Indian Journal of Geo-Marine Sciences
Vol. 42(3), June 2013, pp. 375-382
Depositional environment of sediments along the Cuddalore coast of Tamilnadu,
India
S.Viveganandan1, C.Lakshumanan1*, M.Sundararajan2*, S. Eswaramoorthi3 & Usha Natesan4
1
Centre for Remote Sensing, Bharathidasan University, Tiruchirappalli-620 023, India
2
National Institute for Interdisciplinary Science and Technology (CSIR),
Thiruvananthapuram, 695 019, India
3
Department of Civil Engineering, Anna University of Technology, Thiruchirappalli-620 023, India
4
Centre for Environmental Studies, Anna University, Chennai- 600 025, India.
[*E-mail: [email protected]/rajanmsundar77 @yahoo.com]
Received 11 April 2011; revised 8 February 2012
Surficial sediments of beaches along the Cuddalore, central coast of Tamilnadu from Ponnaiyar estuarine to
Thirumulaivasal were studied for their textural parameters namely Mean (Grain size) phi, Standard deviation, Skweness and
Kurtosis and mineral percentages. Observed variation of energy conditions are controlled by the fluvial profile in the river
channel. Textural analysis of medium sand shows the existence of comparatively high energy condition in the marine
environment and low energy conditions in the fluvial zone. Linear Discriminant Function (LDF) analysis of the samples
indicates a shallow marine environment origin for most of the samples and very few numbers of samples originated from
fluvial environment. Heavy mineral content serves as an index for stratigraphic correlation of unfossilferrous strata. The
lowest heavy mineral content indicates progradational activity and low energy wave conditions. These results show that
reworked sediments, submerged during the Holocene marine transgression are being deposited on present day beaches by
waves, currents and rivers in the study region.
[Keywords: Beach sediments, Grain size, Depositional environment, India]
Introduction
In India, coastal regions are increasingly being used
for placer sand mining, recreation, aquaculture, coral
mining, and fishing. Earlier workers1-4 attempted the
application of light mineral analysis in provenance
studies. Anirudhan5 illustrated the petrography of light
detrital minerals of Bharathapuzha to decipher the
depositional history. Muthukrishnan6 studied light
minerals from the Gadilam River in order to understand
the maturity of quartz, orthoclase and microcline. The
studies of light minerals from Vaippar and Gadilam
River sediments concluded that they are influenced the
continental block provenances7-8. The introduction of the
Coastal Regulation Act and the Offshore Mining Bill for
the exploitation of mineral deposits off the Indian coast
has highlighted the importance of documenting coastal
processes and sediment characteristics. The increasing
demand for exploring and exploiting non-living coastal
resources like placer deposits emphasises the need to
compile more extensive inventories of these deposits
that include sediment systematics such as grain size.
Present study consists he documentation and the
characteristics of grain size and mineral content from the
Cuddalore coast to characterize the sediment source.
Materials and Methods
Study area
The study area is located on the Cuddalore coast of
Tamilnadu in Southern India and it is bordered on the
east by Bay of Bengal. It lies Ponnaiyar estuarine in
north and Thirumulaivasal in south and lies
between11° 50’ to 11° 10’ N latitude and 79° 45’ to
79° 55’E longitude Fig. 1. The nearest major sediment
Fig. 1Location map of the study area
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INDIAN J. MAR. SCI., VOL. 42(3), JUNE 2013
source for this coastal segment is the Ponnaiyar,
Gadilam, Uppanar Rivers in the north and Vellar and
Coleroon River in the south.
Sediment samples were collected from 18 locations
of different landforms from Cuddalore beach and
locations of samples were recorded carefully with GPS.
Sediment samples were collected from 100-150 ft
distance from water using spatula to a depth of 15cm.
Distance between samples were used for 2-3 km
parallel to the coast at the elevation of above 10ft.
Sediment samples were stored in polythene bags.
Samples were heated constant temperature of 60°C in
a hot air oven to remove moisture. In order to ensure
the uniformity of heavy mineral distribution, about
120 grams was removed by repeated coning and
quartering method, while the remaining samples were
kept for further reference. From the subsamples,
100 g was used for granulometry study and 20 g was
used for heavy mineral separation. Then the samples
were washed under mechanical stirring, with liberal
amount of distilled water and decanted carefully to
prevent losses. Process of washing and decantation
was repeated until a clear water column was present.
After decantation, the samples were kept for drying.
The 30% by volume of H2O2 was added to the
sample to remove the organic debris in the sediments.
Sample was then washed with distilled water and dried.
After drying it was weighed to measure the organic
material losses. Same samples were treated with ~10%
HCl to remove the calcareous materials present in the
sediments. After proper washing and drying, sample
was weighed to measure the carbonate losses. Dried
samples were used for heavy mineral separation.
For sieving, ASTM sieves from +10 to -230 mesh
sizes (2 mm to 63µm) were used with 1/2 phi intervals9.
Ro-tap sieve shaker was employed for separation with a
15 minutes shaking time for every sample. Sieved
materials were weighed separately. Then the fractions
were properly tabulated and the sands of the respective
fractions were kept for further studies. Grain size
parameters like Graphic Mean (Mz), Inclusive Graphic
Standard Deviation (SD), Inclusive Graphic Skewness
(Sk1) and Graphic Kurtosis (KG) were determined using
the software package. Linear Discriminant Function
(LDF) of Sahu10 was used for the multivariate analysis of
the beach sediments. Separating funnel was used for
heavy mineral separation with Bromoform of 2.89
specific gravity11. Separated heavy fraction was washed
first with methyl alcohol and then with distilled water.
Washed fractions were dried in a hot air oven (60°C),
until the moisture was completely removed. Then the
dried fractions were weighed and the values noted.
Results and Discussion
Mean Grain size
Mean is the arithmetic average size of the sediment
and is expected to be influenced by source of supply,
transport and environment of deposition. The moment
mean values are observed to be identical to the graphic
mean data for the analysed samples, Folk and Ward9,
observed that ‘the graphic mean values are twice as
accurate an approximation as the moment means value.
Coarsest sediments were found in the northern part of
Cuddalore (stations 1 and 2) and southern part (stations
14, 15 and 16), the graphic mean size ranges from 0.6 to
0.94 Ø (Fig. 2). Because of the prevailing high wave
energy environment, strong winnowing must have
removed the fine sediments, leaving the coarser
sediments. This is also evidenced by the erosive action
of the waves. Varadachari12 reported high energy
condition is also attributable to the presence of
submarine canyons in the Pondicherry and Cuddalore
regions. Chauhan13 also reported the coarser sediments
at Cuddalore to be the result of erosion. In other areas
(Stations 3 and 11), the mean size ranged from 1.03 to
1.78 Ø indicating the predominance of medium sands.
Standard Deviation
The sorting values for sample stations (1, 2, 5, 6, 7,
9, 10, 12, 13, 14, 15, 16, and 17) range from
0.42 to 0.70 indicated that the sediments are well
sorted (0.35-0.5 range) to moderately well sorted
(0.5-0.7range) (Fig. 3). This well sorted nature
Fig. 2Mean grain size of Cuddalore beach sediments from north
to south (station 1-18)
Fig. 3Standard deviation of Cuddalore beach sediments (n = 18)
VIVEGANANDAN et al: DEPOSITIONAL ENVIRONMENT OF SEDIMENTS ALONG THE CUDDALORE COAST
(station 1, 15, 16 and 17) can be put down to the mixing of
sediments brought by waves and currents, in addition to the
input of palaeo-sediments from the major river systems
(Ponnaiyar and Coleroon). Moderately sorted sands are
predominant on the beaches (station 4, 8 and 18) of the east
coasts of India14. Sorting values from 0.51 to 0.70 and
0.72 to 0.97 (Table 1) indicate that these sediments are
moderately well (0.5-0.7 range) to moderately sorted
(0.7-1.0 range). This is the result of the mixing of the
sediments brought from the adjacent beach ridges.
Standard deviation varies between 1.3 and 1.18,
indicating that the sediments are poorly sorted
(1.0-2.0 range). It is characterized by high energy wave
conditions and mixed type of sediments. Folk and Ward9
observed that the medium to fine sediments are better
sorted than very fine sediments. However our study
shows that the medium grained sands are poorly sorted.
This may be due to the influence of various modes of
transport leading to poorly sorted sediments. During
monsoon and cyclonic storms enormous quantities of
suspended sediments are pushed from north to south.
This may result in for the poor sorting of sediments in
this area. Figures 4 and 5 shows the frequency weight
percentage and cumulative weight percentage diagrams
of the 18 sampled beach sediments. Frequency curve
indicated symmetrical distribution for most of the
stations. But the curve is showing very poor sorting and
deficiently peaked kurtosis to the phi values in the case
of stations 3 and 11. Cumulative weight of the beach
sediments shows sigma distribution between the phi
values of 0 to 2.5 in the case of stations 3 and 11
whereas the distribution is typically very poor. Bivariant
377
plot of mean vs standard deviation (Fig. 6) also shows
that the sediments in both the stations are poorly sorted.
Skewness
The positively skewed distribution indicates a
depositional tendency15. All the tested sediments are
positively skewed suggesting the influence of fine
sediments discharged by the rivers. River mouths are
also marked by the growth of small sand bars.
Stations from non-river point show positive Skewness
Fig. 4Frequency weight percentage curves of Cuddalore beach
sediments (n = 18)
Fig. 5Cumulative weight percentage curves of Cuddalore beach
sediments (n = 18)
Table 1 Statistical analysis of Grain size distribution of Cuddalore beach sediments.
S.No
Mean
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
0.6
0.94
1.64
1.16
1.25
1.19
1.09
1.78
1.03
1.26
1.76
1.16
1.44
0.79
0.72
0.84
1.07
1.06
Standard deviation Skewness Kurtosis
0.49
0.55
1.3
0.97
0.7
0.51
0.58
0.72
0.52
0.66
1.18
0.51
0.54
0.6
0.48
0.42
0.48
0.77
0.18
0.49
0.13
0.1
0.18
0.14
0.13
0.2
0.14
0.08
0.22
0.14
0.45
0.15
0.13
0.3
0.15
0.36
1.15
1.38
0.74
1.29
1.01
1.12
1.31
1.02
1.3
0.87
1.03
1.18
1.3
0.73
1.12
1.13
1.13
2.52
Mean
Coarse sand
Coarse sand
Medium sand
Medium sand
Medium sand
Medium sand
Medium sand
Medium sand
Medium sand
Medium sand
Medium sand
Medium sand
Medium sand
Coarse sand
Coarse sand
Coarse sand
Medium sand
Medium sand
Standard deviation
Skewness
Well sorted
Fine skewed
Moderately Well sorted Very fine skewed
Poorly sorted
Fine skewed
Moderately sorted
Fine skewed
Fine skewed
Moderately Well sorted
Fine skewed
Moderately Well sorted
Fine skewed
Moderately Well sorted
Moderately sorted
Fine skewed
Fine skewed
Moderately Well sorted
Fine skewed
Moderately Well sorted
Poorly sorted
Fine skewed
Fine skewed
Moderately Well sorted
Moderately Well sorted Very fine skewed
Moderately Well sorted
Fine skewed
Well sorted
Fine skewed
Well sorted
Fine skewed
Well sorted
Fine skewed
Moderately sorted
Very fine skewed
Kurtosis
Leptokurtic
Leptokurtic
Platykurtic
Leptokurtic
Mesokurtic
Leptokurtic
Leptokurtic
Mesokurtic
Leptokurtic
Platykurtic
Mesokurtic
Leptokurtic
Leptokurtic
Platykurtic
Leptokurtic
Leptokurtic
Leptokurtic
Very
Leptokurtic
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INDIAN J. MAR. SCI., VOL. 42(3), JUNE 2013
(Fig. 7). Positive value indicates an excessive supply
of fine materials brought in by littoral currents. Rao16
reported the positive Skweness of the beach sediments
of False Devi point in Andhra Pradesh to the
excessive supply of fine sediments brought in by
littoral current. In the present study mean size Vs
Skewness plot (Fig. 8) indicates that, the severe
contribution of supplying fine sediments from the
offshore region except low current estuaries.
Standard deviation Vs Mean plot (Fig. 9) shows
most of the sediments are moderately well to
moderately sorted. This sector has no fluvial influence
except the two samples (stations 3 and 11) were poorly
sorted. This plot clearly indicates these sediments are
the influence of fluvial environment because the river
input is more than the littoral current.
Scatter plot of standard deviation Vs Skewness
(Fig. 10) also helps to characterize these sediments. In
the study area from north to southern region, all the
samples have no fluvial influence except at the
stations 3 and 11 but the station 4 is closer to the
fluvial influence. Station 4 is nearer to the mouth of
Uppanar River and based on the wave and seasonal
influence play an important role.
Fig. 6Scatter plot of Mean Vs Standard deviation for Cuddalore
beach sediment
Fig. 9Scatter plot of Standard deviation Vs Mean for Cuddalore
beach sediment
Kurtosis
The graphic kurtosis is the qualitative measures of
the part of sediments already sorted elsewhere in a
high energy environment and later transported and
modified such as beach, shallow marine and fluvial
environment. Values of the graphic Kurtosis range
between 0.73 and 2.52 (Fig. 11). Majority of the
Fig. 7Skewness of Cuddalore beach sediments (n = 18)
Fig. 10Scatter plot of Standard deviation Vs Skewness for
Cuddalore beach sediment
Fig. 8 Scatter plot of Mean Vs Skewness for Cuddalore beach
sediment
Fig. 11Kurtosis of Cuddalore beach sediments (n = 18)
VIVEGANANDAN et al: DEPOSITIONAL ENVIRONMENT OF SEDIMENTS ALONG THE CUDDALORE COAST
samples falls under leptokurtic nature of distribution.
Very small number of samples falls under the platykurtic
and mesokurtic nature but station 18 falls under the very
leptokurtic nature. Variation in the kurtosis values is a
reflection of the flow characteristics of the depending up
on the medium, the dominance of medium size sands of
leptokurtic nature reflecting the maturity of the sand.
This may be due to the aggregation of sediment particle
size by dense and the variations in the sorting values are
likely due to continuous addition of medium/coarse
materials in varying proportions.
4.5 Linear Discriminant Function analysis (LDF)
According to the variations in the energy and
fluidity factors seem to have excellent correlation with
different processes and the environment of
depositions17. Sahu’s 10 Linear Discriminant Function
Analysis (LDF) of Y1 (Aeolien, Beach), Y2 (Beach,
Shallow agitated water) and Y3 (Shallow marine,
Fluvial) were used to decipher the process and
environment of deposition. With reference to the Y1
and Y2 values, all the samples fall in beach process and
ten samples fall in shallow agitated water and rest of
them falls in Beach. Further the samples in Y3 indicate
that they were of the combination of shallow marine
and fluvial process (Table 2). Most of the samples fall
in shallow marine process except those from the
locations 3, 4 and 11. These samples located in the
mouth of the river Uppanar and Vellar reflect the
influence of a fluvial environment. The sediments
discharged by the river Uppanar and Vellar must have
been redeposited in this region by the wave action. It
can be inferred that the sediments in the present day
beaches must have been deposited in a shallow marine
environment and marine deterioration must have led to
the development of the present day shorelines.
Minerals
Beach is a temporary or short lived deposit on the
shore. Most of the materials are sand and silt sized
grains. The waves and tides have played a major role
in the shaping of shoreline. Weight percentage of
heavy minerals varies from 0.92 to 23.22% with an
average of 5.6% (Fig. 12). Stations 11, 12, 15 and
17 show a relative high percentage of heavy minerals
(Fig. 13). Heavy mineral percentage of sample at
station 11, 12, 15, and 17 (9.24%, 10.52%, 6.41% and
23.22% respectively). This percentage is attributed to
Fig. 12Heavy mineral distribution map of the study area
Table 2Linear discriminate function values (Sahu 10)
S.No
Y1
Y2
Y3
Y1
379
Y2
Y3
1
1.95
49.70
-2.75
Beach
Beach
Shallow marine
2
1.04
68.99
-4.71
Beach
Shallow agitated
Shallow marine
3
2.43
152.76
-14.93
Beach
Shallow agitated
Fluvial
4
3.15
105.66
-8.33
Beach
Shallow agitated
Fluvial
5
0.12
73.71
-4.76
Beach
Shallow agitated
Shallow marine
6
-0.08
58.97
-2.57
Beach
Beach
Shallow marine
7
1.16
65.76
-3.20
Beach
Shallow agitated
Shallow marine
8
-1.67
84.42
-4.961
Beach
Shallow agitated
Shallow marine
9
1.08
60.48
-2.69
Beach
Beach
Shallow marine
10
-0.34
65.89
-3.80
Beach
Shallow agitated
Shallow marine
11
1.62
142.08
-12.72
Beach
Shallow agitated
Fluvial
12
0.20
59.61
-2.57
Beach
Beach
Shallow marine
13
-0.94
73.90
-4.28
Beach
Shallow agitated
Shallow marine
14
0.47
52.24
-3.62
Beach
Beach
Shallow marine
15
1.50
49.48
-2.39
Beach
Beach
Shallow marine
16
0.55
51.08
-2.71
Beach
Beach
Shallow marine
17
0.24
55.51
-2.39
Beach
Beach
Shallow marine
18
5.50
108.70
-6.53
Beach
Shallow agitated
Shallow marine
Note: This table indicates all the samples in beach sediments and the depositional environment is mostly shallow marine
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INDIAN J. MAR. SCI., VOL. 42(3), JUNE 2013
the intensive role of winnowing action of waves and
currents. The higher percentage indicates that the light
minerals are removed by winnowing of waves.
Weight percentage of light mineral deposits varies
from 76.78% to 99.08% (Fig. 14) with an average of
94.4% for the 18 sampled Cuddalore beach sediments.
Relative higher percentages were recorded at the stations
5, 7, 9, 13, 14 & 16 (>98%). This higher percentage of
light minerals indicates the progradational activity and
low energy wave condition in the study area.
Heavy minerals
Sediment samples were used for microscopic study
for the identification of heavy minerals. Only five
estuarine stations such as Ponnaiyar, Gadilam, Uppanar,
Vellar and Coleroon were selected and five different
heavy minerals were identified but Ponnaiyar estuary
has resulted two types of heavy minerals whereas, Vellar
and Coleroon have resulted similar type of mineral.
ferro and calcium magnesium- silicate minerals, such
as amphiboles and pyroxenes in prominent amounts,
and lesser amount of kyanite could indicate igneous
and/or metamorphic sources11. Presence of pyroxenes
reflects basic igneous rocks; and amphiboles, represents
igneous and/or metamorphic rocks19-20 (Fig. 15).
Kyanite
Kyanite is a polymorph mineral that shares the same
chemistry but a different crystal structure with another.
It is an attractive mineral that has a near sapphire-like
blue colour but also can be white, gray or green.
Kyanite has a nearly unique characteristic in that it has
a wide variation in hardness in same crystal face
(Fig. 16a). The hardness of Kyanite is approximately
4.5 to 6.5 and specific gravity of 3.58. It is a refractory
material and it has a high melting point, low thermal
conductance and maintains its strength upto 1100°C.
Hypersthene
Pyroxene, Amphibole
The pyroxenes are a group of important
rock-forming inosilicate minerals found in many
igneous and metamorphic rocks. Amphiboles are
minerals of either igneous or metamorphic origin; in
the former case occurring as constituents (hornblende)
of igneous rocks, such as granite, diorite, andesite and
others. Calcium is sometimes a constituent of
naturally occurring amphiboles18. The occurrence of
Hypersthene is a relatively common mineral and is
found in igneous and some metamorphic rocks as well
as in stony and iron meteorites. Hypersthene is the
intermediate member with around 50% iron and
ferrosilite is the iron rich end member of the series. It is
an orthopyroxene or a pyroxene with an orthorhombic
symmetry (Fig. 16b). At high temperatures, its structure
changes to a monoclinic symmetry and a clinopyroxene.
Hypersthene has an ornamental variety. A weathered
variety that has a sub metallic luster and a bronze like
colour is called “bronzite”. It is sometimes used as an
ornamental stone. It is a gray, brown colour mineral and
hardness is approximately 5-6. The specific gravity of
this mineral is approximately 3.4-3.9.
Ilmenite
Fig. 13Heavy mineral percentage of Cuddalore beach sediments
(n = 18)
Fig. 14Light mineral percentage of Cuddalore beach sediments
(n = 18)
Ilmenite is an economically important and black
colour mineral. It is named for its place of discovery at
Ilmen Lake in the Ilmen Mountain, Russia. It forms as a
primary mineral in mafic igneous rocks. It also occurs in
pegmatites and some metamorphic rocks as well as in
the sedimentary rocks that are formed from the
weathering and erosion of them (Fig. 16c). The hardness
of ilmenite is 5-6 and its specific gravity is 4.5 -5.
Fig. 15Mineral composition
VIVEGANANDAN et al: DEPOSITIONAL ENVIRONMENT OF SEDIMENTS ALONG THE CUDDALORE COAST
381
Fig 16Different type of heavy minerals in Cuddalore estuaries: (a) Pyroxene ,Amphibole, Kyanite (Ponnaiyar estuary), (b) Pyroxene
,Amphibole, Hypersthene (Ponnaiyar estuary),(c) Pyroxene ,Amphibole, Ilemnite (Gadilam estuary), (d) Pyroxene ,Amphibole, Laterite
(Uppanar estuary), (e) Pyroxene, Amphibole, Sillimanite (Vellar estuary), (f) Pyroxene ,Amphibole, Sillimanite (Coleroon estuary).
Laterite
Laterites are soil types rich in iron and aluminum,
formed in hot and wet tropical areas. Nearly all
laterites are rusty-red because of iron oxides. They
develop by intensive and long-lasting weathering of
the underlying parent rock. Tropical weathering
(laterization) is a prolonged process of chemical
weathering which produces a wide variety in the
thickness, grade, chemistry and ore mineralogy of the
resulting soils (Fig. 16d).
Sillimanite
Sillimanite is an alumino-silicate mineral. It is an
orthorhombic with square cross sections and rounded.
It is presented in white to gray, also brown, yellow,
and yellow-green. A polymorph is a mineral that
shares the same chemistry but a different crystal
structure with another, or other minerals. Sillimanite
is the rarest of the three trimorphs (Fig. 16e and f).
The hardness is 7.5 in large crystals but more fibrous
forms are softer and the specific gravity is
approximately 3.2.
Conclusion
Most of the sediments are medium to coarser
grained sand as beaches are steeply sloping and high
wave energy conditions. The location 3, 4 and 11
under moderate sloping beach sediments are medium
owing the fluvial discharge. Mixing of sediments
under high and low energy conditions has affected the
sorting of sediments. Beach processes have affected
the sorting characteristics of the sediments. Skewness
values indicates the depositional processes such as
winnowing action of waves and currents and
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INDIAN J. MAR. SCI., VOL. 42(3), JUNE 2013
decreasing energy of the transporting process in some
of the places. This is endorsed by the development of
sand bars at the mouth of the river point. Bivariant
plots such as mean vs standard deviation, mean vs
skewness, standard deviation vs mean and standard
deviation vs skewness present an overlapping of the
fluvial, marine and beach environments in the beach
samples of the study area. LDF result shows that most
of the sediments are deposited under shallow marine
environment by beach and fluvial processes due to near
shore agitating turbidity action of water. Landforms
help to infer various stages of the study region. Nature
of the concentration of heavy mineral is suggestive of
the influence of higher wave energy in middle and
southern part of the study area. Poor concentration of
heavy mineral have been attributed to large
progradational activity and the low energy wave
condition, whereas the higher concentration of heavy
mineral percentage is ascribed to accurate coast line. It
also suggests that these minerals are derivatives of
common source like palaeo sediments influence which
are reworked by present day coastal processes.
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