Relationship Among the Physico-Chemical Parameters of Soil and Water in Different Wetland Ecosystems

Abstract

The quality of life in water bodies depends on their physico-chemical properties and biodiversity. These physico-chemical properties are
being disturbed by continuous addition of industrial, municipal and agricultural wastes which make them unfit for different organisms.
This study describes the physico-chemical factors in soil and water of all sampled wetlands and the relationship among them in wetland
ecosystem. All these analysis were done by using analytical techniques as described by standard methods for examination of water and
wastewater. Physico-chemical parameters of water and soil also interlinked and correlated among each other. Sometimes these parameters
work as a cycle to maintain the equilibrium in the ecosystem. Higher level of research work is needed to control the source of pollution to
wetlands. By controlling the physico-chemical parameters of habitat, the diversity, density and richness of various wetland dependent
species can be controlled in wetland ecosystem.

Full text

AJ CSIAN OURNAL OF HEMISTRY
AJ CSIAN OURNAL OF HEMISTRY
https://doi.org/10.14233/ajchem.2020.22616
INTRODUCTION
Water and soil are the two most important components of
ecosystem. With the development of the society, the pollution is
also increasing in soil and water from various sources. The quality
of life in water bodies depends on their physico-chemical prop-
erties and biodiversity [1]. Various physico-chemical properties
have different sources as well as different nature. The presence
of chloride found due to deposition of salt by natural or from
any effluent. Nitrate is the most highly oxidized form of nitrogen
compounds commonly present in natural waters. Fluoride ions
have dual significant in water supplies for which it should be
within the limits. Sulphate ions usually found in natural waters
due to its soluble nature in water. Most of them originate from
the oxidation of sulphate ores. Phosphorous occurs in various
form in natural water and wastewater. Conductivity is the capacity
of water to carry an electric charge by ionized substances in the
water. These inorganic ionized substances contribute to conduc-
tance. The capacity of water for precipitating soap is commonly
Relationship Among the Physico-Chemical Parameters of
Soil and Water in Different Wetland Ecosystems
BIBHU PRASAD PANDA1, , MANAS BARIK1, , BISWAJITA MAHAPATRA1, ,
SIBA PRASAD PARIDA2, , ADITYA KISHORE DASH3 and ABANTI PRADHAN3,*,
1Environmental Sciences, Department of Chemistry, ITER, Siksha 'O' Anusandhan Deemed to be University, Bhubaneswar-751030, India
2Department of Zoology, School of Applied Sciences, Centurion University of Technology and Management, Bhubaneswar-752050, India
3Department of Chemistry & BBRC, ITER, Siksha 'O' Anusandhan Deemed to be University, Bhubaneswar-751030, India
*Corresponding author: E-mail: abantisahu@gmail.com
Received: 30 December 2019; Accepted: 30 March 2020; Published online: 27 June 2020; AJC-19932
The quality of life in water bodies depends on their physico-chemical properties and biodiversity. These physico-chemical properties are
being disturbed by continuous addition of industrial, municipal and agricultural wastes which make them unfit for different organisms.
This study describes the physico-chemical factors in soil and water of all sampled wetlands and the relationship among them in wetland
ecosystem. All these analysis were done by using analytical techniques as described by standard methods for examination of water and
wastewater. Physico-chemical parameters of water and soil also interlinked and correlated among each other. Sometimes these parameters
work as a cycle to maintain the equilibrium in the ecosystem. Higher level of research work is needed to control the source of pollution to
wetlands. By controlling the physico-chemical parameters of habitat, the diversity, density and richness of various wetland dependent
species can be controlled in wetland ecosystem.
Keywords: Physico-chemical parameters, Soil, Water, Wetland ecosystem.
Asian Journal of Chemistry; Vol. 32, No. 7 (2020), 1681-1690
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creation. You must give appropriate credit, provide a link to the license, and indicate if changes were made.
known as hardness of water. The physical, chemical and biol-
ogical activities in water body decide the dissolved oxygen level
in water and wastewater [2].
These physico-chemical properties are being disturbed
by continuous addition of industrial, municipal and agricultural
wastes which make them unfit for different organisms [3-8].
Wetlands and water-bodies provide habitat for micro to macro
organisms like invertebrate, fish, bird and many more [9]. Many
researchers studied and described the stress on fish growth
and reproduction due to several physico-chemical and biological
factors [10]. The positive correlation among the chemical,
physical and biological properties of soil was well known. The
physical and chemical composition of soil is influenced by
the deposition of different mineral, organic matter and pollutants
from different sources [11], which ultimately affects water quality.
Many organisms are considered as ecological indicators but
birds are most sensitive health indicators of ecological conditions
of an ecosystem [12].

Wetlands are used by birds for various purposes like breed-
ing, nesting, roosting, foraging and social interaction with other
organisms. By occupying several trophic levels in nutrient cycle
of wetland, aquatic birds become an important component of
wetland ecosystem. Though food chain is the main link between
wetland quality and ecosystem health, water bird activities
are the key indicator towards it [13].
Most of the birds feed on aquatic organisms as well as on
soil macro invertebrate and water dependent vertebrates. So
the physico-chemical parameters of water as well as soil of
wetland habitat affect the distribution and abundance of water
dependent organisms [14]. These changes in physico-chemical
parameters continue in corresponding food web upto secon-
dary production levels [7]. These interactions among water,
soil and biodiversity describes the complexity of wetland eco-
systems [15]. This study describes the physico-chemical factors
of all sampled water-bodies and the relation among physico-
chemical parameters of different wetland habitats with different
anthropogenic pressure.
EXPERIMENTAL
This study was performed in different environmental seg-
ments of Odisha state of India. Eight different wetlands were
identified from all over the state. The sampling site selection
of those eight places from different districts of Odisha was due
to their different exposure to contamination and sampling suit-
ability. The district and geographical locations of all sampling
sites are listed in Table-1 (Fig. 1).
82°0'0"E 84°0'0"E 86°0'0"E
82°0'0"E 84°0'0"E 86°0'0"E
16°0'0"
N
18°0'0"
N
20°0'0"
N
22°0'0"
N
24°0'0"
N
16°0'0"
N
18°0'0"
N
20°0'0"
N
22°0'0"
N
24°0'0"
N
NN
E
W
S
Legend
Samplin
g
locations
Districts of Odisha
0 15 30 60 90 120
Miles
Fig. 1. Map of study area showing location of sampling sites
TABLE-1
SAMPLING LOCATIONS OF DIFFERENT DISTRICTS OF
ODISHA STATE OF INDIA WITH LATITUDE AND LONGITUDE
Sam-
pling
point
Location Latitude Longitude District
1 Chilika 85°26'19.55" 19°53'16.78" Khurda
2 Hirakud 83°48'53.73" 21°28'56.03" Bargarh
3 Bhadrak 86°38'11.24" 20°59'30.4" Bhadrak
4 Chandaneswar 87°28'7.29" 21°38'1.03" Balasore
5 Talche r 85°13'20.03" 20°57'43.74" Angul
6 Daringbadi 84°6'47.91" 19°53'34.36" Kandhamal
7 Titlagarh 83°9'10.26" 20°16'18.96" Bolangir
8 Koraput 82°42'41.17" 18°48'16.2" Koraput
The sampling of water was conducted thrice during the
year in different seasons like pre-monsoon, monsoon and post-
monsoon. The physico-chemical parameters like total hardness
(TH), calcium hardness (CaH), magnesium hardness (MgH),
chloride, fluoride, sulphate, alkalinity, phosphate, nitrate, pH,
conductivity, oxidation reduction potential (ORP), dissolved
oxygen (DO), salinity and total dissolved solid (TDS) were
investigated.
Chloride concentration was estimated using argentometric
method. Nitrate was investigated by phenol disulphonic acid
(PDA) method. The colorimetric method (SPANDS) was used
for analysis of fluoride concentration. Turbidimetric method
was used for sulphate concentration analysis. Stannous chloride
method was used to investigate phosphate concentration. Alkal-
inity of the sample was estimated by titration method. Hardness
was measured by EDTA method, while Winkler′s method was
used for the determination of dissolve oxygen. Other parameters
like pH, ORP and salinity were estimated by electrode method.
All these analysis were done by using analytical techni-
ques as described by standard methods for examination of water
and wastewater [2] while some of them are recorded in field
condition before taking the samples in tightly capped poly-
propylene plastic bottles to the laboratory. The statistical analysis
and graphs were done with MS-EXCEL, correlation and its
scatter-plot was done using corr-plot in the programme R
version 3.4.4. In addition, all the data were estimated at p <
0.05 level of significance.
RESULTS AND DISCUSSION
Examination of water: This study describes that 15 para-
meters were analyzed and taken for correlation. The parameters
were total hardness, calcium hardness, magnesium hardness,
chloride, fluoride, sulphate, alkalinity, phosphate, nitrate, pH,
conductivity, oxidation reduction potential (ORP), dissolve
oxygen (DO), salinity and total dissolved solid (TDS).
The concentration comparison in every season of different
location of every parameter is illustrated in Fig. 2. The mean
± SD of all parameters at each sampling site is described in
Table-2. The correlations among them are shown in Table-3.
The corr-plot and scatter-plot of these parameters are given in
Figs. 3 and 4, respectively.
Present study revealed that the chloride concentration in
water varies nearly in between seasons. It was slightly higher
1682 Panda et al. Asian J. Chem.

200
150
100
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1200
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0.7
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1000
800
600
400
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0
Chloride conc. (mg/ L)
To t al ha rd ne ss
conc. (mg/L)
Magnesium hardnes s
conc. (mg/ L)
Calcium hdarness
conc. (mg/L)
Fluoride conc. (mg/L)
Phosphate conc. (mg/L)
Sulphate conc. (mg/L)
Nitrate conc. (mg/L)
pH
Conductivity
conc. (µS/cm)
Oxidation reduction
potential conc. (mV)
Dissolve oxyg en
conc. (mg/L)
Salinity conc. (mg/L)
TDS conc. (mg/L)
Alkalinity conc. (mg/L)
Pre-monsoon
Pre-monsoon
Pre-monsoon
Pre-monsoon
Pre-monsoon
Pre-monsoon
Pre-monsoon
Pre-monsoon
Pre-monsoon
Pre-monsoon
Pre-monsoon
Pre-monsoon
Pre-monsoon
Pre-monsoon
Pre-monsoon
Monsoon
Monsoon
Monsoon
Monsoon
Monsoon
Monsoon
Monsoon
Monsoon
Monsoon
Monsoon
Monsoon
Monsoon
Monsoon
Monsoon
Monsoon
Post-monsoon
Post-monsoon
Post-monsoon
Post-monsoon
Post-monsoon
Post-monsoon
Post-monsoon
Post-monsoon
Post-monsoon
Post-monsoon
Post-monsoon
Post-monsoon
Post-monsoon
Post-monsoon
Post-monsoon
Chilika
Chilika
Chilika
Chilika
Chilika
Chilika
Chilika
Chilika
Chilika
Chilika
Chilika
Chilika
Chilika
Chilika
Chilika
Hirakud
Hirakud
Hirakud
Hirakud
Hirakud
Hirakud
Hirakud
Hirakud
Hirakud
Hirakud
Hirakud
Hirakud
Hirakud
Hirakud
Hirakud
Bhadrak
Bhadrak
Bhadrak
Bhadrak
Bhadrak
Bhadrak
Bhadrak
Bhadrak
Bhadrak
Bhadrak
Bhadrak
Bhadrak
Bhadrak
Bhadrak
Bhadrak
Chandaneswar
Chandaneswar
Chandaneswar
Chandaneswar
Chandaneswar
Chandaneswar
Chandaneswar
Chandaneswar
Chandaneswar
Chandaneswar
Chandaneswar
Chandaneswar
Chandaneswar
Chandaneswar
Chandaneswar
Talcher
Talcher
Talcher
T
alcher
T
alcher
Talcher
Talcher
Talcher
Talcher
Talcher
Talcher
T
alcher
T
alcher
T
alcher
Talcher
Daringbadi
Daringbadi
Daringbadi
Daringbadi
Daringbadi
Daringbadi
Daringbadi
Daringbadi
Daringbadi
Daringbadi
Daringbadi
Daringbadi
Daringbadi
Daringbadi
Daringbadi
Titlagarh
Titlagarh
Titlagarh
Titlagarh
Titlagarh
Titlagarh
Titlagarh
Titlagarh
Titlagarh
Titlagarh
Titlagarh
Titlagarh
Titlagarh
Titlagarh
Titlagarh
Koraput
Koraput
Koraput
Koraput
Koraput
Koraput
Koraput
Koraput
Koraput
Koraput
Koraput
Koraput
Koraput
Koraput
Koraput
Sampling po int
Sampling po int
Sampling po int
Sampling po int
Sampling po int
Sampling po int
Sampling po int
Sampling po int
Sampling po int
Sampling po int
Sampling po int
Sampling po int
Sampling po int
Sampling po int
Sampling po int
Fig. 2. Concentration of physico-chemical parameters in water of every season at each sampling site
Vol. 32, No. 7 (2020) Relationship Among the Physico-Chemical Parameters of Soil and Water in Different Wetland Ecosystems 1683

TABLE-2
MEAN ± SD OF ALL VARIABLES OF WATER FROM ALL SAMPLING SITES
Chilika Hirakud Bhadrak Chandaneswar Talcher Daringbadi Titlagarh Koraput
Chloride (mg/L) 119.73 ±
9.80
44.87 ±
5.77
146.03 ±
22.11
128.8 ± 12.67 126.57 ±
8.17
24.3 ±
4.40
57.27 ±
6.54
49.53 ±
1.75
Total hardness CaCO3 (mg/L) 226.67 ±
64.29
160.00 ±
52.92
186.67 ±
50.33
246.67 ±
50.33
300.00 ±
91.65
286.67 ±
41.63
360.00 ±
80.00
373.33 ±
50.33
Calcium hardness (mg/L) 126.67 ±
64.29
100.00 ±
34.64
93.33 ±
30.55
120.00 ±
34.64
153.33 ±
64.29
120.00 ±
34.64
193.33 ±
23.09
193.33 ±
80.83
Magnesium hardness (mg/L) 100.00 ±
20.00
60.00 ±
20.00
93.33 ±
41.63
126.67 ±
64.29
146.67 ±
92.38
166.67 ±
30.55
166.67 ±
83.27
180.00 ±
72.11
Fluoride (mg/L) 0.16 ±
0.00
0.19 ±
0.06
0.22 ±
0.08
0.23 ± 0.06 0.37 ±
0.09
0.49 ±
0.15
0.23 ±
0.06
0.09 ±
0.01
Sulphate (mg/L) 46.16 ±
5.17
1.30 ±
0.12
89.50 ±
8.14
16.76 ± 1.44 140.66 ±
20.54
5.25 ±
1.31
1.41 ±
0.22
11.90 ±
1.68
Alkalinity 221.33 ±
18.04
370.00 ±
30.00
553.33 ±
70.24
433.33 ±
50.33
496.67 ±
70.95
213.33 ±
30.55
776.67 ±
85.05
148.00 ±
12.00
Phosphate (mg/L) 2.35 ±
0.35
26.61 ±
6.48
6.72 ±
2.49
7.57 ± 1.14 6.14 ±
1.01
5.45 ±
0.82
8.33 ±
1.25
5.18 ±
0.78
Nitrate (mg/L) 4.90 ±
1.02
2.49 ±
0.41
39.51 ±
6.75
19.22 ± 3.19 17.26 ±
2.86
3.94 ±
0.75
14.99 ±
2.58
3.22 ±
1.01
pH 6.42 ±
0.34
6.57 ±
0.35
6.54 ±
0.34
7.08 ± 0.37 6.45 ±
0.34
6.13 ±
0.32
6.59 ±
0.35
6.37 ±
0.34
Conductivity (µs/cm) 962.50 ±
315.49
188.10 ±
61.65
785.40 ±
257.44
402.60 ±
131.96
819.50 ±
268.61
742.50 ±
243.37
556.60 ±
182.44
272.80 ±
89.42
ORP (mv) 147.11 ±
15.58
140.56 ±
14.12
136.40 ±
13.49
134.69 ±
13.53
142.74 ±
19.04
42.10 ±
4.23
22.48 ±
4.40
24.93 ±
2.50
DO (mg/L) 5.98 ±
0.35
5.60 ±
0.62
4.04 ±
0.88
6.27 ± 0.52 1.94 ±
0.77
5.71 ±
0.57
1.89 ±
0.60
1.43 ±
0.42
Salinity 473.00 ±
155.04
88.00 ±
28.84
385.00 ±
126.19
198.00 ±
64.90
407.00 ±
133.41
105.00 ±
117.15
275.00 ±
90.14
132.00 ±
43.27
TDS (mg/L) 498.13 ±
100.56
98.40 ±
21.70
391.20 ±
92.04
209.19 ±
41.20
407.07 ±
128.19
38.40 ±
8.47
287.60 ±
73.14
142.80 ±
31.48
1.0
0.8
0.6
0.4
0.2
0
-0.2
-0.4
-0.6
-0.8
-1.0
a
b
c
d
e
f
g
h
i
j
k
l
m
n
o
a
b
c
d
e
f
g
h
i
j
k
l
m
n
o
Fig. 3. Corr-plot showing correlations among all physico-chemical parameters of water with colour gradient (a) chloride, (b) TH, (c) CaH, (d)
MgH, (E) flouride, (f) sulphate, (g) alkalinity, (h) phosphate, (i) nitrate, (j) ph, (k) conductivity, (l) ORP, (m) DO, (n) salinity, (o) TDS
1684 Panda et al. Asian J. Chem.

TABLE-3
CORRELATION OF DIFFERENT PARAMETERS OF WATER
a b c d e f g h i j k l m n o
a 1
b -.354 1
c -.320 .940** 1
d -.349 .950** .787* 1
e -.160 .040 -.218 .271 1
f .716* -.129 -.138 -.108 .217 1
g .281 .046 .131 -.037 .066 .210 1
h -.352 -.503 -.341 -.599 -.142 -.312 .124 1
i .724* -.250 -.293 -.184 .027 .548 .613 -.216 1
j .494 -.232 -.139 -.293 -.358 -.068 .425 .197 .383 1
k .484 -.067 -.169 .033 .421 .599 .074 -.656 .316 -.356 1
l .723* -.800* -.707* -.801* -.073 .542 .021 .226 .326 .394 .259 1
m .094 -.725* -.796* -.584 .164 -.290 -.326 .213 -.116 .223 .086 .492 1
n .780* -.116 -.038 -.176 -.082 .728* .298 -.513 .478 .029 .799* .483 -.119 1
o .797* -.127 -.005 -.226 -.222 .687 .318 -.448 .467 .122 .699 .507 -.142 .988** 1
*Correlation is significant at the 0.05 level (2-tailed); **Correlation is significant at the 0.01 level (2-tailed).
(a) chloride, (b) TH, (c) CaH, (d) MgH, (E) flouride, (f) sulphate, (g) alkalinity, (h) phosphate, (i) nitrate, (j) pH, (k) conductivity, (l) ORP, (m) DO,
(n) salinity, (o) TDS
200 350
60 120 0 60 140 5 15 25 6.2 6 .8 20 80 140 100 400
20 80 140 100 160 0.1 0.3 0.5 200 600 10 30 200 800 2 4 6 100 400
100 20 6.2 5 25 0 120 60 180 200
100 2 5 200 10 200 0.1 0.5 100 20 140
Chloride
Tot al
hardness
Calcium
hardness
Magnes ium
hardnes s
Flouride
Sulphate
Alkalinity
Phosphate
Nitrate
pH
Conduc-
tivity
ORP
DO
Salinity
TDS
Fig. 4. Cluster analysis in the form of Scatter plot matrices showing concentrations of physico-chemical parameters of water
in monsoon and post-monsoon than the pre-monsoon. The
dumping of sewage, human excreta, and animal organic waste
as well as waste from industries can contribute to the chloride
concentration in water and soils [6,16]. Total hardness was
found highest in pre-monsoon among all seasons in most of
the sampling sites and less in the monsoon season. It may be
due to the dilution of water in rainy season. Calcium hardness
also showed similar result like magnesium hardness. Calcium
concentration varies due to discharge of swage and low due to
the good unpoll-uted water quality of nature [17]. Chandaneswar
was the only exception where the concentration of calcium
hardness was higher in post-monsoon. Magnesium hardness
was found higher in pre-monsoon and post-monsoon seasons
than monsoon in most of the sampling sites. The higher concen-
Vol. 32, No. 7 (2020) Relationship Among the Physico-Chemical Parameters of Soil and Water in Different Wetland Ecosystems 1685

tration of magnesium hardness in monsoon supports the increa-
sing amount of rainfall and sewage entry from other sources
to the aquatic ecosystem [18].
Fluoride concentration was found highest in pre-monsoon
season than other seasons. In monsoon, the concentration was
low in all sampling sites except Daringbadi, where it was little
higher in monsoon than the post-monsoon. Phosphate concen-
tration was found nearly equal in all three seasons but in monsoon
it was found highest. The runoff from agricultural fields and
anthropogenic pressure increases the phosphate concentration
in monsoon [19]. Sulphate was also found like the pattern of
phosphate. It varied with the presence of industrial activity
near the wetland [20].
Nitrate concentration was found highest in monsoon. It
may be due to the runoff from the soil and agricultural field in
rainy season [14]. The pH concentration was found little higher
in pre-monsoon. The reason can be attributed due to the uptake
of carbon dioxide by photosynthe-sizing organism in pre-
monsoon is higher which increases the pH [15]. Moreover,
dilution of water, low temperature and decomposition of
organic matter in monsoon, can be the reason for low pH [21].
In monsoon, the conductivity was found higher in all sampling
sites. Present findings were supported by other studies [22]
where it described as the higher concentration of dissolved
solids in water during monsoon season. The oxidation reduction
potential (ORP) concentration was found higher in pre-monsoon
than other seasons in water. Dissolved oxygen (DO) concentra-
tion varies in all seasons but in most of the places, DO was
higher in post-monsoon, which can be due to vary in seasons
with the anthropogenic pressure like industrial and human
activities [2]. Salinity was found higher in monsoon in all
sampling site, moreover coastal areas were found with high
salinity. Total dissolved solids (TDS) was also found high in
the monsoon due to the runoff from inland water [3,19]. Alka-
linity was found higher in pre-monsoon and post-monsoon due
to the presence of carbonates and bicarbonates [23].
Correlation among all the parameters of water were tested
with Pearson′s correlation (r) test and found to be highly corre-
lated with each other (Table-3). The significance level was
found very high between TH and CaH (r = 0.94, p < 0.01), TH
and MgH (r = 0.95, p < 0.01), salinity and TDS (r = 0.98, p <
0.01). Chloride concentration was found significant with sulphate
(r = 0.71, p < 0.05), nitrate (r = 0.72, p < 0.05), conductivity (r
= 0.72, p < 0.05), salinity (r = 0.78, p < 0.05), TDS (r = 0.79,
p < 0.05). Total hardness was found significant with ORP (r =
−0.80, p < 0.05) and DO (r = −0.72, p < 0.05). The significance
level between CaH with MgH (r = 0.78, p < 0.05), ORP (r =
−0.70, p < 0.05), DO (r = −0.79, p < 0.05). MgH was found
significant with ORP (r = −0.80, p < 0.05). Sulphate was posit-
ively correlated with salinity (r = 0.72, p < 0.05). Conductivity
and salinity were positively correlated with high significance
(r = 0.79, p < 0.05). This correlation among all parameters is
described in colour gradient for easier representation (Fig. 3).
The cluster analysis clearly describes the physico-chemical
structures in Fig. 4, which represents the concentration plot
on relation with each other among all parameters. All the 15
parameters of water were described in cluster format among
X-axis and Y-axis. Taking the seasons as variable the concen-
tration of each parameter is described. Though some parameters
were high in pre-monsoon, some were high in post monsoon.
So, cluster plot described the variety in all plots as the seasonal
data.
Examination of soil: This study describes the 9 parameters
of soil were analyzed and taken for correlation. The parameters
were total hardness (TH), calcium hardness (CaH), magnesium
hardness (MgH), chloride, fluoride, sulphate, alkalinity, phos-
phate and nitrate. The concentration comparison in every season
of different locations of every parameter is illustrated in Fig.
5. The mean ± SD of all parameters at each sampling site is
described in Table-4 and the correlations among them are shown
in Table-5. The scatter plot of this correlation is shown in Fig.
7.
Present study revealed that the chloride concentration in
soil was found only in Chilika and Chandaneswar. These two
are the coastal sampling sites. It may be due to the influence
of seawater. Total hardness was found highest in pre-monsoon
TABLE-4
MEAN ± SD OF ALL VARIABLES OF SOIL FROM ALL SAMPLING SITES
Sampling point Chilika Hirakud Bhadrak Chandaneswar Talcher Daringbadi Titlagarh Koraput
Chloride 511.65 ±
14.34
0.00 ± 0.00 0.00 ± 0.00 36.00 ±
12.266
0.00 ± 0.00 0.00 ± 0.00 0.00 ± 0.00 0.00 ± 0.00
Total hardness 566.67 ±
94.52
580.00 ±
105.83
393.33 ±
94.52
406.67 ±
70.24
366.67 ±
41.63
546.67 ±
133.17
686.67 ±
147.42
613.33 ±
102.63
Calcium hardness 200.00 ±
60.00
186.67 ±
23.09
233.33 ±
61.10
186.67 ±
23.09
240.00 ±
60.00
226.67 ±
30.55
293.33 ±
11.55
273.33 ±
64.29
Magnesium hardness 366.67 ±
41.63
393.33 ±
100.66
160.00 ±
34.64
220.00 ±
52.92
126.67 ±
23.09
320.00 ±
158.75
393.33 ±
136.14
340.00 ±
52.92
Fluoride 0.05 ± 0.01 0.45 ± 0.12 0.09 ± 0.02 0.09 ± 0.02 0.22 ± 0.09 0.05 ± 0.02 0.14 ± 0.08 0.19 ± 0.04
Sulphate 57.75 ±
9.92
1.62 ± 0.28 57.69 ±
10.14
89.88 ± 57.54 146.33 ±
25.47
142.54 ±
8.02
167.43 ±
19.07
146.16 ±
11.25
Alkalinity 80.00 ±
20.00
236.67 ±
25.17
166.67 ±
30.55
380.00 ±
20.00
580.00 ±
111.36
260.00 ±
20.00
973.33 ±
98.33
766.67 ±
90.18
Phosphate 13.89 ±
6.95
22.80 ±
11.49
7.51 ± 3.14 8.26 ± 4.13 21.82 ±
10.55
15.67 ±
7.83
11.21 ±
6.67
34.56 ±
20.79
Nitrate 19.40 ±
11.42
47.27 ±
37.24
33.87 ±
18.86
17.95 ± 13.17 24.73 ±
8.37
6.62 ± 4.30 65.63 ±
41.09
8.56 ± 5.61
1686 Panda et al. Asian J. Chem.

600
500
400
300
200
100
0
1200
1000
800
600
400
200
0
200
150
100
50
0
60
50
40
30
20
10
0
120
100
80
60
40
20
0
0.6
0.5
0.4
0.3
0.2
0.1
0
600
500
400
300
200
100
0
350
300
250
200
150
100
50
0
900
800
700
600
500
400
300
200
100
0
C
hl
o
ride c
o
nc. (mg
/
L
)
Alkalinity conc.
(mg CaCO /L)
3
Sulphate conc. (ppm)
Phosphate conc. (ppm)
Nitrate conc. (ppm)
Fluoride conc. (ppm)
M
a
gnesium h
a
rdness
conc. (ppm)
C
a
lcium h
a
rdness
conc. (ppm) Total hardness
conc. (ppm)
Pre-monsoon Pre-monsoon
Pre-monsoon
Pre-monsoon
Pre-monsoon
Pre-monsoon
Pre-monsoon
Pre-monsoon
Pre-monsoon
Monsoon Monsoon
Monsoon
Monsoon
Monsoon
Monsoon
Monsoon
Monsoon
Monsoon
Post-monsoon Post-monsoon
Post-monsoon
Post-monsoon
Post-monsoon
Post-monsoon
Post-monsoon
Post-monsoon
Post-monsoon
Chilika
Chilika
Chilika
Chilika
Chilika
Chilika
Chilika
Chilika
Chilika
Hirakud
Hirakud
Hirakud
Hirakud
Hirakud
Hirakud
Hirakud
Hirakud
Hirakud
Bhadrak
Bhadrak
Bhadrak
Bhadrak
Bhadrak
Bhadrak
Bhadrak
Bhadrak
Bhadrak
Chandaneswar
Chandaneswar
Chandaneswar
Chandanes war
Chandaneswar
Chandaneswar
Chandaneswar
Chandaneswar
Chandaneswar
Ta lcher
Tal che r
Talcher
Ta lcher
Tal c h e r
T
alcher
Talcher
Tal c h er
Talcher
Daringbadi
Daringbadi
Daringbadi
Daringbadi
Daringbadi
Daringbadi
Daringba di
Daringbadi
Daringbadi
Titlagarh
Titlagarh
Titlagarh
Titlagarh
Titlagarh
Titlagarh
Titlagarh
Titlagarh
Tit lagar h
Koraput
Koraput
Koraput
Koraput
Koraput
Koraput
Koraput
Koraput
Koraput
Sampling point Sampling point
Sampling point
Sampling point
Sampling point
Sampling point
Sampling point
Sampling point
Sampling point
Fig. 5. Concentration of physico-chemical parameters of soil of every season at each sampling site
TABLE-5
CORRELATION OF DIFFERENT PARAMETERS OF SOIL AMONG THEMSELVES
a b c d e f g h i
a 1
b .135 1
c -.345 .422 1
d .275 .943** .096 1
e -.353 .151 -.151 .222 1
f -.308 .165 .775* -.104 -.403 1
g -.460 .404 .824* .141 .105 .756* 1
h -.165 .309 .256 .246 .520 .174 .302 1
i -.188 .336 .265 .272 .409 -.134 .369 -.294 1
*Correlation is significant at the 0.05 level (2-tailed); **Correlation is significant at the 0.01 level (2-tailed).
(a) Chloride, (b) TH, (c) CaH, (d) MgH, (E) Flouride, (f) Sulphate, (g) Alkalinity, (h) Phosphate, (i) Nitrate
Vol. 32, No. 7 (2020) Relationship Among the Physico-Chemical Parameters of Soil and Water in Different Wetland Ecosystems 1687

among all seasons in most of the sampling sites and less in the
monsoon season. It may be due to the dilution of salty water in
rainy season. Magnesium hardness was found higher in pre-
monsoon and post-monsoon seasons than monsoon in most of
the sampling sites. Calcium hardness also behaved like magnesium
hardness. Fluoride concentration was found highest in pre-
monsoon season than other seasons. In monsoon, the concen-
tration was low in all sampling sites except Talcher, where it
was little higher in monsoon than the post-monsoon. Phosphate
concentration was found highest in monsoon among all sampling
sites. Sulphate was found with very low differences. In pre-
monsoon and post-monsoon, the concentration of alkalinity
was found higher than monsoon. Nitrate concentration was
found highest in monsoon. It may be due to the runoff from
the soil in rainy season.
Correlation among all parameters of soil were tested with
Pearson′s correlation (r) test and found to be highly correlated
with each other (Table-5). The significance level was found very
high between TH and MgH (r = 0.94, p < 0.01). The signifi-
1.0
0.8
0.6
0.4
0.2
0
-0.2
-0.4
-0.6
-0.8
-1.0
a
b
c
d
e
f
g
h
i
a
b
c
d
e
f
g
h
i
Fig. 6. Corr-plot showing correlations among all physico-chemical parameters of soil with color gradient (a) chloride, (b) TH, (c) CaH, (d)
MgH, (E) flouride, (f) sulphate, (g) alkalinity, (h) phosphate, (i) nitrate
cance level between CaH with sulphate (r = 0.77, p < 0.05),
alkalinity (r = 0.82, p < 0.05). Sulphate was positively correlated
with alkalinity (r = 0.75, p < 0.05). This correlation among all
the parameters is described in colour gradient for easier
representation (Fig. 6). This cluster analysis clearly describes
the physico-chemical structures in Fig. 7. All the 9 parameters
of soil were described in cluster format among X-axis and Y-
axis. Though some parameters were high in pre-monsoon and
some others were also high in post-monsoon. So, the cluster
plot described the variety in all plots as the seasonal data.
With physico-chemical variables, various components of
avian diversity like species richness, bird abundance and diversity
also differ in different locations with seasons [14,24]. The water
depth plays an important role in plant diversity and cause prompt
changes in fish, amphibians, invertebrates which ultimately
leads to waterbird community [17]. Many aquatic plant species
distribution is influenced by changes in water chemistry [25]
which ultimately related to the species diversity and abundance
who depends on those aquatic plants and weeds [24]. Slightly
1688 Panda et al. Asian J. Chem.

alkaline pH is an indicator of higher macro invertebrates and
overall productivity of wetland ecosystem which also support
the avifaunal diversity in those regions [10] but this study
revealed that the pH was slightly acidic (6.13-7.08) and this
leads to the negative correlation with avian diversity. Phosphate
concentration fluctuations of water bodies affect the waterfowl
abundance [26]. Some group of birds like ducks were signifi-
cantly negatively correlated with the DO but for other species
there was a positive correlation between DO and bird diversity.
Earlier studies [10,17,27] described that chloride, conductivity,
ORP, DO, salinity and TDS were positively correlated with the
abundance and diversity of birds. So for biomonitoring, every
component of the ecosystem is important and should be taken
into consideration.
Conclusion
In any habitat, physico-chemical parameters of soil and
water play an important role for the plant and animal compo-
sition. These parameters of one ecosystem influence the floral
diversity of that region, which ultimately leads to support the
faunal diversity. In aquatic ecosystem, the physico-chemical
parameters control the weed diversity and water quality which
influences the wetland birds. These parameters of water are
also correlated among themselves. Physico-chemical
parameters of water and soil also interlinked and correlated
among each other. It goes from the soil to water with the
rainwater and deposited on the sediment from the water.
Sometimes these parameters work as a cycle to maintain the
equilibrium in the ecosystem. Many activities by congregation
of birds were always influenced by the physical and chemical
400 500 600 150 250 350 0 50 100 150 10 20 30
0 200 400 200 240 280 0.1 0.3 200 60 0 1000 10 30 50
10 25 0 100 150 300 400 600
0 300200 2600.1 0.3200 80010 40
Chloride
To ta l
hardness
Calcium
hardnes s
Magnesium
hardnes s
Fluoride
Sulphate
Alkalinity
Phosphate
Nitrate
Fig. 7. Cluster analysis in the form of Scatter plot matrices showing concentrations of physico-chemical parameters of soil
compositions of habitat. One single factor can not be the reason
for the composition of species. With these factors, water depth
also plays an important role for bird congregation [28]. Flock
size of waterbirds also affected by the habitat selection with
many biotic and abiotic factors [1]. There were instances where
some egrets changed their feeding habit according to water
management in agricultural fields [29]. Higher level of research
work is needed to control the source of pollution to wetlands.
By controlling the physico-chemical parameters of habitat,
the diversity, density and richness of residential and migratory
birds and other wetland dependent organisms can be cont-
rolled.
CONFLICT OF INTEREST
The authors declare that there is no conflict of interests
regarding the publication of this article.
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