Seasonal Variation of Beach Sediment Dynamics of the Coleroon Coast, Tamil Nadu, India

477 International Journal of Earth Sciences and Engineering

ISSN 0974-5904, Vol. 04, No. 03, June 2011, pp. 477-487

#02040512 Copyright © 2011 CAFET-INNOVA TECHNICAL SOCIETY. All rights reserved.

Seasonal Variation of Beach Sediment Dynamics of

the Coleroon Coast, Tamil Nadu, India

ANITHA MARY. I. T. RAMKUMAR and S. VENKATRAMANAN Department of Earth Sciences, Annamalai University, Annamalainagar, 608 002, India

Email: [email protected], [email protected], [email protected]

Abstract: The present study was carried out in order to study about the textural

characteristics of sediments, and their seasonal changes along the coast of Coleroon.

Samplings were done at different station during two seasons from monsoon 2009 to

postmonsoon 2010. Granulometric studies reveals that the grain size parameters at

different beach locations do not suggest a general trend of longshore variations, except on

the beach close to the river mouth. The differences between the seasons were larger than

those between the geomorphological units. During the monsoon the mean size was

medium, sorting was worse and the distribution was more positively skewed. The major part

of the sediment fall in a medium to fine grained category.

Keywords: Grain size analysis, beach sediments, Coleroon, east coast

1. Introduction:

Analysis of grain size distribution has been

widely used by sedimentologists to classify

sedimentary environments and elucidate

transport dynamics. Grain size is also an

important a biotic component of the dune

ecosystem. The grain sizes of sediments

provide an indication of the shear stress that

must be applied by the medium to initiate

and sustain particle movement. The

importance of sediments to the overall

quality of aquatic systems, sediment

analysis is often included in environmental

assessment studies (Adekola and Eletta

2007; Li et al. 2006; Jain et al. 2005;

Horsfall and Spiff 2002). Grain size

distribution is affected by other factors such

as distance from the shoreline, distance

from the source (river), source material,

topography and transport mechanisms.

Musila (1998) found that the mean particle

size of the sand was the most important

factor influencing vegetation composition,

structure and distribution in the Malindi Bay

coastal sand dunes in Kenya. Musila (1998)

noted that geomorphological units consisting

of fine grained sand had high species

diversity in contrast to those with medium-

grained sand which were mostly

unvegetated or sparsely vegetated; these

differences may be accompanied by

differences in chemical composition and/or

substrate processes. The grain size

distribution of beach can be affected by

multiple controls, including sediment source,

hydrodynamics, and biological factors that

modify erosion/accretion processes. Based

on physics alone, sediments tend to become

coarser towards the land in wave-dominated

environments (Fox et al, 1966; Komar,

1976; Trenhaile, 1997), whereas the

opposite is true in tide-dominated areas with

a coinciding gradual landward reduction in

current velocity (Amos, 1995; Woodroffe,

2003). Sediments are important sinks for

various pollutants like pesticides and heavy

metals and also play a significant role in the

remobilization of contaminants in aquatic

systems under favorable conditions Ikem et

al (2003), Naji et al, (2010). The purpose of

the present study is to determine statically

the significant variation in grain size

distribution within beach sediments and

interpret sediment movement in the beach

segment of Tirumullaivasal to Puthupattinam

with special mention about the processes

operating around the Coleroon river mouth.

2. Description of Study Area:

The study area is drained by Coleroon river

and its distributaries. These entire rivers are

ephemeral and carry floods during monsoon.

They generally flow from west towards east

and the pattern is mainly sub parallel. The

eastern coastal part near Pazhayar is

characterized by back water. Coleroon river,

478 ANITHA MARY. I. T. RAMKUMAR and S. VENKATRAMANAN

International Journal of Earth Sciences and Engineering


a major waterway of the Tiruchirapallia and

district thanjavur district, is formed by the

bifurcation of the Cauvery flows through the

Chidambaram taluk for 36 miles and finally

joins the Bengal 6 miles south of Portonova

(Parangipettai). Since the district is

underlined by sedimentary formation ,the

major land forms that occur are natural

levees near Maliaduthurai coastal plain

covering almost the entire district with

beaches beach ridges, mudflats swamps,

and backwater along the coastal stretch .

The deltaic plains are found near the

confluence of river Coleroon with sea in the

east and also in the south. Flood plain

deposits are observed along the river course

(Fig.1).

3. Methodology:

A total of forty sediment samples collected

from high and low tide levels of the beach

by using a plastic spatula at each of the 20

sites, covering the period of Monsoon 2009

and postmonsson 2010. Samples were

stored frozen until ready for analysis. The

sieve data were processed using a computer

programme for the calculation of percentile

values and inclusive graphic measures (Folk

and ward, 1957).For each of the grain size

parameter smoothed frequency distribution

curves were drawn. Then, they were dried

in an oven at 60°C for 24 hours to a

constant weight (Holme and Mac Intyre,

1971). Sieving technique is applied to

separate the grains of various size classes

(Ingram, 1970). Initially 100 gm of sample

is prepared by removing carbonate and

organic matters by treating with 10% dilute

hydrochloric acid and 6% hydrogen peroxide

respectively. Sieving was carried out in

ASTM sieve at ½ φ intervals for about 20

minute in Digital sieve shaker (Retsch AS

200). This basic data i.e. weight percentage

frequency data is converted into cumulative

weight percentage data, served as basic tool

for the generation of other statistical

parameters (Table.1A and B) using USGS

GSSTAT and SEDPLOT (Poppe et al., 2004)

described herein generates statistics to

characterize sediment grain-size

distributions and can extrapolate the fine-

grained end of the particle distribution. It is

written in Microsoft Visual Basic 6.0 and

provides a window to facilitate program

execution. The input for the sediment

fractions is weight percentages in whole-phi

notation (Krumbein, 1934; Inman, 1952).

4. Results and Discussion:

The comparative study of the histograms of

retained fractions of sieve analysis i.e.

weight percentage frequency curves

(Mcbride, 1971) most of the samples show

that the sediments range from coarse to

fine-grain, however, a few samples having

high percentage of medium sand are

basically due to fine-grained nature of the

sample during monsoon and postmonsoon

respectively. Most of the cumulative curves

show almost similar trend, exhibiting a little

sorting of grains and dominance of medium

sand size sediments (Fig. 2A and B). Median

value of the particles by weight is coarser to

it and half is fine. During monsoon obtained

values range from 1.97 to 2.64 φ and

postmonsoon ranged from 1.67 to 2.42 φ.

These values, in general, show the

dominance of medium sand size sediments.

Graphic mean is a measure of central

tendency, which is calculated by the formula

φ 16 + φ 50 + φ 83 /3. During monsoon

the average mean value is 2.35 φ but

postmonsoon season obtained value is 2.08

φ its indicates the most of the samples fall

in medium to fine grained nature dominance

long shore current activity. Standard

deviation values ranged from 0.42 to

0.89(monsoon season, Fig.4A) and the

observed minimum and maximum values

ranged from 0.6 to 1.07 φ most of samples

are moderately well sorted during monsoon

but postmonsoon season some of the

sample shows poorly sorted. The skewness

measures the systematic of the distribution

or predominance of coarse or fine-

sediments. It is calculated by the formula φ

84 + φ 16 – 2 φ 50 / (φ 84 - φ 16) + φ 95

+ φ 5 – 2 φ 50 / (φ 95 – 2 φ 5). The

negative value denotes coarse-skewed

material, whereas, the positive value

represents more material in the fine-tail i.e.

fine skewed. During monsoon and

postmonsoon the skewness value ranged

from -0.14 to +0.32 φ and -0.12 to 0.23 φ

it indicates the near- symmetrical, fine-

skewed and some of them coarse skewed

479 Seasonal Variation of Beach Sediment Dynamics of the Coleroon Coast,

Tamil Nadu, India



category. In general, the sediments show

the tendency of more material in fine tail.

Kurtosis values obtained ranges from 1.0 to

1.65 φ (monsoon) and 0.94 to 1.6 φ

(postmonsoon, Fig.3A,B,C & D)

4.1 Bivariate Plot:

The relationship of specific size-parameters

is significant to interpret various aspects of

deposition environment, as the textural

parameters of the sediments are often

environmentally sensitive (Folk and Ward,

1957; Passega, 1957; Friedman, 1961,

1967; Moiola and Weiser, 1968; Visher,

1969). During monsoon season, mean vs

standard deviation plot of the present

samples, shows the nature of the sediments

is dominantly bimodal, of which, the

dominant constituent is sand. The silt is

subordinate making the admixture

moderately-sorted and the mean vs

skewness sinusoidal nature is because of

proportionate admixture of two size-classes

of the sediments i.e. gravel and sand. In

general, the ideal fractions are nearly

symmetrical but the mixing produces either

positive or negative skewness depending

upon the proportions of size-classes in the

admixture. The present values mostly fall in

the positive-skewed area of the graph;

however, one or two samples fall in

negatively skewed, in the mean-size range.

It clearly indicates nature of sediments with

higher percentage of sand and subordinate

silt. The relation between mean-size and

kurtosis is complex and theoretical. The plot

denotes the mixing of two or more size-

classes of sediments, which basically affect

the sorting in peak and tails i.e. index of

kurtosis. It shows that the sediment-

admixture is dominated by medium sand to

fine-sand and including silt. Similarly, the

plot between skewness and standard

deviation produce a scattered trend in the

form the skewness is decreases, standard

deviation improves it may be due to two

conditions i.e. either unimodal samples with

good sorting or equal mixture of two modes.

The plot between standard deviation and

kurtosis, most of the samples are leptokurtic

to very leptokurtic and moderately sorted

moderately well sorted because of the

dominance of fine sand-size sediments. The

plot between skewness vs kurtosis depends

on more or less equally scattered it may be

due to the dominance of fine sand size

sediments its due to low littoral current

carries coarse grains only remaining more

fine grains. During postmonsoon season, the

bivariate plotted between mean grain size

and standard deviation reveals that as the

grain size decreases, sorting improves. The

concentration of fine grain size sediments at

either side of the mouth of colroon river

shows that they carried away by the coastal

processes. Fine grain size and moderate

sorting nature indicate low energy

environment. Low energy is expected to

produce at the river mouth due to

interaction of strong outflow of the river

water and incoming wave and tidal currents.

The lower energy levels permit deposition of

finer sediments as well as transportation of

a much wider range of coarser sediments

(Bryant, 1982). The plot mean Vs skewness,

the mean size increases, sediments become

moderately sorted as well as more

negatively skewed. Thus it is seen that

moderately well sorted sediments are more

negatively skewed. The range of size

parameters is lower during monsoon as

compared to that of the post monsoon

season. The relation between mean Vs

kurtosis indicates the most of the samples

fall in leptokurtic to very leptokurtic

category. The plot between skewness and

standard deviation produce a scattered

trend in the form the skewness is increases,

standard deviation decreased it may be due

to the variations under the influence of

littoral currents occasionally of opposing

nature. The plot between standard deviation

and kurtosis, most of the samples are very

leptokurtic and moderately well sorted

because of the dominance of fine sand-size

sediments this kind of result was observed

at Deepti Dessai (2009). The plot between

skewness vs kurtosis must be acting as a

obstruction to littoral currents and are

responsible for changing the direction. The

change in direction of sediment movement

has resulted in the formation of a bar

slightly towards northern side of the

Coleroon river mouth seen especially during

postmonsoon (Fig.4A, B & C).




4.2 Triangular plot:

Sedimentological datasets are typically large

and compiled into tables or databases, but

pure numerical information can be difficult

to understand and interpret. Thus, scientists

commonly use graphical representations to

reduce complexities, recognize trends and

patterns in the data, and develop

hypotheses of the graphical techniques; one

of the most common methods used by

sedimentologists is to plot the basic gravel,

sand, silt, and clay percentages on

equilateral triangular diagrams. This means

of presenting data is simple and facilitates

rapid classification of sediments and

comparison of samples (Poppe and Eliason,

2008). Further, sediment classification has

been attempted by plotting the percentage

of sand, silt and clay in a triangular diagram

proposed by Folk (1957, 1974). The study

reveals that the beach sediments of

Coleroon mouth either side to Nagpattinum

distict fall in medium and fine grained

category of the size grade scale during

monsoon season. During postmonsoon

season all the samples fall in sand category.

As the sediments of the puthpattinum to

thirumulaivazal coast contain a very large

amount of sand and meager amount of silt

and clay (Fig.5).

4.3 CM plot:

Passega (1957) introduced C-M plot to

evaluate the hydrodynamic forces working

during the deposition of the sediments. It is

a relationship of ‘C’ i.e. coarser one

percentile value in micron and ‘M’ i.e.

median value in micron on log-probability

scale. The present plot is made and

interpreted following Passega (1957, 1964)

and Passega and Byramjee (1969).

Accordingly, during monsoon season most of

the samples fall in N-O region of sector I,

which denotes rolled sediments with little or

no suspension. postmonsoon season most of

the samples fall in P-O region of sector I,

which indicate rolling and suspension field.

However, a few sediment falling in the

sector II, showing suspension and rolling

mode of sedimentation are due to

comparatively more percentage of fine sand

grained material (Fig.6).

5. Conclusions:

Grain size analysis was carried out Coleroon

coastal sediment samples mostly medium to

fine fine-grained of Coleroon of coast area

has been carried out. The important

conclusion drawn is as follow, the frequency

curves are dominantly indicative of two

season, monsoon, and post monsoon,

medium to fine-grained nature of the

sediments. The graphic mean value in two

season monsoon season majority of the

sample fine sand particles, during

postmonsoon season medium sand size to

fine sand size. The gradual decrees in

energetic condition of fluvial regime towards

coast. The sediment, in general, show

during monsoon season moderately sorted

to moderately well sorted nature, during

postmonsoon season same kind of result

was observed, it is noted that the sorting

with the lowering of mean size. The graphic

skewness, shows during monsoon season

near symmetrical to fine skewed category.

Same kind of result was observed during

postmonsoon season. Towards the coastal

region of the study area beaches

predominance of fine skewed to very fine

skewed nature in noticed, which exhibit the

removal of fine population. The graphic

kurtosis it shows during monsoon season

most of the samples fall in leptokurtic to

very leptokurtic nature, during postmonsoon

seson meusokurtic to very leptokurtic in

nature. The frequency curves of downstream

sand are polymodal with moderate to high

peak, because the total sediment is made up

to concentration of multi dominant

population resulting leptokurtic to

mesokurtic. The kurtosis nature of the

sediment in the Coleroon downstream

suggest that the sediment achived very poor

sorting in the low energy environment.

Various bivariate plots between mean,

skewness, kurtosis and standard deviation

are also interpreted bimodal in nature.

Standard deviation vs mean and standard

deviation vs skewness indicate a fluvial

environment. The sediments are mostly

rolled and deposited by traction currents,

however, a few samples showing suspension

mode is because of more quantity of fine


Tamil Nadu, India



grained material during monsoon and

postmonsoon seasons.

References:

[1] Adekola, F. A.,&Eletta,O.A.A.

(2007).Astudy of heavy metal pollution

of Asa river, Ilorin, Nigeria; Trace metal

monitoring and geochemistry.

Environmental Monitoring Assessment,

125, 157–163.

[2] Amos, C.L., 1995. Siliclastic Tidal Flats.

In: Perillo, G.M.E. (Ed.), Geomorphology

and Sedimentology of Estuaries.

Development of Sedimentology, 53, 273-

306.

[3] Bryant Edward. 1982, Behavior Of Grain

Size Characteristics On Reflective And

Dissipative Foreshores, Broken Bay,

Australian Journal Of Sedimentary

Petrology, .52, 431-450.

[4] Dessai D.V.G , Nayak ,G.N., (2009)

Distribution and speciation of selected

metals in surface sediments, from the

tropical Zuari estuary, central west coast

of India Environ Monit Assess 158:117–

137.

[5] Folk R.L. And Ward W.C. 1957. A Study

In The Significance of Grain Size

Parameters, Journal of Sedimentary

Petrology, 27, 3-26.

[6] Folk, R.L.1974, Petrology of Sedimentary

Rocks Hemphill Publishing Co., Austin.

[7] Fox, W.T., Ladd, J.W., Martin, M.K.,

1966. A Profile of the Four Moment

Measures Perpendicular to a Shoreline,

South Haven, Michigan. Journal of

Sedimentary Petrology, 36, 1126-1130.

[8] Friedman G.M. 1961, Distinction

between Dune, Beach and River Sands

from their Textural Characteristics,

Journal of Sedimentary Petrology, 31,

515-529.

[9] Friedman G.M. 1967, Dynamic Processes

and Statistical Parameters Compared for

Size Frequency Distribution of Beach and

River Sands, Journal of Sedimentary

Petrology, .37, 327-354.

[10] Horsfall, M., & Spiff, A. I. (2002).

Distribution and partitioning of trace

metals in sediments of the lower

reaches of the new Carlabar river, port

Harcourt, Nigeria. Environmental

Monitoring and Assessment, 78, 309–

326.

[11] Holme N.A. And Macintyre A.D. 1971,

Methods for the Study of the Marine

Benthos, I.B.P. Handbook No.16,

Blackwell, Oxford.

[12] Ingram R.L. 1970, Sieve Analysis,

Procedures in Sedimentary Petrology,

Willey Interscience, Newyork.

[13] Inman D.L., 1952, Measures for

Describing Size of Sediments, Journal of

Sedimentary Petrology, 19, 125–145.

[14] Ikem, A,. Egiebor, O.N., Nyavor,

K,.(2003). Trace elements in water, fish

and sediment from Tuskegee Lake,

southern USA, Water, Air, and Soil

Pollution 149, 51–75.

[15] Jain, C. K., Singhal, D. C., & Sharma, U.

K. (2005). Metal pollution assessment

of sediment and water in the river

Hindon, India. Environmental

Monitoring and Assessment, 105, 193–

207.

[16] Komar, P.D., 1976. Beach Processes

and Sedimentation. Prentice-Hall,

Englewood Cliffs, .429.

[17] Krumbein W.C., 1934, Size Frequency

Distribution of Sediments, Journal of

Sedimentary Petrology, 4, 65–77.

[18] Li, Y., Yu, Z., Song, X., & Mu, Q.

(2006). Trace metal concentrations in

suspended particles, sediments and

clams from Jiaozhou Bay of China.

Environmental Monitoring and

Assessment, 121, 491–501.

[19] Mcbride E.F. 1971, Mathematical

Treatment of Size Distribution Data. In:

R.E. Carver (Ed.), Procedures in

Sedimentary Petrology. Wilson

Interscience.

[20] Moiola R.J. and Weiser. D. 1968,

Textural Parameters: An Evaluation,

Journal of Sedimentary Petrology, 38,

45-53.

[21] Musila, W.M., 1998. Floristic

Composition, Structure and Distribution

Patterns of Coastal Sand Dune

Vegetation: A Case Study Of The

Coastal Dunes Between Malindi And

Mambrui. M.Phil. Dissertation,

Moiuniversity, Eldoret, Kenya, .160.

[22] Naji A , Ismail A , Ismail A.R., (2010).

Chemical speciation and ontamination




assessment of Zn and Cd by sequential

extraction in surface sediment of Klang

River, Malaysia Microchemical Journal

95, 285–292.

[23] Passega R. 1957, Texture as a

Characteristic of Clastic Deposition.

American Association of Petroleum

Geology, 41, 1952-1984.

[24] Passega R. 1964, Grain Size

Representation by C-M Pattern as a

Geological Tool, Journal of Sedimentary

Petrology, 34, 830-847.

[25] Passega R. and Byramjee R. 1969,

Grain Size Image of Clastic Deposits,

Sedimentology, 13, 180-190.

[26] Poppe L.J. And Eliason A.H. 2008, A

Visual Basic Program to Plot Sediment

Grain-Size Data on Ternary Diagrams,

Computers & Geosciences, 34, 561–

565.

[27] Poppe L.J., Eliason A.H., Hastings M.E.

2004, A Visual Basic Program to

Generate Sediment Grain-Size Statistics

and to Extrapolate Particle Distributions,

Computers & Geosciences, 30, 791–

795.

[28] Trenhaile, A.S., 1997. Coastal Dynamics

and Landforms. Clarendon Press,

Oxford, 365.

[29] Visher G.S. 1969, Grain Size

Distributions and Depositional

Processes. Journal of Sedimentary

Petrology, 39, 1074-1106.

[30] Woodroffe, C.D., 2003. Coasts: Form,

Processes and Evolution. Cambridge

university Press, Cambridge, 623.

Table 1A: Graphic Measure from the Grain-Size Analysis of the Samples (Monsoon)

Station Median Mean Standard

deviation Skewness Kurtosis

Sand

%

Silt

%

Clay

%

MS1 2.55 2.59 0.76 0.06 1.23 96.62 3.24 0

MS2 1.99 2.03 0.83 0.12 1.17 94.65 4.98 1.23

MS3 1.97 1.96 0.67 -0.01 1 96.62 1.98 1.87

MS4 2.2 2.12 0.63 -0.14 1.03 96.62 1.23 3.42

MS5 2.44 2.42 0.49 -0.02 1.56 99.02 0 0

MS6 2.42 2.4 0.51 -0.03 1.54 98.34 0.54 0.43

MS7 2.31 2.25 0.59 -0.07 1.21 96.62 2.43 0.65

MS8 2.37 2.33 0.6 -0.02 1.4 96.62 0 0.08

MS9 2.35 2.3 0.58 -0.06 1.31 96.62 0 2

MS10 2.39 2.36 0.63 0.01 1.43 94.23 6.78 1.34

MS11 2.32 2.26 0.59 -0.07 1.24 96.63 2.45 0

MS12 2.44 2.43 0.42 -0.09 1.37 90.32 6.33 2.54

MS13 2.43 2.41 0.53 0 1.58 96.63 1.08 3.55

MS14 2.49 2.49 0.57 0.08 1.65 96.62 0 0.44

MS15 2.51 2.53 0.61 0.09 1.55 96.62 1.34 0.97

MS16 2.38 2.33 0.71 -0.05 1.42 96.62 2.08 0.01

MS17 1.98 1.92 0.89 -0.06 1.14 96.62 0.83 0

MS18 2.58 2.63 0.52 0.25 1.45 96.62 2.34 0.43

MS19 2.64 2.74 0.55 0.32 1.28 96.62 0.32 0.65

MS20 2.54 2.56 0.52 0.16 1.63 96.62 0 4.07

Minimum 1.97 1.92 0.42 -0.14 1 90.32 0 0

Maximum 2.64 2.74 0.89 0.32 1.65 99.02 6.78 4.07

Average 2.35 2.35 0.614 0.029 1.356 96.14 2.03 1.26


Tamil Nadu, India



Table 1B: Graphic Measure from the Grain-Size Analysis of the Samples (Postmonsoon)

Station Median Mean Standard

deviation Skewness Kurtosis

Sand

%

Silt

%

Clay

%

PMS1 2.28 2.24 0.72 0.01 1.22 98.32 2.34 0

PMS2 2.16 2.12 0.66 -0.02 1.09 90.32 5.67 4.32

PMS3 2.42 2.4 0.59 -0.01 1.6 96.61 3.45 0

PMS4 1.83 1.87 0.63 0.1 0.99 91.32 4.32 2.35

PMS5 2.31 2.25 0.63 -0.04 1.27 96.61 2.34 0.43

PMS6 2.24 2.18 0.64 -0.07 1.15 96.62 1.24 0.86

PMS7 1.73 1.73 0.83 0.01 1.05 96.62 2.34 1.34

PMS8 2.38 2.33 0.62 -0.06 1.5 98.23 1.03 0

PMS9 2.23 2.17 0.61 -0.12 1.07 96.63 2.34 1.87

PMS10 2.27 2.21 0.69 -0.02 1.24 96.62 0 3.98

PMS11 1.84 1.87 0.66 0.05 1.02 99.32 0.12 0.43

PMS12 2.29 2.21 1.01 -0.1 1.1 96.62 2.35 0

PMS13 1.76 1.82 0.7 0.11 1.11 96.61 3.98 0

PMS14 2.04 2.05 0.66 0.1 1.08 97.34 1.23 0.87

PMS15 1.67 1.76 0.61 0.23 1.18 96.62 2.34 1.34

PMS16 1.89 1.94 0.6 0.13 0.95 96.61 2.48 0.65

PMS17 2.13 2.09 0.58 -0.09 0.94 96.61 1.09 0

PMS18 2.34 2.28 0.6 -0.09 1.32 96.62 0 3.67

PMS19 1.92 1.95 0.58 0.1 0.94 98.45 2.98 0

PMS20 2.31 2.25 0.62 -0.06 1.27 96.63 0 0

Minimum 1.67 1.73 0.58 -0.12 0.94 90.32 0 0

Maximum 2.42 2.4 1.01 0.23 1.6 99.32 5.67 4.32

Average 2.096 2.084 0.67 0.0122 1.16 96.3 2.15 1.2




Figure 1: Location Map of the Area of Study

Figure 2A: Cumulative Curves Showing the Trends of All the Samples (Monsoon)

Figure 2B: Cumulative Curves Showing the Trends of All the Samples (Postmonsoon)


Tamil Nadu, India



Figure 3: (A) Mean, (B) Standard Deviation, (C) Skewness, (D) Kurtosis




Figure 4A: Mean Vs Standard Deviation

Figure 4B: Mean Vs Skewness

Figure 4C: Mean Vs Kurtosis


Tamil Nadu, India



Figure 5: Tringular Diagram Showing Distribution of Study Area

Figure 6: C-M Plot Showing Distribution of Sediment Samples

Seasonal Variation of Beach Sediment Dynamics of the Coleroon Coast, Tamil Nadu, India

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