Procedia Engineering 116 ( 2015 ) 794 – 801

1877-7058 © 2015 The Authors. Published by Elsevier Ltd. 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 , IIT Madras , and International Steering Committee of APAC 2015doi: 10.1016/j.proeng.2015.08.366

ScienceDirectAvailable online at www.sciencedirect.com

8th International Conference on Asian and Pacific Coasts (APAC 2015)Department of Ocean Engineering, IIT Madras, India.

Textural Characterization of Coastal Sediments along Tamil Naducoast, East coast of India.

Sathish Sathasivama, R.S.Kankaraa, S. Chenthamil Selvana, Manikandan Muthusamya, ArockiarajSamykannua and Rajan Bhoopathia

aMinistry of Earth Sciences,ICMAM – Project Directorate, NIOT Campus, Chennai- 600 100, IndiaEmail:athi_geo@yahoo.co.in

Abstract

Particle size characterizations of beach sediments along Tamil Nadu coast was carried out in the present study. The mainobjective of this work is to identify the textural behaviour of beach sediments and how wave energy correlates with grain sizedistribution.To achieve this goal tri-plot analysis was performed. Grain size characteristics such as central tendency, kurtosisand skewness were estimated using an updated version of the GRADISTAT programme and discussed in this paper. Thehighest sediment samples having medium sand with unimodal and bimodal characters at all along the coast. The entire coastalarea was characterized as well sorted, moderately well sorted and moderately sorted sediment environments. Sediments wereidentified as fine skewed to coarse skewed with platykurtic, mesokurtic and leptokurtic characters. Grain characteristics variedspatially and temporally along with beach orientation, foreshore slope withwave action and skewness correlates with shorelinechanges. In some coastal tract having the negative skewness along the study region, but not very significant. The study depictsthat the sedimentary coastal environment were influenced by the relatively medium wave action and some places were observedhigh wave action. From this study, it was concluded that the beach erosion, accretion, and stability of beaches are controlled bystrong hydrodynamic and hydraulic process.

© 2014 The Authors. Published by Elsevier B.V.Peer-review under responsibility of organizing committee of APAC 2015, Department of Ocean Engineering, IIT Madras.

Keywords:Grain Size, Weight Percentage, Mean, Skewness, Kurtosis, Gradistat, Tri-plot.

Coasts (APAC 2015)

© 2015 The Authors. Published by Elsevier Ltd. 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 , IIT Madras , and International Steering Committee of APAC 2015

795 Sathish Sathasivam et al. / Procedia Engineering 116 ( 2015 ) 794 – 801

1. Introduction

Grain size is the one of most significant physical property of sediment and commonly used parameterforunderstanding the processes involved in transportation and deposition of sediments (Inman, 1952; Folk and Ward,1957; Mason and Folk, 1958; Friedman, 1961; Krumbein and Sloss, 1963; Nordstrom, 1977). Some of thepioneering studies on grain size characteristics are still referred by many researchers. Grain-size parameters arerequired and the mean size of medium to very coarse silt has proved to be a useful measure of the speed of thedepositing flow(McCave, 2008) . Geologist employs the sediment particle size data to study the trends of surfaceprocesses related to the dynamic conditions of transportation and deposition. Engineers apply grain size to revisesample permeability and stability under load. In the great majority of cases, this has been for non-cohesive sandsand gravels. Hydrologists use it when studying the movement of subsurface fluids (McCave and Syvitski,1991). The objectives of a grain-size analysis are to accurately measure the individual particle sizes to determinetheir frequency distribution, and to calculate a statistical report that effectively characterizes the samples. In thisstudy, an attempt has been made to analyse the beach sediment characterstics along Tamil Nadu coast.

2. Study Area

The study area covers 950 km coastline between Kalpakam to Colachal in Tamil Nadu (TN), covering 11coastaldistricts(Figure.1). The coastline is endowed with various geomorphologic features. The coastal zone is underdevelopment pressure and coast is experiencing a range of management problems including shoreline erosion.About 42% of TN coast is facing erosion. The mean tidal range varies between 0.6 m - 1.5 m. and average waveheight varies from 0.3m-1.8m.

Figure 1: Map of the study site showing the sampling locations.

Tamil Nadu is having a two-monsoon system viz. Southwest summer monsoon (June to September) and theNortheast monsoon (October to December). Coastal Tamil Nadu receives about 60% of its annual rainfall andinterior Tamil Nadu receives about 40-50% of annual rainfall during the northeast monsoon. The beaches andbeach ridges along the southern division of the east coast of India around Tirunelveli, Kanyakumari and

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Manavalakurichi are occurred with economically viable placer deposits (Loveson, 1993; Bruckner, 1988). Thesedeposits are economically feasible and being mined in many places and brings revenue for our country. Thesediment of coastal area have age ranging from Late Pleistocene to Recent(Chauhan, 1989).

3. Materials and Methods

One sixty five sediment samples were collected during the month of August, 2013from the backshore, bermlineand foreshore of Tamil Nadu coastal prefecture. Hereafter backshore, bermline and foreshore are BS, BL, and FSrespectively. Concurrently positioning of samples was conducted by using handled GPS. Samples were carefullypreserved in polythene bags and they brought into the ICMAM-PD sedimentology lab. In the laboratory, deadshells were separated from sediments and the mixed saline content was removed from the grains by washing withwater. The grain size distribution was carried out by using a sieve shaker and it is consisting of 8 sieves containingmesh sizes 75µm, 125µm, 180µm, 250µm, 355µm, 500µm, 1000µm and 2000µm.

Figure 2: Weight % curves of samples

The sediment distribution is presented graphically as weight percentage curves of backshore (Figure.2a), bermline(Figure.2b) and foreshore (Figure.2c). The statistical parameters such as mean, standard deviation, skewness andkurtosis were computed by (Folk and ward, 1957) using the GRADISTAT grain size distribution and statisticalpackage (Blott and Pye, 2001).

a

b

c

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3.1. Measurements of Statistical properties

Sediments have many imperative characteristics of which particle size is only one. Particle size refers to thesizes of all of the particles in sediment. If you compute the mean particle size, this does not tell you about the rangeof sizes occurring. If you estimate a range, this does not tell you the shape of the distribution, which might benormal or strongly skewed to coarse or fine particles. Mean is the arithmetic average size of the sediment and isexpected to be influenced by source of supply, transportation and environment of deposition.

4.Result

The parameters used to describe the particle size distribution fall into four primary groups: those are the mean,standard deviation (sorting), skewness and kurtosis. These parameters can be easily acquired by mathematical orgraphical methods. The mathematical ‘method of moments’ (Krumbein and Pettijohn, 1938; Friedman andJohnson, 1982) is the most accurate since it represented the entire sample population. However, consequently thestatistics are greatly affected by outliers in the tails of the distribution, and this form of analysis should not be usedunless the size distribution is known (Mcmanus, 1988). The grain size parameters of the study area and statisticalproperties of grain sizes and its interpretations are shown in figures 3-6. Standard deviation of most of thebackshore samples emerge well sorted to moderately sorted (1.29 to 1.79), mean values indicating medium sand tocoarse sand (135.60 to 807.10), skewness values having symmetrical to coarse skewed (-0.25 to +0.36) andkurtosis values depicts mesokurtic to leptokurtic (0.82 to 1.49). The bermline values conquered that moderatelywell sorted to well sorted, mean values dominating from fine sand to medium sand and the skewness issymmetrical to coarse and kurtosis occurred in all types. In foreshore, standard deviation values implyingmoderately well sorted to well sorted (1.2 to 1.98),the meanvalue indicating fine sand to medium sand (130.00to490.80), the kurtosis depicts platykurtic to leptokurtic (0.84 to 1.69). Friedman (1962) suggested that extreme highor low values of kurtosis imply that part of the sediment achieved its sorting elsewhere in a high energyenvironment. The skewness is varying coarsely skewed to fine skewness (+0.55 to -0.35). The negative skewnessvalues indicate coarse-skewed material, whereas the positive values represents more material in fine skewed. Finesediments were found in the northern part(Kalpakkam to Kodiakarai) of the study area because of the prevailinghigh wave energy condition. This is also evidenced by the erosive action of the waves (Rajamanickam et.al.,(1995) reported high energy condition is also attributable to the presence of submarine canyons in the Pondicherryand Cuddalore regions. Numerous factors influenced to textural characteristics of coastal sediments. They arecomposed of neighbouring lands, climatic condition of that area, tide, littoral transport, length and energy ofsediment transport, redox conditions in the depositional environments (Bhatia and Cook, 1986; Fralick andKronberg, 1997; Anithamary et.al., 2011). Moreover, spatial dissimilarity in sediment composition can help todetermine the present environmental conditions. Statistical methods are commonly employed to simplify thenecessary comparisons among samples and quantify the observed differences. Sedimentologists follow to describeparticle distributions by mathematical moments (Krumbein and Pettijohn,1938) and inclusive graphics (Folk,1974) and statistical methods. In this context, the particle distribution is used for grain size analysis.

Figure 3: Standard deviation of BS, BL, FS

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Figure 4: Mean of BS, BL, FS

Figure 5: Kurtosis of BS, BL, FS

Figure 6: Skewness of BS, BL, FS

5. Discussion

The weight percentage distribution curves show that the grain size variation was more along foreshore due tothe effect of wave activity compared to bermline. The statistical properties of sediment samples illustrate thatunimodal and bimodal character is dominated in the backshore, bermline and foreshore along the study area. Thebackshore sediments predominantly having the medium sand with moderately well sorted to well sorted samples.In bermline samples, the fine sand to medium sand with moderately well sorted and well sorted was found. Inforeshore, mainly fine sand to medium sand and moderately sorted to moderately well sorted was observed. Therange of kurtosis values more or less same from samples 1-23 (northern part) and sample from 23-55 (southernpart). The 29% (16 nos) of backshore samples are negatively skewed, while 31% (17 nos) bermline samples arenegatively skewed. However, the foreshore samples have relatively lower 24% (13 nos) negatively skewspecimens. The study showed that the negatively (coarse) skewed and positively (fine) skewed samples, indicatingstrong deposition and erosion tendency along the study region. The negative skewness was correlated with the long

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term shoreline change (1990-2014) result. It was observed that the eroding locations such as Vyalikuppam,Ganapathychettikulam,Chinnamudhaliyarchavadi,Pombuhar,Tharangapadi, Mimisal, Muthaipuram andPeriyathalai (Kankara and Selvan, 2012) had similar trend of skewness. The results of shoreline changes v/snegative skewness for foreshore locations are shown in figure 7. In addition, to understand the hydrodynamicprocess such as wave with particle size distribution, unconventionally the tri-plot (Figure. 8) method was alsoadopted. From the tri-plot analysis, in backshore area, Central part of the Tamil Nadu coast, having fine sand,Southern part of Tamil Nadu has medium sand and Northern region of coastal zone has coarse sand. Whereas inbermline, Central part of the Tamil Nadu coast possesses fine sand, Southern part of Tamil Nadu has medium sandand Northern side consists of coarse sand. In foreshore zone, Northern side comprises fine sand and the Southernside is dominating the medium sand. The above finding is closely matched with the wave distribution pattern fromsouth to north of Tamilnadu coast (Sivakokholandu et.al., 2014) where the significant wave height is showing adecreasing trend from Kanyakumari to Pondicherry

Figure 7: Comparison of measured shoreline change and skewness values where erosion is prominent.

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SiltClay

Sand

10%

1:2 2:1S ilt:C lay

S and 50%

S and 90%

C layeyS and M uddy

S and

S andy S andyS andy

C lay Mud S ilt

S iltyS and

Coarse sand

Medium sandFine sand

c oars e

mediumfine

c oars e

mediumfine

c oars e

mediumfine

Figure 8: a)tri-plot for textural analysis of all sediments, b)Different type of sands, c)Foreshore samples,d)Backshore samples, e)Bermline samples

6. Conclusion

In order to conclude the discussion above which reveals that surface sediment properties of the TN coastal area,their major inputs and their main transport, depositional processes. Geomorphology and climatic conditions play acrucial role to control the sediment dynamic nature of the study area. The northern part of TN coast starting fromKalpakkam to Kodiakarai having fine sand with high energy condition existing, central coast begins withKodiakarai and ended with Mandapamincluding Rameshwaram was dominated by medium sand with less energycondition and similar feature also observed in the southern part from Mandapam to Kanyakumari.

Acknowledgements: Authors would like to thank Dr.Shailesh Nayak, Secretary, Ministry of Earth Sciences,Government of India and Dr. M.A. Atmanand, PD-ICMAM for their keen interest, encouragement and providedfacilities for this study.

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