainfall in last three decades

is 775.6 mm. About 78 % of the annual rainfall is received

during the period from June to September (CGWB 2007).

Geology

The rock formations in the area include river terraces,

gravel beds, alluvial fans and calctufa beds of recent origin

and conglomerates, sandstones and claystones of Upper

Shiwalik (Fig. 2). The Upper Shiwalik mostly comprises of

boulder conglomerate beds with poorly to moderately sor-

ted sandstone beds. The conglomerate bands are poorly

cemented and include cobbles and pebbles with some

boulders of quartzite, sandstone and siltstone with stray

fragments of coarse and fine-grained granites, banded

quartzite, limestone, trap rock, claystone, carbonaceous

phyllite, schist and purple shale. Sub-recent to recent

deposits include mainly gravel beds, alluvial fans, river

terraces and calctufa beds. The regime of rivers Satluj and

Soan is occupied by a vast span of alluvium containing

sand, silt and clay in various proportions (Singh et al.

2011a). The nearly horizontal beds of calc-tufa mixed

intimately with calcareous shales and siliceous matter rest

over the sub-horizontal beds of coarse-grained micaceous

and calcareous sandstone and conglomerates of Upper

Shiwalik. River terraces and gravel beds constitute and

important source for the quartzite fragments (CGWB 2007).

Materials and methods

Samples of groundwater were collected in polypropylene

bottles (Tarsons) during 2007 from adjoining areas of

National Fertilizers Limited, Punjab Chemicals Limited,

floodplain of River Satluj, areas besides canals along with

other areas in the district representing different landuse/

landcover classes. Most of these groundwater samples were

collected from hand pumps, dug wells and borewells. Care

was taken to discard water of first 20–25 strokes in order to

minimize the impacts of iron pipes through which water

was pumped out. The study was carried out with the help of

Survey of India toposheets, Garmin GPSmap60CS, Arc

GIS 9.2. GPS was used to map the location of each sam-

pling site (Fig. 3). The fieldwork included collection of

water samples from borewells, dug wells and hand pumps.

The physical parameters, such as pH (Hanna, HI 98107),

total dissolved solids (TDS) and electrical conductivity

(EC) were measured on the site using electrodes (Hanna,

HI 98311).

Environ Earth Sci

123

At each site, water samples were collected in two

separate clean polypropylene bottles (Tarsons; 250 and

125 ml), rinsed two to three times with groundwater to

be sampled. One of the bottles (125 ml) containing

sample was acidified to stabilize trace metals and was

used for determination of major cations and trace met-

als. The other bottle (250 ml) containing un-acidified

sample was used for anions analysis. The samples were

stored in ice containing styrofoam boxes and brought to

laboratory and stored at 4 �C for further analysis.

Samples were vacuum filtered with 0.22-lm Millipore

filter paper. Major cations and anions were analyzed

using ion chromatograph (Dionex). Heavy metals were

analyzed using Atomic Absorption Spectrophotometer

(Thermo Fischer, AA series). Nitrate was analyzed using

brucine method in spectrophotometer (Perkin Elhmer,

Lamda 35).

The GIS-based analysis of spatial distribution of water

quality parameters was done using Spatial Analyst module

of Arc GIS 9.2. The interpolation technique used in the

analysis is inverse distance weighted (IDW) method

(Tabios and Salas 1985; Tomczak 1998; Mueller et al.

2004). Weights are computed by taking the inverse of the

distance from an observation’s location to the location of

the point being estimated. The inverse distance can be

raised to a power (e.g. linear, squared or cubed) to model

different geometries (e.g. line, area, volume) (Burrough

and McDonnell 1998). US Salinity Laboratory hazard

diagram (USSL), Doneen Diagram and Gibbs plot was

plotted using Watclast software.

Fig. 1 Study area

Environ Earth Sci

123

Result and discussion

Spatial variation of groundwater quality parameters

The water quality parameters that were analyzed along

with their minimum, maximum, mean, median and stan-

dard deviation values are given in Table 1. The number

and percentage of samples exceeding the allowable limits

set by WHO (2008) is given in Table 2. The pH of

groundwater varied between 7.06 and 8.29 (7.62 ± 0.28).

The groundwater in the area is mainly alkaline in nature.

The electrical conductivity varied from 693.6 to 1,295 lS/cm,

highest being in Rurki. The areas that had very high values

for electrical conductivity are Chanalon, Landran, Bhalan.

The concentration of bicarbonate in the study area var-

ied from 169 to 448 mg/l with the mean value of

299.4 ± 75.88 mg/l. The high values were observed in

some northern, southern and western part of study area,

including villages of Kharar, Bhalan, Bela, Dheri, Bera

Chaunta and Landran. The concentration of chloride ran-

ged from 14 to 197 mg/l. The mean value was

50.45 ± 49.35 mg/l. The high values were observed for

Rurki, Landran and Chanalon with highest being in Rurki.

The variation in concentration of sulfate was from 5 to

Fig. 2 Geological map of study

area [Sedimentary (Sed),

consolidated (Con),

conglomerated (Cong),

unconsolidated (Uncon),

alluvium (allu)]

Environ Earth Sci

123

120 mg/l with the mean value being 53.50 ± 38.26 mg/l.

The higher concentration of sulfate was although observed

at sites of Nurpurbedi, Bhagwantpur, Mianpur, Chanalon

and Rurkiharan (120 mg/l) with Rurkihiran being the

highest; it was still very much under the permissible limit

(500 mg/l) as per WHO (2008). The nitrate concentration

ranged from 0.5 to 80 mg/l with 20.76 ± 24.95 mg/l as

the mean concentration of the various sampling sites in the

study area. The concentration of nitrate exceeding the

permissible limit (50 mg/l) of WHO (2008) was observed

in Nurpurbedi, Sandwan, Bhalan, Saijowal and Chanalon

with the highest being in Sandwan (80 ppm). There were

some other sites from where nitrate concentrations were

close to the permissible limit, i.e. Landran (42 ppm). Out

of the 22 samples five exceeded the maximum permissible

limit of nitrate (Fig. 4). The higher nitrate concentration

can be attributed to agricultural sources, such as fertilizers,

animal waste, crop residues and mineralization of soil

organic nitrate and on the other hand non-agricultural

sources such as septic tanks, effluents containing nitrogen

discharged from industries.

Hydrogeochemical processes

The chemical properties of groundwater also depend upon

the chemistry of water in the recharge area as well as on the

Fig. 3 Sampling locations

Environ Earth Sci

123

Ta

ble

1W

ater

qu

alit

yp

aram

eter

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pli

ng

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on

sp

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ian

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Std

.D

ev0

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Un

its

inm

g/l

exce

pt

pH

and

EC

(lS

)

Environ Earth Sci

123

different geochemical processes that are occurring in the

subsurface. These geochemical processes are responsible

for the seasonal and spatial variations in groundwater

chemistry (Matthess 1982; Cederstorm 1946; Singh et al.

2011a). Because the study region experiences typical

tropical climatic condition, evaporation may also contrib-

ute in hydrogeochemistry. Hence, Gibbs plot is employed

in this study to understand and differentiate the influences

of rock–water interaction, evaporation and precipitation on

water chemistry (Gibbs 1970). The Gibbs (1970) diagram

(Fig. 5) plots the total dissolved solids (TDS) on a loga-

rithmic axis against the ratio of sodium and the sum of

sodium and calcium on a linear axis. Gibbs plot illustrates

that most of the groundwater samples of the Sutlej River

basin fall in the water–rock interaction field and few

samples plotted on evaporation zone, which suggests that

the weathering of rocks primarily controls the major ion

chemistry of groundwater in this region. Therefore, the

concentrations of major ions in groundwater and the min-

eralogy of different rocks have been used to determine the

source of these major ions to the groundwater and their

relation to regional geology and weathering processes

(Kumari et al. 2011). Some of the points lie outside the

dotted triangle representing anthropogenic influence (Ku-

mari et al. 2012). The areas near hills have dolomitic

limestone and weathered lime overlying carbonate rocks,

i.e., kankar. These weathered carbonate rocks might have

reached groundwater during rain infiltration, irrigation and

recharged the groundwater thus imparting it carbonate

character (Singh et al. 2012).

Weathering and dissolution

Calcium and sodium are the dominant cations followed by

magnesium and potassium, respectively. Similarly, among

the anions bicarbonate and chloride are dominant anions

followed by sulphate, nitrate and fluoride, respectively.

Carbonate-rich rocks, such as crystalline limestone, dolo-

mitic limestone, calcgranulite and kankar (lime-rich

weathered mantle overlies carbonate rocks) are the major

sources for carbonate weathering. The available carbonates

in these rocks might have been dissolved and added to the

groundwater system during irrigation, rainfall infiltration

and groundwater movement. In Ca2??Mg2? vs

HCO3- ? SO4

2- scatter diagram (Fig. 6), the points fall-

ing along the equiline (Ca2??Mg2? = HCO3- ? SO4

2-)

suggest that these ions have resulted from weathering of

carbonates and sulphate minerals (gypsum or anhydrite)

(Datta et al. 1996). Moreover, if the Ca2? and Mg2? solely

originated from carbonate and silicate weathering, these

should be balanced by the alkalinity alone. However, most

of the points are placed in the Ca2? ? Mg2? side, which

indicates excess calcium and magnesium derived from

other process, such as reverse ion exchange reactions

(Kumari et al. 2012). In silicate terrain, if the calcium and

bicarbonate in groundwater are solely originated from

calcite, the equivalent ratio of dissolved Ca2? and HCO3-

in the groundwater is 1:2, whereas from dolomite weath-

ering, it is 1:4 (Garrels and Mackenzie 1971; Holland

1978). Similarly, if the calcium and sulphate in ground-

water derived from dissolution of gypsum or anhydrite,

then the Ca2?/SO42- ratio is almost 1:1 (Das and Kaur

2001). Most of the samples show excess of calcium over

sulphate, samples lying on the equiline suggest dissolution

of anhydride or gypsum and the samples lying above the

equiline, showing excess of sulphate over calcium thus

suggesting precipitation of calcite thus removing calcium

from the system (Fig. 7). If Ca2?/Mg2? molar ratio is equal

to one, then dissolution of dolomite should take place

(Maya and Loucks 1995), whereas a higher ratio is indic-

ative of greater calcite contribution. If the Ca2?/Mg2?

molar ratio is higher ([2) then dissolution of silicate

minerals takes place (Katz and Hornsby 1998). In the

present study, it was observed that the molar ratio of Ca2?/

Mg2? suggests dissolution of dolomite along with calcite is

prominent. In Ca2? vs alkalinity scatter diagram (Fig. 8),

Table 2 Drinking water specifications of the study area in compar-

ison with WHO (2008)

Units Desirable

limit

(WHO)

Maximum

permissible

limit

(WHO)

No. of

samples

exceeding

maximum

permissible

limit

Samples

exceeding

maximum

permissible

limit (%)

pH 6.5–8.5 9.2 0 0

TDS mg/l 500 1,500 0 0

EC lS/cm – 1,500 0 0

HCO3 mg/l – – – –

Cl mg/l 200 600 0 0

SO4 mg/l 200 400 0 0

NO3 mg/l 45 – 5 22.72

F mg/l – 1.5 0 0

Ca mg/l 75 200 0 0

Mg mg/l 50 150 0 0

Na mg/l – 200 0 0

K mg/l – – – –

Cd mg/l – 0.003 22 100

Cr mg/l – 0.05 4 18.18

Cu mg/l 2 2.5 0 0

Fe mg/l – 3 0 0

Mn mg/l – 0.4 2 9.09

Pb mg/l – 0.01 8 36.36

Zn mg/l – 3 – –

SiO2 mg/l – – – –

Environ Earth Sci

123

the groundwater samples fall above and below equiline

(1:1) suggesting the contribution of both calcite and dolo-

mite weathering on groundwater chemistry in Sutlej River

Basin. The relationship between Na ? K and total cations

(Tz?) of the area (Fig. 9) indicate that the majority of the

samples shows the involvement of silicate weathering in

the geochemical processes, which contributes mainly

sodium and potassium ions to the groundwater (Stallard

and Edmond 1983; Sarin et al. 1989). However, some

samples deviated from the line and show lower Na ? K

concentration, which seems to be Ca/Na exchange

reactions.

Geochemical modeling

Phreeqc is a program for simulating chemical reactions and

transport processes in natural or polluted water. The pro-

gram works on equilibrium chemistry of aqueous solutions

interacting with minerals, gases, solid solutions, exchang-

ers, and sorption surfaces. It is based on an ion-association

aqueous model and has capabilities for speciation and

saturation-index calculations.

Saturation indexes (SI) are used to evaluate the degree

of equilibrium between water and respective mineral.

Different stages of hydrochemical evolution can be

Fig. 4 Spatial variation of

nitrate

Environ Earth Sci

123

Fig. 5 Gibbs plot

Fig. 6 Scatter plot of Ca ? Mg versus HCO3 ? SO4

Fig. 7 Scatter plot of Ca versus SO4

Fig. 8 Scatter plot of Ca versus HCO3

Fig. 9 Scatter plot of Na ? K versus total cations (Tz?)

Environ Earth Sci

123

illustrated to identify changes in saturation state which can

help in identifying the geochemical reactions that are

important in controlling water chemistry. The saturation

index of a mineral can be obtained using following

equation:

SI ¼ log IAP=Kt

� �

where IAP is the ion activity product of the dissociated

mineral and Kt is equilibrium solubility at mineral

temperature.

Saturation indices express the extent of chemical equi-

librium between water and mineral phases in the matrix of

the aquifers and could be regarded as a measure of disso-

lution and/or precipitation processes relating to the water–

rock interaction (Drever 1997). The SI of a mineral

therefore provides information on whether the mineral is

thermodynamically likely to precipitate or dissolve. SI \ 0

indicates that the groundwater is under-saturated with

respect to that particular mineral and such a value could

reflect the character of water from a formation with

insufficient amount of the mineral for solution or short

residence time and SI [ 0 specifies that the groundwater is

oversaturated with respect to the particular mineral and

therefore incapable of dissolving more of the mineral. Such

an index value reflects groundwater discharging from an

aquifer containing ample amount of the mineral with suf-

ficient resident time to reach equilibrium. Figure 10 shows

the SI variation for anhydride, aragonite, calcite, chalce-

dony, chrysolite, CO2, dolomite, gypsum, halite and sepi-

olite. Geochemical modeling using Phreeqc suggests that

sodium has source other than halite-albite, calcium has

source other than gypsum-carbonate or silicates and ion

exchange, gypsum dissolution and anthropogenic input

seems to be an important source of calcium enrichment in

groundwater in the study area. Exchange of Na and K by

Ca and Mg, sorbed on the surface of the clay minerals can

cause their (Ca, Mg) higher concentration. In addition to

ion exchange, the industrial and/or agricultural input of Na

and Mg also contributes to the increase in these ions in

groundwater (Guo and Wang 2004).

It clearly indicates that groundwater is undersaturated

with respect to dissolution of halite, CO2, anhydrite,

chrysolite, gypsum and sepiolite (except 3 locations) in

most of the places, thus enriching Ca2?, Mg2? and other

ions in the groundwater by dissolution of these minerals.

Oversaturation can be possibly produced by factors that

include incongruent dissolution, common ion effect and

evaporation (Rosso et al. 2011, Kumari et al. 2012). The

samples were found to be oversaturated with respect to

dolomite, calcite, aragonite, chalcedony thus suggesting

that these minerals have precipitated earlier and are not

contributing Ca2? and Mg2? in the groundwater. It also

suggests that besides ion exchange, sodium is contributed

by anthropogenic sources which is also clear from the plot

of (Na??K?) and Cl (Fig. 11).

Calcium has source other than calcite, dolomite and

aragonite; and gypsum dissolution and contributions from

anthropogenic activity seem to be an important source of

calcium enrichment in groundwater. Gypsum and anhy-

drite are having SI values less than zero thus they are

responsible occurrence of sulphate in groundwater. Sepi-

olite is frequently found in marl-clay sediments, either

with gypsum, chert (micro-crystalline quartz) or dolomite

(Leguey et al. 2010). Therefore, undersaturation and

oversaturation of sepiolite suggests that a general process

for dolomite dissolution and recrystallization could have

been associated with sepiolite differentiation (Kumari

et al. 2011). In addition, the formation of sepiolite might

possibly be related to the biomineralization of dolomite

during diagenetic evolution of these sedimentary forma-

tions. The processes can be confirmed by further research

on biogeochemical reactions. The saturation indices for

different minerals suggest that evaporites, ion exchange,

dissolution along with anthropogenic activities are con-

trolling the hydrogeochemistry of groundwater in this

region.

Fig. 10 Saturation index variation for different minerals Fig. 11 Scatter plot between Na ? K versus Cl

Environ Earth Sci

123

Salinity and alkalinity hazard

The high concentration of Na?, HCO3- and CO3 in irri-

gation water affects the agricultural soil and plants thus

reducing the productivity. These ions lower the osmotic

pressure structural cells of plants and thus water is not able

to reach the upper part of the tree, i.e. branches and leaves.

Electrical conductivity is measure of salinity hazard as it

reflects the content of total dissolved solids in groundwater.

Sodium adsorption ratio (SAR) is used for determining the

suitability of groundwater for irrigation because it is a

measure of alkali/sodium hazard in an area. The analyzed

parameters were plotted on the US salinity diagram pro-

posed by US Salinity Laboratory Staff (1954) (Fig. 12)

illustrates that 31.81 % of samples fall in the field of C3–

S1, indicating water of high-salinity hazard and low

sodium hazard, which can be used for irrigation in almost

all types of soil with low probability of exchangeable

sodium. Salt-tolerant crops can be grown in this region.

68.19 % of the samples lie in C2–S1, indicating medium

salinity and low sodium hazard. This water will be suitable

for plants and are suitable for irrigation. Thus, the

groundwater of the study area is good to moderate in

quality based on the USSL diagram.

Sodium percentage

Sodium plays an important role in evaluating the ground-

water quality for irrigation as it causes an increase in the

soil hardness and reduction in its permeability (Tijani

1994). High concentration of sodium causes soil mineral

particles to disperse and less water to infiltrate (Jalali

2007). Its effect becomes as infiltration rate of a soil is

reduced to the extent that the crops does receive adequately

amount of water.The sodium percentage (Na %) is calcu-

lated using the equation:

%Na ¼ Naþ þ Kþð Þ � 100

Ca2þ þMg2þ þ Naþ þ Kþ� �

The Na % indicates that four samples are excellent, nine

samples are good and five samples belong to permissible

criterion leaving 4 samples of groundwater in doubtful

category (Table 3). Thus, 18 groundwater water sampling

locations water can be used for irrigation leaving only four

sampling locations unsuitable for irrigation. Adsorption of

sodium on clay by its exchange with Mg2? and Ca2? ions

takes place when sodium is high. This results in poor

permeability and drainage of soil, leading to restricted air

and water circulation in it and thus makes it hard (Tijani

1994; Collins and Jenkins 1996; Saleh et al. 1999). The

areas with high value (doubtful) of Na % are Nurpurbedi,

Rurki, Bela and Dheri.

Sodium adsorption ratio (SAR)

It is used to measure of alkali/sodium hazard to crops. The

excessive sodium content relative to the calcium and magne-

sium reduces the soil permeability and thus inhibits the supply

of water needed for the crops. It is an important parameter to

determine the suitability of groundwater for irrigation. The

excess sodium or limited calcium and magnesium are evaluated

by SAR which is expressed as (Karanth 1987)

SAR ¼ NaþffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiCa2þ þMg2þ�

2

q

The SAR values for the samples are shown in Table 4.

The SAR value’s indicated that 27.27 % of samples belong

to doubtful (S3) and 4.5 % of samples belong to unsuitable

category (S4). The areas having high SAR under S3 and S4

categories are Nurpurbedi, Bela, Bhawantpur, Rurki,

Landran, Mianpur and Dheri, respectively.

Permeability indices

The permeability of soil is affected as a result of long-term

irrigation in alluvial areas, influenced by cations (Na?,

Fig. 12 USSL diagram

Table 3 Classification of groundwater on sodium percentage

% Na Water class No. of samples Samples (%)

\20 Excellent 4 18.18

20–40 Good 9 40.9

40–60 Permissible 5 22.72

60–80 Doubtful 4 18.18

[80 Unsuitable – –

Environ Earth Sci

123

Ca2?, Mg2?) and HCO3- contents of the soil. The per-

meability index (PI) values also indicate the suitability of

groundwater for irrigation. Permeability indices (PI) for the

groundwater samples (Ragunath 1987) were calculated

using following equation

PI ¼Naþ þ

ffiffiffiffiffiffiffiffiffiffiffiffiffiHCO3

p� �� 100

Ca2þ þMg2þNaþ þ Kþ� �

Permeability indices were plotted together with the total

ionic content of the groundwater samples on a Doneen’s

chart (Domenico and Schwartz 1990). The Doneen’s chart

(Fig. 13) showed classifies the water into three classes:

Class I The value of PI is low. It is water of good

quality for irrigation;

Class II Higher value of PI with respect to class I and

the water in this category is generally

acceptable;

Class III Waters is completely ruled out for irrigation.

It is observed in Fig. 13 that nearly 95 % of water

belongs to Class I category under permeability index and

only one sample falls in Class II category.

Hydrochemical facies

The Piper (1944) diagram suggests that the cationic species

as Ca, Na and Mg and anionic species as bicarbonate to be

dominate in the aquifer of this region.

Thus, the majority of groundwater samples belong to

calcium, sodium/magnesium-bicarbonate type. The Piper

trilinear plot (Fig. 14) suggests strong influence of dolo-

mitic limestone with gypsum in the rocks of the recharge

area. The majority of samples belonged to Ca–Mg–HCO3

facies which is result of interaction of water with dolomitic

limestone and calcareous slates found in the study area.

Some of the samples belonged to Na–HCO3 type facies

confirming the interaction of water with the rocks com-

prising schists, quartzites and granites. The leaching of

sodium and potassium from schists and granites is the main

source of alkali enrichment. The water facies reflects the

signatures of natural water recharge and water–soil/rock

interaction. Atmospheric CO2 and biogenic CO2 infiltrate

in the subsurface with surface water and reacts with

alumino-silicates including feldspar and mica releasing

cations such as Ca and Mg into the water which in turn,

raises the pH and concentration of HCO3 is observed in the

water due to incongruent dissolution (Freeze and Cherry

1979). Weathering of Na–K-bearing minerals, cation-

exchange process and industrial and/or agricultural activi-

ties are responsible for the dominance of Ca, Na, Mg in

groundwater in region (Singh et al. 2011a).

Heavy metal pollution

The concentration of cadmium in the study area varied

from a minimum of 0.003 mg/l to a maximum of

0.016 mg/l with a mean value of 0.009 ± 0.004 mg/l. The

concentration at all the locations is above the prescribed

limit (0.003 mg/l) of WHO (2008). The highest concen-

tration was observed at Ahmedpur, Hardinamoh, Nupurb-

edi, Kubaheri, Kakrali and Dumewal with Hardinamoh and

Ahmedpur being the highest (0.016 mg/l). The chromium

concentration varied from 0.005 to 0.067 mg/l, with

0.036 ± 0.018 mg/l as the mean value. The higher con-

centration of chromium was although observed at sites of

Kakrali (0.067 ppm), Bera Chauta, Saijowal, Sandawan,

Chakdera and Chanalon with Kakrali being the highest. At

all the places mentioned above, the concentration was well

above the permissible limit of 0.05 mg/l by WHO (2008).

The concentration of manganese varied from 0.002 to

1.158 mg/l, with the mean value of 0.258 ± 0.336 mg/l.

The concentration was very high at Gogha, Landran

(1.149 ppm), Bhagwantpur and Hardinamoh than the

WHO (2008) standards (0.5 mg/l) with Gogha reaching up

Table 4 Classification of groundwater based on SAR values

SAR Alkalinity

hazard

Water

class

No. of

samples

Samples

(%)

\10 S1 Excellent 10 45.45

10–18 S2 Good 5 22.72

18–26 S3 Doubtful 6 27.27

[26 S4 Unsuitable 1 4.5

Fig. 13 Doneen’s diagram depicting Permeability index

Environ Earth Sci

123

to 1.158 mg/l. Ahmedpur and Bela concentration very near

to the permissible limits. The concentration of cadmium in

the study area varied from a minimum of 0.003 mg/l to a

maximum of 0.063 mg/l with a mean value of 0.027 ±

0.021 mg/l. The concentration at most of the locations is

more than the prescribed limit (0.003 mg/l) of WHO

(2008) with highest concentration being at Dheri

(0.063 mg/l). The concentration of zinc varied from 0.049

to 2.867 mg/l, with the mean value being 0.75 ±

0.881 mg/l. The concentration at some places as Landran,

Gogha, Mianpur and Rurkihiran were high reaching the

permissible limit (3 mg/l) prescribed by WHO (2008) with

highest being at Landran (2.867 mg/l). The spatial varia-

tion of few of the heavy metals is shown in Fig. 15.

Heavy metal pollution index

The HPI method assigns a rating or weightage (Wi) for

each chosen parameter and select the pollution parameter

on which the index is to be based. It can be defined as

inversely proportional to the recommended standard (Si)

for each parameter (Mohan et al. 1996). In this study, the

concentration limits (i.e., the highest permissible value for

drinking water (Si) and maximum desirable value (MAC)

(Ii) for each parameter) were taken from the WHO stan-

dard. The uppermost permissive value for drinking water

(Si) refers to the maximum allowable concentration in

drinking water in the absence of any alternate water source.

The desirable maximum value (Ii) indicates the standard

limits for the same parameters in drinking water.

The HPI, assigning a rating or weightage (Wi) for each

selected parameter, is determined using the expression

below (Mohan et al. 1996):

HPI ¼Pn

i¼1 WiQiPni¼1 Wi

where Qi and Wiare the sub-index and unit weight of the ith

parameter, respectively, and n is the number of parameters

considered. The sub-index (Qi) is calculated by

Qi ¼Xn

i¼1

Mi �ð Þlif gSi � li

x100

where, Mi, Ii and Si are the monitored heavy metal, ideal

and standard values of the ith parameter, respectively. The

sign (-) indicates numerical difference of the two values,

ignoring the algebraic sign.

The HPI represents the composite influence of metals on

the overall quality of water (Kumar et al. 2012; Prasanna

Fig. 14 Piper diagram

Environ Earth Sci

123

Fig. 15 Cadmium, chromium, manganese, lead

Environ Earth Sci

123

et al. 2012). The rating is based on the relative importance

of individual quality considerations and defined as inver-

sely proportional to the recommended standard for each

heavy metal (Mohan et al. 1996). The critical pollution

index of HPI value for drinking water as given by Prasad

and Bose (2001) is 100. In this indexing, weights (Wi)

between 0 and 1 were assigned for each metals. Metals

such as Cd, Cr, Cu, Fe, Mn, Pb and Zn were considered in

the present study. Almost all of the samples except two fall

in high critical pollution index category as per Prasad and

Bose (2001) (Table 5). The HPI value of more than 300

was recorded for Kakrali and Saijowal region of the study

area. The higher HPI values suggest the effect of industrial,

agricultural and urban sewerage pollution on groundwater

quality.

Conclusion

The hydrochemical analysis of the study reveals that the

groundwater of the study is contaminated in terms of trace

metals, such as cadmium, chromium, manganese and lead.

The groundwater is also contaminated in terms of nitrate

concentration exceeding much above the permissible limits

of WHO. The major cause for nitrate pollution is mainly

anthropogenic. The majority of groundwater chemical

facies belongs to Ca–Mg–HCO3 facies which is result of

interaction of water with dolomitic limestone and calcare-

ous slate which is also supplemented by Gibbs diagram. The

Gibbs plot suggests that the rock weathering along with

anthropogenic activities control the hydro-geochemistry of

groundwater. The processes, such as dolomite, calcite dis-

solution is dominant in the Sutlej River Basin. The sub-

stantial influence of carbonate and silicate weathering can

also be observed in groundwater chemistry. Groundwater is

oversaturated with respect to dolomite, calcite, aragonite,

chalcedony thus suggesting that these minerals have pre-

cipitated in past and are not contributing Ca2? and Mg2?.

Moreover, ion exchange, sodium is contributed by anthro-

pogenic sources which is also clear from the plot of

(Na??K?) and Cl. The groundwater at areas such as Rurki,

Berachauta, Bela and Dheri show high value of sodium

percentage. The heavy metal pollution index also suggests

that the groundwater quality is severely deteriorating. The

overall quality states that the areas such as Berachauta,

Bela, Gogha, Landran, Chanalon and Rurki are areas which

demands urgent attention. These results are important for

the development of proper management and remediation

strategies to decrease non-point source pollution.

Acknowledgments The author (CKS) thanks to Sat Pal Mittal trust

for providing the fellowship. The author also thanks the anonymous

reviewers for their constructive suggestions. The author also

acknowledges Jawaharlal Nehru University for providing various

instrument facilities to carry out research work.

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