Hydrochemical Characteristics of Groundwater in and around the
Peenya Industrial Area in Bengaluru City
PAVITHRA N.1,2,*, RAMAKRISHNAIAH C. R.2
1Department of Civil Engineering, Government SKSJTI,
Visvesvaraya Technological University,
Bengaluru, Karnataka,
INDIA
2Department of Civil Engineering, BMS College of Engineering,
Visvesvaraya Technological University,
Bengaluru, Karnataka,
INDIA
*Corresponding Author
Abstract: - The present study aims to use the Water Quality Index (WQI) modeling method to know about
groundwater hydrochemistry and drinking suitability in and around (5 km) the Peenya industrial area/estate in
Bengaluru city. For this research study, 116 bore well samples were collected and examined for the pre (dry)
and post (wet) monsoon seasons in 2021, following APHA standard procedures. According to the BIS standard,
the TH, Ca, Mg, NO3, and TDS exceed the desirable limits in both seasons. The water quality examination data
shows that TDS concentration is found to be higher above the desired limit (500 mg/l) during the pre- (63%)
and post- (45%) monsoon seasons. Furthermore, 55% (pre-monsoon) and 15% (post-monsoon) of the
groundwater samples exceed the BIS's nitrate allowable limit (45 mg/l). Among the analyzed samples, the
calcium content in 19% and 20% of samples exceeded the desirable limit (75 mg/l), and magnesium content in
87% and 83% exceeded the desirable limit (30 mg/l) in pre- and post-monsoon seasons. In 95% of samples, TH
content exceeded the desirable limit (200 mg/l) in both pre- and post-monsoon seasons. Piper diagram plots
were utilized to determine sources of dissolved constituents, rock-water interaction, and other factors that
influenced the region's groundwater composition. Based on hydro-chemical facies the Ca-Mg-HCO3 type of
water predominates in the study area during pre (dry) and post (wet)-monsoon seasons of the year 2021. The
chemistry of groundwater has deteriorated significantly because of several industrial and anthropogenic
activities. The WQI spatial distribution map shows that groundwater quality has the greatest impact in the west
and a few places in the north and south regions of the research area. This study was conducted in Bangalore's
Peenya industrial area to determine whether groundwater is suitable for drinking, identify the mechanisms
governing groundwater's geochemistry, and evaluate the effects of an industrial area on groundwater quality.
The primary focus of this study is the major ion chemistry in this field.
Key-Words: - Groundwater, Hydrochemistry, Drinking suitability, Peenya industrial area, India.
Received: March 23, 2023. Revised: October 19, 2023. Accepted: December 13, 2023. Published: December 31, 2023.
1 Introduction
Groundwater is a vital natural resource that meets
our rural and urban needs. Bengaluru is one of the
most economically fast-growing cities in the south
zone of Karnataka, dominated by intense growth of
small- and large-scale industrial activities. 40 sq.
km lies in the North part of Bengaluru city and
contains around 2100 industries, the majority of
which are chemical, leather, pharmaceutical,
plating, polymer, and allied industries. The
industrial estate is fully surrounded by private and
residential mixed industrial activity. The Peenya
industrial area/estate uses groundwater mostly for
domestic, industrial, and drinking uses. Demand for
groundwater in big cities like Bengaluru is
increasing. Therefore, human health is directly
impacted by the quality of groundwater. Between
the authorized Peenya Industrial land/estate and the
area around it, there is no existing buffer zone.
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Several investigations were done inside the
industrial estate to determine the levels of
pollution, but none were done outside of it to
identify the contaminated bore water or the factors
that significantly contribute to pollution due to
runoff from the industrial estate. To prevent further
groundwater contamination concerns that influence
public health and related health issues, continual
monitoring and assessment of water quality are
necessary both inside and outside the Peenya
Industrial Area, [1], [2].
The interaction between surface water,
groundwater, and aquifer minerals, leaching of
industrial activities from the surface, and other
human activities are among the geogenic and
anthropogenic variables that contribute to the
variance in groundwater quality. Groundwater's
chemical makeup varies as a result, changing over
time. Additionally, the parent rock, the rate of
weathering, the length of stay, and environmental
elements like temperature and precipitation all play
a role. Groundwater's major and minor ion
concentration is regulated by hydrogeochemical
processes such as weathering, dissolution, mixing,
and ion exchange. Industrial locations are
susceptible to pollution from effluents with
complicated compositions. In the vicinity of these
industrial facilities, major ions and heavy metals
are frequently the most common pollutants. The
chemical ions found in groundwater because of
these factors dictate whether it is suitable for
industrial and drinking uses, [3], [4].
WQI is a helpful mathematical technique for
assessing groundwater quality for drinking. This
concept of WQI was developed and proposed first
by Horton. WQI represents a single number that is
easily understood by the public and decision-
makers, [5]. Geographic information system (GIS)
is computer-based technology employed to
illustrate the spatial-temporal distribution of
groundwater characteristics, [6]. The main
advantage of GIS is that it handles huge amounts of
data, simplifies the understanding of complex data,
and facilitates quick judgments through graphical
representations, [7]. GIS also offers the ability to
decide and present precise information.
Considering the foregoing background information,
the current investigation study aimed to (1)
determine the suitability of the groundwater in and
around (5 km) the Peenya industrial area using the
WQI model for both the pre- and post-monsoon
period; and (2) to discuss hydrochemistry
combined with a Geographic Information System
(GIS) to suggest groundwater management
strategies.
2 Study Area
Peenya Industrial area/estate in Bengaluru,
Karnataka, India is one of the largest and oldest
industrial Areas in Southeast Asia. The study area
taken lies between latitude 130 1’ 42" N and
longitude 770 30’ 45" E. It was established in the
late 1970s by the Karnataka Small Industries
Development Corporation as Stage I, II III, and
Phase IV. The total extent of the area/estate is
about 40 sq. km and is in the north-western suburbs
of Bengaluru city, Figure 1. The main industries in
the Peenya industrial area/estate are Galvanizing,
Degreasing, Spray painting, Powder coating
process, Pickling, Phosphating, Anodization,
Textile Dying, Garment Washing, Electroplating,
Lead Processing, and Pharmaceuticals
Formulations, etc. The Peenya Industrial Area is
recognized by both the Central and State
Governments as the main hub of industrial activity
in the State and an important source of
manufactured goods with a reputation for quality
for both domestic and export markets. The study
area's geology is a component of the Peninsular
Gneissic Complex, which is represented by biotite,
granodioritic, and mafic gneiss with intrusive rocks
such as pegmatites and dykes. The industrial area
/estate in general is witnessed by red sandy soil,
[2]. The soil cover extends up to 1 to 2 meters
below the ground level. The peninsular gneissic
group, which includes the granites, gneisses, and
migmatites, is responsible for most of the aquifers
in Bengaluru's urban regions. Igneous and
metamorphic rocks combine to form migmatite
rock. The area's weathered zone and the freshly
formed gneisses and granite rock beneath it make
up the aquifer system. The northern part of
Bengaluru has phreatic groundwater. Over the
previous 50 years, the research region received 923
mm of yearly rainfall on average. Groundwater
depths before and during the monsoon season vary
from 0 to 49.95 metres, and from 0.20 to 58.97
metres, respectively NGRI, [8]. The industrial area
is located on an extremely undulating terrain. The
highly undulating topography with a sub-dendritic
nature has given rise to the origin of several micro
watersheds with varying hydrological
characteristics as per NGRI, [8].
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Fig.1: Location map of the study area with
groundwater sampling points
2.1 Methodology
A total of 116 Groundwater samples were collected
from both in and around (5KM) Peenya industrial
area, Figure 1 during the pre and post-monsoon
period (March 2021). 30 samples from inside the
Peenya industrial area and 86 samples from the
surrounding Peenya industrial area/estate within a
5km distance from the boundary of the Peenya
industrial area were collected. The collected bore
well samples were transferred into a washed
polyethylene bottle for analysis of physio-chemical
characters. The bore well Sampling point’s
coordinates were noted using GPS. Once collected,
each water sample was securely stored before being
sent to the Environmental Engineering lab for
analysis. The collected groundwater samples were
tested for pH, EC, chlorides, total alkalinity, total
dissolved solids, magnesium, calcium, iron,
fluoride, total hardness, potassium, sodium,
bicarbonates, sulfates, and nitrate using the
standard procedures recommended by APHA-2005
guidelines, [9]. The obtained test results were
compared to the recommended standard allowable
levels as per the standards recommended by the
Bureau of Indian Standards (BIS:10500, 2012),
[10]. The analytical data obtained can be used for
calculating WQI, plotting piper-tri-linear diagrams,
Box-and-whisker plots, and spatial distribution
maps.
2.2 WQI Calculations
The WQI provides an accurate representation of
surface and groundwater quality for most domestic
uses. WQI is defined as a rating that represents the
combined impact of several water quality factors.
The groundwater quality of the study area is
determined using a most effective mathematical
tool known as the Water Quality Index (WQI).
WQI provides a single indicator value that
represents water quality by integrating different
water quality variables, [11], [12], [13].
WQI estimations include the following
successive steps, [14], [15], [16]. The first step is
“assigning weight”: each of the 11 parameters has
been assigned a weight (wi) according to its relative
importance based on the quality of groundwater for
domestic purposes as shown in Table 1. In the
weights assigned between 1 and 5, the most
significant parameters have been provided with a
greater value and the least significant have been
assigned a lower value. The second step is the
“relative weight” (Wi): which is computed from the
following arithmetic index formula
Where Wi is the relative weight, is the ratio of
weight given for each parameter to the summation
of weightage of all the parameters. The wi is the
weight of each parameter. The calculated relative
weight (Wi) values of each physico-chemical
parameter are given in Table 3.
The third step is “quality rating scale
calculation (qi)”: Using the BIS drinking water
standard, [10], each parameter's quality rating scale
is determined by dividing its concentration in each
water sample (Ci) by the corresponding standard
(Si), and then multiplying the result by 100:
qi = (Ci / Si) x 100
Finally, the Wi and qi are used to calculate the
SIi for each chemical parameter, where SIi is the
sub-index of each parameter and then it is used to
calculate WQI as shown below:
SIi = Wi x qi
WQI = ∑ SIi
Table 1. Relative weightage of physicochemical
parameters
Wi=
wi
∑wi
Sl No Paramater
Weight (wi)Relative Weight (Wi)BIS:10500 (2012)
1pH 4 0.11111 6.5-8.5
2 Chlorides,mg/l 3 0.08333 250
3 Total hardness,mg/l 2 0.05556 200
4 Iron, mg/l 4 0.11111 0.3
5 Nitrate, mg/l 5 0.13889 45
6 Calcium,mg/l 2 0.05556 30
7 Magnesium, mg/l 2 0.05556 75
8 Total dissolved solids, mg/l 4 0.11111 500
9 Fluoride, mg/l 4 0.11111 1-1.5
10 Sulphates, mg/l 4 0.11111 200
11 Total alkalinity,mg/l 2 0.05556 200
∑wi =36 ∑Wi =1.0000
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3 Results and Discussion
Table 2 shows the statistics of groundwater quality
parameters in the pre and post-monsoon seasons of
2021. The pH ranges of the water samples in the
current investigation were 5.1 to 8.1 and 7.8 to 8.8
in the pre and post-monsoon seasons, respectively.
It was observed that 97% and 91% of samples fall
within the desirable pH limit of 6.5 to 8.5 mg/l. The
pH value of water is a crucial indication of water
quality. Although pH has no direct impact on
human health, changes in pH have an impact on
several biological processes as well as some
psychological impacts, [17]. The chloride value is
specified as 250-1000 mg/l as per BIS 10500
standards. The study area's 35% and 3% chloride
concentration values are beyond the acceptable
limit in pre-/post-monsoon. Excessive levels of
chloride in the water are indicators of pollution and
are used as an indicator for groundwater
contamination caused by industrial and human
waste. Drinking water with higher chloride content
has a salty taste and a laxative effect, [18]. The TH
concentration limit is 200 mg/l to 600 mg/l as per
the BIS Standards. It was observed that 95% of
water samples are beyond the acceptable limit in
both seasons. water above 300 mg/l is considered
hard. Soap consumption by hard water represents
an economic loss to the water user, [19]. The
calcium concentration limit in the groundwater is
between 75 to 200 mg/l, it was found that 19% and
20% of samples are beyond the acceptable limit in
pre-/post-monsoon. The magnesium concentration
level in the groundwater is within the limit of 30 to
100mg/l as per BIS 10500 standards. From the
study, magnesium samples are found 13% and 83%
more than the desirable limit pre-/post-monsoon.
The concentration of magnesium and calcium salts
in water determines its overall hardness. The salts
of calcium, together with those of magnesium are
responsible for the hardness of water. In the current
investigation, the concentration level of TDS is
specified as 500-2000 mg/l as per BIS 10500
standards. It was observed that 63% and 45% of
TDS values are beyond the acceptable limit in pre-
/post-monsoon respectively. Groundwater with
high TDS is of inferior palatability and may
produce unfavorable physiological reactions in the
transient consumer, [20]. Many of the groundwater
samples are noticed with a high nitrate
concentration in pre-monsoon 55% of the samples
are beyond the maximum permissible limit and
15% of samples are beyond the acceptable limit in
post-monsoon. It results from several industrial
operations. The presence of excessive nitrate in
water may adversely affect the health of infants
causing blue baby disease. The iron concentration
limit is 0.3 mg/l as per the BIS Standards. It was
observed that 28% of water samples are beyond the
acceptable limit in the post-monsoon season only.
Higher iron concentrations make the water
unpleasant in taste. The fluoride, and sulfate
concentration levels in the groundwater samples of
the entire study area fall under the desirable limits.
The percentage compliance for the respective
parameters measured for both seasons is shown in
Table 3.
Table 2. Descriptive statistics of groundwater
quality parameters in pre and post-monsoon
seasons of 2021
Table 3. Methods of Estimation of physico-
chemical Characteristics of groundwater quality
Five categories are established from the
computed WQI values, [15], [21]: "excellent
water," "good," "poor," "very poor," and "water
unsuitable for drinking." In the current research
study, the calculated WQI values for the 116
Groundwater samples both in and around the
Peenya industrial area ranged from 39.103 to
224.168 & 39.641 to 192.387 and pre-/post-
monsoon season, with 4 % and 8% of the waters
being “excellent water” in pre-/post-monsoon
season, 59 % and 66% “good water” in pre-/post-
monsoon season,36 % and 27% in “poor water” in
pre-/post-monsoon season and 1% “very poor water
for drinking” in pre-monsoon season (Table 4). The
figured WQI values for the 30 Groundwater
samples from inside the Peenya industrial area
ranged from 70.57 to 196.01and pre-/post-monsoon
Paramater
Pre-Monsoon
Post-Monsoon
Drinking Water Standards
Sl No Paramater Method BIS:10500 (2012) Pre-Monsoon Post Monsoon
1pH pH meter 6.5-8.5 97 91
2 Chlorides,mg/l Argentometric method 250 65 97
3 Total hardness,mg/l EDTA method 200 5 5
4 Iron, mg/l Spectrophotomete 0.3 100 72
5 Nitrate, mg/l Ion Meter 45 45 85
6 Calcium,mg/l EDTA method 30 81 80
7 Magnesium, mg/l EDTA method 75 87 17
8 Total dissolved solids, mg/l TDS Meter 500 37 55
9 Conductivity, µs/cm Conductivity Meter - - -
10 Fluoride, mg/l Ion Meter 1-1.5 100 100
11 Sulphates, mg/l Gravimetric Method 200 100 100
12 Total alkalinity mg/l Volumetric Method 200 9 0
13 Bicarbonates,mg/l Volumetric Method - - -
14 Sodium, mg/l Flame Photometer - - -
15 Potassium, mg/l Flame Photometer - - -
Percentage Compliance
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season, with only 13 % and 7% “good water” in
pre-/post-monsoon season, 83 % to 93% “poor
water” in pre-/post-monsoon season and 3% “very
poor water for drinking” in pre-monsoon season
(Table 5). Further WQI values for the 86
Groundwater samples from outside (5km) Peenya
industrial area ranged from 70.57 to 196.01and and
pre-/post-monsoon season, with only 6 % and 10%
“excellent water” in pre-/post-monsoon season,74%
and 86% “good water” in pre-/post-monsoon
season, 20 % to 3% “poor water” in pre-/post-
monsoon season water for drinking” (Table 6).
Because of the high amounts of TDS, TH, nitrate,
calcium, and magnesium from industrial activity,
the Peenya industrial area has low water quality
standards during the pre- and post-monsoon season
respectively. In contrast, post-monsoon season
outside the industrial region exhibits an
improvement in water quality because of the
diluting effect of rainwater. The pie chart showing
the percentage of water samples based on WQI
values during pre/post-monsoon-2021 is shown in
Figure 2 and Figure 3.
Table 4. Water quality classification based on
WQI value for both inside and outside Peenya
Industrial Area
Table 5. Water quality classification based on WQI
value for Inside Peenya Industrial Area
Table 6. Water quality classification based on WQI
value for Outside Peenya Industrial Area
Fig. 2: Pie chart showing the percentage of water
sample based on WQI values during pre-monsoon-
2021
No of Samples Percentage No of Samples Percentage
< 50 Excellent 5 4% 97%
50-100 Good Water 68 59% 76 66%
100-200 Poor Water 42 36% 31 27%
200-300 Very Poor Water 0 1% 00%
>300
Water Unsuitable for
Drinking
00% 00%
Pre-Monsoon
Post-Monsoon
WQI Value
Water Qulity
No of Samples Percentage No of Samples Percentage
< 50 Excellent 0 0% 00%
50-100 Good Water 4 13% 27%
100-200 Poor Water 25 84% 28 93%
200-300 Very Poor Water 1 3% 00%
>300
Water Unsuitable for
Drinking
00% 00%
WQI Value
Water Qulity
Pre-Monsoon
Post-Monsoon
No of Samples Percentage No of Samples Percentage
< 50 Excellent 3 6% 910%
50-100 Good Water 64 74% 74 86%
100-200 Poor Water 17 20% 34%
200-300 Very Poor Water 0 3% 00%
>300
Water Unsuitable for
Drinking
00% 00%
WQI Value
Water Qulity
Pre-Monsoon
Post-Monsoon
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Fig. 3: Pie chart showing the percentage of water
sample based on WQI values during post-monsoon-
2021
The water quality at each location was shown
and its acceptability for drinking was established by
the WQI spatial variation map (Figure 4 and Figure
5). The maps of WQI show five different types of
water quality categories: <50 excellent quality
water,50-100 good water,100-200 poor water,200-
300 very poor water, and >300 unsuitable for
drinking purposes, [15], [21]. The region on the
maps with a poor category water quality index is
shown by the color yellow patches. Most of the
groundwater in the poor category is found inside
the Peenya Industrial Area because of the discharge
of industrial wastewater. The percentage of
groundwater that comes under the poor category
outside the Peenya Industrial area, indicates that
pollution in groundwater moved towards lower-
level areas. Due to the groundwater sample sites'
lower height, it is noticed that groundwater quality
is determined to be in the poor category towards the
west while being in the good category in the east
(higher elevation).
Fig. 4: Spatial distribution of WQI in pre-monsoon
Fig. 5: Spatial distribution of WQI in post-monsoon
Figure 6, shows the elevation map of the
Peenya industrial area. The pink and purple color
on the elevation map indicates steeper slopes
whereas orange and red colors indicate higher
elevation. Figure 7, Bar graphs showing the
comparison of TDS values with groundwater
sampling location elevation values. It is observed
that at groundwater sampling points having lower
elevation values, TDS concentration is high. In
groundwater sampling points having higher
elevation, TDS concentration is low. This
comparison study indicates that pollution in
groundwater moves towards lower-level areas. The
Water tables often follow the topography of the
area, or upward and downward tilts and the land
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above them, [15]. The groundwater moves more
quickly towards down steeper slopes than down
shallow slopes. For this reason, it was observed that
pollution migration is more towards the west
direction of the study area, Figure 7. The areas
which come under poor water quality. This study
adds novelty to the current work because it includes
investigations that have not been done before in the
study field.
Fig.6: Map showing elevation at the groundwater
sampling location
Fig.7: Bar graphs showing the comparison of TDS
values with groundwater sampling location
elevation values
The results from the chemical analysis of the
groundwater sample were plotted using the Piper-
tri-linear model, [22]. According to the ionic
composition of groundwater samples, a specialized
graph called the piper-tri-linear can be used to
reveal chemical correlations between samples
(Figure 8). Two triangle fields, one diamond-
shaped field, and three distinct fields make up the
Piper diagram, [23]. The cations and anions are
shown in separate ternary plots. The two ternary
plots are then projected onto a diamond-shaped
field, from which inference is drawn based on the
hydro-geochemical facies concept, [24]. The
analytical results obtained from the groundwater
samples are designed on a Piper trilinear diagram.
Figure 9 and Figure 10, reveal the Hydrochemical
regime of the study area. It identifies the water
compositions and variations in ion concentrations,
[25]. In pre-monsoon (Table 7), it was found that
Alkaline earth (Ca+Mg) exceeds alkalies (Na+K)
type is the most dominant facies in the study area
(constituting 84%). Weak acids (CO3+HCO3)
exceed Strong acids (SO4+Cl) type (constituting 62
%) ranked second and Magnesium bicarbonate type
facies ranked third in abundance (constituting 52
%). In post-monsoon (Table 7) it was Weak acids
(CO3+HCO3) exceed Strong acids (SO4+Cl) type is
the most dominant facies in the study area
(constituting 95%). Alkaline earth (Ca+Mg)
exceeds alkalies (Na+K) type (constituting 93%)
ranked second and Magnesium bicarbonate type
facies ranked third in abundance (constituting 85
%). The investigated sample’s hydrochemistry
indicates that the alkaline earth > alkali metals and
weak acid > strong acidic anions. The dominant
hydrochemical facies of groundwater in the study
area is Ca–Mg–HCO3. In Pre-Monsoon, the
diamond field of Piper shows the mixed
classification of water type i.e., gypsum ground
waters and drainage, shallow, fresh ground waters,
and deeper ground waters influenced by ion
exchange. In Post-Monsoon- the diamond field of
Piper shows typical shallow, fresh ground waters
nature. There is no significant change in the hydro-
chemical facies noticed during the study period
(pre- and post-monsoon), which indicates that most
of the major ions are natural in origin. The mixed
type of the other groundwater samples suggests that
they are impacted by rainwater infiltration, which
comparatively revealed enrichment of Mg, Cl, and
HCO3 ions, or by anthropogenic contaminations
such as Mg, Cl, and Na. The reason is groundwater
passing through Migmatite rock dissolves only
small quantities of mineral matter because of the
relative insolubility of the rock composition.
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Fig. 8: Classification diagram for anion and cation
facies in the form of major-ion percentages. Water
types are designed according to the domain in
which they occur on the diagram segments
Table 7. Characterization of groundwater in and
around Peenya industrial area of Karnataka based
on Piper tri-linear diagram
Fig. 9: Pre-monsoon groundwater samples plotted
in the piper-Trilinear diagram
Fig. 10: Post-monsoon groundwater samples
plotted in the piper-Trilinear diagram
Pearson’s correlation matrix is used to measure
and find the association between two variables.
This simple statistical tool has been used to
quantify the relationship between two variables and
illustrate the extent to which one variable depends
on the other, [25]. It is observed Magnesium and
total hardness is found to have a very strong
association both before and after the monsoon
season (Table 8 and Figure 9). This
interrelationship between these two variables
indicates that the hardness of the groundwater is
permanent. A Box and Whisker Plot was prepared
in the present study. It is an appropriate way of
visually displaying the data distribution through
their quartiles, [25]. Groundwater samples collected
in and around the Peenya industrial region over the
two seasons are displayed in a box-whisker plot
showing the analytical results together with their
maximum, lowest, median, and percentile values
(Figure 11 and Figure 12).
Table 8. Correlation matrix of various parameters
analyzed in the pre-monsoon season
Pre-Monsoon Post-Monsoon
1
Alkaline earth (Ca+Mg) Exceed alkalies (Na+K) 84.5 93.1
2
Alaklies exceeds alkaline earths 15.5 6.9
3
Weak acids (CO3+HCO3) exceed Strong acids
(SO4+Cl)
62.1 94.8
4
Strong acids exceeds weak acids 37.9 5.2
5
Magnesium bicarbonate type 51.0 85.3
6
Calcium-chloride type 3.4 0.9
7
Sodium-chloride type 3.4 0.9
8
Sodium-Bicarbonate type 0.0 0.0
9
Mixed type (No cation-anion exceed 50%) 42.2 12.9
Subdivision of
the
diamond
Characteristics of corresponding
subdivisions of diamond-shaped
fields
Percentage of samples in this category
Parameter pH TDS Cl
SO4NO3FTH Ca Mg Fe TA
pH 1
TDS -0.067 1
Cl -0.209 0.440 1
SO40.001 0.010 -0.174 1
NO30.163 0.186 0.132 -0.050 1
F0.057 0.192 0.136 -0.205 0.012 1
TH -0.147 0.400 0.571 0.118 0.175 -0.134 1
Ca -0.351 0.523 0.301 -0.169 0.027 0.067 0.270 1
Mg -0.054 0.270 0.510 0.181 0.165 -0.150 0.948 0.031 1
Fe 0.034 0.053 -0.001 0.110 0.266 -0.175 0.230 0.080 0.205 1
TA 0.061 0.430 -0.025 0.476 0.115 -0.153 0.295 0.173 0.234 0.421 1
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Table 9. Correlation matrix of various
parameters analyzed in post-monsoon season
Fig. 11: Box-and-whisker plot of water quality
parameters in pre-monsoon season
Fig. 12: Box-and-whisker plot of water quality
parameters in pre-monsoon season
4 Conclusions
The main aim of this study was to assess the
groundwater quality in and around (5 km) the
Peenya industrial area/estate in Bengaluru City,
India. Various physical and chemical
characteristics were assessed in groundwater
samples collected during and after the monsoon
season. The quality of groundwater varied greatly
in comparison to drinking water regulations. The
predominant cations in groundwater are Ca2+ and
Mg2+ for both seasons. The prevalence of anion in
groundwater for both seasons is due to Cl− and NO3
respectively. The groundwater which is
contaminated by untreated industrial waste sewage
has penetrated through the soil and contaminated
the groundwater of the study region. WQI values
for the 116 Groundwater samples both in and
around the Peenya industrial area ranged from
39.103 to 224.168 and 39.641 to 192.387 and pre-
/post-monsoon season. out of which 30
Groundwater samples inside the Peenya industrial
area ranged from 70.571 to 196.017, with 83 % and
93% poor water in pre-/post-monsoon season. Poor
to very poor categories of WQI (water quality
index) were observed inside the industrial areas,
where the contamination level is higher. Based on
the results of this study, policymakers can reduce
Parameter pH TDS Cl
SO4NO3FTH Ca Mg Fe TA
pH 1
TDS -0.366 1
Cl -0.521 0.576 1
SO40.024 0.399 0.147 1
NO3-0.037 0.375 0.131 0.162 1
F-0.040 0.003 0.095 0.165 -0.087 1
TH -0.465 0.570 0.596 0.173 0.162 0.131 1
Ca -0.376 0.366 0.532 0.089 0.101 0.036 0.496 1
Mg -0.433 0.553 0.521 0.275 0.132 0.229 0.659 0.071 1
Fe -0.136 0.532 0.311 0.523 0.351 0.183 0.318 0.164 0.406 1
TA -0.261 0.270 0.149 0.120 0.075 0.033 0.227 0.064 0.425 0.158 1
WSEAS TRANSACTIONS on ENVIRONMENT and DEVELOPMENT
DOI: 10.37394/232015.2023.19.127
Pavithra N., Ramakrishnaiah C. R.
E-ISSN: 2224-3496
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Volume 19, 2023
the amount of work involved in initiating water
quality management activities for groundwater
remediation in the northeastern regions of the study
area. It is also recommended that groundwater
quality be periodically monitored within the
industrial areas and in the western region outside
the Peenya industrial area to stop further
deterioration of the water quality in the study area.
The type of water that predominates in the
examined area is Ca-Mg-HCO3 type during both
pre- and post-monsoon seasons of the year 2021,
based on hadrochemical facies. Continuous
monitoring of water quality in this area will help in
understanding the progressive improvement in
groundwater quality during the process of
restoration to improve the groundwater quality.
Acknowledgement:
The First author is thankful to the AICTE,
Government of India, New Delhi for sponsoring the
opportunity to carry out this study. The author
would also like to acknowledge Dr.
Ramakrishnaiah C. R, Professor, Civil Engineering
Department, BMS College of Engineering,
Bengaluru for his study assistance.
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Contribution of Individual Authors to the
Creation of a Scientific Article (Ghostwriting
Policy)
- Pavithra N carried out Conceptualisation,
investigation, data curation, methodology,
writing – original draft, visualization, and
validation.
- Dr. Ramakrishnaiah C R was responsible for
Supervision, conceptualization, reviewing, and
editing.
Sources of Funding for Research Presented in a
Scientific Article or Scientific Article Itself
This work is supported by institutional scholarship
from AICTE, Government of India, New Delhi.
Conflict of Interest
All authors certify that they have no affiliations
with or involvement in any organization or entity
with any financial or non-financial interest in the
subject matter or materials discussed in this
manuscript.
Creative Commons Attribution License 4.0
(Attribution 4.0 International, CC BY 4.0)
This article is published under the terms of the
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WSEAS TRANSACTIONS on ENVIRONMENT and DEVELOPMENT
DOI: 10.37394/232015.2023.19.127
Pavithra N., Ramakrishnaiah C. R.
E-ISSN: 2224-3496
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Volume 19, 2023