京都大学防災研究所年報 第 56 号 B 平成 25 年 6 月
Annuals of Disas. Prev. Res. Inst., Kyoto Univ., No. 56 B, 2013

3D umerical Study of Time Dependent Bed Changes in the Flushing Channels for
Free Flow Sediment Flushing in Reservoirs
Taymaz ESMAEILI(1), Tetsuya SUMI, Yasuhiro TAKEMON and Sameh A. KANTOUSH(2)(1) Ph.D. student, Dept. Of Urban Management, Graduate School of Engineering, Kyoto University(2) Assoc. Professor, Dept. Of Civil Engineering, German University Cairo (GUC)
Synopsis
Dams are extensively used for different purposes (i.e. irrigation, water supply, flood
control and hydro-electric power supply) and flushing is one of the proposed methods
for preserving the storage capacity of dam reservoirs. In the free-flow sediment flushing,
the water level is drawndown during a flood and subsequently the increase in the flow
velocity results in sediment erosion in dam reservoir. The efficiency of the free-flow
sediment flushing depends on various parameters such as hydraulic condition, sediment
properties and reservoir geometry. Owing to this fact that advanced numerical models
could simulate many aspects of the hydraulic characteristic of flow and sedimenterosion-deposition field, application of these models could provide the initialassessment of the different impacts of upcoming free-flow sediment flushing. In thepresent study a fully 3D numerical model, SSIIM, used for assessing the temporal bed
changes during the free-flow sediment flushing in various shallow reservoir geometries.
The outcomes of the numerical simulations reveal the capability of the 3D numericalmodel to simulate the different stages of channel formation in shallow reservoirs andalso modeling the flow field when the bed topography is in the equilibrium condition.
Keywords: Reservoir sedimentation, 3D numerical simulation, free-flow sedimentflushing

1.

Introduction

One of the most important side effects of dam
construction over the streams is disturbing thenatural sediment transport trend from upstream tothe downstream area. When the stream flow entersa dam reservoir, the flow velocity decreases andsubsequently in such a condition, all bed load andall or a portion of the suspended load deposits in thedam reservoir. Also, the fine sediments aretransported deeper into the reservoir by the flow.
Deposition of sediment reduces the storage capacityof the dam reservoir during the operational periodof dam. The annual rate of reservoir storage
capacity loss to sedimentation in the world is0.5-1% and it varies dramatically from river basin
to river basin due to the different forest cover andgeological conditions (White 2001). A decreased
storage volume reduces the amount of water forflood control purpose, electricity production andwater supply. This loss of storage volume
represents a huge economic loss and the reductionof flood control benefits (Morris & Fan, 1998).
Moreover, in some areas with sedimentation rates
above the average (e.g. China 2.3% or the Middle
East 1.5%) the lifetime of the dam would be― 655 ―

reduced drastically. Furthermore, the sedimentyields of the Japanese rivers are high in comparison
with other countries due to the topographical,
geological and hydrological conditions (Sumi,
2006).
In order to control the reservoir sedimentation,different approaches such as bypassing, dredging,flushing, sluicing and upstream sediment trapping
have been developed. Although the combination ofthese sediment control measures usually adopted togain the maximum effect, the flushing and sluicing
method plays an important role in the sedimentremoval and reduction, especially the flushingapproach, as it is an efficient hydraulic sedimentremoval technique to restore the reservoir storage
capacity (Liu et al. 2004). Free-flow sedimentflushing through dam reservoirs is one of thetypical techniques in Japan because of sufficient
rain fall, economical issues, independency fromother facilities and potential for high efficiency.
During the free-flow sediment flushing, the bottom
outlets of the dam are opened and the water level in
dam reservoir is drawndown in a short time. This
process will increase the flow velocity and the bed
shear stress, results in forming a channel throughdeposited sediment in reservoir and flushing thefine and coarse sediment. In some cases, thefree-flow sediment flushing is performed during aflood event, with respect to a speculated standard,
to facilitate the sediment discharge out and also
preventing the negative environmental effects in thedownstream. The coordinated free-flow sedimentflushing in DASHIDAIRA & UNAZUKI dam
reservoir in Kurobe River, located in Toyama
prefecture, is a pioneer example as shown
schematically in Fig. 1.

Fig. 1 Outline of coordinated sediment flushing(Minami et al. 2012)

Many reservoirs are not flushed because an
accurate prediction of the success of an upcoming
reservoir flushing is time and cost-intensive (Haun& Olsen 2012). Loss of the stored water besides thelack of knowledge about the amount of the flushed
out sediment and location of the erosion-depositionarea in the reservoir will be the negative factors forchoosing the free-flow sediment flushing.
Following that, the environmental effects
downstream of the reservoir caused by the flushing
are difficult to estimate because of the complexityof free-flow sediment flushing process. So, it isimportant to have an initial assessment of theefficiency of upcoming free-flow sedimentflushing.
The common way is physical model study thatis time consuming, usually not cost effective forcomplex natural geometries and also takes a longtime. The other issue relates to the physicalmodeling is scale effects which will be further
magnified if the fine sediments should be used.
The RESCON model developed by the WorldBank in 1999, including the theoretical formulas
suggested by Atkinson (1996), to predict theeconomical feasibility of different approaches forremoving the accumulated sediment through dam
reservoirs. More specifically, this model is acomputer model of RESCON approach developed
as a demonstration tool (Palmier et al. 2003).
However, results are likely to vary noticeably
owing to the reservoir and sediment characteristics.
Subsequently this approach is only recommended
for use in early design stages as a preliminary study.
However, an accurate assumption of the deposition
pattern is not feasible with these theoreticalformulas (White & Bettes 1984).
Numerical models were developed as analternative over the last decades to avoid scaling
problems and because of an expected time and cost
reduction (Chandler et al. 2003). Niu (1987) & Ju
(1990) used one-dimensional diffusion model for
simulating the volume of flushed out sediment andbed deformation change during the flushing process.
One dimensional numerical model usually uses
some assumptions and simplifications that could
not represent the real nature of complex interacting
flow-sediment field during the flushing process.
Kitamura (1995) and Zigler & Nisbet (1996) use the― 656 ―

one-dimensional numerical model with a forming
flushing channel as limiting factor. More advanced
two-dimensional numerical models were used by
Olsen (1999) & Badura et al. (2008) for simulating
the flushing in a physical model scale and prototype
scale respectively.
Three-dimensional numerical models are still
under development for application in this field.
Atkinson (1996), Khosronejad (2008) and Haun &Olsen (2012) used three-dimensional models for
simulating the flushing process in the physicalmodel scale. Application of three-dimensional
numerical models for simulating the complex
structure of interacting flow and sediment fieldwould be useful for understanding the different
stages of flushing process and utilize the outcomesfor application in the prototype scale.
In the Present study, Three-dimensional
numerical program SSIIM (Simulation of Sediment
Movements In Water Intakes With Multiblock
Option) was used for simulating the flow field and
bed changes when the free-flow sediment flushingis conducted in shallow reservoirs with different
geometries.
2.

umerical model SSIIM

2.1 Three dimensional flow model
The SSIIM program solves the Navier-Stokes
equations with the k-ε model on a three dimensional
generalnon-orthogonal
coordinates.
These
equations are discretized with a control volume
approach. The SIMPLE or SIMPLEC methods canbe used for solving the pressure-poisson equation.
An implicit solver is used, producing the velocity
field in the computational domain. The velocities
are used when solving the convection-diffusion
equations for different sediment sizes (Olsen 2011).
The
Navier-Stokes
equationsfor
non-compressible and constant density flow can bemodeled as:

∂ui
=0
∂xi

(1)

(

∂ui
∂u
1 ∂
+uj i =− Pδ ij − ρ ui′u ′j∂t∂x j ρ ∂x j)

(2)

where the first term on the left side of theEquation (2) is the transient term. The next term isthe convective term. The first term on theright-hand side is the pressure term and the second
term on the right side of the equation is the
Reynolds stress term. In order to evaluate this term,a turbulence model is required. SSIIM program canuse different turbulence models, such as thestandard k-ε model or the k-ω model by Wilcox(2000). However, the default turbulence model isthe standard k-ε model.
The free surface is modeled as a fixed-lid, withzero gradients for all variables. The locations of the
fixed lid and its movement are as a function of time,
which can be computed by different algorithms.
The 1D backwater computation is the default
algorithm and it is invoked automatically.
Pressure and Bernoulli algorithm can be used forboth steady and unsteady computations. The
algorithm is based on the computed pressure field.
It uses the Bernoulli equation along the water
surface to compute the water surface location basedon one fixed point that does not move. The
algorithm is fairly stable, so that it can also be usedin connection with computation of sedimenttransport and bed changes (Olsen 2011).
For the wall boundary treatment, it is assumed
that the velocity profile follows a certain empiricalfunction called a wall law. It is a semi-analytical
function to model the turbulence near the wall inthe boundary layer and consequently the CFD
model will not need to resolve the turbulence offlow in boundary layer. As a result, it would notnecessary too many grid points near the wall:U 1  30 y = lnu x κ  k s 

(3)where the shear velocity is denoted ux, κ is aconstant equal to 0.4, y is the distance to the walland ks is the roughness equivalent to a diameter ofparticles on the bed.
2.2 Morphological model
The sediment transport process in rivers is
described by the following equation, Exner’s
equation, which is the sediment continuity equation― 657 ―

integrated over the water depth:(1 − λ )∂zb ∂qtx ∂qty
+
+
=0
∂t
∂x
∂y

(4)

where zb is the bed elevation, λ is the porosity of
bed material, and qtx and qty are components of
total-load sediment transport in x- and y-directions,
respectively.
In this 3D CFD program, the suspended load
can be calculated with the convection-diffusion
equation for the sediment concentration, which isexpressed as follows:

∂c
∂c
∂c
∂
∂c
+uj
+w =
(ΓT
)
∂t
∂x j
∂z ∂x j∂x j

(5)where w is the fall velocity of sediment particles
and ΓT is the diffusion coefficient and can be
expressed in the following way:

ΓT =

νT

the sediment particle diameter, a is a reference levelset equal to the roughness height, τ is the bed shear
stress, τc is the critical bed shear stress for
movement of sediment particles according toShield’s curve, ρw and ρs are the density of waterand sediment, ν is the viscosity of the water and g is
the acceleration of gravity.
Once Equation (5) is solved, the suspended load
can be calculated as follows:zf

qs ,i = ∫ ui c dz

where qs,i (i=1,2) are components ofsuspended-load sediment transport in x-and
y-directions, respectively.
For calculating the bed load in Equation (4), thefollowing relation proposed by van Rijn’s formula(1987) is used:

qb

(6)

Sc

1.5

D50

where Sc is the Schmidt number representing
the ratio of diffusion coefficient to eddy viscosity
coefficient νT and set to 1.0 as default.
For calculating the suspended load in Equation(4), Equation (5) is solved incorporated with theformula by van Rijn (1987) for computing theequilibrium sediment concentration close to the bed
as the bed boundary. In order to solve Equation(4) and Equation (5), conditions of z and C should
be given at inflow and outflow boundaries. For the
inlet boundary, due to the clear water scour
conditions, z=C=0 can be given and for the outlet(8)a( ρs − ρw ) g

ρw= 0.053τ − τ c  τc 

1.5

0.3  ( ρ − ρ w ) g D50  s2 ρ wν(9)
0.1

where D50 is the mean size of sediment. Then,the components of bed-load sediment transport in xand y-directions can be calculated as follows:

qbx = qb cos(α b ); qby = qb sin(α b )(10)where αb is the direction of bed-load sedimenttransportation.

boundary, far away from the pier, ∂C = ∂z = 0 can

3.

be given due to the uniform flow.
The concentration formula has the following
expression:

3.1 Experimental set-up
In this paper experimental data provided by
Kantoush & Schleiss (2009) were employed. All
experimental tests were conducted in a rectangularshallow basin and width of the inlet and outlet was
0.25 m for all cases.
Adjacent to the reservoir, a mixing tank wasused to prepare the water-sediment mixture. The
water-sediment mixture was supplied by gravity
into the water-filled rectangular basin. The∂xCbed = 0.015

τ − τ c  τc 

∂x

1.5

d 0.3
a  ( ρ − ρ ) g  0.1
s
w


2
 ρ wν


Experimental conditions(7)

where, Cbed is the sediment concentration, d is

― 658 ―

sediments were added to the mixing tank during thetest. To model the suspended sediment currents inthe laboratory, non-uniform crushed walnut shells
with the median grain size (d50) of 50 µm anddensity of 1500 kg/m³ was used in all experiments.
This is a non-cohesive, light weight andhomogeneous grain material (Kantoush & Schleiss2009). The Ultrasonic Velocity Profiler (UVP) as
well as Large Scale Particle Image Velocimetry
technique (LSPIV) used for measuring the surface
velocity field. The evolution of the bed level wasmeasured with a miniature echo sounder. The
hydraulic and sediment condition were set to fulfill
the requirements for subcritical and fully developed
turbulent flow condition. The water discharge andwater level was equal to 0.007 m³/s and 0.2 m
respectively and they were kept constant for theexperimental runs. Fig. 2 illustrates theexperimental set-up of the reference rectangularbasin.
(a)in three phases. In the first phase the shallow basins
filled with clear water and after reaching to thestable state, in the second phase, the mixture ofwater-sediment drained by the gravity into thewater-filled reservoir. In this stage the flow velocity
as well as the bed morphology measurements
conducted in every 90 minutes interval for a total
period of 4.5 hours. The pump was turned off after
each time step to record the bed morphology.
In the third phase two types of free-flow
flushing (with and without drawdown) performed.
The final bed topography from the second phase
was used as the initial bed for two types of flushing.
Moreover, the clear water introduced into the basin
to evaluate the effect of sediment flushing on the
bed deformation and the distribution of thehorizontal flow velocity pattern. In the case of
free-flow flushing with drawdown the water level
decreases to half of the normal water depth (0.1 m)
whereas it was kept constant in the case without
drawdown. The duration of runs was 48 hours but
there was no noticeable change in the bed
morphology and flow character after about 24
hours.
4.

(b)

Fig. 2 (a) plan view and (b) view looking over thedownstream of experimental set-up (Kantoush &Schleiss 2009).
3.2 Test procedure
Kantoush & Schleiss (2009) configured the tests

umerical simulation

4.1 Domain description
In the present study, shallow reservoirs withdifferent geometries were considered to represent
the capability of three-dimensional numericalmodel for assessing the flow velocity distribution
and also bed topography changes during thefree-flow flushing. Fig. 3 demonstrates the four
different types of reservoir geometries (T1, T8, T11
and T13) that were used for the numerical study. T8,
T11 and T13 used for modeling the surface flow
velocity distribution. Free-flow flushing without
drawdown was conducted for run T1 while
free-flow flushing with drawdown employed for T8
and T13.
Regarding the procedure of the experimental
runs described in the preceding section, in
numerical simulations, the final bed morphology
obtained in the second phase was used as the initial
bed topography before free-flow sediment flushingprocedure. Moreover, the final bed morphology inthe equilibrium condition was utilized for― 659 ―

distribution, the total number of cells were 230400,
190320, 960000 and 576000 respectively.
For the inflow boundary condition, the velocity
distribution was specified by the numerical model
while the gradient of pressure is given zero. At theoutflow boundary, the vertical gradient of velocity
is zero and the hydrostatic pressure distribution is
specified according to the water depth. For the solidboundary, wall laws introduced by Schlichting(1979) were used for the side walls and the bed.
During the simulations it was found that it isimportant to model the drawdown procedure
appropriately for T8, T11 and T13 runs. So, thewater level in the reservoir lowered during a shortperiod of time (about 1.5 minutes) to the half andsubsequently due to the increased flow velocity andbed shear stress the flushing channel start to form
along the reservoir. Because of the hydraulicallycomplex nature of the drawdown and then flushingchannel formation, it is necessary to adjust theroughness, time step, discretization method andsediment related parameters to get the satisfying
results with respect to the measured experimental
data. So, because of the shallow water condition
and also different expansion ratio it is necessary tocheck different set of input parameters. Moreover,some simplification in sediment size distribution
was assumed in order to introduce the non-uniform
sediments to the model.

simulating the three-dimensional flow field.
(a)

(b)

(c)

(d)

Fig. 3 Geometrical configuration of (a) run T1,(b) run T8, (c) run T11 and (d) run T13.
Making an appropriate grid is a very important
process in the preparation of input data for SSIIM
program. The size and alignment of the cells willstrongly influence the accuracy, the convergenceand the computational time (Olsen 2011).
The cell sizes for T1, T8, T11 and T13 in X andY direction were 5 cm × 2.5 cm, 5 cm × 1.5 cm,
2.5 cm × 1 cm and 2.5 cm × 1 cm respectively.
Considering the 12 cells for vertical grid

4.2 Simulation of flow velocity field
Measuring the surface velocity using LSPIV(Large Scale Particle Image Velocimetry) is usuallyconducted as a part of monitoring process during
the free-flow sediment flushing from dam
reservoirs (i.e. Unazuki and Dashidaira resrvoirs inJapan). Furthermore, measuring the flow velocity
during the flushing process can help us to better
understand of the erosion and deposition dynamic
during the flushing.
Owing to the importance of the flow velocity
measurement after full draw down, the simulated
flow velocity field by the numerical model SSIIM
compared to that of measured during theexperimental runs. So, the final bed morphology
after the free-flow sediment flushing withdrawdown introduced to the model and thethree-dimensional flow field was calculated.

― 660 ―

Fig. 4 shows the simulated surface velocity
distribution pattern versus the measured one forruns T8, T11 and T13 respectively.

(c1)

(a1)

Y

(a2)

X

(c2)

Y
X

(b1)

Y
X

Y

(b2)

Y

X
X

Y
X

Fig. 4 (a1), (b1) and (c1) measured surface velocityand (a2), (b2) and (c2) simulated surface velocity
for run T8, T11 and T13 respectively. The flow
direction is from left to right.
Fig. 5 illustrates the simulated and measured
horizontal velocity distribution in transversal
direction at the water surface. The measurements
were in two positions, namely the middle anddownstream half of the channel. The downstream
half position was X=4.75m for T8 and X=4m forT11 and T13.
As can be clearly observed form the Fig. 4, themodel could simulate the surface flow velocity
pattern, almost similar to the measured one, withthe main aspects such as the flow velocity direction― 661 ―

3
2.8
2.6
2.4

Y(m)

2.2
2
1.8

X=3m_simulated

1.6

X=3m_measured

1.4

X=4.75m_simulated

1.2

X=4.75m_measured

1
-0.15

-0.10

-0.05

0.00

0.05

0.10

0.15

Horizontal velocity (m/s)

0.20

0.25

0.30

(b)

4
3.6
3.2
2.8

Y(m)

2.4
2
1.6
X=3m_simulated

1.2

X=3m_measured

0.8

X=4m_simulated

0.4
0
-0.20

X=4m_measured

-0.15

-0.10

-0.05

0.00

0.05

0.10

0.15

0.20

0.25

0.30

Horizontal Velocity (m/s)

(c)
4
3.6
3.2
2.8
2.4

Y(m)

and the position of different eddies and circulation
areas. As for the surface velocity of run T8, thesimulation shows the asymmetric flow structure
similar to the measurements but the recirculation
zone beside the right wall is different than obtainedby the measurements. Concerning the T11 and T13
run, the symmetric flow pattern with two
distinguished circulation zones on the both sides
can be observed in the simulation outputs. But, still
the circulation domain and consequently the mainhigh flow velocity trajectory field is not completely
similar to the measurements. Furthermore, Fig. 5
reveals that although the numerical model
quantitatively could simulate the magnitude of thehorizontal flow velocity in the water surface, results
has better agreement with the measured values in
the middle of the channel. This can be attributed tothe more stable flow velocity pattern in the middle
part of the channel than the downstream half. It is
obvious that the flow field in the downstream half ismore complex because of the strong reverse flow
formation while a portion of the stream flow
discharged out from the outlet gate. The
discrepancy between simulated and measured flow
velocities beside the walls is higher than other areas.
As mentioned before, it is assumed that the velocity
profile follows a certain empirical functions
whereas reverse flows accompanying with eddies
present a complex flow field beside the walls.
However during the simulations it was foundthat the lateral expansion ratio (reservoir width/inlet
width) and aspect ratio (reservoir length/reservoir
width) when the total area of the reservoir is same,
are important parameters which can strictly affectthe stability and also the accuracy of the numericalmodel results.
(a)

2
1.6
X=3m_simulated

1.2

X=3m_measured

0.8

X=4m_simulated

0.4
0
-0.20

X=4m_measured

-0.15

-0.10

-0.05

0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

Horizontal Velocity (m/s)

Fig. 5 Horizontal surface velocity in the transversal
direction for (a) T8, (b) T11 and (c) T13.
More specifically, the total area of runs T8 andT13 are same but the flow field computation wasmuch more stable in run T8 than run T13.
4.3 Simulation of bed changes and flushingchannel formation
Drawdown is the lowering of the water level ina reservoir. Hydraulic flushing involves reservoir
drawdown by opening the bottom outlet to generate
and accelerate unsteady flow towards the outlet(Morris & Fan, 1998). This process will initiate theprogressive and retrogressive erosion pattern in thedeposited sediment that leads in to formation of theflushing channels in the reservoir.
Nonetheless, investigation and explanation
about formation and also the characteristic offlushing channel in different type of reservoirs isnecessary. The characteristic of the flushingchannel when the reservoir is fully drawdown canbe briefly introduced by the location, width, side
and longitudinal slope and shape.
In this paper a free-flow flushing without
drawdown for the run T1 and with drawdown for― 662 ―

the run T8 and T13 were conducted by employing
the three-dimensional numerical model SSIIM. The
simulated final bed morphology was compared tothe measured data by Kantoush & Scleiss (2009).
Fig. 6 demonstrates the final measured andsimulated bed topography contours for T1, T8 andalso T13. Because the equilibrium condition was
obtained after one day, the simulation period for
bed changes was 24 hours. In order to further
discussion about the characteristics of flushingchannel formation, the cross-section change causedby lateral bank erosion in the middle of thereservoir has been shown for T8 and T13 in Fig. 7.
Also, Fig. 7c provides data about degradation along
the center line of T13 reservoir.
For the run T1, the final bed topography
obtained in phase 2, used as the initial topography.
Then, the clear water without sediment injected into
the reservoir with the constant hydraulic condition(Q=7 l/s and h=0.2 m). As shown in Fig. 6a and 6b,
if the flushing is performed with the constant waterlevel, sediment will be flushed from a very small
area mostly close to the inlet. In such a condition,
the free-flow flushing effect would be very local
and tongue-shaped crater topography would be
visible (Fig. 6a and 6b).
In free-flow flushing with drawdown, the waterlevel lowering will generate high flow velocity that
initiates the flushing channel formation. The
erosion pattern along with strong jet flow, then,develops the initial flushing channel geometry. In
this stage the initial flushing channel deepened andwidened. The location of the flushing channel
depends on the flow characteristic and reservoir
geometry. In the next stage, during a relatively
short period, a rapid widening of the flushingchannel with an advancing front is visible.
Fig. 6d and 6f reveals that in the simulation
results for both T8 and T13 runs, the flushingchannel location was in the centerline along theshortest path between the inlet and outlet whereas
measured data demonstrate the flushing channel
development direction is towards the left side in the
run T8. Both the simulation outputs and theexperimental measured bed, illustrate the same
location for the flushing channel in the run T13.
Moreover, the measured final bed topographyshows that the channel width increased in thedownstream direction similar to a T shape head.
The same trend witnessed in the simulation results(Fig. 6e & 6f). However, the sediment deposition
pattern in the simulation seems different, although
there are some similarities. So, the various set of
input parameters should be employed to have moreaccurate bed deposition pattern.
The bed topography, geometry of the reservoir
and also flow pattern developed by the entrance jet
can affect the location, size and shape of theflushing channel. However, the final bed deposition
pattern would also able to change the flow pattern.
So, deviation of the jet trajectory from the short andstraight path from inlet to the outlet likely to resultin different characteristic of scoured channel.
Regarding the run T8, this can be the reason fordifferent location, size and shape of the flushingchannel in the simulation and measurement.
5.

Conclusions

In this paper, first, the final measured surface
velocity using the LSPIV technique compared withthesimulation
results
utilizingthethree-dimensional numerical model SSIIM. In thenext step, free flow flushing without drawdown for
one case and with drawdown for two cases were
performed. The following results obtained from thestudy:
1The SSIIM model can simulate the complex
characteristics of the surface velocity using
the equilibrium final bed morphology, almost
similar to the measured one. Many aspects
such as jet trajectory, recirculation zones,
eddies and the flow distribution pattern canbe presented quantitatively. In addition,comparing the simulated horizontal surface
velocity to the measured one reveals thecapability of the numerical model for
quantitatively assessing the surface flow
velocity.
2Free-flow flushing without drawdown had
only a very local effect. Small nosed shapeflushing channel emerged close to the inlet
and it did not expand and distribute to thedownstream direction. Nevertheless, a smallcone shaped erosion area appeared beside theoutlet in the numerical simulation results.

― 663 ―

3-

During the free-flow flushing for two
geometry type reservoirs (namely wide andnarrow), straight flushing channel along thecenterline formed in numerical simulations.
On the other hand, experimental runs show

(e)

(a)

(f)

(b)

Fig. 6 Contours of measured bed after flushing for(a) T1, (c) T8 and (f) T13 versus simulated bed
contours for (b) T1, (d) T8 and (f) T13.
(c)(a)
Initialt=11 hours

Elevation (m)0.06

t=1 hourt=24 hours

t=3 hours
Final_measured

t=5 hours

0.04
0.03
0.01
-0.01
1

1.2

1.4

1.6

1.8

2

2.2

2.4

2.6

2.8

3

Y (m)

(b)
(d)

Initialt=11 hours

Elevation (m)0.06

t=1 hourt=24 hours

t=3 hours
Final_measured

t=5 hours

0.04
0.03
0.01
-0.01
0

0.5

1

1.5

2

2.5

3

3.5

4

Y (m)

(c)
Initialt=5 hours

Elevation (m)0.06

t=1 hourt=11 hours

t=2 hours
t=24 hours

t=3 hours
Final_measured

0.04
0.03
0.01
-0.01
0.1

0.6

1.1

1.6

2.1

2.6

3.1

X (m)

Fig. 7 Lateral development of flushing channel for(a) T8 and (b) T13 during the free-flow flushing― 664 ―

with drawdown; (c) Channel degradation along thecenterline of reservoir T13.
the different location of the flushing channel for
narrow reservoir. Reservoir geometry, bed
topography, flow pattern affect the location, sizeand shape of the flushing channel and at the sametime, the final bed topography has the potential toinfluence the flow pattern. In addition, the flow
pattern is important to boundary condition. Owing
to the dynamic interaction between various
effective parameters, the exact prediction of thegeometrical character of flushing channel isdifficult. In addition, a deviation in the entrance
flow would have a major effect on flushing channel
formation procedure.
4Although the location, shape and size of theflushing channel are important, it isnecessary to have the insight about theupcoming flushing efficiency. Specifically,
estimating the volume of the flushed out
sediment by numerical model would be
useful both from the hydraulic andenvironmental point of view. The numericalmodels, especially three-dimensional models
with reasonable accuracy, can be acost-effective
andalso
time-saving
alternativeforphysical
experiments.
Furthermore, various shapes of reservoirs
should be considered in order to evaluate
different geometric and hydraulic aspects offlushing channel formation in the futurestudies.
References
Atkinson, E., (1996): The feasibility of flushingsediment from reservoirs, Tech. report, HR
Wallingford, UK.
Badura, H., Knoblauch, H. and Schneider, J.
(2008): Pilot project Bodendorf, Work Package 8“ Pilot Actions ”. Report of the EU Interreg IIIB
Project ALPRESREV, Austria.
Chandler, K., Gill, D., Maher, B., Macnish, S. andRoads, G. (2003): Cooping with maximum
probable flood-an alliance project delivery for
Wivenhoe Dam, Proceedings of 43rd conference,
Hobart, Tasmania.

Haun, S. and Olsen, N. R. B. (2012):
Three-dimensional numerical modeling ofreservoir flushing on a prototype scale, Int. J.
River Basin Management, Vol., (10), No. 4, pp.
341-349.
Ju, J., (1990): Computational method of headwatererosion and its application, Journal of SedimentResearch, Vol. (1), 30-39 (In Chinese).
Kantoush, A. S. and Schleiss, A. J. (2009): Channel
formation during flushing of large shallow
reservoirs
withdifferent
geometries,
Environmental Technology, Vol. (30), No. 8, pp.
855-863.
Khosronejad, A., Rennie, C.D., Salehi Neyshabouri,
A.A. and Gholami, I. (2008): Three dimensional
numerical modeling of sediment release, Journalof Hydr. Research, Vol. (46), No. 2, pp. 209-223.
Kitamura, Y., (1995): Erosion and transport processof cohesive Sediments in dam reservoirs, Journalof Hydroscience and Hydraulic Engineering, Vol.
(13), No. 1, pp. 47-61.
Liu, J., Minami, S., Otsuki, H., Liu, B. and Ashida,K. (2004): Prediction of concerted sedimentflushing, Journal of Hydr., Eng., ASCE, Vol.
(130), No. 11, pp. 1089-1096.
Minami, S., Noguchi, K., Otsuki, H., Fukuroi, H.,
Shimahara, N., Mizuta, J. and Takeuchi, M.
(2012): Coordinated sediment flushing and effectverification of fine sediment discharge operationin Kurobe River, Proceedings of the International
symposium on dams for changing world, ICOLD,
Kyoto, Japan.
Morris, G. L., & Fan, J. (1998): Reservoir
Sedimentation
Handbook,
NewYork:
McGraw-Hill Inc.
Olsen, N. R. B., (1999): Two-dimensional modelingof flushing process in water reservoirs, Journal of
Hydraulic Research, Vol. (37), No. 1, pp. 3-16.
Olsen, N. R. B., (2011): A three-dimensional
numerical model for simulation of sediment
movements in water intakes with multiblock
option, www.ntnu.no, Online User's manual.
Palmier, A., Shah, F., Annandale, G.W. and Dinar,
A. (2003): Reservoir Conservation Volume 1: The
RESCON approach, World Bank.
Schlichting, H. (1979): Boundary-Layer Theory,
New York: Mc-Graw Hill Inc.

― 665 ―

Sumi, T., 2006: Reservoir sediment management
measureandnecessary
instrumentation
technologies to support them, The 6thJapan-Taiwan Joint Seminar on Natural Hazard
Mitigation.
White, W.R. and Bettess, R. (1984): The feasibilityof flushing sediment through reservoirs.
Challenges in African Hydrology and Water
Resources. Proceedings of the Harare Symposium,
IAHS press, Wallingford, UK.

White, R., (2001): Evacuation of sediments fromreservoirs, Thomas Telford Press.
Wilcox, D.C. (2000): Turbulence modeling for CFD,
California: DCW Industries Inc.
Ziegler, C.K. and Nisbet, B.S. (1995): Long term
simulation of fine-grained sediment transport inlarge reservoir, Journal of Hydr., Eng., ASCE, Vol.
(121), No. 11, pp. 773-781.

― 666 ―

(Received June 10, 2013)