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Int. J. Life. Sci. Scienti. Res., 2(6): 692-699 NOVEMBER- 2016
http://ijlssr.com Copyright © 2015-2016 International Journal of Life-Sciences Scientific Research Page 692
Hydrological Parameters of East Kolkata
Wetlands: Time Series Analysis
Atanu Roy1*
, Rima Roy2
, Diganta Sarkar1
, Madhumita Roy1
and Abhijit Mitra3
1
Department of Biotechnology, Techno India University, Salt Lake Campus Kolkata, India
2
Department of Microbiology, Techno India University, Salt Lake Campus, Kolkata, India
3
Department of Marine Science, University of Calcutta, 35 B.C. Road, Kolkata, India
*
Address for Correspondence: Atanu Roy, Research Scholar, Department of Biotechnology, Techno India University,
Salt lake Campus, Kolkata, India
Received: 21Sept 2016/Revised: 29 Sept 2016/Accepted: 19 Oct 2016
ABSTRACT- Three decades data (1984 – 2015) was used to study the effect of surface water temperature, pH, dissolved
oxygen, nitrate, phosphate and silicate on chlorophyll a concentration in three water bodies meant for fish culture (locally
known as Bheries) in East Kolkata Wetlands. The data revealed significant spatio-temporal variations (p < 0.01). The
increasing trend of temperature, nitrate and phosphate reflects the effect of intense urbanization at local level. The
pronounced variation of dissolved oxygen and chlorophyll a (decreasing trend) may be attributed to increased load of
sewage in the selected water bodies, which has posed an adverse impact on the phytoplankton standing stock as revealed
through decreasing chlorophyll a trend.
Key-words- East Kolkata Wetlands (EKW), Phytoplankton, Chlorophyll a, Nutrients, ANOVA
-------------------------------------------------IJLSSR-----------------------------------------------
INTRODUCTION
Wetlands are one of the most productive ecosystems of the
planet Earth [1-3]
. East Kolkata Wetlands (EKW) present in
the maritime state of West Bengal (India) has been
designated as Ramsar Site and is noted for its high nutrient
level and considerable fish production [4-6]
.
Many reports of EKW include management programmes to
conserve this well known wetland which spans over the
entire eastern outskirts of the metropolitan city of Kolkata
[6-9]
. However, very few works documented the
inter-relationship between relevant hydrological parameters
and phytopigment (chlorophyll a) which may serve as
proxy to primary productivity of the aquatic system.
The present paper analysis the dependency of chlorophyll a
on the nutrient levels in the aquatic phase of EKW. For
this, a data bank of three decades (1984–2015) has been
relied upon to interpret the result. This data bank is the
average of three seasons in the three sampling bheries
selected in EKW and is retrieved from the archives of
Department of Marine Science, University of Calcutta.
Access this article online
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DOI: 10.21276/ijlssr.2016.2.6.8
MATERIALS AND METHODS
Study Site
EKW is situated at the eastern outskirts of the mega city of
Kolkata, India (22o
25' to 22o
40' N and 88o
20' to 88o
35' E).
The fish ponds of the area offers important ecosystem
services like flood control, recycling of municipal wastes
and effluents (generated from urban and semi urban areas),
aesthetic beauty, fish production, livelihood, etc. EKW is
extremely dynamic from the point of view of primary
production and is a unique reservoir of a galaxy of
phytoplankton, which serve as the foundation stone of food
chain existing in the system. The present sampling bheries
were selected at Captain Bheri (22o
33’06.7” N to
88o
24’38.5” E), Munshir Bheri (22o
34’18.3” N to
88o
26’22.9” E) and Natur Bheri (22o
32’49.9” N to
88o
25’30.1” E) with the aim to analyze the chlorophyll a
and few relevant physio-chemical variables (like surface
water temperature, pH, dissolved oxygen, nitrate,
phosphate and silicate).
Analysis of Hydrological Parameters
Surface water temperature was recorded by using a
0o
- 100o
C mercury thermometer and pH of the surface
water was measured by using a portable pH meter
(sensitivity = ±0.01). The dissolved oxygen was measured
by a DO meter in the field and subsequently cross-checked
in the laboratory by Winkler’s method.
Surface waters for nutrient analyses were collected in clean
Research Article (Open access)
Int. J. Life. Sci. Scienti. Res., VOL 2, ISSUE 6
http://ijlssr.com Copyright © 2015-2016 International Journal of Life-Sciences Scientific Research Page 693
TARSON bottles and were transported to the laboratory in
ice-freeze condition. Triplicate samples were collected
from the same collection site to maintain the quality of the
data. The standard spectrophotometric method [10]
was
adopted to determine the nutrient concentration in surface
water. Nitrate was analysed by reducing it to nitrite by
means of passing the sample with ammonium chloride
buffer through a glass column packed with amalgamated
cadmium filings and was finally treated with
sulphanilamide solution. The resultant diazonium ion was
coupled with N - (1-napthyl)- ethylene diamine to give an
intensely pink azo dye. Determination of the phosphate was
carried out by treatment of an aliquot of the sample with an
acidic molybdate reagent containing ascorbic acid and a
small proportion of potassium antimony tartarate.
Dissolved silicate was determined by treating the sample
with acidic molybdate reagent.
Pigment Analysis
For pigment analysis, 1 litre of surface water was collected
from each of the sampling sites and filtered through a 0.45
µm Millipore membrane fitted with a vacuum pump. The
residue along with the filter paper was dissolved in 90%
acetone and was kept in a refrigerator for about 24 hours in
order to facilitate the complete extraction of the pigment.
The solution was then centrifuged for about 20 minutes at
5000 rpm and the supernatant solution was considered for
the determination of the chlorophyll pigment by recording
the optical density at 750, 664, 647 and 630 nm with the
help of Systronics UV-visible spectrophotometer model
No-117 (micro controller based). All the extinction values
were corrected for a small turbidity blank by subtracting
the 750 nm signal from all the optical densities, and finally
the phytoplankton pigment was estimated as per the
following expression of Jeffrey and Humphrey (1975) [11]
.
Chl a = 11.85 OD664 – 1.54 OD647 - 0.08 OD630
All the extinction values were corrected for a small
turbidity blank by subtracting the 750 nm signal from all
the absorbance values. The values obtained from the
equations were multiplied by the volume of the extract (in
ml) and divided by the volume of the water (in litre)
filtered to express the chlorophyll a content in mg.m-3
. All
the analyses were done in triplicate (on the basis of
collection of three samples from the same site) in order to
ensure the quality of the data.
STATISTICAL ANALYSIS
It is the final phase in which statistical tools were applied to
understand the spatio-temporal variation in the study site.
For this, ANOVA was performed to evaluate statistically
significant differences between years and selected bheries.
RESULTS AND DISCUSSION
Surface water temperature, pH, dissolved oxygen, nutrients
level and chlorophyll a concentration recorded in the three
sampling sites are shown in Figures 1-7.
All these hydrological parameters were subjected to
ANOVA and significant variations (p < 0.01) were
observed between years and bheries (Tables 1-7). This may
be due to different standing stock of phytoplankton present
in the selected bheries (Annexure 1). The profiles of the
selected hydrological parameters are discussed separately.
Temperature
Surface water temperature ranged from 29.2o
C (in Natur
Bheri during 1984) to 32o
C (in Munshir Bheri during 2015)
(Figure 1). There exist pronounced variations in surface
water temperature between years and bheries (p < 0.01) as
depicted in Table 1. The variation between the three
selected bheries may be attributed to different degrees of
exposure to solar radiations although they are located in the
same geographical locale of EKW. The shades provided by
the vegetations around the selected bheries may be related
to such local level variations.
The yearly variation pointed out towards the gradual
warming of the atmosphere due to climate change induced
warming in this tropical belt as pointed out by earlier
researchers [2-3, 12-13]
.
Figure 1: Decadal variations of surface water
temperature
Table 1: ANOVA result for Surface Water
Temperature
Source of
Variation
for Surface
water
temperature
SS df MS F P-value F
crit
Between
Years 29.37 31 0.95 23.70 3.97 × 10-24
1.64
Between
Bheries 2.34 2 1.17 29.30 1.1 × 10-09
3.15
Error
2.48 62 0.04
Total
34.19 95
Int. J. Life. Sci. Scienti. Res., VOL 2, ISSUE 6
http://ijlssr.com Copyright © 2015-2016 International Journal of Life-Sciences Scientific Research Page 694
pH
The pH of the waters in the study sites ranged from 6.7 (in
Captain Bheri during 1990) to 8.2 (in Captain Bheri during
2015) (Figure 2). It is interesting to note that unlike other
parameters, the pH of the aquatic phase in the selected
bheries of the bheries of EKW did not exhibit any
pronounced variation (Table 2). This is due to the fact that
all these bheries are managed by the local people who use
lime on regular basis to maintain the acid-base balance of
the water bodies.
Table 2: ANOVA result for pH
Source of
Variation
for pH
SS df MS F P-value F crit
Between
Years
2.52 31 0.08 1.31 0.18 1.64
Between
Bheries
0.09 2 0.04 0.70 0.50 3.15
Error 3.86 62 0.06
Total 6.48 95
Figure 2: Decadal variations of pH
Dissolved Oxygen
Dissolved Oxygen (DO) ranged from 3.92 ppm (in Munshir
bheri during 2003) to 6.77 ppm (in Munshir bheri during
2009) (Figure 3). There exist pronounced variations in DO
between years and bheries (p < 0.01) as depicted in Table 3.
The variation between the three selected bheries may be
attributed to different degrees of exposure to solar
radiations although they are located in the same
geographical locale of EKW. The variation is the outcome
of different degree of photosynthetic rate due to difference
in the standing stock of phytoplankton (Annexure 1). The
yearly variation (decreasing trend) may be the effect of
increased load of sewage with the rapid pace of
urbanization in and around EKW. The gradual decrease of
DO in the study area was also pointed out by earlier
researchers [14]
.
Table 3: ANOVA result for Dissolved Oxygen
Source of
Variation
for
Dissolved
Oxygen
SS df MS F P-value F
crit
Between
Years 10.12 31 0.33 4.44 2.99 × 10-07
1.64
Between
Bheries 6.51 2 3.26 44.28 1.14 × 10-12
3.15
Error 4.56 62 0.07
Total 21.19 95
Figure 3: Decadal variations of Dissolved Oxygen
Nutrients
The nitrate concentration varied from 24.17 g at l-1
(in
Munshir bheri during 1984) to 55.89 g at l-1
(in Natur
bheri during 2015) (Figure 4) and the phosphate
concentration ranged from 2.51 g at l-1
(in Munshir bheri
during 1984) to 6.73 g at l-1
(in Natur bheri during 2015)
(Figure 5). These two nutrients are primarily generated
from municipal waste discharge, which is gradually
increasing on account of rapid pace of industrialization and
urbanization [4, 15-16]
. Both of them showed pronounced
variation between years and bheries (p < 0.01) (Table 4 and
5). The silicate concentration ranged from 54.48 g at l-1
(in Munshir bheri during 2014) to 102.93 g at l-1
(in
Munshir bheri during 2009) (Figure 6). Silicate which is
primarily produced due to churning action of the
underlying pond substratum and regulated by
phytoplankton community [16-17]
also exhibited pronounced
spatial and temporal variations (Table 6). The spatial
variation is regulated by phytoplankton stock in the
selected ponds and the temporal variation is keenly related
to erosion and other physical factors that have increased in
recent times.
Int. J. Life. Sci. Scienti. Res., VOL 2, ISSUE 6
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Table 4: ANOVA result for Nitrate
Source of
Variation
for
Nitrate
SS df MS F P-value F
crit
Between
Years 3933.01 31 126.87 59.39 1.47 × 10-35
1.64
Between
Bheries 131.92 2 65.96 30.88 4.96 × 10-10
3.15
Error 132.46 62 2.14
Total 4197.39 95
Figure 4: Decadal variations of Nitrate
Table 5: ANOVA result for Phosphate
Source of
Variation
for
phosphate
SS df MS F P-value F
crit
Between
Years 39.62 31 1.28 6.21 5.8 × 10-10
1.64
Between
Bheries 21.83 2 10.91 53.04 3.74 × 10-14
3.15
Error 12.76 62 0.21
Total 74.20 95
Figure 5: Decadal variations of Phosphate
Table 6: ANOVA result for Silicate
Source of
Variation
for
Silicate
SS df MS F P-value F
crit
Between
Years 5566.70 31 179.57 7.411 1.47 × 10-11
1.64
Between
Bheries 2245.80 2 1122.90 46.34267 4.91 × 10-13
3.15
Error 1502.28 62 24.23
Total 9314.77 95
Figure 6: Decadal variations of Silicate
Chlorophyll a
Chlorophyll a serves as proxy to phytoplankton standing
stock and ranged from 4.19 mg.m-3
(in Natur Bheri during
2012) to 12.29 mg.m-3
(in Munshir Bheri during 1984) in
the study area (Figure 7). The pronounced spatial and
temporal variations (Table 7) of the phytopigment may be
the result of variation in phytoplankton population, which
again is controlled by nutrient level of the ambient aquatic
phase. The dependency of phytoplankton on nutrient is
revealed from the expression (CH2O)108(NH3)16H3PO4 and
in case of diatoms it is slightly modified as
(CH2O)108(NH3)16H3PO4(SiO4)40
[18]
. These constituents of
phytoplankton suggest the necessity and subsequent
utilization of nitrate, phosphate and silicate from the
ambient waters [19- 23]
. The significant negative correlation
between nutrient level and phytoplankton speaks in favour
of the uptake of nutrients by the phytoplankton, as these
nutrients act as building blocks of phytoplankton.
Chlorophyll a, the primary constituent of phytoplankton
needs special importance with respect to maintenance of
ecological stability, primary production and energy flow
through the food chains spun in the water bodies of EKW
through long evolutionary period of time. The decreasing
trend of chlorophyll a is a warning signal in context to
primary production of the system as the dynamics of
energy flow in any aquatic system is regulated by
phytoplankton standing stock with chlorophyll a, as its
Int. J. Life. Sci. Scienti. Res., VOL 2, ISSUE 6
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major constituents. Hence regular monitoring and
conservation of these free floating tiny producer community is extremely important to upgrade the ecological health of the
system. The dependency of phytoplankton on nutrient levels demands the regulation of waste discharge in the EKW so
as to optimize the growth of phytoplankton. The local economy and livelihood of EKW is primarily pisci-centric and
therefore the primary producer community needs to be conserved in order to generate a sustainable secondary production.
Table 7 ANOVA result for Chlorophyll a
Source of Variation for
Chlorophyll a
SS df MS F P-value F crit
Between Years 104.29 31 3.36 26.52 1.76 × 10-25
1.64
Between Bheries 253.92 2 126.96 1000.96 6.44 × 10-48
3.15
Error 7.86 62 0.13
Total 366.07 95
Figure 7: Decadal variations of Chlorophyll a
CONCLUSION
The time series analysis on the selected hydrological parameters of EKW highlights few core findings as listed below:
Significant variations of hydrological parameters exist between the selected bheries (except aquatic pH), which might be
due to different nutrient supply (preferably through sewage) to the bheries.
The uniformity of aquatic pH may be attributed to application of lime on regular basis, which is a common practice of the
beneficiaries of the bheries of EKW.
Chlorophyll a, which is proxy to the productivity of the bheries oscillates as a function of nutrient load of the
aquatic phase. Hence, regulation of nutrients is of utmost importance to maintain the productivity of the bheries
located in the EKW.
Annexure 1: Standing stock of phytoplankton species in the selected sites of East Kolkata Wetlands
S.
No.
Phytoplankton Species Standing Stock (No./L)
Captain Bheri Munshir Bheri Natur Bheri
1 Merismopedia trolleri 10132.49 8952.38 12632.06
2 Merismopedia glauca 9133.41 8797.29 10700.41
3 Merismopedia minima
2384.49 2250.07 2762.49
4 Merismopedia punctata
33519.31 31950.14 35252.09
5 Synechococcus elongatus 4316.18 4158.55 4699.3
3522.94 3404.25 4046.49
Int. J. Life. Sci. Scienti. Res., VOL 2, ISSUE 6
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6 Synechocystis aquatilis
7 Coelosphaerium pallidum
225131.2 218202.63 227153.21
8 Rhabdogloea rhaphidioides
23381.79 21894.74 24735.6
9 Rhabdoderma irregular
867.82 651.18 1209.82
10 Rhabdoderma lineare 413.65 324.78 533.65
11 Rhabdogloea fascicularis
1420.8 1255.07 1555.88
12 Rhabdogloea smithii
20300.37 19240.8 20768.98
13 Microcystis aeruginosa
3603.63 3757.13 4301.63
14 Chroococcus disperses
4724.94 4171.14 5334.15
15 Chroococcus dispersus var. minor
4152.08 3764.9 4590.08
16 Chroococcus limneticus
1185.05 1005.77 1474.05
17 Chroococcus turgidus
1170.16 1009.27 1284.2
18 Gomphosphaeria aponina
37792.22 36521.99 39088.83
19 Spirulina subsalsa
40750.11 37024.92 42018.74
20 Spirulina nordstedtii
38358.4 35577.78 39671.08
21 Spirulina subtilissima
2259.56 2241.1 3861.23
22 Spirulina laxissima 1832.76 1901.92 2565.09
23 Pseudanabaena catenata
1634.5 1649 2467.42
24 Planktolyngbya contorta 1838.47 1644.05 2018.14
25 Pseudanabaena galeata
2338.18 2151.66 2704.98
26 Oscillatoria subbrevis
3478.13 3188.87 3821.97
27 Oscillatoria limnetica
16495.92 15691.4 17228.5
28 Oscillatoria rubescens
28315.68 26456.24 29066.02
29 Oscillatoria acutissima
108.37 85.8 242.27
30 Cyanarcus hamiformis
8852.51 8316.51 9318.79
31 Anabaenopsis raciborskii
35155.48 33211.39 36309.34
32 Anabaenopsis arnoldii
3290.73 3213.38 3901
33 Anabaenopsis circularis
283.3 212.06 404.23
34 Anabaenopsis Tanganyika
2152.19 1981.33 2507.89
35 Navicula cryptocephala
299.45 240.1 409.46
36 Navicula peregrine
127.6 85.39 197.536
Int. J. Life. Sci. Scienti. Res., VOL 2, ISSUE 6
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37 Navicula tripunctata
185.46 154.16 266.12
38 Navicula phyllepta 2654.14 2548.63 2969.27
39 Craticula halophila
1327.03 1216.92 1558.98
40 Craticula cuspidate
45702.66 41648.81 48377.66
41 Cymbella lanceolata
2480.27 2228.71 2731.72
42 Pleurosigma angulatum
492.5 386.43 613.5
43 Amphora coffeaeformis
449.5 318.33 629.39
44 Nitzschia acicularis
587.8 439.2 732.92
45 Nitzschia frustulum
613.2 475.34 745.29
46 Nitzschia palea
4868.8 4479.54 5170.93
47 Nitzschia fruticosa
661.5 585.46 758.9
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International Journal of Life-Sciences Scientific Research (IJLSSR)
Open Access Policy
Authors/Contributors are responsible for originality, contents, correct
references, and ethical issues.
IJLSSR publishes all articles under Creative Commons
Attribution- Non-Commercial 4.0 International License (CC BY-NC).
https://creativecommons.org/licenses/by-nc/4.0/legalcode
How to cite this article:
Roy A, Roy R, Sarkar D, Roy M, Mitra A: Hydrological Parameters of East Kolkata Wetlands: Time Series Analysis. Int. J. Life. Sci.
Scienti. Res., 2016; 2(6): 692-699. DOI:10.21276/ijlssr.2016.2.6.8
Source of Financial Support: Nil, Conflict of interest: Nil

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Hydrological Parameters of East Kolkata Wetlands: Time Series Analysis

  • 1. Int. J. Life. Sci. Scienti. Res., 2(6): 692-699 NOVEMBER- 2016 http://ijlssr.com Copyright © 2015-2016 International Journal of Life-Sciences Scientific Research Page 692 Hydrological Parameters of East Kolkata Wetlands: Time Series Analysis Atanu Roy1* , Rima Roy2 , Diganta Sarkar1 , Madhumita Roy1 and Abhijit Mitra3 1 Department of Biotechnology, Techno India University, Salt Lake Campus Kolkata, India 2 Department of Microbiology, Techno India University, Salt Lake Campus, Kolkata, India 3 Department of Marine Science, University of Calcutta, 35 B.C. Road, Kolkata, India * Address for Correspondence: Atanu Roy, Research Scholar, Department of Biotechnology, Techno India University, Salt lake Campus, Kolkata, India Received: 21Sept 2016/Revised: 29 Sept 2016/Accepted: 19 Oct 2016 ABSTRACT- Three decades data (1984 – 2015) was used to study the effect of surface water temperature, pH, dissolved oxygen, nitrate, phosphate and silicate on chlorophyll a concentration in three water bodies meant for fish culture (locally known as Bheries) in East Kolkata Wetlands. The data revealed significant spatio-temporal variations (p < 0.01). The increasing trend of temperature, nitrate and phosphate reflects the effect of intense urbanization at local level. The pronounced variation of dissolved oxygen and chlorophyll a (decreasing trend) may be attributed to increased load of sewage in the selected water bodies, which has posed an adverse impact on the phytoplankton standing stock as revealed through decreasing chlorophyll a trend. Key-words- East Kolkata Wetlands (EKW), Phytoplankton, Chlorophyll a, Nutrients, ANOVA -------------------------------------------------IJLSSR----------------------------------------------- INTRODUCTION Wetlands are one of the most productive ecosystems of the planet Earth [1-3] . East Kolkata Wetlands (EKW) present in the maritime state of West Bengal (India) has been designated as Ramsar Site and is noted for its high nutrient level and considerable fish production [4-6] . Many reports of EKW include management programmes to conserve this well known wetland which spans over the entire eastern outskirts of the metropolitan city of Kolkata [6-9] . However, very few works documented the inter-relationship between relevant hydrological parameters and phytopigment (chlorophyll a) which may serve as proxy to primary productivity of the aquatic system. The present paper analysis the dependency of chlorophyll a on the nutrient levels in the aquatic phase of EKW. For this, a data bank of three decades (1984–2015) has been relied upon to interpret the result. This data bank is the average of three seasons in the three sampling bheries selected in EKW and is retrieved from the archives of Department of Marine Science, University of Calcutta. Access this article online Quick Response Code: Website: www.ijlssr.com DOI: 10.21276/ijlssr.2016.2.6.8 MATERIALS AND METHODS Study Site EKW is situated at the eastern outskirts of the mega city of Kolkata, India (22o 25' to 22o 40' N and 88o 20' to 88o 35' E). The fish ponds of the area offers important ecosystem services like flood control, recycling of municipal wastes and effluents (generated from urban and semi urban areas), aesthetic beauty, fish production, livelihood, etc. EKW is extremely dynamic from the point of view of primary production and is a unique reservoir of a galaxy of phytoplankton, which serve as the foundation stone of food chain existing in the system. The present sampling bheries were selected at Captain Bheri (22o 33’06.7” N to 88o 24’38.5” E), Munshir Bheri (22o 34’18.3” N to 88o 26’22.9” E) and Natur Bheri (22o 32’49.9” N to 88o 25’30.1” E) with the aim to analyze the chlorophyll a and few relevant physio-chemical variables (like surface water temperature, pH, dissolved oxygen, nitrate, phosphate and silicate). Analysis of Hydrological Parameters Surface water temperature was recorded by using a 0o - 100o C mercury thermometer and pH of the surface water was measured by using a portable pH meter (sensitivity = ±0.01). The dissolved oxygen was measured by a DO meter in the field and subsequently cross-checked in the laboratory by Winkler’s method. Surface waters for nutrient analyses were collected in clean Research Article (Open access)
  • 2. Int. J. Life. Sci. Scienti. Res., VOL 2, ISSUE 6 http://ijlssr.com Copyright © 2015-2016 International Journal of Life-Sciences Scientific Research Page 693 TARSON bottles and were transported to the laboratory in ice-freeze condition. Triplicate samples were collected from the same collection site to maintain the quality of the data. The standard spectrophotometric method [10] was adopted to determine the nutrient concentration in surface water. Nitrate was analysed by reducing it to nitrite by means of passing the sample with ammonium chloride buffer through a glass column packed with amalgamated cadmium filings and was finally treated with sulphanilamide solution. The resultant diazonium ion was coupled with N - (1-napthyl)- ethylene diamine to give an intensely pink azo dye. Determination of the phosphate was carried out by treatment of an aliquot of the sample with an acidic molybdate reagent containing ascorbic acid and a small proportion of potassium antimony tartarate. Dissolved silicate was determined by treating the sample with acidic molybdate reagent. Pigment Analysis For pigment analysis, 1 litre of surface water was collected from each of the sampling sites and filtered through a 0.45 µm Millipore membrane fitted with a vacuum pump. The residue along with the filter paper was dissolved in 90% acetone and was kept in a refrigerator for about 24 hours in order to facilitate the complete extraction of the pigment. The solution was then centrifuged for about 20 minutes at 5000 rpm and the supernatant solution was considered for the determination of the chlorophyll pigment by recording the optical density at 750, 664, 647 and 630 nm with the help of Systronics UV-visible spectrophotometer model No-117 (micro controller based). All the extinction values were corrected for a small turbidity blank by subtracting the 750 nm signal from all the optical densities, and finally the phytoplankton pigment was estimated as per the following expression of Jeffrey and Humphrey (1975) [11] . Chl a = 11.85 OD664 – 1.54 OD647 - 0.08 OD630 All the extinction values were corrected for a small turbidity blank by subtracting the 750 nm signal from all the absorbance values. The values obtained from the equations were multiplied by the volume of the extract (in ml) and divided by the volume of the water (in litre) filtered to express the chlorophyll a content in mg.m-3 . All the analyses were done in triplicate (on the basis of collection of three samples from the same site) in order to ensure the quality of the data. STATISTICAL ANALYSIS It is the final phase in which statistical tools were applied to understand the spatio-temporal variation in the study site. For this, ANOVA was performed to evaluate statistically significant differences between years and selected bheries. RESULTS AND DISCUSSION Surface water temperature, pH, dissolved oxygen, nutrients level and chlorophyll a concentration recorded in the three sampling sites are shown in Figures 1-7. All these hydrological parameters were subjected to ANOVA and significant variations (p < 0.01) were observed between years and bheries (Tables 1-7). This may be due to different standing stock of phytoplankton present in the selected bheries (Annexure 1). The profiles of the selected hydrological parameters are discussed separately. Temperature Surface water temperature ranged from 29.2o C (in Natur Bheri during 1984) to 32o C (in Munshir Bheri during 2015) (Figure 1). There exist pronounced variations in surface water temperature between years and bheries (p < 0.01) as depicted in Table 1. The variation between the three selected bheries may be attributed to different degrees of exposure to solar radiations although they are located in the same geographical locale of EKW. The shades provided by the vegetations around the selected bheries may be related to such local level variations. The yearly variation pointed out towards the gradual warming of the atmosphere due to climate change induced warming in this tropical belt as pointed out by earlier researchers [2-3, 12-13] . Figure 1: Decadal variations of surface water temperature Table 1: ANOVA result for Surface Water Temperature Source of Variation for Surface water temperature SS df MS F P-value F crit Between Years 29.37 31 0.95 23.70 3.97 × 10-24 1.64 Between Bheries 2.34 2 1.17 29.30 1.1 × 10-09 3.15 Error 2.48 62 0.04 Total 34.19 95
  • 3. Int. J. Life. Sci. Scienti. Res., VOL 2, ISSUE 6 http://ijlssr.com Copyright © 2015-2016 International Journal of Life-Sciences Scientific Research Page 694 pH The pH of the waters in the study sites ranged from 6.7 (in Captain Bheri during 1990) to 8.2 (in Captain Bheri during 2015) (Figure 2). It is interesting to note that unlike other parameters, the pH of the aquatic phase in the selected bheries of the bheries of EKW did not exhibit any pronounced variation (Table 2). This is due to the fact that all these bheries are managed by the local people who use lime on regular basis to maintain the acid-base balance of the water bodies. Table 2: ANOVA result for pH Source of Variation for pH SS df MS F P-value F crit Between Years 2.52 31 0.08 1.31 0.18 1.64 Between Bheries 0.09 2 0.04 0.70 0.50 3.15 Error 3.86 62 0.06 Total 6.48 95 Figure 2: Decadal variations of pH Dissolved Oxygen Dissolved Oxygen (DO) ranged from 3.92 ppm (in Munshir bheri during 2003) to 6.77 ppm (in Munshir bheri during 2009) (Figure 3). There exist pronounced variations in DO between years and bheries (p < 0.01) as depicted in Table 3. The variation between the three selected bheries may be attributed to different degrees of exposure to solar radiations although they are located in the same geographical locale of EKW. The variation is the outcome of different degree of photosynthetic rate due to difference in the standing stock of phytoplankton (Annexure 1). The yearly variation (decreasing trend) may be the effect of increased load of sewage with the rapid pace of urbanization in and around EKW. The gradual decrease of DO in the study area was also pointed out by earlier researchers [14] . Table 3: ANOVA result for Dissolved Oxygen Source of Variation for Dissolved Oxygen SS df MS F P-value F crit Between Years 10.12 31 0.33 4.44 2.99 × 10-07 1.64 Between Bheries 6.51 2 3.26 44.28 1.14 × 10-12 3.15 Error 4.56 62 0.07 Total 21.19 95 Figure 3: Decadal variations of Dissolved Oxygen Nutrients The nitrate concentration varied from 24.17 g at l-1 (in Munshir bheri during 1984) to 55.89 g at l-1 (in Natur bheri during 2015) (Figure 4) and the phosphate concentration ranged from 2.51 g at l-1 (in Munshir bheri during 1984) to 6.73 g at l-1 (in Natur bheri during 2015) (Figure 5). These two nutrients are primarily generated from municipal waste discharge, which is gradually increasing on account of rapid pace of industrialization and urbanization [4, 15-16] . Both of them showed pronounced variation between years and bheries (p < 0.01) (Table 4 and 5). The silicate concentration ranged from 54.48 g at l-1 (in Munshir bheri during 2014) to 102.93 g at l-1 (in Munshir bheri during 2009) (Figure 6). Silicate which is primarily produced due to churning action of the underlying pond substratum and regulated by phytoplankton community [16-17] also exhibited pronounced spatial and temporal variations (Table 6). The spatial variation is regulated by phytoplankton stock in the selected ponds and the temporal variation is keenly related to erosion and other physical factors that have increased in recent times.
  • 4. Int. J. Life. Sci. Scienti. Res., VOL 2, ISSUE 6 http://ijlssr.com Copyright © 2015-2016 International Journal of Life-Sciences Scientific Research Page 695 Table 4: ANOVA result for Nitrate Source of Variation for Nitrate SS df MS F P-value F crit Between Years 3933.01 31 126.87 59.39 1.47 × 10-35 1.64 Between Bheries 131.92 2 65.96 30.88 4.96 × 10-10 3.15 Error 132.46 62 2.14 Total 4197.39 95 Figure 4: Decadal variations of Nitrate Table 5: ANOVA result for Phosphate Source of Variation for phosphate SS df MS F P-value F crit Between Years 39.62 31 1.28 6.21 5.8 × 10-10 1.64 Between Bheries 21.83 2 10.91 53.04 3.74 × 10-14 3.15 Error 12.76 62 0.21 Total 74.20 95 Figure 5: Decadal variations of Phosphate Table 6: ANOVA result for Silicate Source of Variation for Silicate SS df MS F P-value F crit Between Years 5566.70 31 179.57 7.411 1.47 × 10-11 1.64 Between Bheries 2245.80 2 1122.90 46.34267 4.91 × 10-13 3.15 Error 1502.28 62 24.23 Total 9314.77 95 Figure 6: Decadal variations of Silicate Chlorophyll a Chlorophyll a serves as proxy to phytoplankton standing stock and ranged from 4.19 mg.m-3 (in Natur Bheri during 2012) to 12.29 mg.m-3 (in Munshir Bheri during 1984) in the study area (Figure 7). The pronounced spatial and temporal variations (Table 7) of the phytopigment may be the result of variation in phytoplankton population, which again is controlled by nutrient level of the ambient aquatic phase. The dependency of phytoplankton on nutrient is revealed from the expression (CH2O)108(NH3)16H3PO4 and in case of diatoms it is slightly modified as (CH2O)108(NH3)16H3PO4(SiO4)40 [18] . These constituents of phytoplankton suggest the necessity and subsequent utilization of nitrate, phosphate and silicate from the ambient waters [19- 23] . The significant negative correlation between nutrient level and phytoplankton speaks in favour of the uptake of nutrients by the phytoplankton, as these nutrients act as building blocks of phytoplankton. Chlorophyll a, the primary constituent of phytoplankton needs special importance with respect to maintenance of ecological stability, primary production and energy flow through the food chains spun in the water bodies of EKW through long evolutionary period of time. The decreasing trend of chlorophyll a is a warning signal in context to primary production of the system as the dynamics of energy flow in any aquatic system is regulated by phytoplankton standing stock with chlorophyll a, as its
  • 5. Int. J. Life. Sci. Scienti. Res., VOL 2, ISSUE 6 http://ijlssr.com Copyright © 2015-2016 International Journal of Life-Sciences Scientific Research Page 696 major constituents. Hence regular monitoring and conservation of these free floating tiny producer community is extremely important to upgrade the ecological health of the system. The dependency of phytoplankton on nutrient levels demands the regulation of waste discharge in the EKW so as to optimize the growth of phytoplankton. The local economy and livelihood of EKW is primarily pisci-centric and therefore the primary producer community needs to be conserved in order to generate a sustainable secondary production. Table 7 ANOVA result for Chlorophyll a Source of Variation for Chlorophyll a SS df MS F P-value F crit Between Years 104.29 31 3.36 26.52 1.76 × 10-25 1.64 Between Bheries 253.92 2 126.96 1000.96 6.44 × 10-48 3.15 Error 7.86 62 0.13 Total 366.07 95 Figure 7: Decadal variations of Chlorophyll a CONCLUSION The time series analysis on the selected hydrological parameters of EKW highlights few core findings as listed below: Significant variations of hydrological parameters exist between the selected bheries (except aquatic pH), which might be due to different nutrient supply (preferably through sewage) to the bheries. The uniformity of aquatic pH may be attributed to application of lime on regular basis, which is a common practice of the beneficiaries of the bheries of EKW. Chlorophyll a, which is proxy to the productivity of the bheries oscillates as a function of nutrient load of the aquatic phase. Hence, regulation of nutrients is of utmost importance to maintain the productivity of the bheries located in the EKW. Annexure 1: Standing stock of phytoplankton species in the selected sites of East Kolkata Wetlands S. No. Phytoplankton Species Standing Stock (No./L) Captain Bheri Munshir Bheri Natur Bheri 1 Merismopedia trolleri 10132.49 8952.38 12632.06 2 Merismopedia glauca 9133.41 8797.29 10700.41 3 Merismopedia minima 2384.49 2250.07 2762.49 4 Merismopedia punctata 33519.31 31950.14 35252.09 5 Synechococcus elongatus 4316.18 4158.55 4699.3 3522.94 3404.25 4046.49
  • 6. Int. J. Life. Sci. Scienti. Res., VOL 2, ISSUE 6 http://ijlssr.com Copyright © 2015-2016 International Journal of Life-Sciences Scientific Research Page 697 6 Synechocystis aquatilis 7 Coelosphaerium pallidum 225131.2 218202.63 227153.21 8 Rhabdogloea rhaphidioides 23381.79 21894.74 24735.6 9 Rhabdoderma irregular 867.82 651.18 1209.82 10 Rhabdoderma lineare 413.65 324.78 533.65 11 Rhabdogloea fascicularis 1420.8 1255.07 1555.88 12 Rhabdogloea smithii 20300.37 19240.8 20768.98 13 Microcystis aeruginosa 3603.63 3757.13 4301.63 14 Chroococcus disperses 4724.94 4171.14 5334.15 15 Chroococcus dispersus var. minor 4152.08 3764.9 4590.08 16 Chroococcus limneticus 1185.05 1005.77 1474.05 17 Chroococcus turgidus 1170.16 1009.27 1284.2 18 Gomphosphaeria aponina 37792.22 36521.99 39088.83 19 Spirulina subsalsa 40750.11 37024.92 42018.74 20 Spirulina nordstedtii 38358.4 35577.78 39671.08 21 Spirulina subtilissima 2259.56 2241.1 3861.23 22 Spirulina laxissima 1832.76 1901.92 2565.09 23 Pseudanabaena catenata 1634.5 1649 2467.42 24 Planktolyngbya contorta 1838.47 1644.05 2018.14 25 Pseudanabaena galeata 2338.18 2151.66 2704.98 26 Oscillatoria subbrevis 3478.13 3188.87 3821.97 27 Oscillatoria limnetica 16495.92 15691.4 17228.5 28 Oscillatoria rubescens 28315.68 26456.24 29066.02 29 Oscillatoria acutissima 108.37 85.8 242.27 30 Cyanarcus hamiformis 8852.51 8316.51 9318.79 31 Anabaenopsis raciborskii 35155.48 33211.39 36309.34 32 Anabaenopsis arnoldii 3290.73 3213.38 3901 33 Anabaenopsis circularis 283.3 212.06 404.23 34 Anabaenopsis Tanganyika 2152.19 1981.33 2507.89 35 Navicula cryptocephala 299.45 240.1 409.46 36 Navicula peregrine 127.6 85.39 197.536
  • 7. Int. J. Life. Sci. Scienti. Res., VOL 2, ISSUE 6 http://ijlssr.com Copyright © 2015-2016 International Journal of Life-Sciences Scientific Research Page 698 37 Navicula tripunctata 185.46 154.16 266.12 38 Navicula phyllepta 2654.14 2548.63 2969.27 39 Craticula halophila 1327.03 1216.92 1558.98 40 Craticula cuspidate 45702.66 41648.81 48377.66 41 Cymbella lanceolata 2480.27 2228.71 2731.72 42 Pleurosigma angulatum 492.5 386.43 613.5 43 Amphora coffeaeformis 449.5 318.33 629.39 44 Nitzschia acicularis 587.8 439.2 732.92 45 Nitzschia frustulum 613.2 475.34 745.29 46 Nitzschia palea 4868.8 4479.54 5170.93 47 Nitzschia fruticosa 661.5 585.46 758.9 REFERENCES [1] Ghermandi, A., Van den Bergh, J.C.J.M., Brander & L.M., Nunes, P.A.L.D. The economic value of wetland conservation and creation: a meta-analysis. [Working Paper 79]. Fondazione Eni Enrico Mattei, Milan, Italy, 2008. [2] Mitra A. In: Sensitivity of Mangrove ecosystem to changing Climate. Springer; 2013: pp. 323. [3] Mitra, A. & Zaman, S. Basics of Marine and Estuarine Ecology, Springer India, 2016. [4] Roy, A., Banerjee, A., Roy, R., Biswas, S., Roy, M. & Mitra, A. Decadal variation of major nutrients in the aquatic phase of East Kolkata Wetlands. International Journal of Innovative Research in Science, Engineering and Technology, 2016, 5(3), pp. 2950-2957. [5] Tyrrel, S.F., “The Microbiological Quality of Water Used for Irrigation.”, Irrigation News, 1999, 27, pp. 39-42. [6] Kundu. N., Pal, M. & Saha S. East Kolkata Wetlands: A resource recovery system through productive activities. Proceedings of Taal 2007: The 12th World Lake Conference, 2008, pp. 868-881. [7] Pradhan, A., Bhaumik, P., Das, S., Mishra, M., Khanam, S., Hoque, B.A., Mukherjee, I., Thakur, A.R. & Ray Chaudhuri, S. Phytoplankton diversity as indicator of water quality for fish cultivation. American Journal of Environmental Science, 2008, 4, 406-411. [8] Raychaudhuri, S., Salodkar, S., Sudarshan, M. & Thakur, A. Integrated Resource Recovery at East Calcutta Wetland: How Safe is these?. American Journal of Agricultural and Biological Science, 2007, 2(2), pp. 75-80. [9] Ray Chaudhuri, S., Mishra, M., Nandy, P. & Thakur, A.R. Waste management: A case study of ongoing traditional practices at east Calcutta wetland. American Journal of Agricultiural and Biological Sciences, 2008, 3, pp. 315-320. [10]Strickland, J.D.H. & Parsons, T.R. A practical handbook of seawater analysis. Fisheries Research Board of Canada, Ot- tawa, 1972, 310. [11]Jeffrey, S.W. & Humphrey, G.R. New spectrophotometric equations for determining chlorophylls a, b. c, and c2 in higher plants, algae and natural phytoplankton. Biochem. Physiol. Pflanz., 1975, 167, pp. 191-194. [12]Mitra, A., Banerjee, K., Sengupta, K. & Gangopadhyay. A. Pulse of climate change in Indian Sundarbans: A myth or re- ality?. National Academy of Science Letter, 2009, 32 (1 & 2), pp. 19-25. [13]Mitra, A. & Zaman, S. Carbon Sequestration by Coastal Floral Community. The Energy and Resources Institute (TERI), TERI Press, India, 2014. [14]Roy, A., Amin, G., Agarwal, S. K., Pramanick, P., Banerjee, A., Roy, M. & Mitra, A. Water Quality Index (WQI) of East Kolkata Wetland using Dissolved Oxygen as Proxy. International Advanced Research Journal in Science, Engineering and Technology, 2016, 3(2), pp. 22-24. [15]Luger, M. & Brown, C. The impact of treated sewage effluent on urban rivers. An ecological, social and economic Perspective, 1999. [16]Conley, D.J. Terrestrial ecosystems and the global biogeochemical silica cycle. Global Biogeochemical Cycles, 2002, 16, pp. 1121–1129. [17]Greenwood, J.E., Truesdale, V.W. & Rendell, A.R. Biogenic silica dissolution in seawater-in vitro chemical kinetics. Proggress in Oceanography, 2001, 48, pp. 1–23. [18]Riley & Chester. Introduction to Marine Chemistry. Academic Press. INC., 1971. [19]Mitra, A., Banerjee, K. & Bhattacharyya, D.P. A study on phytopigment spectrum in relation to anthropogenic pressure around the Indian Mangrove Ecosystem. Indian Science Cruiser, 2003, 17(3), pp. 29-36. [20]Mitra, A., Banerjee, K., Choudhury, A. & Bhattacharyya, D.P. Taxonomy of coastal phytoplankton inhabiting polluted waters. Ecology of Polluted Waters (Editor Arvind Kumar, IJEE), 2002, chapter-78.
  • 8. Int. J. Life. Sci. Scienti. Res., VOL 2, ISSUE 6 http://ijlssr.com Copyright © 2015-2016 International Journal of Life-Sciences Scientific Research Page 699 [21]Banerjee, K., Mitra, A., Bhattacharyya, D.P. & Choudhury, A. Role of nutrients on phytoplankton diversity in the north–east coast of the Bay of Bengal. Ecology and Ethology of Aquatic Biota (Editor Arvind Kumar, IJEE), 2002, chapter-6, pp. 102-109. [22]Banerjee, K., Mitra, A., Bhattacharyya, D.P. & Choudhury, A. A preliminary study of phytoplankton diversity and water quality around Haldia port-cum-industrial complex. Proceedings of the National Seminar on Protection of the Environment - An urgent need IPHE, Kolkata. 2000. [23]Lilli, C.M. & Parsons, T.R. Biological Oceanography – An Introduction, 2nd Edition, The Open University Set Book. 1997. International Journal of Life-Sciences Scientific Research (IJLSSR) Open Access Policy Authors/Contributors are responsible for originality, contents, correct references, and ethical issues. IJLSSR publishes all articles under Creative Commons Attribution- Non-Commercial 4.0 International License (CC BY-NC). https://creativecommons.org/licenses/by-nc/4.0/legalcode How to cite this article: Roy A, Roy R, Sarkar D, Roy M, Mitra A: Hydrological Parameters of East Kolkata Wetlands: Time Series Analysis. Int. J. Life. Sci. Scienti. Res., 2016; 2(6): 692-699. DOI:10.21276/ijlssr.2016.2.6.8 Source of Financial Support: Nil, Conflict of interest: Nil