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Remote Sensing and GIS Techniques for Evaluation of Groundwater Quality in Municipal Corporation of Hyderabad (Zone-V), India

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Groundwater quality in Hyderabad has special significance and needs great attention of all concerned since it is the major alternate source of domestic, industrial and drinking water supply. The present study monitors the ground water quality, relates it to the land use / land cover and maps such quality using Remote sensing and GIS techniques for a part of Hyderabad metropolis. Thematic maps for the study are prepared by visual interpretation of SOI toposheets and linearly enhanced fused data of IRS-ID PAN and LISS-III imagery on 1:50,000 scale using AutoCAD and ARC/INFO software. Physico-chemical analysis data of the groundwater samples collected at predetermined locations forms the attribute database for the study, based on which, spatial distribution maps of major water quality parameters are prepared using curve fitting method in Arc View GIS software. Water Quality Index (WQI) was then calculated to find the suitability of water for drinking purpose. The overall view of the water quality index of the present study area revealed that most of the study area with >50 standard rating of water quality index exhibited poor, very poor and unfit water quality except in places like Banjara Hills, Erragadda and Tolichowki. Appropriate methods for improving the water quality in affected areas have been suggested.
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Int. J. Environ. Res. Pub
lic Health
200
7, 4(1),
45
-
52
International Journal of
Environmental Research and Public Health
ISSN 166
1-7827
www.ijerph.org
© 200
7
by MDPI
© 200
7
MDPI. All rights reserved.
Remote Sensing and G
IS
Techniques for Evaluation of Groundwater
Quality in
Municipal Corporation o
f Hyderabad (Zone
-
V), India
S
.
S. Asadi
1*
, Padmaja Vuppala
2
and M. Anji Reddy
3
1
Centre for Environment, Institute of Science & Technology, Jawaharlal Nehru Technological University, Hyderabad-
500072,
A.P, India
2
Centre for Environment, Institute of Science & Technology, Jawaharlal Nehru Technological University, Hyderabad-
500072,
A.P, India
3
Institute of Science & Technology, Jawaharlal Nehru Technological Un
iversity, Hyderabad
-
500072, A.P, India
*
Correspondence to Dr.
S. S. Asadi
. E
-
mail:
ssvp_envi@yahoo.co.in
;
asadienviron@yahoo.com
;
padmaja_vuppala@yaho.co.in
Received:
24 January 2007
/ Accepted:
15 March 2007
/ Published
:
31 March 2007
Abstract:
Groundwater quality in Hyderabad has special significance and needs great attention of all concerned since it
is the major alternate source of domestic, industrial and drinking water supply. The present study monitors the ground
water quality, relates it to the land use / land cover and maps such quality using Remote sensing and GIS techniques for a
part of Hyderabad metropolis. Thematic maps for the study are prepared by visual interpretation of SOI toposheets and
linearly enhanced fused data of IRS-ID PAN and LISS-III imagery on 1:50,000 scale using AutoCAD and ARC/INFO
software. Physico-chemical analysis data of the groundwater samples collected at predetermined locations forms the
attribute database for the study, based on which, spatial distribution maps of major water quality parameters are prepared
using curve fitting method in Arc View GIS software. Water Quality Index (WQI) was then calculated to find the
suitability of water for drinking purpose. The overall view of the water quality index of the present study area revealed
that most of the study area with > 50 standard rating of water quality index exhibited poor, very poor and unfit water
quality except in places like Banjara Hills, Erragadda and Tolichowki. Appropriate methods for improving the water
quality in affected areas have been suggested.
Keywords:
Groundwater quality, Landuse/Landcover, Spatial distribution, Remote sensing & Geographical Information
System (GIS).
Keywords
: I
ntimate partner violence, risk factors for partner violence, alcohol abuse
Introduction
The urban environment quality is deteriorating day by
day with the largest cities reaching saturation points and
unable to cope with the increasing pressure on their
infrastructure. Hyderabad, the capital city of Andhra
Pradesh, which lies between 78
0
22’ 30” and 78
0
32’ 30”
East longitude and between 17
0
18’30” and 17
0
28’30”
North latitude, is facing a rapid change in the
environmental quality. Rapid urbanization brings with it
many problems as it places huge demands on land, water,
housing, transport, health, education etc [1]. Environmental
pollution has reached alarming levels in the last 5-6 years
mainly due to industries and automobiles. The city
witnessed an increase in population from 0.448 million in
1901
- 1.429 million in 1961, between 1981 and 1991 the
population went upto 4.34 million and the growth rate so
far is 67.04% [2]. As per the population estimates,
Hyderabad is likely to become a mega city with about 7.5
million population by 2011. This rising population density
will continue to have an impact on the quality and quantity
of local water resources.
Fresh water being one of the basic necessities for
sustenance of life, the human race through the ages has
striven to locate and develop it. Water, a vital source of
life in its natural state is free from pollution but when man
tampers the water body it loses its natural condition
s.
Ground water has become an essential resource over the
past few decades due to the increase in its usage for
drinking, irrigation and industrial uses etc. The quality of
ground water is equally important as that of quantity.
Remote sensing and GIS are effective tools for water
quality mapping and land cover mapping essential for
monitoring, modeling and environmental change detection
Int. J. Environ. Res. Public Health
2007
,
4(1)
46
[3]. GIS can be a powerful tool for developing solutions
for water resources problems for assessing water quality,
deter
mining water availability, preventing flooding,
understanding the natural environment, and managing
water resources on a local or regional scale [4]. Keeping
this in view, we have Integrated Remote Sensing, GIS and
field studies for the evaluation of the impacts of land use
changes on the ground water quality of zone-V under
MCH. There is an urgent need to have a first hand
asesment of the prospective ground water quality in MCH,
especially in view of the latest proposal in January 2007 to
implement policy of greater Hyderabad, The current
asessment of water quality in MCH Zone - V is an
uptodate beginning in that direction.
Study Area
The total area of Municipal Corporation of Hyderabad
(MCH) is 179 Km
2
and divided into 11 planning zones
wherein the present study area (Zone-V) consists of 31.68
Km
2
out of the total MCH area and is situated in between
78
0
25’22” East Longitude and 17
0
22’48” North Latitude.
The climate is fairly equitable with a daily mean maximum
temperature varying from a minimum of 11.6
0
C during the
month of December to a maximum of 40.56
0
C in April.
Hyderabad gets its rainfall mainly from southwest
monsoon with the total annual average rainfall of about
73.55 cm. It is located at an altitude of 570m above mean
sea level.
Methodolog
y
Data Used
Different data products required for the study include
the 56K/7 and 56K/11 toposheets which are obtained from
Survey of India (1:50,000) and fused data of IRS 1D
PAN and LISS
-
III satellite imagery of path 100 and row 60
from National Remote Sensing Agency (NRSA),
Hyderabad.
Database Creation
IRS
-ID PAN and LISS-III satellite imageries are
georeferenced using the ground control points with SOI
toposheets as a reference and further merged to obtain a
fused, high resolution (5.8m of PAN) and colored (R,G,B
bands of LISS-III) output in EASI/PACE v6.3 Image
processing software. The study area is then delineated from
the fused data based on the latitude and longitude values
and a final hard copy output prepared which is further
interpreted visually for the generation of thematic maps.
These thematic maps (Raster data) are converted to vector
format by scanning using an A0-Flatbed Deskjet scanner
and digitized in AUTOCAD 2000. The map is further
edited in ARC/INFO v3.5.1 and final hardcopy output is
prepared using ARC/VIEW v3.1 GIS software. The
methodology adopted for creation of database is given in
Fig. 1.
Figure 1: Flow chart showing the methodology adopted
for the generation of database
Spatial database
Thematic maps like base map and drainage network
maps are prepared from the SOI toposheets on 1:50,000 scale
using AutoCAD and Arc/Info GIS software to obtain a
baseline data. All the maps are scanned and digitized to
generate a digital output. Land use/Land cover map of the
study area was prepared using visual interpretation technique
from the fused satellite imagery (IRS
-
ID PAN + LISS
-
III) and
SOI toposheets along with ground truth analysis.
Attribute database
Fieldwork was conducted and groundwater samples
were collected from predetermined locations based on the
land use change and drainage network maps of the study
area. Map showing sampling points overlaid on sa
tellite
imagery as shown in Fig 2. The water samples were then
analyzed for various physico-chemical parameters adopting
stand
ard protocols [5]. The water quality data thus obtained
forms the attribute database for the present study (Table 1).
Int. J. Environ. Res. Public Health
2007
,
4(1)
47
Table 1
: Ground water quality of Zone
V
All units except pH and Water quality index are in mg/l
Sample
No,
Sample
Location
pH
TDS
Cl
-
SO
4
-2
F
-
Alkalinity
NO
3
-
Hardness
Na
+
Water
Quality
Index
Water Quality
Rating
1
Banjara hills
7.82
520
107
39
1.41
119
160
310
56
90.5
Very Poor
2
VN bus stop
B.Hills
7.94
280
42
21
0.683
110
6.2
200
27
46.6
Good
3
NVT nagar
B.Hills
7.7
775
199
65
1.96
250
2
300
150
104.4
UFD
4
Rd no 10
B.Hills
7.03
795
121
42
1.84
190
290
500
56
110
UFD
5
Rd no 4B.Hills
6.89
736
114
37
1.18
290
116
460
63
48.5
Good
6
Yellareddyguda
7.15
1010
149
44
3.12
215
535
460
190
133.2
UFD
7
Yousufguda
6.89
630
71
26
1.62
200
88
380
44
77.9
Very Poor
8
Erragada
(NGAC)
6.93
690
140
38
0.506
250
148
390
61
116
UFD
9
Erragada
7.61
1350
178
64
2.73
400
320
500
110
58.4
Poor
10
Erragada
7.1
540
114
19
0.818
180
52
350
30
46.4
Good
11
Humayunagar
7.51
745
92
57
0.67
350
216
400
81
51.1
Poor
12
Mehadipatnam
7.46
690
92
34
0.98
275
120
400
53
24.1
Excellent
13
Mehadipatnam
7.38
340
64
18
0.77
120
52
200
29
31.7
Good
14
Hakimpet
7.78
862
213
65
0.44
230
360
560
71
86.5
Very Poor
15
Film nagar
7.56
520
85
43
1.6
220
44
300
49
114
UFD
16
Rd no 10 Film
nagar
7.54
845
142
67
1.4
310
84
47
0
67
104
UFD
17
Jubilee
Hills(CP)
7.51
800
178
65
2.9
225
160
460
78
43.1
Good
18
Banjara hills(2)
7.68
350
50
18
1.9
140
52
200
67
27.1
Good
19
L.V.Prasad eye
hospital
7.98
325
50
17
2.4
150
160
190
28
31.8
Good
20
Tolichowki
7.41
805
49
34
0.59
230
140
240
26
26.0
Good
21
Sheikpet
6.82
500
92
50
0.36
470
500
970
122
55.5
Poor
22
Kanch colony
7.2
685
128
35
0.40
250
344
630
50
113
UFD
23
Madhapur
(near)
6.75
615
142
54
0.34
230
64
410
56
56.5
Poor
24
Moti nagar
7.09
870
149
92
0.85
180
500
380
58
1
02.3
UFD
25
Kamlapuri
7.23
940
107
92
1.2
150
240
550
73
53.9
Poor
Int. J. Environ. Res. Public Health
2007
,
4(1)
48
Figure 2
:
Sampling points overlaid o
n
s
atellite
i
magery
Integration of Spatial and Attribute Database
The spatial and the attribute database generated are
integrated for the generation of spatial distribution maps of
selected water quality parameters like pH, alkalinity,
chlorides, sulphates, nitrates, TDS, total hardness, fluorides
and Water Quality Index (WQI) and overlaid on satellite
imagery. The water quality data (attribute) is linked to the
sampling location (spatial) in ARC/INFO and maps
showing spatial distribution are prepared to easily identify
the variation in concentrations of the above parameters in
the ground water at various locations of the study area
using curve fitting technique of ARC/VIEW GIS software.
Spatial
Modeling
and Surface Interpolation through IDW
GIS can be a powerful tool for developing solutions
for water resources problems for assessing water quality,
determining water availability, preventing flooding,
understanding the natural environment, and managing
water resources on a local or regional scale [6]. Though
there are a number of spatial
modeling
techniques available
with respect to application in GIS, spatial interpolation
technique through Inverse Distance Weighted (IDW)
approach has been used in the present study to delineate
the locational distribution of water pollutants or
constituents. This method uses a defined or selected set of
samp
le points for estimating the output grid cell value. It
determines the cell values using a linearly weighted
combination of a set of sample points and controls the
significance of known points upon the interpolated values
based upon their distance from the output point thereby
generating a surface grid as well as thematic isolines.
Important water quality indicating parameters and their
distribution patterns were studied in Hyderabad metropolis
also with the help of cartographic techniques. Thus, GIS
enable
s us to look into the cause and effect relationship
with visual presentation [7].
Estimation of Water Quality Index (WQI)
Water Quality Index (WQI) is a very useful and
efficient method for assessing the quality of water [8].
Water Quality Index (WQI) is a very useful tool for
communicating the information on overall quality of water
[9
,
10]. To determine the suitability of the groundwater for
drinking purposes, WQI is computed adopting the
following formula [11].
WQI = Antilog [
W
n
n=1
log
10
q
n
]
(1)
w
here,
W, Weightage factor (W) is computed using the
following equation, (Table 2)
W
n
= K / S
n
(2)
and K, Proportionality constant is derived from,
K = [1 /
(
n
n=1
1/S
i
)]
(3)
S
n
and S
i
are the WHO / ICMR standard values of the
water quality parameter.
Quality rating (q) is calculated using the formula,
Int. J. Environ. Res. Public Health
2007
,
4(1)
49
Table 2: Water q
uality
parameters, their ICMR/WHO
s
tandards,
and a
ssi
gned unit w
eights
Parameter
Standard (Sn & S
i
)
Weightage (Wn)
PH
8.5
0.1428
Chloride
250
0.0048
Sulfate
250
0.0048
Alkalinity
120
0.0101
Nitrates
50
0.0242
Total hardness
300
0.0040
TDS
1000
0.0012
Sodium
200
0.0060
Fluoride
1.5
0.809
q
ni
= {[(V
actual
V
ideal
) / (V
standard
V
ideal
)] * 100}
(4)
w
here,
q
ni
= Quality rating of i
th
parameter for a total of n
water quality parameters
V
actual
= Value of the water quality parameter obtained
from laboratory analysis
V
ideal
= Value of that water quality parameter can be
ob
tained from the standard tables.
V
ideal
for pH = 7 and for other parameters it is
equalent to zero.
V
standard
= WHO / ICMR standard of the water quality
parameter
Based on the above WQI values, the ground water
quality is rated as excellent, good, poor, very poor and
unfit for human consumption (Table 3).
Table 3:
Water Quality Index Categories
Results and Discussion
Land Use/ Land
Cover Distribution
An analysis of the nature and rate of land use change
and its associated impact on groundwater quality is
essential for a proper understanding of the present
environmental problems [12]. In the present study area,
built
-up land includes dense, medium and sparse
residential areas, which comprises of 18.88 km
2
of the total
study area out of which 9.74km
2
is of dense residential and
4.73km
2
medium residential and 4.57km
2
sparse residential
areas as shown in Fig 3 and Fig 4.
Figure 3
:
Land use / Land cover Map
Agricultural land occupies 1.18km
2
. The major water
bodies that are present in this zone are Durgam cheruvu,
Yousufguda cheruvu, Hakimpet cheruvu and Sheikpet
cheruvu. Among these Yousufguda cheruvu is conve
rted in to
a solid waste dumping site and Durgam cheruvu is developed
for tourist recreational purpose. Land without scrub, the most
common category, which transforms to built-up land in the
urban areas comprises of 1.1km
2
of total area. The study area
com
prises of 4.8km
2
of the area under barren sheet area.
Figure 4:
Land use / land cover distribution in the study area
Groundwater Quality Variation
The pH of the water samples in the study area ranged
in between 6.0 - 8.0. High alkaline water with
concentrations ranging above 300mg/l was observed at
Yellareddyguda and Erragadda, which is due to decay of
organic matter, weathering of rocks and minerals. The
concentration of chloride in most of the areas is within the
permissible limits except at Banjara Hills N.V.T. Nagar,
which has 260mg/l of chloride. The highest concentration
of total dissolved solids was found to be 1350 mg/l at
Erragadda and at Yellareddyguda with 1010mg/l which is
due to the presence of dense residential area and due to
BSA land form. Solid waste dumping site situated at
Yousufguda and locations of industries at Sanath Nagar
have
an impact on the groundwater of these areas. A high
concentration of TDS was also observed at Southern
Jubilee Hills (1245mg/l) and Sheikpet (1120mg/l), which
is attributed to agricultural practices (Fig. 5). TDS in
Water quality index
Description
0-25
Excellent
26
-
50
Good
51
-
75
Poor
76
-
100
Very poor
>100
Unfit for drinking (UFD)
Int. J. Environ. Res. Public Health
2007
,
4(1)
50
ground water also originate from natural sources, sewage,
urban run
-
off and industrial wastes [13].
Figure 5
: Spatial Distribution of Total Dissolved Solids
High concentration of total hardness is found in
Shaikpet (970mg/l) and Hakimpet (630mg/l) where the
land use pattern is completely BSA and some of the land is
under agricultural practice. The other places where high
concentrations of total hardness were found are in
Yousufguda and its surroundings, which have been
converted into solid waste dumping sites. The other areas
nearby showed a moderate range of hardness values, which
is due to common contamination due to dense residential
human activities and weathering and leaching of salts into
the ground water. Interestingly the highest concentration of
nitrate is around 400 mg/l in the areas of Yousufguda,
Kamalapuri (Jubilee Hills) and Vinayak Nagar. Nitrate
formed by the biochemical activities of microorganisms or
added in chemically synthesized forms to lithosphere and
biosphere enters hydrosphere with relative ease, all these
environmental components are dynamically interconnected
[14]. High nitrate concentrations indicate sources of past or
present pollution [15]. The direction of the slope from
Yousufguda cheruvu towards Vinayak Nagar could be one
of the reasons where the high contents of wastes were
dumped and also due to residential areas. Sheikpet (500)
also showed high concentration owing to the agricultural
practices in this pocket that can leach and enter into the
ground water. The other places like Jubilee Hills, Banjara
Hills, Hakimpet and a part of Punjagutta showed a range
between 200
-
400 mg/l.
Figure 6
:
Spatial Distribution of Fluoride
Fluoride, the most commonly occurring form of
fluorine, is the natural contaminant of water. Ground water
usually contains fluoride dissolved by geological formation
[16]. The concentration of fluoride was observed to be 3.15
mg/l at Yellareddyguda and the concentration above
permissib
le limit was seen near Jubilee Hills, Sheikpet,
Erragadda and Sanathnagar (Fig. 6).
Excessive consumption of fluorine (>2mg/l) causes a
dental disease known as fluorosis while regular
consumption in excess may give rise to bone fluorosis and
other skeletal fluorosis. On the other hand, fluorides
<2mg/l causes dental cavities in children [17]. This could
be due to the effect of industrial area and weathering of
fluorine bearing minerals like fluoride and apatite. The
other parameters like sodium, potassium and phosphorous
were found to be within the permissible limits.
Correlation
of
Water Quality
with
Land Use/ Land Cover
Water Quality index is calculated to determine the
suitability of water for drinking purpose [18 & 19]. Water
quality index values revealed that the ground water at six
locations of the study area was of good quality with the
WQI ranging in between 0-50 and therefore can be used
for human consumption. Eight samples were of poor
quality with WQI ranging in between 50-75 and six
samples were of very poor quality and cannot be used for
domestic purposes. The WQI was found to be above 100 in
areas like NVT Nagar and Road No.10 of Banjara Hills,
Yellaredduguda, Erragadda and Motinagar and therefore
cannot be used for human consumption. The WQI map is
shown in Fig 7.
Figure 7:
Water Quality Index Map
Since major portion of the groundwater samples were
collected from residential category, the major land use
class of the study area, the impact of different residential
classes on water quality is discussed. The correlation of
land use with water quality as depicted in Table 4 and Fig.
8 indicate that the extent of water quality deterioration has
a linear correlation with the residential land use sub-
divided into dense, medium and sparse based on density of
population.
Int. J. Environ. Res. Public Health
2007
,
4(1)
51
Table 4:
Correlation of Water Quality with LU/LC
Of the nine samples collected and analyzed in dense
residential area, four samples (44.44%) were rated as unfit,
two (22.22%) as very poor, and the remaining three
samples (33.33%) as poor. Four samples were collected
from medium residential area, which exhibited excellent
(25%), good (25%), very poor (25%) and unfit (25%)
quality. Of the four samples collected in sparse residential
land use, two samples (50%) exhibited good water quality
and the remaining two samples exhibited poor (25%) and
unfit (25%) quality. It is observed that the number of
samples rated as poor, very poor and unfit in dense
residential areas were high when compared to the medium
and sparse residential areas. The samples exhibiting good
water quality were comparatively greater in sparse
residential areas than medium (25%) residential land use
class. There were no samples exhibiting good water quality
in dense residential class. Five samples collected from
BSA land use in areas like Banjara Hills, M
ehdipatnam
and Erragadda exhibited good (50%), poor (25%) and
unfit
(25%) quality. From the results obtained it is clear that the
residential land use with varying population densities play
a major role on the ground water quality of the area.
Figure 8
:
Correlation of land u
se /
l
and
c
over with
water
q
uality
C
onclusion
Based on the correlation between water quality and
the existing land use type, the problematic areas of the
zone were identified. The results indicate that cer
tain
parameters such as nitrates, TDS, chlorides and fluorides
were beyond the permissible limits in areas, which are
densely residential and industrial. The overall view of the
water quality index of the present study zone showed a
satisfactory result with most of the area having a WQI of <
50 in areas nearby VN bus stop and Road No.4 of Banjara
hills, Jubilee Hills, Mehdipatnam where the ground water
quality was good. But few areas like Yousufguda,
Erragadda, Sheikpet and Hakimpet had a higher WQI
value indicating the deteriorated water quality. Therefore
comprehensive sewerage system for safe disposal of
wastes should be developed to safeguard ground water
quality in most of the residential areas.
The analysis of the results drawn at various stages of
the
work revealed that integration of Remote Sensing and
GIS are effective tools for the preparation of various digital
thematic layers and maps showing spatial distribution of
various water quality parameters. Overlaying spatial
distribution water quality maps on Satellite imagery is a
very authenticate concept to identify the water quality
problems and to correlate them with the land use to
interpret the reasons for deterioration of environmental
quality.
Monitoring of pollution patterns and its trends with
respect to urbanization is an important task for achieving
sustainable management of groundwater. An integrated
Remote sensing and GIS study proves to be an essential
tool to evaluate and quantify the impacts of land use / land
cover on ground water quality. Spatial distribution maps of
various pollution parameters are used to demarcate the
locational distribution of water pollutants in a
comprehensive manner and help in suggesting groundwater
pollution control and remedial measures in a holistic way.
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erences
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Gyananath, G.; Islam, S.R.; Shewdikar, S.V.
Assessment of Environmental Parameter on ground
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, 21, 289
-
294.
2.
Directorate of Census Operations. District Census
Handbook of Hyderabad, 1991, Andhra Pradesh,
Census of India.
3.
Skidmore, A.K.; Witske Bijer; Karin Schmidt; Lalit
Kumar, K. Use of Remote sensing and GIS for
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.
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, 3
(4), 302
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Ferry Ledi Tjandra; Akihiko Kondhoh; Mohammed
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Hydrology Using GIS. Proceedings of Asia Pacific
Association of Hydrology and Water Resources
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March 2003
, 13
-
15, Kyoto, Japan.
WQI
LU/LC
Dense
Residential
Medium
Residential
Sparse
Residential
Land
without
scrub
Parks
BSA
Excellent
0 1 0 0 0 0
Good
0 1 2 1 2 2
Poor
3 0 1 0 0 1
Very
Poor
2 1 0 0 0 0
Unfit for
Drinking
4 1 1 0 0 1
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... WQI is a dependable and effective technique for evaluating, interpreting, and reporting water quality information (Asadi et al. 2007). In line with Vasanthavigar et al. (2010), suitable ranks were allocated to the physical and chemical parameters based on their perceived contamination potential (Table 3), whereas the relative weight Wi for every parameter was calculated using the equation provided by Krishna et al. (2015). ...
Article
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Sustainable management of groundwater resources in geological transition zones (GTZ) is essential due to their complex geology, increasing population, industrialization, and climate change. Groundwater quality monitoring and assessment represent a viable panacea to this problem. Therefore, there is a great need to investigate groundwater resources in terms of their chemistry and pollution to ascertain their quality and implement robust pollution abatement strategies. This study focused on the characterization of groundwater in a typical geological transition zone in northeastern Nigeria. Eighty-seven (87) groundwater samples were collected from dug wells and boreholes during the 2017 dry season. pH, conductivity, and total dissolved solids (TDS) were measured in situ using a multiparameter probe, while major cations and anions were measured using atomic absorption spectrometry and ion chromatography, respectively. Data were analyzed using descriptive statistics, principal component analysis (PCA), water quality index, and standard hydrochemical plots. TDS ranged between 95 and 1154 mg L⁻¹ in basement terrains and between 49 and 1105 in sedimentary areas. pH ranged between 6.8 and 7.7 mg L⁻¹ in basement terrains and between 5.0 and 6.5 in sedimentary areas, suggesting a moderately acidic to alkaline low mineralized groundwater. Calcium (2.6–128.0 mg L⁻¹) was the dominant cation in the basement areas, suggesting silicate weathering/dissolution, while sodium (1.9–106.0 mg L⁻¹) dominated the sedimentary zones due to base exchange reactions. The PCA analysis suggests that mineral dissolution (mostly silicate weathering) controls the hydrochemistry of the basement aquifers, while ion exchange and albite weathering, with some influence of anthropogenic factor, control the sedimentary aquifers. The water quality index revealed that the basement setting was predominated by poor to unsuitable groundwater, while the sedimentary terrain was characterized by potable groundwater. The dominant hydrochemical facie in the basement areas was Ca²⁺–(Mg²⁺)–HCO3⁻ characteristic of recharge meteoric water. The Na⁺– (K⁺)–HCO3⁻ facie characterized the sedimentary zones, indicative of cation exchange reactions, while the mixed water facie typifies the geological contact zones. The shallow nature of the basement groundwaters makes them more susceptible to geogenic and anthropogenic pollution compared to the sandstone aquifers. However, the basement aquifers have better irrigation indices (Kelly ratio and soluble sodium percent) as compared to the sandstone aquifers, which exhibit poor Kelly ratios (< 1) and soluble sodium percent (> 50) ratings. Results from the study clearly highlight the poor-unsuitable groundwater quality in parts of the studied GTZ and can be very instrumental to the policymakers in implementing sustainable water treatment strategies and cleaner production technologies in GTZ to forestall the incidence of water-related diseases. Graphical abstract
... Similarly, different weights were assigned to each geosystem parameter's unique sub-variable. The GIS layers on lineament density, geomorphology, slope, and drainage density were thoroughly examined throughout this procedure, and weightages were given to each sub-variable (Butler et al. 2002;Skubon 2005;Asadi et al. 2007;Yammani 2007). The GIS layers with final weightages for six geosystem characteristics were also added, and the research region was finally split into various groundwater potential zones relying on the additional weights. ...
Chapter
Hydrological modelling is an essential tool, in this century, for effective planning and management of water resources. Ground observations serve as the backbone of hydrological models in which inadequate field data obtained from a watershed have become a challenge to the research community for proper management of the watershed. Despite several progresses in the models, the heterogeneity of watersheds limits the measurement of hydrological parameters, resulting in uncertainty and affecting the applicability and confidence of the models. In this chapter, a detailed survey has been carried out to address the development in the hydrological models over the decades and the reliability of different models. Summarising the calibration and uncertainties of the hydrological models, adopting datasets obtained through space technology is highly recommended, and new approaches need to be developed with the integration of information technology, statistics, and space inputs to overcome the limitations.KeywordsHydrological modelsCalibrationUncertaintyUngauged stationsHydrological advances
... Similarly, different weights were assigned to each geosystem parameter's unique sub-variable. The GIS layers on lineament density, geomorphology, slope, and drainage density were thoroughly examined throughout this procedure, and weightages were given to each sub-variable (Butler et al. 2002;Skubon 2005;Asadi et al. 2007;Yammani 2007). The GIS layers with final weightages for six geosystem characteristics were also added, and the research region was finally split into various groundwater potential zones relying on the additional weights. ...
Chapter
The hydrological cycle (HyC) is affected by several factors, but climate and land use/land cover (LU/LC) are the most influential ones. This chapter has tried to show some satellite-based land use/land cover feature extraction methods that are useful for climate studies. Several literature works have claimed that climate is more influential than land use. Land use has an impact on several components of the hydrological cycle. This chapter provides a perspective on climate change, urbanization, land degradation, and other disasters and also on the usage of land use/land cover features in the study of the hydrological cycle. The anomaly in solar radiation due to greenhouse gas (GHG) emissions and its impact on climatic factors and the hydrological cycle with its implication in food production is briefed. Some of the global measurement missions for precipitation and land surface temperature (LST) are also discussed. To investigate the influence of land use/land cover on the hydrological cycle, identification of a particular class or all land use classes of a particular region may be essential. This chapter uses the synoptic view of satellite data and attempts to exercise certain indices to identify certain classes and classification algorithms to classify land use classes. This work has also experimented with certain classification algorithms to delineate some land use/land cover features and has also pointed out some limitations in the application of indices. This chapter discusses the factors that influence the hydrological cycle and highlights the usage of satellite data in regional studies.KeywordsHydrological cycleLand use/land coverClimateUrbanization and greenhouse gases
... In India, fluoride contamination in drinking water (>1.5 mg L − 1 ) is affecting 66 million individuals (Brindha et al., 2011;Dey et al., 2012;Adimalla and Li, 2019;Adimalla et al., 2018b;Chidambaram et al., 2013). Table S1 summarizes fluoride levels in groundwater and soil systems across India (Adimalla and Venkatayogi, 2017;Arif et al., 2012;Arumugam and Elangovan, 2009;Arveti et al., 2011;Asadi et al., 2007;Avtar et al., 2013;Beg et al., 2011;Bishnoi and Arora, 2007;Brindha et al., 2011;Chidambaram et al., 2013;Dar et al., 2011;Das et al., 2003;Dey et al., 2012;Dhiman and Keshari, 2006;Dutta et al., 2006;Gupta et al., 2005Gupta et al., , 2006Hussain et al., 2012;Karthikeyan et al., 2010;Kaushik et al., 2004;Kumar et al., 2007;Kundu et al., 2001;Kundu and Mandal, 2009;Madhnure et al., 2007;Magesh et al., 2013;Mamatha and Rao, 2010;Mondal et al., 2014;Narsimha and Sudarshan, 2017a;Raj and Shaji, 2017;Raju et al., 2009Raju et al., , 2012Ramakrishnaiah et al., 2009;Ramanaiah et al., 2006;Rao, 2009;Rao and Devadas, 2003;Ravindra and Garg, 2006;Ray et al., 2000;Reddy et al., 2010;Salve et al., 2008;Sankararamakrishnan et al., 2008;Shaji et al., 2007;Sharma et al., 2011;Singaraja et al., 2013;Singh et al., 2011;Singh and Mukherjee, 2015;Srinivasamoorthy et al., 2011Srinivasamoorthy et al., , 2012Srivastava and Ramanathan, 2008;Subba, 2003;Sujatha, 2003;Suthar et al., 2008;Vikas et al., 2009Vikas et al., , 2013Yadav et al., 2009). Ahada and Suthar (2019) reported up to 5.07 mg L − 1 concentration of fluoride in groundwater and a high risk of non-carcinogenesis health issues in children in the Punjab regions of India. ...
Article
Fluoride () is one of the essential elements found in soil and water released from geogenic sources and several anthropogenic activities. Fluoride causes fluorosis, dental and skeletal growth problems, teeth mottling, and neurological damage due to prolonged consumption, affecting millions worldwide. Adsorption is an extensively implemented technique in water and wastewater treatment for fluoride, with significant potential due to efficiency, cost-effectiveness, ease of operation, and reusability. This review highlights the current state of knowledge for fluoride adsorption using biochar-based materials and the limitations of biochar for fluoride-contaminated groundwater and industrial wastewater treatment. Biochar materials have shown significant adsorption capacities for fluoride under the influence of low pH, biochar dose, initial concentration, temperature, and co-existing ions. Modified biochar possesses various functional groups (–OH, –Cdouble bondC, –C–O, –CONH, –C–OH, X–OH), in which enhanced hydroxyl (–OH) groups onto the surface plays a significant role in fluoride adsorption via electrostatic attraction and ion exchange. Regeneration and reusability of biochar sorbents need to be performed to a greater extent to improve removal efficiency and reusability in field conditions. Furthermore, the present investigation identifies the limitations of biochar materials in treating fluoride-contaminated drinking groundwater and industrial effluents. Since fluoride removal using biochar-based materials at an industrial scale for understanding the practical feasibility is yet to be documented, thus the review work recommended the potential feasibility of biochar-based materials in column studies that can be worth research on fluoride remediation in the future.
... The quality and quantity of groundwater are equally important. (Asadi et al., 2007). The groundwater quality readily relies on hydrological, physical, chemical and biological factors. ...
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This paper aimed to analyze the groundwater quality and its suitability for drinking in northeastern Karnataka, India. For this study, groundwater samples were collected from randomly selected sixty-five bore well. The standard analysis techniques used to analyze samples for physicochemical parameters like pH, EC, TDS, total alkalinity, total hardness, Ca 2+ , Mg 2+ , SO 4 2-, Cl-, F-, NO 3-, PO 4 2-, Na + and K +. The suitability of groundwater for drinking is assessed based on the concentration of physicochemical parameters and water quality index. Groundwater quality index (GWQI) exhibited that about 61.53% of the samples belonged to the excellent-good category, and 38.47% belonged to the poor category for drinking purposes. The spatial variability map for all parameters prepared using ArcGIS ver. Xx.xxx software. Gibbs ratio confirmed that mineral content in the groundwater is from rock origin.
... Groundwater always flows more from the hydraulic head to the less hydraulic head. Therefore, if a part of the aquifer is contaminated, information about the flow direction helps a lot in the contamination process [ASADI et al. 2007;NAS, BERKTAY 2010]. In this regard, using GIS software, knowing that the flow lines perpendicular to the lines are potential, the direction of groundwater movement in the aquifer was obtained [JHA et al. 2020]. ...
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Full-text available
Surface and groundwater resources are two important sources in meeting agricultural, urban, and industrial needs. Random supply of surface water resources has prevented these resources from being a reliable source of water supply at all times. Therefore, groundwater acts as insurance in case of water shortage, and maintaining the quality of these resources is very important. On the other hand, studying vulnerability and identifying areas prone to aquifer pollution seems necessary for the development and optimal management of these valuable resources. Identifying the vulnerabilities of the aquifer areas to pollution will lead to a greater focus on preserving those areas. Therefore, groundwater quality assessment was performed in this study using the groundwater quality index (GQI), and groundwater vulnerability to pollution was assessed using the DRASTIC index. GQI is developed based on the values of six quality parameters (Na + , Mg 2+ , Ca 2+ , SO 4 2-, Cl-, and TDS). The DRASTIC index is developed based on the values of seven parameters (depth to the water table, net recharge, aquifer media, soil media, topography, impact of vadose zone, hydraulic conductivity). The zoning of both indexes has been done using geographic information system (GIS) software. The results show that the GQI of the region was about 93, and its DRASTIC index was about 86. Therefore, the quality of aquifer groundwater is excellent, and its vulnerability to pollution is low.
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Groundwater is an essential factor in the aquifer recharging and management for the drinking, irrigation, and economy. Currently unpredictable rainfall due to climate change and pollution on the earth's surface, these problems directly affect the demand for groundwater in the more affected area of the globe. In this study, we have selected two methods such as Analytical Hierarchy Process (AHP) and Multiple Influence Factors (MIF), which would be applied for the groundwater potential zone maps. We have been prepared the nine thematic layers such as LULC, geomorphology, soil, drainage density, slope, lineament density, elevation, groundwater level, and geology maps using remote sensing and GIS techniques. These layers are integrated in the Arc GIS software with the help of AHP and MIF methods. We were identified into four classes, i.e., Poor, Moderate, Good, and Very Good based on AHP and MF methods. The groundwater potentials zones area is 241.50 (ha.). Poor, 285.64 (ha.) moderate, 408.31 (ha.) good, and 92.75 (ha.) very good using AHP method. However, the other groundwater potential zones area is shown as 351.29 (ha.) poor, 511.18 (ha.), moderate, 123.95 (ha.) good, and 41.78 (ha.) very good using MIF method. Both the groundwater potential zone maps have been validated with the water yield data using Arc GIS software 10.8. The ROC and AUC models' results are found to be 0.80 (good) and 0.93 (excellent) using MIF and AHP methods, respectively. The main purpose of this study is to identify the best method for demarcated the groundwater potential zone map, which method is better for preparation of watershed planning, and groundwater development policy, specific in basaltic rock and drought condition. The present study's framework 84work and results will be valuable to improving the efficiency of irrigation, conservation of rain water and maintain the ecosystem in India.
Chapter
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This study has been conducted in Adigrat Town and its surrounding area, Ethiopia, to identify suitable groundwater potential zones and methods of proper groundwater management and find suitable groundwater potential zones using recent scientific approaches to remote sensing and GIS techniques. To identify the groundwater potential of the study area, the parameters of geology, slope, drainage, geomorphic units, lineament density, and land use/land cover were generated and integrated with an inverse distance weighted (IDW) model based on GIS data. For each of these parameters, appropriate weightage factors were assigned. Weightage factors were assigned to the various geomorphic units based on their ability to store groundwater. This procedure was repeated for each of the remaining layers, and the resulting layers were reclassified. After that, the reclassified layers were integrated to demarcate zones as very good, good, moderate, low, and poor. The analysis identified groundwater potential zones with very good, good, moderate, low, and poor prospects covering 7.19 km2, 55.13 km2, 28.03 km2, 29 km2, and 28.45 km2, respectively. This groundwater potential data could be used to effectively identify suitable locations for potable water extraction for rural populations.KeywordsGroundwater potential zonesGISRemote sensingIDWThematic map
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A systematic study of the water quality index (WQI) for 12 selected water quality parameters of 10 ground water samples around a phosphatic fertilizer plant at Paradip has been investigated over a period of one year from October 1995 to September 1996. The result of all the findings are discussed in details which reflect the quality of ground water.
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