Study of Sediment Deposits for Reservoir Dredging
Tiao J. Chang1, Travis D. Bayes2, Scott McKeever3
Abstract
Many reservoirs in the country are aging, and dredging has been the most common means
to maintain continuing uses of these reservoirs. By investigating geographic distribution
of sediment deposits in a reservoir, this study was to gather information for developing
the guidance for future dredging programs for other similar reservoirs. Based on the
recent topographical survey and the original topographical map of the studied lake, sixty
sampling locations were selected to geographically represent the lake. A gravity corer,
two feet long and three inches in diameter, was used to collect sediment samples. These
samples were first classified by color and then the general physical characteristics of the
sediment deposits were recorded in a field book. Each sample of sediment deposit was
then bagged and marked with its geographical location using a global positioning system
and physical landmarks in conjunction with a detailed map. Samples were dried and
analyzed by mechanical sieve analysis to develop a particle-size distribution curve for all
sampling locations. Grain sizes of sediment deposits at sampling locations, assumed to be
geographically referenced variables, were spatially interpolated to form a regional
distribution. The analysis of sediment grain sizes and texture classification resulted in
grids of raster-based values that can be expressed by spatial images. The analyzed results
were used to develop the guidance for future dredging programs.
Introduction
Particles in water such as sediment deposits settle if the densities of particles are greater
than that of water. The motion of this settling process is essentially involved with three
forces, namely, the particle weight, W, the buoyancy force, Fb, and the drag force, Fd. W
W is a downward force while Fb and Fd are downward forces. When the particle reaches
a constant velocity, U, in the falling process, the net force is equal to zero, i.e.,
W  Fb  Fd  0,
(1)
Let w be the density of water, D be the diameter of the falling particle, and µ be the
dynamic viscosity of water, then the Reynolds number, Re, can be expressed as
 UD
(2)
Re  w
,

Based on the Stokes law, if the Reynolds number is less than one, the drag force, Fd, can
be estimated by (Streeter and Wylie, 1985)
Fd  (
1
24  wU 2 D 2
)(
)(
)  3UD,
Re
2
4
(3)
Professor, Civil Engineering Department, Ohio University, Athens, OH 45701
Research Assistant, Civil Engineering Department, Ohio University, Athens, OH 45701
3
Manager of Special Projects, Muskingum Watershed Conservancy District, New Philadelphia, OH 44663
2
where the constant velocity, U, is called the settling velocity. Let s be the density of the
falling particle, then Equ. 1 can be rewritten as
4
3
D
2
4
3
D
2
 s ( ) ( )3   w ( ) ( )3  3UD  0,
(4)
where g stands for the gravitational acceleration. Equ. 4 can be rearranged to result in an
expression for the settling velocity as follows:
U
(  s   w ) gD
,
18
(5)
Based on Equ. 5, the settlement of a sediment particle depends mainly upon the density
and diameter of the particle in a given water body. Sediment particles may not be
spherical, but Stokes’ law can still give a good representation of the settling velocity. In
general, the diameter of the particle carries the most weight in determining the settling
velocity. The settling velocity of a particle increases linearly with an increase of particle
diameter. This has an implication on the sizes of sediment deposits settling at the bottom
of a reservoir or river.
The settling velocity expressed in Equ. 5 is based on the calm water body. Turbulence of
the flow may also affect the particle deposit. If the average velocity of the current is
constant and fluctuations in the current’s turbulence are small, the sediment will be well
graded (Trash, 1950). Soil particles that are small enough to stay suspended will do so,
while the larger particles fall out. On the other hand, when the current changes in
velocity or turbulence, the large particles have deposited earlier, so the range of particle
size is small.
Therefore, in an ideal reservoir, sediment deposits can be predictable; the coarser soil
particles will be deposited near the entrance stream and the finest material will settle near
the dam. The flow velocity decreases and results in finer material deposits as it gets
closer to the dam. The depth of the sediment would generally be the greatest near the
dam as shown in a schematic diagram in Figure 1 (Annandale, 1987).
Figure 1. Schematic diagram for reservoir sedimentation
Background
The studied reservoir, Charles Mill Lake, is on the edge of the glaciated region of Ohio.
The reservoir has a shallow slope while it resides in several valleys so that it has an
irregular shape as shown in Figure 2. Because of this, the amount of sediment deposits
and the size of the sediment are not easily predicted.
Reports have been made that the sediment deposition in the lake is gradually filling the
lake. Residents in the surrounding areas and users of the lake have complained about
poor navigability. In addition, the reservoir has reduced its effectiveness in controlling
floods.
Charles Mill Lake is located four miles east of Mansfield, Ohio in Richland and Ashland
counties. It receives its inflow from the Black Fork Creek, located on the north of the
lake. The water from the lake ultimately discharges to the Ohio River via the
Muskingum River. The dam holding Charles Mill Lake was constructed in 1935 for the
purpose of flood control. The Muskingum Watershed Conservancy District (MWCD)
owns the lake and surrounding land and is responsible for the conservation management
and recreational activities. The dam is owned and operated by the U.S. Army Corps of
Engineers.
The man-made lake contains three natural lakes, Mifflin, Bell, and Mud, which existed
before the dam was built. It also includes fourteen islands. The average depth of the lake
has decreased by about one foot in the last 60 years. It means a decrease of about 20% of
the volume of the lake. The watershed draining into Charles Mill Lake is 217 mi2. Table
1 lists facts about Charles Mill Lake and its watershed.
Table 1. Facts of Charles Mill Lake and its associated watershed
Lake Length
20,700 feet
6,300 meters
Lake Breadth
6,200 feet
1,900 meters
Original Average Depth
5 feet
1.5 meters
Current Average Depth
4 feet
1.2 meters
Maximum Depth
34 feet
10.4 meters
Original Volume
11,369 acre-feet
14,034,230 km3
Current Volume
8,129 acre-feet
10,034,678 km3
Water Surface Area (normal pool)
1,339.5 acres
5.42 km2
Shoreline Length
34 miles
53.5 km
Lake Elevation (normal pool)
997.1 feet (MSL)
304.0 meters
Lake Elevation (spill way)
1020.0 feet (MSL)
311.0 meters
Watershed Area
217 mile2
562 km2
Methodology
Digitized topography and hydrography of the studied area were downloaded from the
Geographic Information System Support Center, Ohio Department of Administrative
Services and converted for use in ArcView GIS. This data were 1:24,000 scale Digital
Line Graphs.
An original topographic map of the land, before the dam was built, was obtained and
digitized. Once the map was digitized, the elevation point data were interpolated over the
whole lake to create a continuous grid and a raster image as shown in Figure 3a.
The recent topographic survey of Charles Mill Lake was obtained from the Army Corps
of Engineers (ACOE). The ACOE surveyed the lake in 1998 with cooperation with the
MWCD using a Global Positioning System (GPS) and sounding equipment. These data
points were also interpolated to create a raster image as shown in Figure 3b.
The analysis of these two topographic images indicates that most of the sediment deposits
has been located in the main channel, especially in the north section of the lake. Based
on this result, the sampling locations were chosen to best represent the lake and sediment
deposits as shown in Figures 4.
The sampling was taken from each sample location in July of 1998. The samples were
retrieved with a gravity corer that could collect a core two feet long and three inches in
diameter. Each sample was described in the field book, and the location was taken down
on the map and with a GPS. The description included the sample number, color, general
soil classification, location, length of core, and time taken. The sample was bagged and
marked with identification.
Moisture content testing and mechanical sieve analysis was conducted for each sample.
The results were input into the associated coordinates along with the sample’s general
description. The data was further analyzed by a spline interpolation method to obtain a
spatial distribution (Mitus and Mitasova, 1988).
The particle-size distribution curve was developed for all samples. From the curves the
D10, D30, D50, D60, and D90 values were interpolated and used for data points at the
respective sampling locations. The D10 is the particle diameter that corresponds to 10%
finer on the particle-size distribution curve. In other words, 90% of the particles, by
weight, are larger than the D10 value. The particle-size distribution curves were further
used to determine the percentages of four-classified materials, namely, gravel, coarse
sand, fine sand, and silt/clay. It is noted that the total of these four percentages should be
equal to one. The size of the soil in each class is listed in Table 2.
Table 2. Soil classification by particle sizes
Soil Classification
Gravel
Coarse Sand
Fine Sand
Silt/Clay
Minimum Size (>)
0.0787 in
0.0157 in
0.00295
0.00000 in
Maximum Size ()
0.0787 in
0.0157 in
0.00295 in
The spline interpolation imposes that the surface must pass exactly through the data
points. In addition, the cumulative sum of the squares of the second derivative terms of
the surface, taken over each point on the surface, must be a minimum. The spline method
fits a mathematical function to a specified number of points, while passing through the
sample points. Since it can be assumed that the sediment deposit data are continuous and
only moderate variations occur between the data points, this method worked well to
smoothly interpolate sampled data.
Results
Data of the four-classified sediment deposits are geographically referenced variables. The
interpolation using the spline method was conducted for each soil class resulting in a set
of grid values that can be expressed as an image. Figure 5 is an example of gravel image
that shows the geographical distribution of gravel deposit in the reservoir. It can be seen
that two locations in the main channel have the high percentage of gravel deposit. One of
the locations is the downstream of a highway bridge and likely has a high velocity. It is
noted that the percentage addition of the four classes should is equal to one at any given
location based on the defined classification. The spline method resulted in 5% error for
only 2.6% of the grid analyzed; only 0.4% of the grid contained more than 10% error.
The total sediment deposit in the lake contained only a small amount of gravel. This
makes sense because stream has to maintain a rapid current to carry suspended gravel to
the reservoir. Since the gradient of the stream is small, the flow is moderate. The total
sediment deposit contains an average of 4.4% gravel. The maximum percentage of
gravel is about 50% near the bridge and in the southwest side of the lake as shown in
Figure 5. The bridge constricts the only connection from the north section to the south
section of the lake and causes the downstream scouring. The smaller particles are eroded
while the larger particles remain. The average D90 for the sediment is 0.070 inches,
where the D90 for downstream of the bridge is 0.30 inches as seen in Figure 6.
On the other hand, the average D10, or effective size, for the sediment deposits is 0.0046
inches. The smallest effective sized sediment deposits are located near the entrance of
the Black Fork shown in Figure 7. This may be due to the velocity decrease before the
flow entering the lake. Once the streamflow enters the lake, the water becomes calm
because of the constriction. The effective size increases after the bridge constriction in
the downstream end. The percent of silt and clay is the greatest near the entrance of the
Black Fork, around 20% as shown in Figure 8. However, an unusual result also sown in
Figure 8 is the percentage of silt and clay decreases nears the dam. This is against the
general rule as explained in the schematic diagram of Figure 1.
The uniformity coefficient (Cu) was used as a factor to further exam the composition of
sampled sediment deposits (Braja, 1994). It is defined as
D
(6)
C u  60 ,
D10
where D60 and D10 are the diameters of particles obtained form the particle-size
distribution curve for 60% and 10%, respectively.
The sediment deposit is usually gravely if the uniformity coefficient is greater than four;
it is sandy if the uniformity coefficient is greater than six. The main sandy area is in the
middle of the southern section of the lake as shown in Figure 9. Most of the sediment
qualifies as non-uniform since its uniformity coefficient is less than four.
The coefficient of gradation (Cc) is used to determine how varied particles of sediment
deposits are graded (Braja, 1994). It is defined as
2
D30
Cc 
,
(7)
D60 * D10
where D30, D60, and D10 are the diameters of particles obtained form the particle-size
distribution curve for 30%, 60%, and 10%, respectively. When the coefficient of
gradation is between one and three, the sediment deposits are considered well graded.
Figure 10 shows the area upstream of the highway bridge is not well graded, but the area
downstream of the bridge is well graded.
Figure 11 is the depth of the sediment deposited in the lake based on the differences of
ground elevation between 1935 and 1998. The original channel in the southern section
has the greatest amount of sediment. Because of the sedimentation, the bottom of the
lake seems to have become smoother and flatter. The sediment deposits seem to be more
concentrated along the originally mainstem of the river and in just upstream and
downstream of a highway bridge.
Conclusions
It can be concluded that the major sediment deposits are along the original mainstem of
the river. There is a minimum percentage of gravel in the composition of sediment
deposits, and the settlement of gravel deposits mainly occur at two apparent locations as
graphically shown in the analyzed result. Further, the images of uniformity and gradation
provide also the geographical distribution of sediment deposits. Based on these results, a
working program for dredging can be developed in terms of priorities.
Appendix - References
Annandale, G. W., 1987. Reservoir Sedimentation, Elsevier Science Publishers
Company, New York.
Braja, M. D., 1994. Principles of Geotechnical Engineering, Third Ed., PWS Publishing
Company, Boston, MA.
Mitas, L. and Mitasova, H., 1988. "General Variational Approach to the Interpolation
Problem," Computers & Mathematics with Applications, Vol. 16, No. 12, pp. 983992.
Streeter, V. L.. and Wylie, E. B., 1985. Fluid Mechanics, Eighth Ed., McGraw-Hill, New
York.
Trash, P. D., 1950. Applied Sedimentation, John Wiley & Sons, New York.