Indian Journal of Geo-Marine Science
Vol. 45(3), March 2016, pp. 410-415
Inter-annual variation of salinity in Indian Sundarbans
Subrata Trivedi1*, Sufia Zaman2, Tanmay Ray Chaudhuri2, Prosenjit Pramanick2, Pardis Fazli3, Gahul Amin4 &
Abhijit Mitra5
1
Department of Biology, Faculty of Science, University of Tabuk, Ministry of Higher Education, Kingdom of Saudi Arabia
2
Department of Oceanography, Techno India University, Salt Lake Campus, Kolkata - 700 091, India
3
Department of Biological and Agricultural Engineering, University Putra, Selangor, Malaysia
4
Department of Physics, Netaji Subhas Open University (Kalyani Campus), Kalyani, India
5
Department of Marine Science, University of Calcutta, 35, B. C. Road, Kolkata-700 019, India
* [ E-mail:
[email protected]]
Received 09 July 2014; revised 01 August 2014
Using secondary data coupled with real time data, inter-annual variation of surface water salinity in three sectors
(western, central and eastern) of Indian Sundarbans during 1984-2013 was studied. Salinity of the aquatic system in the
present deltaic complex, situated in the inshore region of Bay of Bengal is primarily regulated by anthropogenic factors
(like barrage discharge, run-off from the adjacent landmasses etc.) and natural factors (like siltation, plate tectonics
etc.). Surface water salinity has decreased by 0.63 and 0.86 psu per year in the western and eastern sectors respectively,
whereas in the central sector, it has increased 1.09 psu per year. Another important objective of the study is to
investigate the future salinity (in 2043, 30 years after 2013) in the three sectors of the deltaic complex considering the
present data set of 30 years as the baseline. Our forecast through exponential smoothening method reveals an alarming
hypersaline environment in the central Indian Sundarbans.
[Keywords: Surface water salinity, Indian Sundarbans, inter-annual variation]
Introduction
India has been identified as one of the 27
countries, which are the most vulnerable to the
impacts of global warming induced sea level
rise 1. Siltation of the Bidhyadhari River since
the late 15th century has decreased the fresh
water flow in the central sector of Indian
Sundarbans to a considerable level2,3,4,5. In
addition to this, there are reports of rising sea
level @3.14 mm per year in Indian Sundarbans6,
which is also a primary factor influencing the
spatio-temporal variation of salinity. UNESCO7
reported that 45-cm rise in sea level (likely by
the end of the 21st century, according to the
IPCC), combined with other forms of
anthropogenic stress on the Sundarbans could
lead to the destruction of 75% of the Sundarban
mangroves. Diamond Harbour, an area just
adjacent to the northern boundary of Indian
Sundarbans exhibit a net sea level rise of 5.74
mm/year (considering the subsidence value),
which is much higher compared to several others
coastal cities of India like Mumbai (1.20
mm/year), Kochi (1.75 mm/year) and
Vishakhapatnam (1.09 mm/year)8 . Present study
aims to analyze the decadal variation of salinity
since 1984 in Indian Sundarbans region located
at the apex of Bay of Bengal. It has great
relevance as salinity is the primary criterion
regulating the distribution of mangrove species
and their growth1,3,4,9,10,11. The entire biological
spectrum of deltaic Sundarbans along with the
livelihood of the local people is also influenced
by salinity of the ambient media.
Material and Method
Deltaic complex of Indian Sundarbans has an
area of 9,630 sq. km and houses about 102
islands 12. 18 sampling sites were selected, 6
each in the western, central and eastern sectors
of Indian Sundarbans (Table 1, Fig. 1). Three
sectors of Indian Sundarbans are demarcated on
the basis of our primary surface water salinity
data of 24 years2 and secondary data (of 27
years)4.
TRIVEDI et al.: INTER-ANNUAL VARIATION OF SALINITY IN INDIAN SUNDARBANS
411
Table 1: Sampling stations in the western, central and eastern sectors of Indian Sundarbans in the lower Gangetic delta
region
Sectors
Sampling stations
Latitude
Longitude
Western sector
Central sector
Eastern sector
Stn. 1
Chemaguri (W1)
21038'25.86"N
Stn. 2
Saptamukhi (W2)
21040'02.33"N
88023'27.18"E
Stn. 3
Jambu Island (W3)
21035'42.03"N
88010'22.76"E
Stn. 4
Lothian (W4)
21038'21.20"N
88020'29.32"E
Stn. 5
Harinbari (W5)
21044'22.55"N
88004'32.97"E
Stn. 6
Prentice Island (W6)
21042'47.88"N
88017'55.05"E
Stn. 7
Thakuran Char (C1)
21049'53.17"N
88031'25.57"E
Stn. 8
Dhulibasani (C2)
21047'06.62"N
88033'48.20"E
Stn. 9
Chulkathi (C3)
21041'53.62"N
88034'10.31"E
Stn. 10
Goashaba (C4)
21043'50.64"N
88046'41.44"E
Stn. 11
Matla (C5)
21053'15.30"N
88044'08.74"E
Stn. 12
Pirkhali (C6)
22006'00.97"N
88051'06.04"E
Stn. 13
Arbesi (E1)
22011'43.14"N
89001'09.04"E
Stn. 14
Jhilla (E2)
22009'51.53"N
88057'57.07"E
Stn. 15
Harinbhanga (E3)
21057'17.85"N
88059'33.24"E
Stn. 16
Khatuajhuri (E4)
22003'06.55"N
89001'05.33"E
Stn. 17
Chamta (E5)
21053'18.56"N
88057'11.40"E
Stn. 18
Chandkhali (E6)
21051'13.59"N
89000'44.68"E
Fig. 1- Location of sector-wise sampling stations in
Indian Sundarbans; the red colour indicates the
mangrove vegetation
A data set of 30 years in this first order
analysis as per the minimum standard norm of
climate related researches is considered in this
study. World Meteorological Organization
and the Intergovernmental Panel on Climate
change (IPCC)13 define “climate” as the
average state of the weather over time with the
period generally being 30 years (although for
88008'53.55" E
some marine climate parameters such as
storminess, longer averages are required)14.
More than two decades of data (1984 2013) were compiled from the archives of the
Department of Marine Science, University of
Calcutta for this study. A number of studies on
different aspects of the Sundarban complex
have been published over the years, which
include description of the data (and methods)
at different times for more than two
decades2,4,11,15,16,17,18,19,20,21,22. Real time data
(through field sampling by the authors) were
also collected simultaneously since 1998 from
18 sampling stations in the lower Gangetic
region during high tide condition to assure
quality and continuity to the data bank. For
each observational station, at least 30 samples
were collected within 500 m of each other and
the mean value of 30 observations was
considered for statistical interpretations.
In situ surface water salinity was estimated
from the selected stations during high tide
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INDIAN J MAR SCI VOL 45,No.3, MARCH 2016
condition with the help of a refractometer
(VEEGEE STX-3). For cross-checking, water
samples from the selected stations were
brought to the laboratory in ice-freezed
condition and analyzed for chlorinity by
argentometric method and converted into
salinity through standard equation.
Time series analysis was performed to
forecast the trend of surface water salinity on
the basis of the past thirty year’s real time
data. Exponential smoothing method produces
maximum-likelihood estimates and can reflect
the future trend of the selected variable. This
approach was adopted to forecast the values
for surface water salinity in the ambient media
of the sampling station till 2043.
Result
It is interesting to note the significant
spatio-temporal variation of surface water
salinity in the study region. In the western
sector, the salinity decrease ranged from 0.58
psu/ year (at Jambu Island) to 1.46 psu/ year
(at
Harinbari).
Although
station
2
(Saptamukhi) is situated in the western sector,
but the salinity has increased by 0.51 psu/year
(Fig. 2). Considering all the six stations in the
western sector, the decrease of salinity is 0.63
psu/year, which represents a decrease of 7.50
psu per decade. Salinity has decreased from
17.30 % (in Jambu Island) to 43.76 % (in
Harinbari) over a period of 30 years (Fig. 2).
Fig. 3- Future trend of surface water salinity in western
Indian Sundarbans
Central sector presents a completely reverse
picture in terms of aquatic salinity.
Irrespective of stations, salinity has increased
(Fig. 4) between the range 1.05 psu/ year (in
Chulkathi) to 1.12 psu/ year (in Matla and
Pirkhali). Considering the salinity values of
selected six stations, the increase is 1.09
psu/year, which is equivalent to 13.05
psu/decade. Percentage of salinity increase in
this sector range from 31.49 psu (in Chulkathi)
to 33.64 psu (in Matla) with an average of
increase 32.62 % over a period of 30 years
(Fig. 4).
Fig. 4- Spatio-temporal variation of salinity in central
Indian Sundarbans
Fig. 2- Spatio-temporal variation of salinity in western
Indian Sundarbans
The exponential smoothing method that
produces maximum-likelihood estimate of the
variable predicts a salinity value of 13.05 psu
in 2043 (Fig. 3), which is a decrease of 38.4%
since 1984 (over a span of 60 years).
Considering the observed data set of 30
years (1984 – 2013), we predict that salinity
will be around 36 psu after a period of 30
years in the central sector of Indian
Sundarbans (Fig. 5), which is an indication of
alarming hypersaline condition (a rise by
67.1%) in 2043 in this sector.
TRIVEDI et al.: INTER-ANNUAL VARIATION OF SALINITY IN INDIAN SUNDARBANS
Fig. 5- Future trend of surface water salinity in central
Indian Sundarbans
Discussion
The results of the long term observed data
on surface water salinity clearly confirms
significant spatio- temporal variations of the
salinity in the study region (p<0.01). Basically
a bell- shaped salinity profile can be a
representation for the region with a
hypersaline environment in the central sector
(mean salinity = 25.43 ± 2.24 psu) between
two hyposaline sectors viz. western (mean
salinity = 19.46 ± 3.46 psu) and eastern (mean
salinity = 13.85 ± 1.48 psu).
35.00
Fig. 6- Spatio-temporal variation of salinity in central
Indian Sundarbans
On the basis of observed data, the
prediction of salinity in 2043 is around 7.54
psu (Fig. 7), which is decrease of 52.4%
considering a time span of 60 years.
Fig. 7- Spatio-temporal variation of salinity in eastern
Indian Sundarbans
30.00
25.00
Salinity (psu)
In the eastern sector, salinity has decreased
(Fig. 6), which ranges from 0.54 psu/year (in
Chamta) to 0.98 psu/year (in Jhilla).
Considering all the six stations in eastern
Indian Sundarbans, the average decrease of
salinity is 0.86 psu/year, equivalent to a
decadal decrease of 10.30 psu. Over a period
of 30 years, the average percentage decrease
of salinity is 25.66 psu (Fig. 6).
413
20.00
15.00
10.00
5.00
0.00
Series1
Series2
Series3
Series4
Series5
Series6
Series7
Series8
Series9
Series10
Series11
Series12
Series13
Series14
Series15
Series16
Series17
Series18
Series19
Series20
Series21
Series22
Series23
Series24
Series25
Series26
Series27
Series28
Series29
Series30
Fig. 8- Bell-shaped nature of salinity profile of Indian
Sundarbans based on 9200 readings; 30 series represent
30 consecutive years (1984 – 2013).
The bell- shaped salinity profile in the
present study region is not merely a
representation of salinity pattern, but it can be
a test bed for future climate related research
due to following reasons:
1. Presence of unique mangrove- centric
gene pool in the deltaic complex [from
microbes to Royal Bengal Tiger
(Panthera tigris tigris)] primarily
influenced by salinity.
2. Ecosystem services of the system to
about 4.2 million people dwelling in the
delta region.
3. No trans-boundary related research has
yet been taken up considering
Sundarbans as an integrated system,
although Farakka discharge (a transboundary anthropogenic component) has
great influence on the mangrove health
and livelihood of the integrated
Sundarbans.
Similar profile is also observed in the
Bangladesh part of Sundarbans, where three
salinity zones have been identified viz. less
saline zone (5- 15 ppt), Moderately Saline
Zone (15-25 ppt) and Strong Saline Zone (2530 ppt) based on degree of salinity23.
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INDIAN J MAR SCI VOL 45,No.3, MARCH 2016
Hyposaline environment of western Indian
Sundarbans may be attributed to Farakka
barrage discharge situated in the upstream
region of Ganga- Bhagirathi -Hooghly river
system. 10-year surveys (1999 to 2008) on
water discharge from Farakka dam revealed an
average discharge of (3.7 ± 1.15) × 103 m3s-1.
Higher discharge values were observed during
the monsoon with an average of (3.81 ± 1.23)
× 103 m3s-1, and the maximum of the order
4524 m3s-1 during freshet (September).
Considerably lower discharge values were
recorded during premonsoon with an average
of (1.18 ± 0.08) × 103 m3s-1, and the minimum
of the order 846 m3s-1 during May. During
postmonsoon discharge, values were moderate
with an average of (1.98 ± 0.97) × 103 m3s-1 as
recorded by earlier workers1.
Central sector represents a hypersaline
environment due to complete obstruction of
the fresh water flow from the upstream region
owing to Bidyadhari siltation since the late
15th century1,4,9,11. Matla estuary in the central
Indian Sundarban cannot be referred to as an
ideal estuary as there is no head on discharge
or dilution of the system with fresh water.
Thus Matla can be designated as a tidal
channel, whose survival depends on the tidal
flow from Bay of Bengal.
The eastern sector of Indian sector exhibits
a low saline profile possibly due to interconnection with several creeks and channels of
Harinbhanga estuary (the aquatic border of
India and Bangladesh Sundarbans) with the
tributaries of Bangladesh Sundarbans that arise
from Padma Meghna (Fig. 9) river system.
On the basis of significant spatio-temporal
variations of salinity and its future trend, we
recommend a trans-boundary coordinated
programme of long-term research linking
monitoring, process studies and numerical
modeling on the foundation of a diverse, interdisciplinary, multi-institution approach and
establishment of a strong institutional network
between researchers and decision makers of
India and Bangladesh.
Trans-boundary
channels/creeks
Fig. 9- Trans-boundary channels feeding freshwater to
eastern sector of Indian Sundarbans
References
1
Mitra A., In: Sensitivity of Mangrove ecosystem to
changing Climate. Springer DOI: 10.1007/978-81322-1509-7, (2013), pp. 323.
2
Mitra A., Banerjee K., Sengupta K &
Gangopadhyay A., Pulse of climate change in
Indian Sundarbans: a myth or reality. Natl. Acad.
Sci. Lett., 32 (2009) 1-7.
3
Mitra A., Sengupta K. & Banerjee, K., Standing
biomass and carbon storage of above-ground
structures in dominant mangrove trees in the
Sundarbans. For. Ecol. Mgmt., (ELSEVIER
DOI:10.1016/j.foreco.2011.01.012), (2011), Vol.
261(7), 1325 -1335.
4
Sengupta K., Roy Chowdhury M., Bhattacharya
S.B., Raha A., Zaman S. & Mitra A., Spatial
variation of stored carbon in Avicennia alba of
Indian Sundarbans. Disc. Nat., 3(8) (2013) 19-24.
5
Roy Chowdhury M., Zaman S., Jha CS., Sengupta
K. & Mitra A., Mangrove Biomass and Stored
Carbon in relation to Soil Properties: A Case Study
from Indian Sundarbans. Intl. J. Pharm. Res. Schol.,
3 (3) (2014) 58-69.
6
Hazra S., Ghosh T., Dasgupta R. & Sen G., Sea
level and associated changes in Sundarbans. Sci.
Cult., 68 (2002) 309 – 321.
7
UNESCO (2007) Case Studies on Climate Change
and World Heritage, Published by UNESCO World
Heritage Centre, 7, place de Fontenoy, 75352 Paris
07 SP France.
8
Tanaji G.J. & Vinod L.N., Response and
adaptability of mangrove habitats from Indian
subcontinent to changing climate. Ambio., 36 (4)
(2007) 328-334.
9
Chaudhuri A.B. & Choudhury A., Mangroves of the
Sundarbans, India. (1994), IUCN
10 Mitra A. & Banerjee K., In: Living Resources of the
Seas: Focus Sundarbans, Published by WWF-India.
(Ed: Col S. R. Banerjee), Canning Field Office, 24
Parganas(S), W.B. (2005), 96 pp.
11 Banerjee K., Sengupta K., Raha A. and Mitra A.,
Salinity based allometric equations for biomass
estimation of Sundarban mangroves. Biomass &
Bioenergy 56 (2013) 382-391.
TRIVEDI et al.: INTER-ANNUAL VARIATION OF SALINITY IN INDIAN SUNDARBANS
12
13
14
15
16
17
18
Mitra A., The Northeast coast of the Bay of Bengal
and deltaic Sundarbans. In: Seas at the Millennium
– An environmental evaluation, Chapter 62 (Editor:
Charles Sheppard, University of Warwick,
Coventry, UK), Elsevier Science, (2000), 143-157.
IPCC (Intergovernmental Panel on Climate
Change), 2007: Climate Change 2007: Impacts,
Adaptation and Vulnerability, Contribution of
Working Group II to the Fourth Assessment Report
of the Intergovernmental Panel on Climate Change.
Geneva, Switzerland. (2007), 976 pp.
Zhang KQ., Douglas BC. & Leatherman SP.,
Twentieth-century storm activity along the US east
coast. J. Clim., 13 (2000) 1748-1761.
Chakraborty S.K. & Choudhury A., Distribution of
fiddler crabs in Sundarbans mangrove estuarine
complex, India. Proceedings of National
Symposium
on
Biology,
Utilization
and
Conservation of Mangroves (1985), 467–472p.
Mitra A., Ghosh PB. & Choudhury A., A marine
bivalve Crassostrea cucullata can be used as an
indicator species of marine pollution. Proc. Natl.
Sem. Est. Mgmt., (1987), 177–180.
Mitra A., Choudhury A. & Zamaddar YA., Effects
of heavy metals on benthic molluscan communities
in Hooghly estuary. Proc. Zool. Soc., 45: (1992)
481-496.
Mitra A. & Choudhury A., Heavy metal
concentrations in oyster Crassostrea cucullata of
19
20
21
22
23
415
Henry’s Island, India. J. Eco. Biol., 6(2), (1994)
157-159.
Saha SB., Mitra A., Bhattacharyya SB. &
Choudhury A., Heavy metal pollution in Jagannath
canal, an important tidal water body of the north
Sundarbans aquatic ecosystem of West Bengal. Ind.
J. Env. Prot. (1999), 801–804.
Banerjee K., Mitra A., Bhattacharyya DP. &
Choudhury A., Role of nutrients on phytoplankton
diversity in the north–east coast of the Bay of
Bengal. In Ecology and Ethology of Aquatic Biota
(2002); (ed. Arvind Kumar), Daya Publishing
House, pp. 102–109.
Banerjee K., Mitra A. & Bhattacharyya DP.,
Phytopigment level of the aquatic subsystem of
Indian Sundarbans at the apex of Bay of Bengal.
Sea Explorers, 6 (2003) 39–46.
Mondal K., Mukhopadhyay SK., Biswas H, De TK.
& Jana T K., Fluxes of nutrients from the tropical
River Hooghly at the land–ocean boundary of
Sundarbans, NE Coast of Bay of Bengal, India. J.
Mar. Syst., 62 (2006), 9–21.
CEGIS (2006). Impacts of Sea Level Rise on
Landuse Suitability and Adaptation Options, Draft
Final Report. Submitted to the Ministry of
Environment and Forest, Government of
Bangladesh and United Nations Development
Programme (UNDP) by Centre for Environmental
Geographic Information Services (CEGIS), Dhaka.