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Aquatic Procedia 4 ( 2015 ) 373 – 380

2214-241X © 2015 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).Peer-review under responsibility of organizing committee of ICWRCOE 2015doi: 10.1016/j.aqpro.2015.02.050

INTERNATIONAL CONFERENCE ON WATER RESOURCES, COASTAL AND OCEAN ENGINEERING (ICWRCOE 2015)

Holocene Records of Human Driven Geological Impacts in a Ramsar Wetland of India

A. Krishnakumar*, Saranya. P, Geethu Prasad. P and Rakhi C Natural Resources and Environmental Management Group

National Centre for Earth Science Studies (NCESS), Ministry of Earth Sciences,Govt. of India Akkulam, Thiruvananthapuram-695031

Abstract

The present study evaluated the extent of accumulation of heavy/trace metals in the recent sediments of Ashtamudi Wetland System (AWS), a Ramsar Site located in the Southern State of India, Kerala; using Contamination Factor (CF), Pollution Load Index (PLI) and Geo-accumulation Index (Igeo) in 4 sub-environments of AWS; viz: Ashtamudi Main Kayal, ChavaraKayal, Kureepuzha- KandachiraKayals and Kumbalathu- KanjirakottuKayals for monsoon and non-monsoon seasons. Spatial distribution diagrams of heavy/trace metals for monsoon and non-monsoon seasons were also prepared in GIS in order to assess the spatial and temporal variation of pollution in the entire Wetland System. Comparing the data with the world shale averages for the concerned elements, it is observed that Cr, Fe, Ni and Cu were in higher concentration, indicating high befouling rate. The ChavaraKayaland Kumbalath and KanjirakottuKayals were found highly polluted with heavy metals compared to other sub-environments. Geo-accumulation index (Igeo)values of most of the elements (Cr, Fe, Co, Cu etc) were in classes above zero indicating high degree ofpollution. However, Cobalt in non-monsoon season, Nickel and Zinc in most of the stations fall under zero class of Igeo, probably due to the predominance of lithogenic flux. Zero class of pollutants (Ni and Co during non-monsoon season and Zn) suggests the dilution and dispersion of elements in the Wetland System. A decadal comparative analysis of the accumulation of heavy/trace metals shows the dramatic increase in the heavy metal deposition in the Wetland System which shed light on the human driven geo-environmental impacts in the AWS and the urgent needs of sustainable conservation measures.

© 2015 The Authors. Published by Elsevier B.V. Peer-review under responsibility of organizing committee of ICWRCOE 2015.

Keywords:Ashtamudi Wetland System;Contamination Factor (CF); Pollution load index (PLI); Geo-accumulation index (Igeo) and average shale value.

* Corresponding author.

E-mail address: drakrishnakumar@gmail.com

© 2015 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).Peer-review under responsibility of organizing committee of ICWRCOE 2015

374 A. Krishna Kumar et al. / Aquatic Procedia 4 ( 2015 ) 373 – 380

1. Introduction

The Ashtamudi wetland system (AWS), a Ramsar Site designated as “wetland of international importance”, is one of the major estuarine wetlands in the tropics and the second largest backwater system of Kerala State.This extensive and deepest Wetland System of South India, connected to the Lakshadweep Sea is havingextraordinary importance for its hydrological functions and biodiversity.Population pressure, industrialization and rapid urbanization in and around the AWS and the proximity to Kollam town is resulting in the fast shattering of the organic structure of the Ashtamudi Wetland System.Modern day developmental activities caused for the elevated levels of heavy metal pollution in water bodies and the toxicity and persistency in the environment made them the centre point of attention for researchers.In the light of the above, an attempt has been made to determine the concentrations of heavy metals and to assess the degree of contamination in the Ashtamudi Wetland System.The assessment of sediment enrichment with elements can be carried out in many ways; and most common ones are the geo-accumulation index (Igeo) and pollution load index (PLI). The Igeo has been widely utilized as a measure of pollution in sediments of water bodiessince late 1960s(Singh et al. 1997), while the PLI represents number of times by which the heavy metal concentrations in the sediment exceeds the background concentration, and gives a summative indication of the overall level of heavy metal toxicity in a particular sample (Tomlinson et al. 1980., Priju et al. 2006). The present types of studies are lacking in the AWSas per the available literature and hence this study is considered to be the first attempt to evaluate the heavy metal pollution in terms of PLI and Igeo. Nomenclature

AWS Ashtamudi Wetland System M Monsoon C ChavaraKayal Nm Non-monsoon KS Kureepuzha and KandachiraKayals PLI Pollution Load Index KE Kumbalath and KanjirakottuKayals Igeo Geo-accumulation Index CF Contamination Factor

1. Study area

Ashtamudi Wetland System, is located between North latitude 80 54’-90 02’ and East longitude 760 32’-760 39’ in Kollam District of Kerala State.The AWS, also called the gate way to the back waters of Kerala, is of utmost importance in terms of natural resource and adorable beauty in addition to the immense direct and indirect uses.The Wetland System is a palm shaped water body with an area of 32 sq.km,has many creeks and branches; eight of which are prominent ones. The main water body – AshtamudiLake is approximately 13km long and 3km wide. 3. Sampling and analysis

The sampling in AWS has been carried out during monsoon (July 2013) and non-monsoon (March 2014) seasons from selected locations of the four sub-environments as mentioned in table 1.

Table 1 Sampling details in the sub-environments of AWS

Serial No. Name of the sub- environment

Location Total samples with code numbers Latitude Longitude

1 Ashtamudi main Kayal 80 561 911- 80 591 2511 N 760 321 111- 760 351 46.711 E 5 (M1-M5)

2 ChavaraKayal 80 551 711 - 80 571 4711 N 760 321 211 - 7603515911 E 6 (C1-C6)

3 Kureepuzha- KandachiraKayals 80 541 1311- 80 551 4511N 760 341 1311- 760 361 5711E 5 (KS1-KS4)

4 Kumbalathu- KanjirakottuKayals 80 571 111- 80 591 5811 N 760 361 111- 760 391 1711 E 5 (KE1-KE5) Sediment samples were collected using stainless steel Van veen Grab Sampler. The samples were dried and powdered to fine by using an agate mortar, which in turn is used for the geochemical analysis. XRF method (Bruker Model S4 pioneer sequential wavelength dispersive X-ray spectrometer)is used for determining heavy metals such as

375 A. Krishna Kumar et al. / Aquatic Procedia 4 ( 2015 ) 373 – 380

Cr, Co, Ni, Cu, Zn, Fe, Al and Mn; in the sediment samples.

Fig 1Location map of the study area

2. Assessment of Metal Pollution

To evaluate the extent of pollution in the sediments, three parameters have been used viz; Contamination Factor (CF), Pollution Load Index (PLI) and Geo- accumulation Index (Igeo), as shown below:

4.1Contamination Factor The level of contamination of sediment by metal is expressed in terms of contamination factor (CF) and calculated as;

(1) CF values for describing the contamination level are expressed as CF<1= low contamination; 1≤CF<3= moderate contamination, 3≤CF< 6= considerable contamination and CF>6 very high contamination (Hakanson, 1980).

376 A. Krishna Kumar et al. / Aquatic Procedia 4 ( 2015 ) 373 – 380

4.2 Pollution Load Index (PLI) Pollution load index (PLI), for a particular site, has been evaluated following the method proposed by Tomlinson etal; as

(2) Where; CF = Contamination factor;n= number of metals. 4.3 Geo-accumulation Index (Igeo) Geo-accumulation index was proposed by Muller (1979) for the quantification of metal accumulation in contaminated sediments and calculated as:

Igeo= Log2(Cn/ 1.5 Bn) (3) Where; Cn= the measured concentration; Bn= the background value (Average Shale) of element ‘n’. Muller proposed seven grades or classes of geo-accumulation index as shown in table 2.

Table 2 Muller’s classification for geo-accumulation index (Igeo) Igeo Value Class Sediment Quality

≤0 0-1 1-2 2-3 3-4 4-5 >6

0 1 2 3 4 5 6

Unpolluted From unpolluted to moderately polluted

Moderately polluted From moderately polluted to strongly polluted

Strongly polluted From strongly to extremely polluted

Extremely polluted

5. Results and discussion

5.1 Contamination Factor (CF)

Data on the concentration ranges of various heavy/trace metals (Fe, Mn, Cu, Co, Ni, Zn, Cr and Al) observed in the AWS were shown in table 3. While computing the contamination factor (CF) of sediments of the study region, world average concentrations of these elements reported for shale (Turekian and Wedepohl, 1961) were taken as the background values. The table clearly illustrates that the concentration of Aluminium, Manganese and Titanium are very negligible compared to their corresponding world shale average. Hence, these metals are not considered for further computation of PLI and Igeo. Sediment analysis depicts that, most of the elements (Cr, Fe, Co, Ni, Ti and Zn) werefound in higher concentrations during monsoon period compared to non-monsoon; due to the wash down and settling of these elements from far and near places. As stated by Jennes (1976) and Forstner and Wittmann (1983) the redox sensitive Fe and Mn hydroxides and oxides under oxidation conditions, constitute significant sink of heavy metals in aquatic ecosystem. This hydroxide and oxide readily sorb or co-precipitate cations and anions; according to them, even a low percentage of Fe (OH)3could play controlling influence on the heavy metal distribution in an aquatic environment. Seralathan (1987) and Padmalal (1992) have also reported that iron oxide coating is one of the important factors responsible for the concentration of trace elements in the aquatic environment. Current study shows that AWS is moderately polluted with Iron; but in contrast to other similar studies, the Fe and Mn has no significant role in controlling the other heavy metals in the sediments of AWS (Table 4 and 5). This may be due to the continuous dredging activities by the Port Department which alter the natural sediment characteristics in a considerable manner. The resulting substratum profile and influence of under currents due to tidal activities remarkably changed the sedimentation behaviour in the AWS. The obtained values in monsoon and non-monsoon strongly support these observations.

377 A. Krishna Kumar et al. / Aquatic Procedia 4 ( 2015 ) 373 – 380

The analysis of contamination factors indicate that AWS is moderately contaminated with Iron, Nickel, Chromium and Copper.The observed Chromium concentration was anomalously high compared to the world shale average and hence the contamination factor has also elevated. The higher chromium concentration is attributed to the anthropogenic inputs such as industrial effluents especially from the metallurgical industries adjacent to the AWS. Chromium toxicity is very dangerous as it is a hazardous and carcinogenic compound; it may also lead to acute skin diseases.

Table 3 Concentration and Contamination factor of metals in Ashatamudi Wetland System Sl

No. Elements*

Observed ranges of Values World

shale average

Contamination Factor (CF) Pollution Status

Monsoon Non- Monsoon Monsoon Non- monsoon

1

2

3

4

5

6

7

8

9

Cr

Al

Mn

Fe

Co

Ni

Cu

Zn

Ti

139.4-172.33

0.56- 11.58

0.025- 0.08

3.72- 8.29

10-14.2

72.8-99.75

50.2-70.25

23.29-73.8

0.56- 0.75

126.75- 143.66

1.08- 10.23

0.03- 0.47

3.52-6.88

10-13.2

51.4-83.5

39.4-83.25

24.7-40

0.504-1.08

90

80,000

900

4.6

19

68

45

95

4600

1.55-1.91

Negligible

Negligible

0.81-1.80

0.53-0.75

0.76-1.47

1.12-1.56

0.25-0.78

Negligible

1.41-1.60

Negligible

Negligible

0.77-1.50

0.36-0.77

0.76- 1.23

0.88-1.85

0.26-0.42

Negligible

Moderate

NC**

NC**

Moderate

Low

Moderate

Moderate

Low

NC**

** NC: No Contamination with respect to this element.

*All values are expressed in ppm except Fe.,

Table 4 Interrelationship among metals in the sediments of AWS during monsoon season

Cr Al Mn Fe Co Ni Cu Zn Ti Cr 1 Al 0.13 1.00 Mn 0.12 -0.93 1 Fe -0.21 -0.23 -0.08 1 Co 0.71 -0.17 0.36 0.080 1 Ni 0.79 -0.50 0.67 -0.027 0.77 1 Cu 0.44 -0.69 0.75 0.315 0.82 0.84 1 Zn 0.15 -0.10 0.08 0.506 0.75 0.26 0.64 1 Ti 0.13 1 -0.93 -0.228 -0.17 -0.50 -0.69 -0.10 1

Table 5Interrelationship among metals in the sediments of AWS during non-monsoon season

Cr Al Mn Fe Co Ni Cu Zn Ti Cr 1 Al -0.53 1 Mn 0.30 -0.32 1 Fe -0.31 0.48 0.32 1 Co 0.83 -0.60 0.44 0.11 1 Ni 0.92 -0.77 0.52 -0.34 0.84 1

378 A. Krishna Kumar et al. / Aquatic Procedia 4 ( 2015 ) 373 – 380

Cu 0.80 -0.78 0.45 -0.04 0.97 0.88 1 Zn 0.82 -0.49 0.15 0.41 0.93 0.68 0.88 1 Ti -0.53 1 -0.32 0.48 -0.60 -0.77 -0.78 -0.49 1

In order to understand the problems due to anthropogenic interventionsfor the last decade in the AWS, a comparison has been made with previous data as shown in table 6. From the tableit is very clear from the table that concentration of Chromium and Copper drastically increased in the AWS. But, in contrast to this, Zinc level has decreased, which may be due to the leaching out of metal from the sediments and the subsequent accumulation to the aquatic biota. Immediate management methods should be adopted to tackle the elevated pollution level of Chromium and Copper as these possess serious health and environmental hazards.

Table 6 Comparative evaluation of heavy metal concentration in AWS

Elements Kerry Black and Baba,2001 (ppm)

Present study (ppm)

Chromium 80-155 136-156 Copper 20-42 59-61

Zinc 57-208 32-49

5.2 PLI of Ashtamudi Wetland System The sub-environments of Ashtamudi Wetland System show difference in PLI values as shown in Table 7due to reasons of location specific nature. It is noticeable that the PLI is higher in monsoon season in all sub-environments. Such increased levels of metals in the sediments may be due to monsoonal land run-off as observed elsewhere (Athaley and Gokhaley, 1989).Retting of coconut husks, industrial activities and fish processing units were also contributed for the high PLI of ChavaraKayalas well as Kumbalath and KanjirakottuKayals.

Table 7 Pollution Load Index of in various sub-environments of Ashtamudi Wetland System

Sub-environments PLI Monsoon Non-monsoon

Ashtamudi Main Kayal 0.16 0.03 ChavaraKayal 0.37 0.12

Kureepuzha&KandachiraKayal 0.09 0.06 Kumbalath&KanjirakottuKayals 0.39 0.10

5.3 Geo-accumulation Index Figure 2 shows the graphical representation of Igeo in AWS. It is evident that Igeo classes in respect of Co, Ni and Zn during non-monsoon seasons remain in class zero at all the stations probably due to the lithogenic flux. In contrast; Co was found in class one in very few stations in the monsoon season. Cr is found falling in class one ie; from unpolluted to moderately polluted. Regarding Fe, except 5 stations, all others fall in class zero. Zero class of other elements studied in the wetland system almost to its background values indicate the dilution and dispersion of elements in the Wetland System.

M1 M2 M3 M4 M5 C1 C2 C3 C4 C5 C6 KS1 KS2 KS3 KS4 KE1 KE2 KE3 KE4 KE5Cr M Cr M

Cr Nm Cr NmFe M Fe M

Fe Nm Fe NmCo M Co M

Co Nm Co NmNi M Ni M

Ni Nm Ni NmCu M Cu M

Cu Nm Cu NmZn M Zn M

Zn Nm Zn Nm

Class zero

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Fig 2 Geo-accumulation index of heavy metals at different stations of AWS in monsoon and non-monsoon seasons

5.4 Spatial Distribution of Heavy metals

Spatial distribution diagram of the heavy metals for different seasons were prepared in GIS platform and that of Cu and Cr presented in Fig 3 and 4. This will give a clear picture on the variation of the heavy metals spatially and temporally.

Fig 3: Spatial distribution of Cu in AWS

Fig 4: Spatial distribution of Chromium in AWS

Class one Class 2

380 A. Krishna Kumar et al. / Aquatic Procedia 4 ( 2015 ) 373 – 380

Human driven location specific issues are the main reasons for the hike in the values noted at the different areas; pointing to the needs of urgent management measures. All these metals were dominant to the coastal regions suggests the inputs in those areas, as the human activities are causing the dispersion of metals. The problems taking place at certain locations have its own implications at the premises and eventually attached to the bottom sediments. Energy conditions prevailing in the AWS cause the displacement of bottom sediments to different zones of the system, and leading to adverse impacts of heavy metal pollution in its different regions.

6. Conclusion The Ashtamudi Wetland System of south India provides many direct and indirect use values to the community in terms of fishing, coconut husk retting, recreation and inland navigation. But due to the anthropogenic interactions the behaviour of the substratum sediments are considerably altered and showing anomalous behaviour. The analysis of contamination factors of metals indicate that Ashtamudi Wetland System is moderately contaminated with Chromium, Iron, Nickel, and Copper. The significant pollution load and spatial variation recorded for some parameters is the reflection of negative impacts of anthropogenic activities as part of the Holocene dynamics. This study, hence, emphasizes the need of sustainable management measures of the Ramsar wetland. The continuous monitoring of sediment quality of different sub-environments of the AWS is proposed for deriving location specific management options needed for the health of the important backwater system.

Acknowledgements

Authors are thankful to the Director, National Centre for Earth Science Studies (NCESS), Thiruvananthapuram for encouragements and support and to the Dept of Port and Fisheries Government of Kerala for the financial assistance to study the AWS. References

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