Indian Journal of Geo Marine Sciences Vol. 47 (02), February 2018, pp. 443-452
Assessment of physio-chemical characteristics of coastal water in Parangipettai and Nagapattinam, South East Coast of India using
statistical approaches
Sankar1,2 R., Sachithanandam*2 V., Thenmozhi1 C., Mageswaran2 T. Sridhar2 R. & Ananthan1 G.
1Centre of Advanced in Marine Biology, Faculty of Marine Sciences, Annamalai University, Parangipettai Campus, Tamil Nadu-608502, India
2 National Centre for Sustainabel Coastal Mannagement, Ministry of Environment, Forests and Climate Change, Anna University Campus, Chennai 600 025, India
[*Email: pondiunisachin@gmail.com ] Received 05 November 2015 ; revised 11 May 2016
In order to understand the relative importance and elucidated seasonal variation samples were collected from two stations at monthly intervals. The results of ANOVA suggested that temperature and salinity shows significant variation from station-wise as well as season wise. From the Box plot analysis, it is inferred that the changes in the physio-chemical parameters are mainly due to climatic change, anthropogenic activity and urbanization and these play a key role in changes in the water column.
[Keywords: Box plots analysis; Coastal pollution; Cluster analysis; Southeast coast of India, ,]
Introduction
The physico-chemical parameters plays a significant role in organism distribution, reproduction, feeding and other aspects in coastal ecosystem1-3. Seasonal variation and anthropogenic pressures bring about a lot of changes in physico-chemical characteristics, which in turn affects the biotic elements4. The Indian coast is threatened by effluent discharges and human uses of marine ecosystem like overfishing, transport, recreation and tourism activities. These coastal areas are subjected to many variations which affect the coastal organisms, living in the marine environment5-12. Coastal ecosystems are affected by several health stresses that significantly deplete the biodiversity. Human population growth
within coastal regions ensures that there will be ongoing impacts on coastal wetland ecosystems meanwhile, changes of hydrological condition and anthropogenic influences make water quality present in different characters in different seasons. It is therefore essential to understand the water column health ecosystem in these coastal waters. So, it is difficult to distinguish the water quality, naturally and to identify temporally and spatially through regular monitoring for effective environmental management prediction. In this concern, the present study is aimed to monitor the environmental water quality parameters in the coastal waters off Parangipettai (St. 1) and Nagapattinam (St. 2) during June 2009 to July 2010.
INDIAN J. MAR. SCI., VOL. 47, NO. 02, FEBRUARY 2018
Materials and Methods
Parangipettai (St. 1) and Nagapattinam (St. 2) coasts have heterogeneous ecosystems like open sea, estuaries, mangroves, backwaters and industrial belt. Further, these areas have important fish landing centres beside shipping harbours and a number of private industrial jetties including fishing industries (Fig. 1).
Parangipettai (Lat. 11°29'50.45"N; Long.
79°46'32.01"E) is a small coastal town, situated about 250 km south of Chennai. This station comprises riverine, estuarine, backwater, mangrove and neritic biotopes .The river Vellar which originates from the Sharvarayan hills of Salem district, Tamil Nadu, flows through a distance of about 480 km and forms an estuarine system at Parangipettai before entering into the Bay of Bengal. The Vellar estuary is connected to the Coleron estuary, a major estuarine system
Fig. 1. Map showing the study area
which is situated at 20 km south of the Vellar estuary and forms backwater near Killai, which is situated 5km southward of Parangipettai. This back water area has a large number of channels bordered with mangrove ecosystem (Fig. 1).
Nagappattinam (Lat. 10°45'55.80"N; Long.
79°53'43.40"E) is one of the important fish landing centers of Tamil Nadu and various tributaries of river Cauvery such as river of Vellaiaru, Kaduviaru, Odampokkiaru and Vettaruare passing through the surrounding areas of this region. The study area is a major domestic disposing site where the wastes from the town directly disposed into the sea.
Apart from this, agricultural drainages and few industries situated in the vicinity of river Cauvery might have are carried into the Bay of Bengal through channels resulted in the contamination of the coastal biota of this region (Fig.1).
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Surface seawater samples were collected at monthly intervals from two different stations (Parangipettai and Nagappatinam) in two transects of each station about 0.5km and 5km distance from the seashore. The estimation of various physico-chemical parameters such as Temperature (ºC), pH, Salinity (PSU) and Dissolved Oxygen (mg/l) were measured using HYDROlab real time probe.
The physio-chemical parameters raw data were analyzed through SPSS 10.1 static software cluster analyzer and ANOVA.
Cluster Analysis (CA) is an unsupervised pattern recognition technique that uncovers the intrinsic structure or underlying behavior of a data set without making prior assumptions about the data, in order to classify the objects of the system into categories or clusters based on their nearness or similarity2, 13. Based on above mentioned studies followed in the present study attempted statistical analysis methods ANOVA and cluster analysis were employed to elucidate the spatial and seasonal variation of physio-chemical parameters in St. 1 and St.
2 coastal waters.
Based on the northeast monsoon, which is normally prevalent during October to December on the southeast coast of India, during which the only period where Parangipettai and Nagappattinam receives the bulk rainfall.
The four main seasons have been categorized in a calendar year viz. post- monsoon (January – March), Summer (April - June), Pre-monsoon (July – September) and Monsoon (October – December) for convenience and easy interpretation of data.
Results
The physico-chemical parameters monthly and seasonal variations observed viz., surface water temperature (ºC), pH, salinity (psu) and dissolved oxygen (mg/l) in water were recorded from the study site.
During the study, the values of surface temperature ranged between 28.19 -30.02oC show significant variation in the water
column with the maximum of 30.02oC recorded at station 2 and a minimum of 28.19oC as was recorded at station 1. In the case of transects, it was maximum (29.79 oC) in 5km at station 2 and minimum (28.40 oC) was at 0.5km in station 1. It ranged from 29.20 to 30.57 each in four different sampling seasons and the temperature was high during summer (May) and low during monsoon (Nov.).
The ANOVA analysis subjected to temperature data of study stations results suggested that it was significantly varied (p<0.001) within and between the stations, transects and seasons (Table 1 & Fig. 2). The high median value and significant temporal and spatial variances were observed among the stations (Fig. 2a). The temperature transect wise statistical data suggested that both the station box plots with long whiskers at the top and bottom of the box at 0.5 & 5 km distances have high correlation values, it indicates that high concentration and large spread indicates seasonal variations of the water column during the study (Fig. 2b).
The seasonal variations of temperature data box plots suggested that post-monsoon had significant values observed in Paragipettai and other seasons were not much different showed from this analysis due to the climatic factors or high river runoff play a role that reflects the tilted standard deviation and median values and long whiskers not showed in Paragipettai (Fig. 2c). However, the Nagapattinam box plot analysis also showed pre-monsoon and post-monsoon have long whiskers at the top of box and remaining seasonal not showed significant values observed due to outflies of data or data error might happen during survey timing. In general, the temperature has long been recognized as a key factor that control in marine ecosystems14-15.
pH was noticed in two stations and two transects in each stations at 0.5km and 5km distance into the seashore. Surface seawater pH was maximum (8.2) in station 1 and minimum (8.18) in station 2. The maximum (8.25) was recorded at 5km in station 2 and minimum (8.11) recorded at 0.5km at station 1. It ranged between 8.07-
INDIAN J. MAR. SCI., VOL. 47, NO. 02, FEBRUARY 2018
8.32 in all the seasons and it was maximum (8.32) during the summer (May) and minimum (8.07) during the monsoon (November). The pH was significantly varied within and between transects and seasons, but not significant within the
stations (Table 1), (Fig.3). The high median value observed from the box plot analysis and significant values of temporal and spatial variances observed in among the station (Fig. 3a).
Table 1. Analysis of variance (ANOVA) for physico chemical parameters presented P* F- value of sampling Seasons, Transects, Stations ** Significant 99%, NS- Not significant.
Parameters Term Df F-Value P-Value Significant
Temperature
Stations 2 40.589 0.001 **
Transects 2 30.116 0.001 **
Seasons 2 24.07 0.001 **
pH
Stations 2 0.126 0.726 NS
Transects 2 5.714 0.003 **
Seasons 2 8.665 0.006 **
Salinity
Stations 2 9.721 0.004 **
Transects 2 35.75 0.006 **
Seasons 2 8.647 0.005 **
Dissolved Oxygen
Stations 2 0.128 0.723 NS
Transects 2 10.128 0.009 **
Seasons 2 7.775 0.09 **
(p < 0.005 = *; p < 0.01 = **)
Fig. 2. Surface water temperature variations box plots analysis (a) two different stations, (b) transects and (c) seasons variations (2009-10). In each plot the central point denoted the median, the interval between the 25% and 75% percentiles, standard deviation represented and the Whisker indicates the range.
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Fig. 3. The variations of water pH in two different stations (a), transects (b) and seasons (c) (2009-10). In each plot the central point denoted the median, the interval between the 25% and 75% percentiles, standard deviation represented and the Whisker indicates the range.
The transect wise pH statistical data suggested that in Paragipettai station box plots with long whiskers at the top and bottom of the box at 5 km of open seaward side, it indicates that high concentration and large spread indicates seasonal variations of the water column during the study survey (Fig. 3b). The seasonal variations of pH data box plots suggested that pre-monsoon box plot analysis had significant values observed in Paragipettai and other season not with much different showed from this analysis due to the climatic factors or high river runoff play a role reflected the skewed and long whiskers not showed in Paragipettai station (Fig. 3c). However, the Nagapattinam station box plot analysis also showed pre-monsoon has long whiskers at the top of the box and remaining seasonal
box plots figure not shown significant values observed due to the outliers data not supported or considered the seasonal variation analysis.
The salinity was measured and observed with maximum (32.35 PSU) and minimum (31.47 PSU) at 5km and 0.5km transects in St. 1 and St. 2 respectively during summer and monsoon seasons. The salinity was varied significantly between the stations, transects and seasons (Table 1; Fig.
4). The salinity data, analysis though ANOVA showed varied significance between stations, transects and seasons substantially varied between stations (Table 1) The high median value and significant values of temporal and spatial variances observed in Paragipettai (Fig. 4a).
INDIAN J. MAR. SCI., VOL. 47, NO. 02, FEBRUARY 2018
The transect wise salinity statistical data suggested that in Paragipettai box plots with long whiskers at the top and bottom of the box in near shore (0.5 km) and open sea side (05 km) and it indicates that high concentration and large spread indicates seasonal variations of the water column during the study survey (Fig. 4b).
The seasonal variations of salinity data box plots suggested that not much significant observed, from this analysis, the climatic factors or high river runoff reflected the skewed and long whiskers which are not shown in Paragipettai (Fig. 4c). However, the Nagapattinam box plot analysis showed
pre-monsoon have long whiskers at the top of the box indicate underlying distribution is skewed toward high concentration. The similar pattern also observed in summer seasonal box plots showed in Fig. 4c for Nagapattinam station.
The monsoon wise box plots data mainly depend upon the freshwater mixing and anthropogenic activity plays vital role in the water column.
The Dissolved Oxygen was maximum (4.45mg.l-1) and minimum (4.42mg.l-1) at near-shore and offshore in St.
1 & 2 during summer and monsoon respectively.
Fig. 4. The variations of salinity in two different stations (a), transects (b) and seasons (c) (2009-10). In each plot the central point denoted the median, the interval between the 25% and 75% percentiles, standard deviation represented and the Whisker indicates the range.
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The dissolved oxygen varied significantly between transects and seasons, but not varied between stations observed, though ANOVA analysis (Table 1). The box plots statically analysis results (Fig.5a) observed and visual impression of the location and shape of median with long whiskers at the top of the box in St. 1. This result indicates the underlying distribution is tilted towards high concentration. In the case of transect distances data results showed that near shore regions had the highest concentration of DO values observed from box plots in both the study stations.
This result clearly concludes that due to the high tidal action near shore regions and
anthropogenic activity might be a reason for the high concentration of DO in near shore or 0.05km region and fresh water runoff but reverse trend in waters at 5km distances towards the open sea (Fig. 5b). The seasonal variation analysis of DO values in the Paragipettai showed monsoon and summer had the highest concentration and a significant positive relationship observed through box plot analysis (Fig.5c). However, the Nagapattinam station, seasonal variation results suggested that summer period had a positive relationship though box plot analysis (Fig. 5c). The DO values in summer season both study stations had with long whiskers and high median showed from this analysis.
Fig.5. The variations of dissolved oxygen in two different stations (a), transects (b) and seasons (c) (2009-10). In each plot the central point denoted the median, the interval between the 25% and 75% percentiles, standard deviation represented and the Whisker indicates the range.
INDIAN J. MAR. SCI., VOL. 47, NO. 02, FEBRUARY 2018
Cluter Anaysis:
The cluster analysis was attributed to the two sampling stations and seasons formed the two major groups based on sampling stations and seasons and it showed similarity based on the seasons.
Each season formed the group individually and also stations. It revealed that the sampling stations and the seasons were significant but not within the group (Fig. 6).
Discussion
Physico-chemical features of the marine environment are subjected to wide chronological variations. The temperature was recorded maximum in 5.0 km distance of the open seashore at two sampling stations, and similarly it was maximum at station 2 (Nagapattinam) when compared to station 1 (Parangipettai). It was statistically significant between seasons (F-value=9.47, p=0.05),
distances (F-value=10.77, p=0.05), and sampling station (p≤0.01). It was positively correlated with pH, and salinity (PSU). The temporal variation was due to the intensity of solar radiation, evaporation and influence entry of fresh water.
Also the controlling behavior of the water movement with changing patterns of currents and the lesser incursion of river water stratification and mixing processes was the dominant features during the summer season and these would have led to the higher surface water temperature at all the stations7, 9. The above processes were reversed during the monsoon season leading to a lower surface water temperature at all the stations7, 16-17. Moreover, temperature has a mediated for biotic responses in marine ecosystem direct or indirect relationship.
Fig. 6. Cluster analysis of physico-chemical parameters at two different stations, transects and seasons (2009-10).
Environmental
Group average
Post monsoon Post monsoon Post monsoon Post monsoon Post monsoon Post monsoon Premonsson Premonsson Premonsson Premonsson Premonsson Premonsson Summer Summer Summer Premonsson Premonsson Premonsson Monsoon Monsoon Monsoon Monsoon Monsoon Monsoon Monsoon Monsoon Monsoon Monsoon Monsoon Monsoon Premonsson Premonsson Premonsson Summer Summer Summer Post monsoon Post monsoon Post monsoon Summer Summer Summer Summer Summer Summer Post monsoon Post monsoon Post monsoon
Samples 100
95 90 85 80
Similarity
Transform: Square root
Resemblance: S17 Bray Curtis similarity
Sampling Station
PNO Nagai
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Conversely, marine organisms that are dependent on water column physio- chemical characteristics such as temperature, pH, DO, salinity to stimulate physiological developments and larval release have significantly moved forward in their seasonal cycle in response to temperature, a trend that has continued over the last decade18.
During the present study, there were only narrow seasonal fluctuations in the pH at all the stations. It was higher during the summer season and low during monsoon season and this might be due to uptake of CO2 by photosynthesizing organisms5, 19-20. In addition to that, the high pH would have resulted as a cause of changes in the sediment and water column, apart from the influence of fresh water9, 21. The lower pH values during monsoon season were attributed to large quantities of fresh water influx, low temperature and decomposition of organic matter as evidenced by Ganesan22 from Gulf of Mannar region. Salinity is one of the prime factors, which influences the abundance and distribution of organisms in the marine environment which in turn is influenced by fresh water and temperature.
Salinity was high during the summer, whereas it was low during the monsoon season at all the stations. The higher salinity was observed during the summer due to more evaporation3, 8, 21.
Dissolved oxygen level was well within normal range (3.5 – 6.8 mg/l) and biochemical oxygen demand (<5 mg/l) in Indian waters reported by IGMAM (Annual report – 2009 -10). Dissolved oxygen concentration was higher during summer at all the stations. This could be due to the photosynthesis and oxygen inputs from the atmosphere and biochemical oxidation of organic matter as evidenced by Govindasamy et al23 and Rajasegar24. Recent research has implicated global climatic changes relationship with marine ecosystem taxon growth changes due to the hydro- climatic changes, positive correlation with sea surface temperature and other factors18. The present study observed considerable inter-seasonal variability in physio-chemical significant changes revealed from the study
area though multivariate statistical approaches. In this study, temporal and spatial patterns of physio-chemical parameters of a marine water column in Nagapattinam and Paragipettai Bay of Bengal region were identified through box plots and cluster analysis. This study concludes that box plots showed the unique phyiso-chemical parameters concentration in a reasonable boundary or threshold revealed. Cluster analysis results conclude that seasonal variation of study stations formed two groups. It revealed that the sampling stations and the seasons were significant. In future need continuous monitoring of physio-chemical and biological parameters may helpful the marine ecosystem conservation and sustainable management of coastal activity.
Acknowledgements
Authors thank the Director, CAS Marine Biology, Annamalai University, Paragipettai campus, Tamil Nadu for providing necessary infrastructure and facilities and their constant supports for this work carried out at Paragipettai campus and Annamalai Nagar, Chidambaram, Tamil Nadu 608 002.
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