5th IAHR Symposium on River, Coastal and Estuarine Morphodynamics (RCEM 2007)

STUDY OF SEDIMENT TRANSPORT RATE OVER
DUNE-COVERED BEDS

Akihiro TOYAMA1, Yasuyuki SHIMIZU 2, Satomi YAMAGUCHI3 and Sanjay GIRI4
1

Dept. of Hydraulic Research, Hokkaido University
Dr. Eng., Professor, Dept. of Hydraulic Research, Hokkaido University
3
Dr. Eng., postdoctoral fellow, Dept. of Hydraulic Research, Hokkaido University
4
Dr. Eng., postdoctoral fellow, Dept. of Hydraulic Research, Hokkaido University
2

Abstract
River bed configuration, as a roughness element, exerts flow resistance and influences sedimenttransport process. In this study, a movable bed experiment has been carried out to evaluate the influenceof form drag, exerted by microscale bedforms, on sediment transport rate. The experimental results havebeen compared with the bedload transport rate calculated by using Ashida & Michiue’s and Meyer-Peter& Muller’s formulae. The bedload transport rate, measured directly in the present experiments, appears to
be in good agreement with the bedload transport estimated by both relationships. Furthermore,experimental result has been compared with the result of bedload transport calculated by using a
numerical model proposed by Giri & Shimizu. This numerical model incorporates a stochastic pick
up-deposition model for non-equilibrium sediment transport with a distribution function of mean
step-length proposed by Nakagawa & Tsujimoto. It is revealed that the mean step-length has an effect on
sediment transport rate, thereby exerts influence on bedform geometry, particularly on wave-length.
Consequently, a basic attempt has been made to calibrate parameter mean step-length based on
experimental result and numerical analysis. Comparison between experimental and numerical simulation
results shows reasonably good agreement for both the bedload transport rate and geometric characteristics
of bedforms.
Key Words : dune, bedload transport rate, sediment transport rate, bedform1. INTRODUCTION
The underlying mechanism of resistance to flow exerted by microscale bedforms, particularly dunes, hasbeen explored since long. Such microscale sand waves have dominant effect in flow resistance and so this is
the issue of a great practical significance in river engineering. Estimates of bedload transport rate consideringsuch bedforms are important to predict channel evolution process. This information is necessary for riverplanning and restoration. On the other hand, flow resistance due to the form drag exerted by bedforms isimportant to quantify its influence on water surface fluctuation. The flow, the bed morphology, and thesediment-transport field are tightly coupled and none may be predicted without knowledge of the others.
A comprehensive review of past investigations on river dunes has been presented by Best (2005). A
variety of approaches have been developed in order to analyze bedform-induced morphology in alluvial
channels and the development of dunes (Engelund, 1970; Engelund & Fredsøe, 1982; Coleman & Melville,
1994; Fredsøe, 1996; Coleman & Melville, 1996; Lisle et al., 1997; Baas, 1999; Smith, 1970; Fredsøe, 1974;
Kobayashi & Madsen, 1985; McLean & Smith, 1986; Nelson & Smith, 1989). Most of them are based onlinear stability theory. Some works were conducted using weakly nonlinear stability analysis (Ji & Mendoza,
1997; Yamaguchi & Izumi, 2005). Some notable examples of field observations include those of Itakura etal. (1986), Kishi and Kuroki (1972), Dinehart (1989), and Carling et al. (2000a, 2000b). All these studies
have revealed the influence of temporal variability contributing to bed form development.
Recently, a significant contribution has been made by Giri & Shimizu (2006), which demonstrates thecapability of a numerical model to reproduce fluid and morphodynamic features of dunes. Proposed model isvertical two-dimensional with non-hydrostatic free surface flow, which is coupled with a stochastic pick
up-deposition model (Nakagawa & Tsujimoto, 1980) for non-equilibrium sediment transport by imposing a
distribution function of mean step-length. This numerical model can simulate formation and migration
process of dunes and physically replicate geometric characteristics of dunes for arbitrary steady or unsteadyflow condition. The model can predict form drag exerted by dunes hydrodynamically.
The microscale sand waves are categorized into three distinctive configurations, namely lower regime,
upper regime and transition. In this study, we have focused on bedform evolution and sediment transport
process under the lower regime. We have made a basic attempt to measure sediment transport rate as well as
bedform geometry in laboratory flume under variety of flow conditions. We have conducted series ofmovable bed experiments to evaluate quantitatively sediment transport rate with bedforms and associatedform drag. We compared the experimental results with the bedload transport rate calculated by using acouple of well-known bedload transport formulae, and also with the result of numerical calculation by using
above-mentioned morphodynamic model.

2. MOVABLE BED EXPERIMENT(1) Experimental procedure

There are few movable bed experiments with bedforms that pay attention to the sediment transport rate.
Some significant set of experiments has been compiled by Guy et al. (1966). Some laboratory experiments
were carried out to evaluate sediment transport rate under unsteady flow condition (De Sutter et al., 2001;
Lee et al., 2004). The primary purpose of this study is to estimate the sediment transport rate simultaneously
conducting observation on temporal bed deformation under steady flow condition with lower regime, andfinally verify the results against numerical computation.
Experimental works reported in this paper have been carried out in the Hydraulic Research Laboratory of
Hokkaido University. Total length of flume was 10m and height was 30cm. Experiments was performed fortwo different flume widths, namely 10cm and 15cm. The flume was made from Plexiglas. The middle part of
the flume (7.5m in case of flume with 10cm width and 8m in case of flume with 15cm width) was covered
with a 5 cm thick sediment layer, which was trapped using acrylic sediment stoppers at the upstream anddownstream part of the flume in order to prevent the degradation of the channel bed. A tail gate was used inorder to control flow-depth and keep the mean velocity under nearly uniform condition.
The experimental setup also included bed load trap to collect bedload sediment transport. The slope ofthe channel bed was set to be 0.002. Well-sorted uniform sediment with 0.335mm median diameter (D50)
was used for all experimental case. The grain size distribution curve is depicted in Fig. 1. The sand feeding
was done manually by filling up the space between movable bed and sand stopper in the upstream boundary
so as to maintain constant amount of the sediment feeding throughout the experiment.
Moreover, the bed elevation at the both upstream and downstream ends was carefully controlled2throughout the experimental run. Initially, a preliminary development of bed was allowed, and a uniform
flow was set up through the adjustment of tail gate to make the mean water surface slope nearly equal to the
bed slope. After sufficiently long period of time, an equilibrium stage was assumed to have achieved. Bed
configuration and water-depth were recorded after achieving the equilibrium condition, the sedimenttransport rate were measured three times with an interval of 30 minutes. The sediment transport rate was
evaluated by taking an average of the three measured values. The migration process of sand dune wasvisualized using a digital camera. Geometric characteristics of dunes (wave-length and wave-height) andmigration rate in each experiment were estimated by taking average value of all representative dunes after
achieving the dynamic equilibrium conditions.
The hydraulic conditions for these experiments are presented in Table 1.

Penetration (%)

Fig. 1 Grain size distribution curve.
Table 1 Experimental condition.

100
90
80
70
60
50
40
30
20
10
0

Run No. Channel Width(cm) Discharge(cm2/sec) Slope Grain Size(mm)A-1
207.69A-2
221.05
10A-3
355.18A-4
439.70B-1
224.23
0.002
0.28
B-2
305.51
B-3
335.4815B-4410.14B-5414.09
0

0.1

0.2

0.3

0.4

Grain size Ds (mm)

0.5

0.6

0.7

(2) Dune-induced bedload transport

The sediment transport rate measured in experiments was compared with the bedload transport rate
calculated by using Ashida & Michiue’s and Meyer-Peter & Muller’s formulae. It is well-known that the
average flow-depth increases when dunes appear on the flat-bed as the total flow resistance becomes larger
due to the form drag exerted by the bed configuration. Following the principle of Einstein & Barbarossa(1952), Kishi & Kuroki (1972) suggested that the total flow resistance is associated with the skin friction of
sediment particles and the form drag exerted by bed configuration. Consequently, the total flow resistance isexpressed as follows:τ * = τ *′ + τ *′′(1)

where τ* = dimensionless bed shear stress, τ’* = dimensionless effective shear stress, τ’’* = dimensionlessform drag.
The skin friction is generally assumed as the effective shear stress, which is usually used to calculate
sediment transport rate. However, this may not be true in the presence of bedforms. The dimensionless total
flow resistance and effective shear stress is expressed as follows (Kishi & Kuroki, 1972):

τ* =

hI
RS d

(2)

τ *′ =

h′ I
RS d

(3)

where I = bed slope, RS = relative density of sediment in water, namely 1.65, d = grain size diameter, h =total flow-depth, h’ = flow-depth, associated with effective shear stress.
The velocity, associated with effective shear stress can be calculated as (Kishi & Kuroki, 1972):U= h ′ q
= gh ′I 6.0 + 5.75 log 10  h k s (4)

where U = average flow-velocity, q = discharge per unit width, g = gravity acceleration, ks = equivalent3

roughness height.
The equivalent roughness height can be calculated as ks = md, in which m is generally proposed to be 2.5.
Consequently, the sediment transport rate can be expressed as follows:q B = q B * R S gd d(5)where qB* = dimensionless sediment transport rate.
In this study, we applied the effective shear stress given by Equation (3) to bedload formulae (Equation 6
and 7 below) instead of the bed shear stress in order to estimate the sediment transport rate over the bed
configuration observed in the present experiments.
The dimensionless sediment transport rate is calculated using Ashida & Michiue’s (1972) andMeyer-Peter & Muller’s formulae repectively as:q B * = 17(τ * )

3/ 2


τ 
τ
1 − c *  1 − c * 
τ *   τ * q B * = 8(τ * )32

 τ c* 
1 −
τ * 


(6)

32

(7)

where τc* = dimensionless critical tractive force.
The dimensionless critical tractive force is estimated using the Iwagaki’s empirical equation:τ c * = 0.0052d − 21 32(8)For, 0.0065(cm ) ≤ d ≤ 0.0565(cm )(3) Experimental resultsq B*

The dimensionless sediment transport rate versus 1.00
dimensionless effective shear stress is plotted in Fig.
Width = 10 cm
2. In this figure, the symbols show the experimental
Width = 15 cm
Ashida & Michiue
value while each line represents the bedload transport
Meyer-Peter & Muller
rate estimated by using Ashida & Michiue’s andMeyer-Peter & Muller’s formulae. According to theFig. 2, the bedload transport rate, which wasmeasured directly in the present experiments, shows
good agreement with the bedload rate estimated by 0.10
both the bedload formulae. It is found that the bedload
rate on dune-covered bed can be estimated by using
these conventional bedload transport formulae using
effective shear stress instead of grain shear stress.
Furthermore, we evaluated geometric characteristicsof dunes for different flow intensity. Fig. 3 shows therelationship between wavelength and unit discharge.
It is clear from Fig. 3 that the wavelength of dune 0.01
0.01
0.10
1.00
tends to be longer with increasing unit discharge.
τ' *Likewise, Fig. 4 shows the wave height versus unit
Fig. 2 Non-dimensional bedload transport versus bed shear
discharge relation. It was found that wave height instress: Comparison between bedload transport formulae and thethe case of 10cm wide flume is higher than in the casemeasurement.
of 15cm wide flume for similar unit discharge.
Fig. 5 depicts the relationship between dune migration rate and unit discharge. It can be seen that thedune migration velocity tends to become faster when the discharge increases. Also, we can see from theresult that migration rate is lower in case of narrow flume for low flow intensity whereas higher for highflow intensity in comparison with the case of wider flume. The inconsistency in the results between flumes
with two different width can be attributed to the wall effect.

4

30
Width = 10 cm
Width = 15 cm

Wavelength (cm)

28
26
24
22
20
18
16
150

200

250

300
350
2
Q (cm /s)

400

450

500

Fig. 3 Relationship between duen wave-length and unit discharge.
3.1
Width = 10 cm
Width = 15 cm

Wave Height (cm)

2.9
2.7
2.5
2.3
2.1
1.9
1.7
1.5
150

200

250

300
350
2
Q (cm /s)

400

450

500

Fig. 4 Relationship between dune wave-height and unit discharge.
2.1
Width = 10 cm
Width = 15 cm

Wave Velocity (cm/min)

1.9
1.7
1.5
1.3
1.1
0.9
0.7
0.5
0.3
150

200

250

300
350
2
Q (cm /s)

400

450

500

Fig. 5 Relationship between dune migration rate and unit discharge.

3. NUMERICAL CALCULATION(1) Numerical calculation method

Giri & Shimizu (2006) performed the numerical calculation of bed deformation with a vertical
two-dimensional model with non-hydrostatic free surface flow, coupled with an Eulerian stochastic
formulation of sediment transport proposed by Nakagawa & Tsujimoto (1980). The proposed sedimenttransport computational approach explicitly considers the flow variability during morphodynamic
computation. Consequently, the exchange of sediment particles, namely pickup and deposition rate at eachtime step, can be computed by coupling sediment transport with the hydrodynamic model. The phase lag
between boundary shear stress and sediment transport is generated due to the imposition of mean step-lengthof sediment particle. The form drag exerted by dune is replicated hydrodynamically by the numerical model.
The rate of bed deformation can be computed using following sediment balance equation:

5


∂y b
1  A3+
 ( p d − p s )d  = 0∂t 1 − λ  A2
(9)

where yb = bed elevation, λ = porosity of sediment particle, A2 and A3 = shape coefficients of sand grain
for two and three dimensional geometrical properties, respectively (= π / 4, π / 6).
The pick-up rate ps is evaluated by using a relationship proposed by Nakagawa & Tsujimoto (1980). In
the dimensionless form, pick up rate can be expressed as follows:p s * = p s d (ρ s ρ − 1)g = 0.03τ * (1 − 0.035 τ * )

3

(10)

where ps* = dimensionless pick up rate, ρs and ρ = fluid and sediment density respectively.
The deposition rate pd is calculated as a product of pick-up rate and the probability density distribution ofmean step-length.
The sediment deposition rate reads as:∞

p d = ∫ p s ( x − s ) f s (s )ds

(11)

0

where pd = sediment deposition rate and fs(s) = distribution function of mean step length.
Distribution function of mean step length is found to be exponential as follows (Nakagawa & Tsujimoto,1980):f s (s ) =1 sexp − 
Λ
 Λ

(12)

where Λ = the mean step length and s = the distance of sediment motion from pick up point.
The mean step-length can be calculated as Λ = αd, in which α is an empirical constant and proposed to be
100. However, we will later show that the dune wavelength depends on this parameter.
The bedload transport rate by using an Eulerian stochastic formulation can be calculated as follows:

qB = qB*

∞
A3 x
′
(
)
R S gd d =d p s x ∫ f s (s )dsdx ′A2 −∫∞x − x′(13)

The numerical model incorporates both the bedload and suspended sediment transport, but in this study
we considered bedload only. Also, we performed numerical calculation for one of the cases, namely run A-2,
within the scope of this study.

4. COMPARISON BETWEEN NUMERICAL AND EXPERIMENTAL RESULTS
We performed numerical computation and evaluated the effect of empirical parameter α that is used to
calculate mean step-length. We performed a couple of cases with α equal to 20 and 50, i.e. the step length
was assumed to be 20 and 50 times of the particle diameter respectively, in order to evaluate the effect ofmean step-length on bed configuration and sediment transport rate.
Fig. 6 shows the instantaneous bed configurations of experiment and numerical simulation in 7200
seconds. Result revealed that wave-length and wave-height of the dune reproduced by the numerical modelin the case of means step-length equal to 20d were 18cm and 2.1cm respectively, while wave-length andwave-height of the dune in the case of 50d were 24cm and 2.5cm respectively, and wave-length and wave
height of the dune observed in experiment were 24.3cm and 3cm respectively. It can be seen that thewave-length of the dune reproduced by the numerical model is longer in case of higher value of mean
step-length (50d) than that of in case of lower value (20d). Consequently, for the calculation conditions
presented herein, the dune formation estimated by numerical model appears to be depending on the mean
step-length. Regarding the migration rate, the average value was found to be 2.020 cm/min in case of mean
step-length equal to 50d which is nearer to observation. However, average migration rate of dunes seems to
be overpredicted in comparison with experimental value. It is found that wave-length and wave height ofdunes estimated by the numerical calculation are in good agreement with measured values in the present
experiments, when the mean step-length is assumed to be 50d.
6

Step length = 20d
z(cm)

5.0
m
c
0.0
0

10

20

30

40

50

60

70

80

90

100

110

60

70

80

90

100

110

0

10

20

x(cm)

Step length = 50d
z(cm)

5.0
m
c
z 0.0
0

10

20

30

40

50
x(cm)

Fig. 6 The bed configurations of experiment and numerical simulation 7200 seconds from water run.

(cm)

Fig. 7 shows the dimensionless sediment transport rate and also the effect of mean step-length depicted
in two different plots. In the same figure, the upper line shows the water-depth, and the lower line shows thedimensionless sediment transport rate. Here also the dimensionless sediment transport rate in the case of 50d
seems to be larger than in the case of 20d.
Step length = 20d

Step length = 50d
0.3

0.3

Water depth

7.5

7.5

Dimensionless sedimenttransport rate

2.5

0.1

0.2

5.0

qb*

Depth(m)

0.2

5.0

qb*

Depth(m)Water depth

0.1

2.5

Dimensionless sedimenttransport rate
0.0

0.0
0

2500

0.0

5000

0.0
0

Time(sec)

2500

5000

Time(sec)

Fig. 7 The water depth and the dimensionless sediment transport rate in the case of each step-length.

7

1.00
Experimental value
Step length = 20d
Step length = 50d
Ashida & Michiue
Meyer-Peter & Muller

q B*

Finally, Fig. 8 shows the relationship between
dimensionless effective shear stress and dimensionlessbedload transport rate, and comparison between
numerical
simulation
andtheexperimental
measurement. In numerical calculation, thedimensionless effective shear stress and thedimensionless bedload transport were evaluated bytaking an average value within the range of 5400
second to 7200 second. We compared calculated
bedload transport rate with experimental measurement
using both value of mean step-length (20d and 50d).
From the result, it can be observed that theexperimental value of effective shear stress is lower
than both numerical calculation results. On the other
hand, bedload transport rate seems to be higher inexperiment in comparison with numerical result whenused mean step-length equal to 20d, whereas it appears
lower in case of step-length equal to 50d. The
comparison shows that the numerical calculation of
bedload transport with step-length equal to 50d is
nearer to experimental value. Some inconsistency is
noticed, which can be attributed to the side wall effecton sediment transport rate.

0.10

0.01
0.01

0.10
τ' *

1.00

Fig. 8 Relationship between dimensionless effective shear
stress and dimensionless bedload transport rate: Comparison
between numerical calculation and the experiment.

5. CONCLUSIONSIn this study, we conducted experiments on bedload transport induced by dunes. We performed
comparison of bedload transport rate between laboratory observation, calculated values using Ashida &Michiue’s and Meyer-Peter & Muller’s formulae, and the results of numerical calculation by using a
two-dimensional morphodynamic model. The bedload transport rate measured directly in the present
experiments shows good agreement with the bedload rate estimated by both the bedload formulae. However,
it is necessary to simply consider the effective shear stress instead of grain shear stress in these conventional
bedload transport formulae. The numerical simulation of dune evolution was found to be depending on themean step-length, an empirical sediment parameter used in pick up-deposition model for non-equilibrium
sediment transport. As a result of the comparison between observation and numerical calculation, it is foundthat the dune formation calculated by numerical model shows good agreement with the observed one in casewhen the mean step-length is employed as 50d. The wavelength of dune tends to decrease in the calculation
when the mean step-length is assumed to be smaller than 50d. The bedload transport rate estimated by thenumerical calculation also shows good agreement with the measured value in the present experiments when
the step-length is assumed to be 50d. It implies that both the bed deformation and sediment transport can becalculated by the numerical simulation with the reasonable value of mean step-length. The influence of mean
step-length and its physical determination is supposed to be explored more comprehensively.

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