CHAPTER-5 GRAIN SIZE. Grain size, refers to the diameter of individual grains of sediment, or the lithified

Transcription

1 CHAPTER-5 GRAIN SIZE 5.1. INTRODUCTION: Grain size, refers to the diameter of individual grains of sediment, or the lithified particles in clastic rocks Grain size distribution is one of the most fundamental physical properties in sedimentology. The determination and interpretation of particle grain size has fundamental role in hydrological, geomorphological and sedimentological (Friedman and Sanders, 1978, Goudie1981) studies. Determination of the sediment grain size is not a trivial task because of the heterogeneity of the shape and density of particles and absorbed materials. Size analysis of sediment is an essential requirement to understand their mechanism of transportation and deposition. Textural parameters are primarily related to mode of transportation and energy condition of the transporting medium. Grain size analysis is one of the important and widely used sedimentological tools to unravel the hydrodynamic conditions of aquatic environments. The grain size distribution, its properties and the statistical parameters worked out from size population are the basic requirements in the understanding of the abiotic fabric of aquatic ecosystems (Allen and Duffy, 1998; Bhat et al., 2002; Nageswara Rao et al., 2005; Kroon et. al., 2008). Careful examination of granulometric parameters and their proper evaluation using standard methods could be used in the discrimination of various depositional environments (Allen, 1970; Goldberg, 1980; Poppe et al., 2000; Woodruff et. al 2001;

2 Selvaraj and Ram Mohan 2003; Alsharhan and El-Sammak, 2004; Yunus et. al., 2008) In this study it is focused on classification of grain size and certain measures (Mean, Sorting, Skewness and Kurtosis) of special relevance in lake sedimentological contexts and some applications related to sediment types and bottom dynamics. Sediments that accumulate in lake basins consist of numerous source materials and reflect changes that have occurred in the lake and in its catchment area. The amount of mineral matter and grain size composition of sediments are indicators of process in the lake basin (Boyle, 2001) and changes in water level (Digerfeldt, 1986; Dearing, 1997). In the present study from each bulk sample from bottom surface (10 No of samples) and one core (23 No of samples i.e. 46cm sub sampled with 2cm) have been analysed (in total 33 samples) to understand the spatial and temporal variation in grain size. The various textural parameters obtained through graphic and moment method are given in table 5.1 and RESULT AND DISCUSSION: FREQUENCY CURVES: Frequency curves show evidence of the illustrative demonstration of weight percentage of different fractions of sediments. The peakedness of fraction and uniformity of the sediments are inferred from it in the study area. Rajan Canal, Sengal odai and Vadavar channel are the important supply of water to Veeranam Lake. The sediments they carry along are debouched into the lake and to Bay of Bengal. In order to decipher the role of different transporting agents and the regulating nature of

3 Table.5.1. Textural parameters of surface sediments in Veeranam Lake. S.NO. ME-Q MSD-Q MCD-Q MSK MKU MED-Q M-Q SD-Q SK KU FP-Q Min Max Mean ME-Q = Moment mean Phi, MSD-Q = Moment standard deviation Phi MCD-Q = Mean cubed deviation Phi, MSK = Moment skewness, MKU = Moment Kurtosis, MED- Q = Median Phi, M-Q = Graphic mean Phi, SD-Q = Graphic standard deviation Phi SK = Graphic skewness, KU = Graphic kurtosis, FP-Q = First percentile Phi

4 Table.5.2. Textural parameters of core sediments in Veeranam Lake. S.NO. ME-Q MSD-Q MCD-Q MSK MKU MED-Q M-Q SD-Q SK KU FP-Q Min Max Mean

5 different sub-populations, size frequency curves have been drawn. The assemblages of frequency curve from different parts of the Veeranam Lake, both bottom surface and core sediments are shown in fig.5.1. The frequency curves of the sediments from Veeranam Lake are mostly polymodal character. The Polymodality of the curves may be due to extreme variation in the velocity of the depositioning agent on lake and of certain grain size in the source material (Sahu, 1964). According to Sahu (1964) polymodality may also arise due to diversity in the size range of source material and due to derivation of sediments from two (or) more sources (Pettijohn, 1984). The polymodal nature of the sediments also implies that transportation by rolling, sliding, saltation and suspension processes in the Veeranam Lake STATISTICAL PARAMETERS: The grain size parameters viz., Mean size (M Z ) Standard deviation (i), Skewness (S ki ) and Kurtosis (K G ) of percentile values derived from the cumulative curves following Folk and Ward (1957) and the moment technique based upon grouped data (Friedman, 1967) are most widely used. The statistical parameters of the Veeranam lake bottom surface and core sediments are as follows; A) Mean (M Z ): Mean represents the average size of the total distribution of sediments. It is the function of, a) Total amount of sediments available b) The amount of energy imparted to the sediments and c) Nature of transporting agent.

6 Fig.5.1. Frequency curves for surface and core sediments in Veeranam Lake.

7 The energy of transporting agent includes the degree of turbulence and the role played by currents and waves. The variations of mean values in different stations are shown in fig 5.1. The variation of the mean values in different locations of bottom surface and at the different depths of core sediments are shown in fig 5.2A & B respectively. i) Spatial Distribution: The mean size of the bottom surface sediments ranges from 5.29 to 5.57 indicating the single dominance of medium silts (Fig.5.2A). The geographic trends in the sediment particle size correspond closely to bathymetric variations, as shown by the increasing finesse abundance towards the deepest part of the Veeranam Lake (Fig.5.3). The distribution of mean size in Northern and Southern part of the Veeranam lake exhibit medium silt with coarser nature when compare to the central part, which is predominant of medium silt with finer nature indicating the majority of supply of sediments from Rajan canal in the north and Vadavar canal in the south with the increase of energy level of current in the N and S directions. The dominance of finer nature of medium silty sediments in the central part of the lake can be also attributed to the high volume of water availability with fewer disturbances in this part. The Veeranam lake finer sediments are occupying in the central part and coarser nature are distributed in the northern and southern of the lake (fig.5.3), while the finest sediments are restricted mostly to the deeper part of the lake, within 5.5m contour in Veeranam lake, there appears to be little correlation between grain size

8 Fig.5.2. Variogram mean diagram of textural parameters in Veeranam Lake sediments. A) Surface B) Core.

9 Fig.5.3. Spatial distribution of variogram mean values of surface sediments in Veeranam lake.

10 and depth. The distribution of the sand to silt ratio indicates that much of the sediment are silt-rich mixture in the Veeranam Lake. ii) Temporal Variation: The mean value of core sediment ranges from 5.14 to 5.42 indicating the entire core sediments are also falls in the category of medium silt (fig. 5.2B) as similar to that of surface sediments. The absence of winnowing action and low energy environment being responsible for the silt size grains in the Veeranam Lake. The water level fluctuations are furthermore reflected in the grain size variation of the sediments. The graphical expression of mean grain size shows that the grain size variations are very narrow, suggests homogeneity of the source material and depositional environment. This means that the main sources for sediment matter were accumulated due to water-level descend. Also the relative unstable mean values in the core sediments (Fig. 5.2.B) suggest that the influence of water level fluctuation. In general, when the water level increase, the fine grain size content of the core in the lake increases. On the otherhand, when the water level reduces, the fine grain size content in the core also decreases. B) Standard deviation (i): Standard deviation is a measure of uniformity (or) degree of sorting. Sorting of sediments serves as a mirror to decipher the energy of the depositional environment and to know the presence (or) absence of coarse and fine grained fractions (McKinney and Friedman 1970). It is one of the most useful textural attributes in classifying sands from different depositional environments. Sorting of sediments is

11 influenced by the many parameters like size, shape, specific gravity, resistant nature, inertness, endurability of sediments, degree of turbulence, velocity of the transporting agent, hydrodynamic properties like wave height, wave length and current velocity, nature of sediments supplied to the depositional environment and rate of supply of the detritus material. The best sorted sediments are usually those with mean size range of 2.0 to 3.0 irrespective of the conditions prevailing in depositional environment (Inman, 1952). The relationship between energy and degree of sorting has been demonstrated by Inman (1949). Accordingly the beach sediments are always found to be better sorted than river sediments (Friedman, 1967). The variation of the sorting values in the bottom surface and core sediments of Veeranam Lake are shown in the fig 5.4A and B. i) Spatial Distribution: The standard deviation value of bottom surface sediments ranges from 0.97 to 1.4 in the verbal scale of Folk and ward (1957), they are of poorly sorted type (Fig.5.4A). It may be attributed to the mixture of the finer materials from tributaries and inlets. The deficiency of attrition and saltation in the process are found to be responsible for poorly sorted nature. Apart from this addition of sediment fraction from Rajan canal in the North and Vadavar canal in the south results the deterioration in the sorting over these region when compared to that of central part of the Lake (Fig. 5.5).

12 Fig.5.4. Variogram standard deviation diagram of textural parameters in Veeranam Lake sediments. A) surface B) core.

13 Fig.5.5. Spatial distribution of variogram standard deviation values of surface sediments in Veeranam Lake.

14 ii) Temporal Variation: The whole core sediments are also exhibits poorly sorted characteristics having the standard deviation values between 1.26 and 1.39 (fig.5.4b). Since the addition of particular finer size fraction by the action of river input leads to the enrichment of silt in the lake environment. As a result, the lake having narrow range of size class in finer region and falls within the medium silt size which exhibit poorly sorted nature. The poorly sorted natures are indicative of the immature sediments that have not been transported far-off. C) Skewness (Ski): Skewness of grain size refers to the relative abundances of coarser and finer fractions in a deposit. It also exhibit how far a deposit approaches to the normal Skewness is a significant parameter in delineating environment, since it is sensitive to subpopulation mixing. Sign of the Skewness is closely related to the environmental energy (Duane, 1964). Negative skewness is correlated with a high energy and the prevalence of turbulence action while positive skewness with low energy conducive to the accumulation of clays size particles. The skewness natures of the sediments in the study region are shown in Fig.5.6A and B. i) Spatial Distributiion: The bottom surface sediments exhibit the skewness values ranging from 0.02 to These values of sediments exhibit that the bottom surface sediments are falls in very coarse skewed nature (fig.5.6a). The very coarse skewed nature of the bottom surface

15 Fig.5.6. Variogram skewness diagram of textural parameters in Veeranam Lake sediments. A) Surface B) core.

16 sediments of the Veeranam lake indicates that the input of sediments are from particular source and also exhibits lacking of sub-populations. The spatial distribution of the textural characteristics like finer in size with high values within the poorly sorting type and the more negatively skewed kurtosis values in the central part of the Lake (fig.5.7) are indicating that the energy increases in the direction of transport. Within the basin, trends are significant in both directions, suggesting that occurrence of transport in the low energy regime. Two reasons which may be responsible for obscuring a preferred direction are, sediment input from canals entering both sides of the lake, such as Rajan Canal and Vadavar canal (Fig.4.1), and the breakdown of the thermocline in winter, resulting in weak and random bottom currents (Pickrill and Irwin, 1983). Samples from the north and south show an apparent trend towards centre, indicating that sediment transport is occurring down slope. It is difficult, however, to imagine that the energy regime is decreasing with shoaling water, the requirement for sediment transport. On the contrary, not only are higher energies associated with shoaling water, but eastward currents (positive values of sample 1 and 2) will be concentrated into outflow. The statistical parameters of the sediments from Veeranam lake shows that sediments also finer, poorly sorted, and more negatively skewed if the energy increases in the direction of transport. ii) Temporal Variation: The core sediment falls within the coarse skewed nature with the values ranging between and The results of core sediment samples also finer, poorly sorted, and more negatively skewed than the bottom surface sediments and demands

17 Fig.5.7. Spatial distribution of variogram skewness values of surface sediments in Veeranam Lake.

18 as fluctuation in the energy regimes. But it was argued that successive deposits would be removed by erosion with an increasing energy regime. The trends in core sediments suggest that such deposits can remain, probably as a result of the difficulty in re-suspensioning of fine silt and clay sized particles once they have been deposited. D) Kurtosis (K G ): Kurtosis measures the ratio of sorting between tail and central portions. Folk and Ward (1957) have explained skewness and kurtosis in terms of the mixing of two normal grain sizes. The graphic kurtosis is a measure of the part of the sediments already sorted elsewhere in an environment and later transported and modified by another type of environment. But the moment kurtosis is an index of mixing of two end populations (Thomas et.al. 1972). Jaquet and Vernet (1976) have advocated the usage of graphic kurtosis to recognize the inherited character of population and moment kurtosis for measuring the mixing between the end populations. Sediments with more (or) less equipropotionate mixing of the modes show platy kurtic distribution, whereas the dominance of one mode gives a distribution of leptokurtic nature. The distribution of graphic kurtosis values for the Veeranam Lake is shown in figure 5.8A and B. i) Spatial Distribution: The kurtosis values of bottom surface sediments ranges from 0.88 to 1.47 and falling in between Platykurtic and very Leptokurtic type (5.8A). The very leptokurtic values are due to the implications of poorly sorted sediments and presence of dominance of

19 Fig.5.8. Variogram kurtosis diagram of textural parameters in Veeranam Lake sediments. A) surface B) core.

20 one mode population. The presence of predominance of platykurtic type in the central part of the lake (Fig.5.9) express that this region has less equipropotionate mixing of two (or) three modes. ii) Temporal Variation: The core sediments have kurtosis values ranging from 1.21 to 1.46 falling in Leptokurtic region (fig.5.8b). The leptokurtic nature of the entire core sediments indicating the concentration of one dominant and other subordinate population during the period of deposition. The dominant fine mode gives rise to leptokurtic values. The general nature of core sediments doesn't show any characteristic variation in kurtosis range due to the minor change in the energy condition and water level BIVARIATE PLOTS: The interrelationship between grain size and frequency distribution has been widely used to discriminate the depositional environments and also to recognise the various operative processes of sedimentation of ancient and recent deposits. Plotting the mean vs. the standard deviation of the bottom surface and core sediments shows clustering of sediment near the boundary of coarse silt and medium silt, poorly sorted sand (Fig. 5.10A). It is inferred that the Veeranam lake do not follow the theoretical consideration of sediment sorting. This may be attributed to various factors including contribution of sediments from older sedimentary formations like Cuddalore Sand Stone, beach ridges, runnel systems, and mixing activities etc.

21 Fig.5.9.Spatial distribution of variogram kurtosis values of surface sediments in Veeranam Lake.

22 Fig Bivariate scatter plot of surface and core sediments in Veeranam Lake, A) Mean Vs Standard deviation, B) Mean Vs Skewness

23 The scattering shown in the plot of the mean grain size vs the skewness of the bottom surface and core sediments shows a tendency of relatively more fine material (Fig. 5.10B). The skewness of the bottom surface sediments shows more fine (5.43), whereas the average sizes of the core sediments are dominantly coarse skewed towards finer particles (5.20). The overall assemblage of the points of all the samples shows two clusters, both indicate very coarse skewed nature in bottom surface sediments and coarse skewed nature in core sediments. The bivariate plot skewness vs kurtosis for the bottom surface and core sediments show that poorly sorted fine mode, loses its sorting which is noticed for the entire lake and is due to the addition of finer sediments. The plot of the mean grain size vs. kurtosis indicates a relationship for the surface and core sediments (Fig. 5.11A), although the both surface and core sediments, almost of which have a medium silt grain size, are exceptionally peaked and flat-peaked. In general, the sediments consisting of medium silt are platykurtic to very leptokurtic in bottom surface sediments and leptokurtic in core sediments; they show a tendency to become more leptokurtic with decreasing mean grain size. The plot of the standard deviation vs. skewness of the surface and core sediments lack any clear pattern (Fig. 5.11B). The sediments show a vague tendency of the skewness to increase towards fine with decreasing sorting. The area as a whole is dominated by poorly sorted sediments. There is a tendency of a gradual decrease in sorting with increasing proportions of fine-grained sediments.

24 Fig Bivariate scatter plot of surface and core sediments in Veeranam Lake, A) Mean Vs Kurtosis, B) Standard deviation Vs Skewness.

25 The standard deviation vs. kurtosis for the core sediments shows a decrease of the kurtosis with decreasing sorting, whereas the surface sediments are platykurtic to leptokurtic near the boundary between poorly and very poorly sorted sediment (Fig. 5.12A). Sediments show a vague tendency of proportional decrease in kurtosis with increasing sorting. The analysis of the entire area shows two trends, viz. (1) a vague tendency of increasing kurtosis with decreasing sorting in a few sediments and (2) a decrease in kurtosis with decreasing sorting. The skewness vs. kurtosis plot lacks any pattern, as there is a narrow scatter of points of the same areas (Fig.5.12B). The overall picture reveals that the coarse skewed sediments show a maximum scattering in the platykurtic category, followed by the mesokurtic and leptokurtic categories. The plot of graphic mean Vs standard deviation (Fig.5.13), originally suggest by Stewart s discrimination field to understand the energy processes, indicates that the almost all the samples of both bottom surface and core samples from Veeranam lake are distributed in the field of Quiet water environment process MULTIGRAIN MULTIVARIANT DISCRIMINANT FUNCTIONS V 1 -V 2 PLOTS: The use of modern analogues is a logical and useful line of research (Greenwood, 1969) in the study of environments and the geological processes linked with it.

26 Fig Bivariate scatter plot of surface and core sediments in Veeranam Lake, A) Kurtosis Vs Standard deviation, B) Skewness Vs Kurtosis.

27 Fig Energy process diagram for surface and core sediments in Veeranam Lake.

28 The unrestricted use of any single variable is often alleged because of its possible interaction with a number of other variables. Using the multivariate statistical analysis on the complex situation having great number of variables, a meaningful uniformitarianism can be accepted with minute errors. Discriminant analysis provides a means of analyzing a large number of sediment parameters simultaneously and arriving at numerical indices which can be used to delineate the group characteristics (Greenwood, 1969). Discriminant analysis is also used to classify cases into the values of a categorical dependent, usually a dichotomy. This is useful for situations where you want to build a predictive model of group membership based on observed characteristics of each case. The procedure generates a discriminant function (s) (for more than two groups) based on linear combinations of the predictor variables that provide the best discrimination between the groups. The functions are generated from a sample of cases for which group membership is known, which can then be applied to new cases with measurements for the predictor variables but unknown group membership. The problem of discriminating between sedimentary environments on the basis of measurable sediment parameters resolves itself with the application of multivariate statistics (Rao, 1952; Greenwood, 1969; Colley and Lohnes, 1971; Bennett and Bowers, 1977, Sahu, 1964, 1983, Mukherjee, et al. 1987). The aim of the present study is to discriminate the different variables (sedimentary textures) in order to classify them within a specific group or facies and those particular characteristics seem to be the dominant and key parameters of that facies. Accordingly it can be proved statistically that there is existence of that particular facies with such assured structural and textural parameters, which can be correlated with field observations to prove its significance.

29 Two-dimensional scatter plots of grain size statistics are lesser in usefulness for environmental discrimination as the other significant variables cannot be recognized due to the non-optimal space for discrimination (Sahu, 1983). A rigorous statistical method of multigroup, multivariant linear discriminant functions proposed by Sahu (1983) was applied for discriminating the depositional environment. Further, partitioning of depositional environments in the field of optimal discrimination plane has been shown in the form of a graphical plot of V1 versus V2 by Euclidean distance measure (V1 V2 = 74.4 ). The plot reveals that both surface and core sediments expresses a river environment (Fig.5.14) C-M- PATTERN: C-M patterns can be applied to establish a possible relationship between the depositional environment and the hydrodynamic forces involved in the deposition of sediments (Passega, 1957, 1964; Passega & Byramjee,1969). The two parameters, C (which denotes the one-percentile value, representing the maximum grain size in microns) and M (the medium grain size in microns), are plotted on logarithmic scale. The pattern is related to the nature of the various types of sediment and the energy of the transporting medium. The easiest way to determine the environmental conditions in which a sediment was deposited is to use the CM diagram or the Passega diagram based on the 1% percentage and on the 50% percentage or the Median (Md), regarded by numerous authors as useful in the hydrodynamic interpretation of grain size data. The Passega diagram (Fig.5.15) shows various segments: ON (rolling), PO (rolling and suspension), QP (suspension and rolling),

30 Fig V1-V2 plot for surface and core sediments in Veeranam Lake.

31 IX III II I VIII VII V IV VI Fig CM pattern plot for surface and core sediments of Veeranam Lake.

32 RQ (graded suspension), SR (uniform suspension) and T (pelagic suspension). The plot distinguishes fields of rolled sediments (I, II, III and IX) and suspension of minor importance (IV, V, VI, VII and VIII). The CM pattern is an important plot used in sedimentology for the analysis of sedimentary environment (Passega, 1957). The CM Pattern of the sedimentary environment are means of analyzing transportation mechanism, depositional environment with respect to size, range and energy level of transportation and also in determining the processes and characteristic agents that are responsible for the formation of clastic deposits. It is also observed that in several environments the coarse fraction of sediment almost invariably is more representative of the depositional agent than the fine fraction. The two parameters used in the plot from the grain-size distribution are of particular significant C, the one percentile value represents the maximum grain size and indicates the competency of the transporting agent and the medium diameter M, expressed median grain-size of sediment transported. The sediments are generally considered as mixture of two to three log-normal subpopulation produced chiefly by three modes of transportation: rolling, saltation and suspension. The suspension may be uniform type (or) graded type. Accordingly a single sample may contain all the three sub-population related to the three modes of transport. The coarser particles are transported by rolling, grain size of lower range are carried by jumping and sliding while the finest particles are carried in suspension. The particles carried in saltation are generally considered to be the product of graded

33 suspension (Passega, 1964). Suspension may also be uniform (or) pelagic type. Two types of bottom currents namely tractive current and turbidity current are capable of transporting sediments. Traction currents are capable of transporting their load either by rolling or in suspension and turbidity current, which is a rapid process, carries the entire load in suspension. In the present study, CM pattern was made following Passega (1957, 1964), and Passega and Byramjee (1969). The CM plot at the present study shows that most of the Veeranam lake sediment samples (bottom surface and core) fall in the intermediate position between PQ and at IV (Fig.5.15). Clustering is imported due to lack of difference in the hydrodynamic regimes prevailing in the area. The samples have first percentile value falling within the field of 200 to 400, reflects suspension and rolling mode of transportational history, indicating unfussiness of hydrodynamic process operating in this system. The PQ segment exhibits that the Veeranam lake sediments were underwent the Rolling and suspension current, which are the prime factors for transportation. Most of the plots of the both bottom surface and core sediments from Veeranam lake occupy IV segment, which is denoted by C < 1mm mainly suspension sediments, rolled sediments <1mm may be incorporated. Thus the study shows that the sediments are mainly transported through traction along with suspension of minor importance. The amount of rolling sediment is negligible and most of the plots occupy the zone of tractive current deposits. Finally, it may be summarized that the sediments were deposited by tractive current, the sediments were being carried by

34 rolling with minor implications of suspension. Therefore it is to infer that the lake bed is influenced by fluvial processes rather than the terrestrial processes besides the morphology of the lake. The same can be supported by the multigrain multivariant discriminant function (fig.5.14) SEDIMENT CLASSIFICATION: Geologists, hydrogeologists, geochemists, and geotechnical engineers commonly use sediment grain-size data. Techniques that describe and summarize grain-size distributions are important to these scientists because the large amount of information contained in textural data sets can be difficult to understand and interpret. Thus, scientists commonly use nomenclature, statistical measures, and graphical representations to reduce complexities, reveal trends and patterns in the data, and develop hypotheses. Nomenclature describing size distributions is important to geologists because grain size is the most basic sediment attribute. Traditionally, geologists have divided sediments into four size fractions that include gravel, sand, silt, and clay and have classified these sediments based on ratios of the various proportions of the fractions. Definitions of these fractions have long been standardized to the grade scale described by Wentworth (1922), and two main classification schemes by Sheppard (1954) and Folk (1954) have been generally adopted to describe the approximate relationship between the size fractions. The original scheme devised by Shepard (1954) utilized a single ternary diagram with sand, silt, and clay in the corners to graphically show the relative proportions among these three grades within a sample. This scheme, however, does not allow for

35 sediments with significant amounts of gravel. Therefore, Shepard s classification scheme was subsequently modified by the addition of a second ternary diagram to account for the gravel fraction (Schlee, 1973). The system devised by Folk (1954, 1974) is also based on two triangular diagrams, but it has 15 major categories, and uses the term mud (defined as silt plus clay). The patterns within the triangles of both systems differ, as does the emphasis placed on gravel. For example, in the system described by Shepard, gravelly sediments have more than 10% gravel; in Folk s system, slightly gravelly sediments have as little as 0.01% gravel. Folk s classification scheme stresses gravel because its concentration is a function of the highest current velocity at the time of deposition and of the maximum grain size of the detritus that is available. Shepard s classification scheme emphasizes the ratios of sand, silt, and clay because they reflect sorting and reworking (Poppe et al., 2005). The classification of the bottom surface and core sediments collected from the Veeranam Lake were performed using Shepard and Folks trilinear classification. The sand, silt and clay percentage and its corresponding Shepards and Folks classification nomenclatures are given in Table.5.3 and 5.4. A) Shepard s Classification Based upon the proportions of sand- silt- clay sized particles, the Veeranam lake sediments were classified according to Shepard's diagram. Shepard's diagram is an example of a ternary diagram - a device for graphing a three-component system summing to 100%. In this case, the components are the percentages of sand, silt, and

36 Table.5.3. Sand-Silt-Clay percentage with Folk and Shepard Nomenclature of surface sediments in Veeranam Lake. Sam.no. Sand% Silt% Clay% Folk Shepard Mud Clayey silt Mud Clayey silt Mud Clayey silt Mud Clayey silt Mud Clayey silt Mud Clayey silt Sandy mud Clayey silt Mud Clayey silt Mud Clayey silt Mud Clayey silt

37 Table.5.4.Sand-Silt-Clay percentage with Folk and Shepard Nomenclature of Core sediments in Veeranam Lake. Depth in 2cm Sand% Silt% Clay% Folk Shepard Mud Clayey silt Sandy mud Clayey silt Sandy mud Clayey silt Sandy mud Clayey silt Sandy mud Clayey silt Sandy mud Clayey silt Sandy mud Clayey silt Sandy mud Clayey silt Sandy mud Clayey silt Sandy mud Clayey silt Sandy mud Clayey silt Sandy mud Clayey silt Mud Clayey silt Mud Clayey silt Mud Clayey silt Mud Clayey silt Sandy mud Clayey silt Sandy mud Clayey silt Sandy mud Clayey silt Sandy mud Clayey silt Sandy mud Clayey silt Mud Clayey silt Sandy mud Clayey silt

38 clay comprising a sediment sample. Each sediment sample plots as a point within or along the sides of the diagram, depending on its specific grain size composition. A sample consisting entirely of one of the components, 100% sand, for example, falls at the same-named apex. A sediment entirely lacking in one of the components falls along the side of the triangle opposite that apex. The rest fall somewhere inbetween. To classify sediment samples, Shepard (1954) divided a ternary diagram into ten classes. Shepard's diagram follows the conventions of all ternary diagrams. For example, Shepard's "Clays" contain at least 75% clay-sized particles. "Silty Sands" and "Sandy Silts" contain no more than 20% clay-sized particles, and "Sand-Silt- Clays" contain at least 20% of each of the three components. Grain size distributions of surface and core sediments from Lake Veeranam are clustered tightly in clayey silt variable (Fig.5.16). Thus, the Veeranam lake sediments is dominance of silt and clay fractions. B) Folk s Classification: Folk's philosophy is that the name of a rock must convey as much information as possible without being a complete description. For this, he proposed five important properties of sandstones to use as defining characteristics. These five properties are: grain size, chemically precipitated cements, textural maturity, miscellaneous transported constituents, and clan designation. However, Folk stated that cements and

39 Fig Sand-Silt-Clay classsification of surface and core sediments in Veeranam Lake (Based on Shepard classification).

40 miscellaneous transported constituents are optional categories as they are not always observed. The other three properties should always be mentioned. Grain size distributions of the Veeranam Lake Bottom surface and core sediments were plotted in the Folks classification diagram (Fig.5.17). The bottom surface sediments are clustered tightly in Mud variable. The core sediments are skewed towards the sandy mode of sediment type and falls in the Mud and sandy mud fields. Thus, the Veeranam lake sediments are dominance of silt fractions. In general, the high mud content suggests a relative low energy regime that favours the sedimentation of fine grained particles.

41 Fig Sand-Silt-Clay classsification of surface and core sediments in Veeranam Lake (Based on Folk classification).