Fall Velocity of Cohesive Sediments in Dez Dam Reservoir
In order to characterize the settling properties of
natural cohesive sediment adjacent to the Dez Dam wall (as a symbol of
a large dam reservoir in arid and semi-arid zones), falling velocity of
particles have been measured using a 2.50 m height and 0.30 m diameter
column. In contrast to the traditional particle size based methods, an
approach relying on time and depth variation of sediment concentration
was employed to estimate the mean value of fall velocity at any depth
and time. Particles in deeper depth, particularly for the samples with
higher rate of sediment concentration accelerated faster and stayed at
higher velocities for longer duration as a result of higher rate of flocculation.
This confirms the greater effect of particle flocculation than their settling
competition. The particles in all depths reached their maximum falling
velocity same time around 15 min after the beginning of the tests. The
low concentration samples reached higher maximum velocity as a result
of lower rate of particle compaction but for a much lower duration in
comparison to the higher concentrated samples.
For large dam reservoir, falling velocity in particular for fine sediment
particles is a key parameter for estimation of sediment transport and
evaluation of trap efficiency and consolidation. Settling properties of
sediments in lakes and reservoirs should be characterized by time and
depth variation of the fall velocity of sediment particles. For cohesive
sediments, the particle aggregation as a result of flocculation increases
falling velocity in contrast to particle competition which tends to reduce
it. As the large dam reservoirs are normally long, only fine and cohesive
suspended particles are able to reach the dam wall.
Sedimentation and decrease of large dam reservoirs` capacity reduces
efficiency and productivity of the dam and power house. In arid and semi-arid
zones of the world with finer eroded soils, rivers transport more suspended
material into dam reservoirs and sedimentation particularly near dam walls
reduce the dam efficacy faster. In some developing countries, where watershed
management measures are not carried out effectively, reservoir storage
is being lost in much larger rate.
This amount in the Asian nations is generally higher than the world average
(Liu et al., 2002). Based on a report by International
Committee of Large Dams (ICOLD), there are more than 40,000 large dam reservoirs
worldwide used for water supply, power generation and flood control. An overall
estimation by ICOLD reveals that 0.5-0.75% of the total storage volume of these
reservoirs is lost each year as result of sedimentation. To maintain current
total storage, as many as 300 to 400 new dams need to be constructed each year.
However, increasing populations and rate of consumption per capita mean that
the demand for storage is rising inexorably despite the increasing use of alternative
sources of energy and the more efficient use of water (White,
2000). A cost of nine billion dollars is estimated just to replace existing
storage capacity without considering the costs to deal with environmental and
social issues (Annandale, 2005). Depending on the sedimentation
source and condition, many methods are deployed today to control sedimentation
and maintain current storage, including watershed management, dredging, density
current venting and flushing. Among these, watershed management is an effective
approach to control the source of sedimentation and maintaining existing storage
capacity, thus minimizing the need to construct as many new dams. It is also
advisable to design new dams in a manner that will facilitate sediment management
and long-term reservoir conservation. Trapping the density current in the reservoir
far enough behind the dam wall is an example of these design techniques.
The problems associated with sedimentation and the reservoir capacity
is directly tied with the settling property of the suspended materials
flowing through the reservoir. As a turbid river rests in the quiescent
water of a reservoir, the process of settling begins and particles concentrate
more and more with time at deeper parts of the reservoir. This allows
for the settling property of sedimentation to be measured based on time
and depth variation of the fall velocity of sediment particles. For modeling
of sedimentation in large reservoirs, the increase in rate of concentration
can be correlated with the quiescent water depth.
As a major parameter to quantify sediment transport, reservoir trap efficiency
and consolidation process, extensive studies have been conducted in the past
to determine the settling velocity parameter for cohesive sediments but less
is resulted due to its complicated behavior (Fathi Moghadam
et al., 2007). In nature, due to size difference, particles do not
settle at the same pace and thus their fall velocity varies considerably. Larger
particles usually have a higher fall velocity than smaller ones. As the settling
particles reduce in size, chemical properties of particles and water overcome
the physical properties and cause the clumping of fine particles to form larger
particles (flocs) which are dropped out more quickly. Fan
and Morris (1992) investigated electrochemical properties of fine sediments
while interaction of flocs and fluid viscosity on deposition of fine sediments
was evaluated by Kranenburg (1999). Morris and Fan (1997)
correlated relationships for four distinct stages of consolidation which are
beyond the first stage of settling. This study will focus mostly on the first
Stock`s law governs the falling velocity of single particles (non-cohesive)
where effects of the competition and flocculation of particles in the process
of settling are not considered. Based on Stock`s law for considering particle
size and fluid viscosity, Krone (1963) and Krishnappan
(2000) developed equations for estimation of fall velocity of sediment particles.
The mathematical models were also correlated with experimental results in order
to estimate settling velocity and sediment transport like in Krishnappan
and Marsalek (2002). Toniolo and Parker (2003) and
Winterwerp (2002) developed 1-D and 3-D models to estimate
fall velocity for long term duration of settling of fine sediments in estuarine
The rate of flocculation and falling competition of particles are main sources
of uncertainty in the existing particle size based relationships for estimation
of settling velocity of fine sediments (Samadi et al.,
2005). Even for particular sludge water during the settling process, sizes
of flocs vary with depth and time. Despite development of the new models for
estimation of settling velocity of cohesive sediments, it is still believed
that an analytical approach based on time and depth variation of sediment concentration
is more accurate in practice than the methods based on sediment particle size.
McLaughlin applied this method graphically using artificial sludge water (uniform
particle size of hydrated aluminum silicate in water) in a short column (Simons
and Senturk, 1992).
Since, the cohesive sediments receive particular attention near large
dam walls, the method is used to estimate depth and time variation of
fall velocity for real cohesive sediments any time after a density current
event with a particular sediment concentration reaches a dam wall. In
nature, real cohesive sediments contain silt and clay with large variety
in particle size. This may result in considerable changes in their characteristics
compared to ideal cohesive sediment as were studied by McLaughlin. Even
geographic location of sediments should be considered in the analysis.
The sludge water in this study was obtained from the vicinity of the Dez
Dam wall in order to represent characteristics of fine sediments in arid
and semi-arid zones.
MATERIALS AND METHODS
Dez Dam Site
The Dez Dam Project in Southwest of Iran, located in a semi-arid zone was
completed in 1962 and consists of a 203 m high double curvature arch dam and
a 60 km long reservoir. Since completion, the sedimentation in the reservoir
has taken up about 20% of the initial reservoir volume of 3,316 million m3.
The sediment drops out along the upper reaches to form a delta, which is slowly
progressing to the dam and the bottom set beds of fine sediment are raising
adjacent to the dam face. The fine sediment is brought to the dam face by highly
concentrated turbidity currents which occur four to six times annually during
short-term rainstorms over the watershed (Fathi-Moghadam
et al., 2008). Recent studies related to extending reservoir life
have ranked the option of turbidity current flushing through low-level outlets
as a promising option. In order to identify the magnitude and frequency of turbidity
currents along the reservoir a measurement program was undertaken during the
wet season of January to May, 2003. The largest event of April 23-24 for that
year had 1,188,500 m3 of density current with average sediment concentration
of 7 g L-1. The analysis of the results for 26 years before 2003
indicated an annual turbidity current of about 2,243,200 m3 year-1
with sediment concentration up to 30 g L-1 for Dez Dam reservoir.
They found the extension of reservoir life by flushing of turbidity currents
would not be large, but could be economically viable provided that downstream
environment guidelines could be adhered to Samadi and Galay
(2005). Sediments trapped near Dez dam wall are classified as cohesive with
55% silt and 45% clay. Hamm and Migniot (1994) showed even
silt particles with a diameter less than 0.03 mm have reasonable properties
of cohesive sediments.
Using a settling column, total derivative of particle concentration
(C) as function of time (t) and vertical distance (z) from a datum line
and time and depth variation of concentration for calculation of falling velocity
will be (Simons and Senturk, 1992).
= Local mean fall velocity of particles and integrating Eq.
at any water depth (d) will be:
and fall velocity of particles at any time and depth is:
The integration in Eq. 4 measures Cz in distance 0
to d between two subsequent times.
Experimental setup, (1) storage tank (0.4 m3)
for mixing water and sediment with desirable density, (2) pump to
deliver water to settling column, (3) a mixer connected to appropriate
electric motor, (4) plexy glass settling cylinder, 3 m height and
0.3 m diameter and (5) sampling outlets, 0.3 m apart
A plexy glass column with 3.0 m height and 0.30 m diameter was used
in this study to determine fall velocity of the cohesive sediments of
the Dez dam reservoir (Fig. 1). Tests were conducted
at the Hydraulics Laboratory of Chamran University of Ahvaz, 200 km south
of the dam site. The sludge water for tests was collected from the muddy
layer of the reservoir near the dam wall around the low level outlets.
The low level outlets are 120 m below the normal water surface and were
initially designed to control irrigation water downstream of the dam.
They have been blocked by cohesive sediments for about 10 years now. The
Master Sizer designated the texture of the sludge water as 55% silt and
45% clay. Using the collected sludge water, concentration rates of 5 and
17 g L-1 were prepared in a 0.40 m3 storage tank
and mixed well before being pumped into the testing column (Fig.
1). The concentration rates were selected to represent reasonable
ranges of density current events. Water samples were taken at 8 depths
along the column through outlets 0.3 m apart, in time intervals of 3,
5, 15, 30, 60, 120, 240 and 480 min starting when water was discharged
into the column. To calculate the percentage of sediment concentration,
the samples were weighted immediately after being taken from the column
and after 24 h of being dried in oven. The measurements for variation
of time, depth and sediment concentration were used to construct the curves
and calculate the falling velocity as shown in Eq. 4.
||Depth variation of concentration at t = 15 min (C =
5 and 17 g L-1)
Results of particle concentration after 15 min of sampling from depths
of 0.30, 0.60, 0.90, 1.20, 1.50, 1.80, 2.10 and 2.40 m for the sludge
water with initial concentrations 5 and 17 g L-1 are shown
in Table 1. Similar tables were constructed for the
elapsed times of 3, 5, 15, 30, 60, 120, 240 and 480 min.
RESULTS AND DISCUSSION
Fine sediments delivered by rivers normally travel more distance along
the reservoir and settle near the dam wall. This is undesired in large
and multipurpose dams as the intakes to the powerhouse and other water
demand control outlets in or adjacent to the dam wall are under blockage
threat. As a major parameter for reservoir sediment management (sediment
transport, trap efficiency, sedimentation and consolidation), the fall
velocity of cohesive sediments near the Dez dam wall was estimated using
a settling column. Due to the fact that field samples contain particles
with considerable size variation, time and depth variation of sediment
concentration were used to estimate mean settling velocity.
Using Table 1, time variation of concentration for
various depths has been compared in Fig. 2 for initial
particle concentrations of 5 and 17 g L-1. The curves merge
together in a much longer time for the denser sludge waters as a result
of a balance between process of fluctuation and particle competition.
Using Table 1 and the rest of the time difference tables
for the initial concentration of 5 g L-1, the percentage of
particle concentration (relative to the initial concentration) for all
sampling depths were calculated and sketched in Fig. 3a
for every sampling time step. Similar is done for 17 g L-1
in Fig. 3b and the rest of the sludge waters with different
initial concentrations. The curves can be used to identify texture and
other physical and chemical properties of the deposited sediments in a
particular time and place. The correlation of the data can result determination
of the sediment ability to flocculate and even the floc size. For example,
the larger percentage of the sediment examined in this study were silt
and flocculated particles which traveled more than 2 m in the first hour
for the initial concentration of 5 g L-1. For 17 g L-1,
almost twice the time was required due to elongation of the process of
flocculation and particle fall competition. For the considerably low part
of the sediments which are very fine, more time is required for evaluation
of fall velocity.
The integration of Cdz in Eq. 4 can be obtained from
the area under the curves from 0 to any distance z for a particular time.
Time variation of this integral is the difference in the measured areas
from time to time for the same distance (Fig. 3). Table
2 shows time variation of this integration for the initial sludge
water with 5 and 17 g L-1. Using Table 2
and initial concentration (C), the representative fall velocity for any
distance z and time interval t is calculated from Eq. 4.
The calculated fall velocities are shown in Fig. 4a,
b for sludge waters with initial particle concentrations
of 5 and 17 g L-1. These concentrations were selected to show
considerable effect of density on fall velocity while being more convenient
to work with in practice. To assume column is endless, fall velocities
below the 180 are not considered in the analysis.
||Time and depth variation of particle concentration (a)
5 g L-1 and (b) 17 g L-1
||Depth variation of particle concentration with time, (a) 5 g L-1
and (b) 17 g L-1
||Area under curves
for initial concentrations 5 and 17 g L-1
Fall velocity of the sludge water collected near the Dez dam
wall, (a) 5 and (b) 17 g L-1
For the lower concentration (5 g L-1), the maximum fall velocity
in all depths accrued in the same time around 15 min after beginning of the
experiments. This may explain the low effect of flocculation and particle competition.
For higher dense water (17 g L-1), the recession side of the curves
has shifted to the right as a result of higher rate of flocculation. Also, all
the curves showed that particles in deeper parts of the column have higher falling
velocities. This is due to higher rate of flocculation as a result of having
higher concentration than in shallow parts. This result along with the range
of calculated fall velocities in Fig. 4 are in accordance
with McLaughlin`s results (Simons and Senturk, 1992). The
difference in curves and considerable increase in fall velocity to those reported
by McLaughlin is due to particle size variation and large quantity of silt particles
in the test samples which are particular properties of cohesive sediments near
the wall of large dam reservoirs. Mehta et al. (1982)
showed that when particle and floc concentrations exceed 5-10 g L-1,
the fall velocity will be reduced. This is correct for maximum fall velocity
as observed in Fig. 4b when, it is being compared with the
lower concentration of 5 g L-1 curves in Fig. 4a.
But it should be noted that curves in Fig. 4b will remain
in higher fall velocities for a much longer duration as result of flocculation.
Time and depth variation of particle concentrations in a column were used to
estimate the fall velocity of fine sediment deposited in the Dez dam reservoir
near the dam wall. The tested samples can be considered as representative of
the natural cohesive sediment in large dam reservoir in arid and semi-arid environments.
The column was long enough to allow the falling velocity to reach a steady state.
The constructed curves for time and depth variation of concentration are capable
of estimating the texture and settling properties of the fine sediments. Using
the results of this study for a density current when reaches a large dam wall
with a particular concentration, the time and depth variation of fall velocity
can be estimated. This receives particular interest for evaluation of the reservoir
capacity and sediment trap efficiency. The estimated fall velocities lay well
among the estimated fall velocities by McLaughlin while the maximum fall velocities
were in accordance with Mehta et al. (1982) and
Mehta (1993). The lower concentration samples showed to
have higher maximum fall velocities than higher concentration samples but for
a much shorter duration. This is due to lower falling competition of particles.
For lower particle concentration, the maximum fall velocity for all depths occurred
after 15 min while it seems to have delayed as initial concentration increases.
However, it is believed that more data is required for the development of a
relationship for estimation of fall velocity of cohesive sediments for the dam
reservoirs in arid and semi-arid environments.
The authors would like to acknowledge Dr. B. Krishnappan at the Canada
Centre for Inland Water, Burlington, Canada for his invaluable comments
on this research. Acknowledgment is also extended to the Shahid Chamran
University, Ahwaz, Iran and Khuzistan Water and Power Authority for financial
support and facilitation of the experiments.
Annandale, G.W., 2005.
Reservoir Sedimentation, in Encyclopedia of Hydrological Sciences Part 7: Erosion and Sedimentation. 1st Edn., John Wiley and Sons, Ltd., New York, CrossRef | Direct Link |
Fan, J. and G.L. Morris, 1992.
Reservoir sedimentation handbook. II: Desiltation and long- term storage capacity. J. Hydraulic Eng., 118: 370-384.
Fathi-Moghadam, M., P.H. Torbi, M. Ghomeshi and M. Shafaei, 2008.
Density current head velocity in expansion reaches. J. Lakes Reservoirs: Res. Manage. Blackwell Pub., 13: 63-68.CrossRef | Direct Link |
Fathi-Moghadam, M., A. Arman and B.H. Samadi, 2007.
Determination of the fall velocity for cohesive sediments at different concentrations. Proceeding of the 10th International Symposium on River Sedimentation, Volume 5, August 1-4, 2007, Moscow, Russia, Pages: 360-Direct Link |
Hamm, L. and C. Migniot, 1994.
Elements of Cohesive Sediment Deposition, Consolidation and Erosion. In: Coastal Estuarial and Harbor Engineers' Reference Book, Abbott, M.B. and A. Price (Eds.). E and F N Spon, New York, pp: 93-106Direct Link |
Kranenburg, C., 1998.
Effect of floc strength on viscosity and deposition of cohesive sediment suspensions. J. Continental Shelf Res., 19: 1665-1680.CrossRef |
Krishnappan, B.G., 2000. In situ
size distribution of suspended particles the fraser river. J. Hydraulic Eng., 126: 561-569.CrossRef |
Krishnappan, B.G. and J. Marsalek, 2002.
Modelling of flocculation and transport of cohesive sediment from an on-stream storm water detention pond. J. Water Res. Oxford, 36: 3849-3859.CrossRef |
Krone, R.R., 1963.
A study of rheologic properties of estuarial sediment. Sanitary Engineering Research Lab., University of California, Berkeley. http://handle.dtic.mil/100.2/AD787313
Liu, J., B. Liu and K. Ashida, 2002.
Reservoir sedimentation management in Asia. Proceedings of the 5th International Conference on Hydro-Science and Engineering, September 18-21, 2002, Warsaw, Poland, pp: 1-10Direct Link |
Mehta, A.J., T.M. Parchure, J.G. Dixit and R. Ariathurai, 1982.
Resuspension Potential of Deposited Cohesive Sediment Beds. In: Estuarine Comparisons, Kennedy, V.S. (Ed). Acadamic Press, New York, ISBN-10: 0124040705, pp: 591-609
Mehta, A.J., 1993.
Hydraulic Behavior of Fine Sediments. In: Coastal, Estuarial and Harbour Engineers Reference Book, Abbott, M.B. and W.A. Price (Eds.). Chapman and Hall, London, ISBN-10: 0419154302, pp: 577-584
Morris, G.L. and J. Fan, 1997.
Reservoir Sedimentation Handbook: Design and Management of Dams, Reservoirs and Watersheds for Sustainable Use. 1st Edn., McGraw-Hill, New York, ISBN: 007043302X, Pages: 3
Samadi-Boroujeni H Fathi-Moghaddam, M., M. Shafaie and H. Samani, 2005.
Modelling of Sedimentation and Self-Weight Consolidation of Cohesive Sediments, Chap. 13 of Sediment and Ecohydraulics Intercoh 2005. 1st Edn., Elsevier B.V. Oxford, UK., ISBN: 978-444-53184-1
Samadi, H. and V.J. Galay, 2005.
Turbidity current measurements within the Dez reservoir, Iran. Proeedings of the 17th Canadian Hydrotechnical Conference, Hydrotechnical Engineering: Cornerstone of a Sustainable Environment, August 17-19, 2005, Edmonton, Alberta, pp: 127-127Direct Link |
Simons, D.B. and F. Senturk, 1992.
Sediment Transport Technology: Water and Sediment Dynamics. 1st Edn., Water Resources Publication, Colorado, USA., ISBN: 0-471-95753-4, Pages: 463
Toniolo, H. and G. Parker, 2003.
1D Numerical modeling of reservoir sedimentation. Proceedings of the IAHR Symposium on River, Coastal and Estuarine Morphodynamics, September 10-14, 2003, Barcelona, Spain, pp: 457-468Direct Link |
Winterwerp, J.C., 2002.
On the flocculation and settling velocity of estuarine mud. J. Continental. Shelf Res., 22: 1339-1360.CrossRef |
White W.R., 2000.
Flushing of sediments from reservoirs. Working Paper of the World Commission on Dams, Cape Town, South Africa. http://www.wii.gov.in/eianew/eia/dams%20and%20development/kbase/contrib/opt184.pdf