sites for the collection of samples. Data regarding tide,
current, waves, depth, turbidity, etc. are also collected during sampling of estuarine sediment for size analysis. An
instrumental tripod ALICE fitted with various sensors is
used to collect data regarding the above physical parameters. Numerical models are used for data interpretation.
Statistical analysis of grain size
The texture of muddy sediments in estuaries is examined
by mechanical analysis following the sieving-cumpipetting method. Sand and gravel fractions are determined by sieve analysis (Krumbein and Pettijohn, 1938)
using sieves of different mesh sizes marked as ASTM
(American Society for Testing and Materials). The statistical size parameters are calculated using the formula of
Folk and Ward (1957) from the cumulative curves drawn
on arithmetic probability paper. Subsequently, rapid sediment analyzers (RSA) propounded by Zeigler et al. (1960)
and Schlee (1966) and electro-resistance multichannel
particle-size analyzers (EMPSA) are introduced for automated analysis and calculation of statistical parameters
of sediments. Contemporaneous with them, Kane and
Hubert (1962) and Schlee and Webster (1967) developed
Formula Translation (FORTRAN) programs for textural
analysis of sediment particle parameters. Gradually, Algorithmic Language (ALGOL) by Jones and Simpkin
(1970), Beginner’s All-Purpose Symbolic Instruction
Code (BASIC) by Sawyer (1977), and handheld calculators by Benson (1981) were programmed for statistical
grain size computations. About the same times, many
workers (Muerdter et al., 1981; Poppe et al., 1985) and
organization (Coulter Electronics Inc., 1989) introduced
hardware and software packages for electro-resistance
multichannel particle-size analysis. Introduction of
computer-driven, integrated particle-size analysis instruments fitted with settling tubes (Zeigler et al., 1964; Rigler
et al., 1981) automated and modernized sediment grain
size analysis. The settling tube, also called rapid sediment
analyzer design based on using the pressure differential
between two columns of water that have a common head,
provides for efficient analysis of sand-sized material by
setting the grains where results are relayed to a personal
computer associated with data acquisition software drivers
(Syvitski et al., 1991). A computer program called
GRADISTAT (Blott and Pye, 2001) has been written for
the rapid statistical analysis of size data from any standard
measuring technique. The program runs with a Microsoft
Excel package. It is very useful and produces a range of
graphical representations, including frequency curves
and plots.
Cumulative curves
Cumulative curves plotted on arithmetic probability paper
represent grain size distributions of different subpopulations which have a lognormal distribution depicting different modes of transportation of sediments (Visher, 1969).
Sediment grain size is determined from grain size curves
drawn on log-probability plots. It helps in the interpretation
of separate populations of estuarine sediments. Three different methods of plotting are considered for grain size distribution, including grain size with frequency percent,
cumulative frequency percent, and the log-probability
cumulative frequency percent. Log-probability cumulative
frequency curves are the most accepted methods used by
sedimentologists in assessing depositional environments
of estuaries. In each log-probability curve, there are at least
four control points, i.e., four separate lognormal
populations, where each population is truncated and the former one joined with the latter one to make a single grain
size distribution. Each lognormal population is composed
of different mean and standard deviation values.
Grain size characteristics of different estuarine
landforms
There is an interrelationship between grain size characteristics and the depositional pattern in a tide-dominated
estuarine environment. Interpretation of the grain size frequency curve is based upon the pattern of curves and splitting of each curve into segments separated by the marked
breaks and inflection. Sediments from different geomorphological areas such as point bar, mid-channel bar, swash
bar, river bank, and areas of other morpho-ecological
interests may be considered for grain size analysis.
Texture of mudflat sediments
The graphic mean size of surficial and subsurface samples
lies within the silt fraction with moderately well to poor
sorting. Sediments of mudflat samples show a positive
skewness and reflect infiltration of suspended clay from
tidal standstill through the pore spaces of the dominating
silt and subordinate sand populations. Sediments of the
mudflats traversing the creek bottom, however, exhibit
negative skewness. This is because of the mixing of
a greater proportion of sand fraction with the dominant silt
population. The removal of clay with flowing creek water
leaves the creek bottom with more sands compared to
other places of the mudflat, and this leads to a negative
skewness of the distribution patterns. Cumulative curves
drawn from the mudflat sediments reveal close similarity
in pattern. The same is true for the creek bottom sediments
when considered separately. The prominent breaks in the
cumulative curves reflect changes in the mode of transport
of suspended particles.
Texture of sand flats and silt flats
The sediments of sand flats consist of well-sorted 95 %
fine to very fine sands in comparison to silt flat sediments
having 10 % sand, 95 % silt, and 5 % clay. Cumulative
curves for the sand flat sediments are very similar in pattern and differ much from the silt flat sediments.
Texture of tidal shoal sediments
Tidal shoals, in general, show greater accumulation of
mud in the upstream portion and sand in the downstream
556
SEDIMENT GRAIN SIZE
current, waves, depth, turbidity, etc. are also collected during sampling of estuarine sediment for size analysis. An
instrumental tripod ALICE fitted with various sensors is
used to collect data regarding the above physical parameters. Numerical models are used for data interpretation.
Statistical analysis of grain size
The texture of muddy sediments in estuaries is examined
by mechanical analysis following the sieving-cumpipetting method. Sand and gravel fractions are determined by sieve analysis (Krumbein and Pettijohn, 1938)
using sieves of different mesh sizes marked as ASTM
(American Society for Testing and Materials). The statistical size parameters are calculated using the formula of
Folk and Ward (1957) from the cumulative curves drawn
on arithmetic probability paper. Subsequently, rapid sediment analyzers (RSA) propounded by Zeigler et al. (1960)
and Schlee (1966) and electro-resistance multichannel
particle-size analyzers (EMPSA) are introduced for automated analysis and calculation of statistical parameters
of sediments. Contemporaneous with them, Kane and
Hubert (1962) and Schlee and Webster (1967) developed
Formula Translation (FORTRAN) programs for textural
analysis of sediment particle parameters. Gradually, Algorithmic Language (ALGOL) by Jones and Simpkin
(1970), Beginner’s All-Purpose Symbolic Instruction
Code (BASIC) by Sawyer (1977), and handheld calculators by Benson (1981) were programmed for statistical
grain size computations. About the same times, many
workers (Muerdter et al., 1981; Poppe et al., 1985) and
organization (Coulter Electronics Inc., 1989) introduced
hardware and software packages for electro-resistance
multichannel particle-size analysis. Introduction of
computer-driven, integrated particle-size analysis instruments fitted with settling tubes (Zeigler et al., 1964; Rigler
et al., 1981) automated and modernized sediment grain
size analysis. The settling tube, also called rapid sediment
analyzer design based on using the pressure differential
between two columns of water that have a common head,
provides for efficient analysis of sand-sized material by
setting the grains where results are relayed to a personal
computer associated with data acquisition software drivers
(Syvitski et al., 1991). A computer program called
GRADISTAT (Blott and Pye, 2001) has been written for
the rapid statistical analysis of size data from any standard
measuring technique. The program runs with a Microsoft
Excel package. It is very useful and produces a range of
graphical representations, including frequency curves
and plots.
Cumulative curves
Cumulative curves plotted on arithmetic probability paper
represent grain size distributions of different subpopulations which have a lognormal distribution depicting different modes of transportation of sediments (Visher, 1969).
Sediment grain size is determined from grain size curves
drawn on log-probability plots. It helps in the interpretation
of separate populations of estuarine sediments. Three different methods of plotting are considered for grain size distribution, including grain size with frequency percent,
cumulative frequency percent, and the log-probability
cumulative frequency percent. Log-probability cumulative
frequency curves are the most accepted methods used by
sedimentologists in assessing depositional environments
of estuaries. In each log-probability curve, there are at least
four control points, i.e., four separate lognormal
populations, where each population is truncated and the former one joined with the latter one to make a single grain
size distribution. Each lognormal population is composed
of different mean and standard deviation values.
Grain size characteristics of different estuarine
landforms
There is an interrelationship between grain size characteristics and the depositional pattern in a tide-dominated
estuarine environment. Interpretation of the grain size frequency curve is based upon the pattern of curves and splitting of each curve into segments separated by the marked
breaks and inflection. Sediments from different geomorphological areas such as point bar, mid-channel bar, swash
bar, river bank, and areas of other morpho-ecological
interests may be considered for grain size analysis.
Texture of mudflat sediments
The graphic mean size of surficial and subsurface samples
lies within the silt fraction with moderately well to poor
sorting. Sediments of mudflat samples show a positive
skewness and reflect infiltration of suspended clay from
tidal standstill through the pore spaces of the dominating
silt and subordinate sand populations. Sediments of the
mudflats traversing the creek bottom, however, exhibit
negative skewness. This is because of the mixing of
a greater proportion of sand fraction with the dominant silt
population. The removal of clay with flowing creek water
leaves the creek bottom with more sands compared to
other places of the mudflat, and this leads to a negative
skewness of the distribution patterns. Cumulative curves
drawn from the mudflat sediments reveal close similarity
in pattern. The same is true for the creek bottom sediments
when considered separately. The prominent breaks in the
cumulative curves reflect changes in the mode of transport
of suspended particles.
Texture of sand flats and silt flats
The sediments of sand flats consist of well-sorted 95 %
fine to very fine sands in comparison to silt flat sediments
having 10 % sand, 95 % silt, and 5 % clay. Cumulative
curves for the sand flat sediments are very similar in pattern and differ much from the silt flat sediments.
Texture of tidal shoal sediments
Tidal shoals, in general, show greater accumulation of
mud in the upstream portion and sand in the downstream
556
SEDIMENT GRAIN SIZE