River Sedimentation – Wieprecht et al. (Eds)© 2017 Taylor & Francis Group, London, ISBN 978-1-138-02945-3

Improvement of a bedload transport rate measuring system in sediment
bypass tunnels
T. Koshiba, C. Auel, D. Tsutsumi, S.A. Kantoush & T. Sumi
Water Resources Research Center, Disaster Prevention Research Institute, Kyoto University, Uji, Japan

ABSTRACT: For long term use of dams, it is required to develop methods of sediment management in reservoirs. As one method, Sediment Bypass Tunnels (SBT) are operated in Japan and Switzerland to prevent reservoir
sedimentation. SBT reduces sedimentation in reservoirs by routing the incoming sediments around the dam. SBT,
however, is prone to severe invert abrasion caused by high sediment flux. Therefore, it is necessary to establisha measurement system of sediment transport rates in the SBT. A geophone was experimentally investigated in alaboratory flume at ETH Zurich. The sediment transport rate is calculated based on the plate vibration causedby hitting of gravels. In this paper, in order to alleviate disadvantages of a geophone, two newly developed
sensor systems, a plate microphone and plate vibration sensor, are suggested and the results of their calibration
experiments are shown. Finally, they are compared with the existing methods.

1

INTRODUCTION

1.1

Background

Many dams in the world are prone to reservoir sedimentation and require urgent sedimentation management. One advanced technique against the problem isthe sediment bypass tunnel (SBT) to reduce suspended
and bed load depositions in reservoirs by routing theincoming sediments around the dam (Sumi et al. 2004,
Auel & Boes 2011). SBTs are an effective strategy
bypassing about 80 to 94% of the incoming sediments(Auel et al. 2016). Figure 1 shows the outlet structure of the operating Solis SBT located in the Swiss
Alps. However, measuring and quantifying the sediment transport in a SBT is challenging and a topicalresearch subject (Hagmann et al. 2015). Especiallyinvert abrasion is a severe problem facing most SBT
which is directly connected to increasing maintenancecost (Auel & Boes 2011, Baumer & Radogna 2015,

Figure 1. Outlet of the Solis SBT (courtesy of C Auel).

Jacobs & Hagmann 2015, Nakajima et al. 2015). The
invert abrasion is caused by a combination of highflow velocities and high sediment transport rates (Auel2014). The sediment which is routed downstream ofthe dam during floods is also important regarding riverenvironmental aspects. Various techniques have beendeveloped to monitor suspended sediment, for example by using turbidity current meter. However, there
are limited techniques for field observation of bedload
sediment transport to understand the mechanisms andto quantify bedload transport rates (BTR).
1.2

Existing measurement techniques for BTR

To measure BTR precisely is not only prospective
to contribute to the maintenance of SBTs but alsomeaningful from the aspect of comprehensive river
basin management. As an indirect BTR measuring system, a geophone was developed in the early 1990ies in
Switzerland. The geophone is mainly used in European
countries especially in mountainous areas of Switzerland, Austria, and Italy (Rickenmann et al. 2012).
The geophone consists of a 50 cm by 36 cm steel
plate with a geophone sensor (Geospace GS-20DX,
manufactured by Geospace Technologies, Houston,
Texas) mounted below, embedded in a steel frame andinstalled directly in the river bed. A geophone estimates BTR based on the plate vibration expressed involtage caused by the passing sediment. A geophonesystem was installed the first time in an SBT at theSolis dam and started operation from 2013 (Hagmann
et al. 2015). At the field observation in Erlenbach
in Switzerland, a good correlation between long term
BTR and the output of geophone was confirmed (Rickenmann et al. 2012). Furthermore, the geophone is1038

robust against the impact of sediment and therefore
feasible to be installed on the invert of a SBT. It is also
revealed that, however, the geophone cannot detect
fine sediments with a diameter smaller than 2 to 4 cm
(Rickenmann et al. 2012). In order to clarify the effects
of abrasion on the SBT invert, the impinging gravel
grain size is important. This is because the amount ofabrasion on the invert not only depends on the sediment
flux but also the grain size.
After the development of geophones in Switzerland, another similar indirect BTR measuring system
was developed in Japan, the hydrophone (Mizuyama
et al. 2010). Japan also has gravel bed rivers in themountains similar to Switzerland. The hydrophoneconsists of a rounded metal pipe installed directlyin the river bed. When gravels and sand pass overthe pipe, the number of hitting particles is counted
by the hydrophone based on sound pressure. The
pipe hydrophone system is already installed in somerivers in Japan and many experiments are conducted at
the Hodaka Sedimentation Observatory, DPRI, Kyoto
University (Tsutsumi et al. 2010). The studies at theobservatory revealed that the hydrophone can detect
fine sediment with a diameter larger than 4 mm. However, the hydrophone often underestimates bedloadwhen the pulses are successive and overlap because thehydrophone does not have a large width in flow direction. Also the hydrophone easily deforms when hit bylarge stones negatively effecting the sound collection.
According to the discussions above, each measuring technique has the similar sediment rate measuring
principle. However, both systems have different features caused by the difference of sensors and design(Tab. 1). To improve the weak points of these two techniques with leaving their advantages, a plate microphone and a new plate vibration sensor were tested.
In this study, a new method to measure BTR withsteel plate microphone is proposed and experimentally investigated for various hydraulic and sedimentconditions.
1.3

New devices to measure BTR

A plate-microphone was developed in Japan as amethod to measure the BTR to overcome disadvantages of the pipe-hydrophone as shown in Table 1. The
plate-microphone system consists of a steel plate likethe geophone and measures bedload transport rates
based on sound pressure like the hydrophone. With
these characteristics, the plate microphone is expected
to record hitting sounds of fine sediment andalso to
be robust against hitting by coarse sediment. Additionally, below the plate also a plate vibration sensor
is mounted which uses a different type of vibration
sensor compared to the geophone (GA-313A as asensor and GA-223 as a converter, manufactured by
KEYENCE, Japan). Figure 2 shows the plate microphone and the plate vibration sensor installed in anexperimental flume at the Laboratory of Hydraulics(VAW) at ETH Zurich. The most significant difference of the geophone and plate vibration sensor isTable 1.

Difference of the geophone and the hydrophone.

Figure 2. Plate microphone and plate vibration sensor in thetest flume.

the disparity of their resonance frequency. The natural frequency of the geophone sensor is 10 Hz andthe frequency is classified as ultra-low frequency. It isbecause the geophone sensor is designed to be used forthe observation of seismic data. On the other hand, thefrequency response of Japanese plate vibration sensor is 100 Hz∼80 kHz and the range is much higher
than the geophone ones. Due to this difference, it isexpected that the plate vibration sensor is more suitable
than the geophone because the impact on the rigid steel
plate possesses higher frequency than ground motion.
In order to confirm this hypothesis, laboratory
experiments were conducted in 2014 at ETH Zurich,
the results are discussed in this paper.

2

EXPERIMENTAL SETUP

2.1 Test flume
The experiments of this study were carried out in a
flume facility at the VAW hydraulic laboratory of ETH
Zurich, Switzerland. A schematic view of the experimental setup and parameters are shown in Figure 3.
The experimental setup consists of an elevated water1039

Figure 3. Schematic view of the laboratory test flume.
Table 2.

Dimensions of tested sediment.

Figure 4. Example of vibration waveform.

Grain size Ds[mm]

B-axis[mm]

Average Weight
[g]

2
5
10
50
100

2.00–2.36
5.00–6.00
10.0–12.0
45.0–55.0
95.0–105.0

3.2 of 200 particles
14.3 of 100 particles
2.1
159.2
2937.6

supply tank that discharges the water through a jetbox(Schwalt & Hager 1992) to a rectangular glass-sided
flume with inner dimensions of 0.50 m width, 0.60 m
height, and 8.00 m length. The flume bed is horizontal
and the water is flowing in steady-state supercriticalfree surface conditions. The steel plate with the microphone and plate vibration sensor are placed just before
the flume outlet at 7.56 m from the inlet. The discharge is controlled by a gate valve. The flow velocity
is obtained by measuring the discharge with a magnetic flow meter and the flow depth with point gaugemeasurements. At the flume end the water plunges intoa stilling basin.
In the experiment, the plate microphone and theplate vibration sensor are installed in the same steel
plate box and all experiments are measured by bothmeasuring systems. The device consists of four parts:
steel plate, a microphone, a vibration sensor and a datalogger. The geometry of the steel plate are: 49.2 cm
width, 35.8 cm length, and 1.5 cm thickness. Water andsediment flows are perpendicular to the plate width.
The microphone which detects the sound wave andthe vibration sensor which records the vibration of theplate are installed under the plate and connected to thedata-logger.
In this experiment, five types of gravels are used.
Grain sizes and average weight are shown in Table 2.
The sediment particle density is ρs = 2700 kg/m3 . The
tested sediment has various shapes including rounded,
irregular and angular particles.

2.2

Recording systems

In accordance with the previous observations by thehydrophone (Mizuyama et al. 2008, Suzuki et al.
2010), the following three parameters were measured
during each experiment: acoustic and vibration waveform, the number of pulses, as well as sound andvibration pressure. The mechanisms of these threeparameters are described in the following.

Figure 5. Process of conversing raw waveform data.

2.2.1 Sound and vibration waveform
The sound waveform is raw data collected by the
microphone and the vibration sensor. A value of voltage was recorded every 20 μs. Figure 4 shows one
example of a raw waveform output.
2.2.2 The number of pulses
The recorded parameter number of pulses I n represents
the number of gravels which hit the pate. The pulse isdetermined by processes shown in Figure 5. First, theraw waveform is 20-times amplified by a preamplifier
and transformed into an absolute value. Then, the specific frequency of acoustic waveform data is extracted
by a bandpass filter and an envelope curve of this wave
is recorded as the waveform and amplified 10-times
again. The envelope curve of the sound waveform iscalled sound pressure. Therefore, the envelope curveof the vibration waveform is called vibration pressurein this paper. The transformed data is exported to 6
different channels, in which the wave was amplified
2, 4, 16, 64, 256, and 1024 times. The amplification
was made to find the best value to detect the highest number of particle impacts. Finally, the numberof pulses whose amplitude is larger than the threshold value of 2V are logged by the logger. Figure 6
explains this process. However, for the vibration waveform, not the positive transformed vibration waveform
but the envelope data is used to count the number ofpulses because of a technical problem. Due to the difference of process between the acoustic waveform andthe vibration waveform, the number of pulses of thevibration waveform is much higher than the acoustic
waveform’s one.
2.2.3 Acoustic energy and vibration energy
When sediment transport rate is high, the number ofpulses exceeding the threshold are underestimated due
to overlapping of each separated pulse. To counter
this problem, the acoustic energy E s and the vibration energy E v are also measured. Figure 7 explains
the principle. The sound pressure is the mean value ofthe envelope amplitude. The mean value is calculated1040

Table 3.

Experimental conditions.
Flow

Figure 6. Process to count the number of pulses.

Figure 7. The principle of recording sound pressure andvibration pressure.

and recorded at 10 seconds intervals. Hence, E s andE v are the average value of the output voltage [mV].
2.3

Experimental conditions

The experimental conditions are presented in Table 3.
The flow depth was kept constant with 0.08 m, whereas
the discharge Q and velocity V were varied two times,
represented as low and high flow conditions. W is theamount of sediment. Normally, the flow velocity ina SBT is higher and often reaches more than 10 m/s(Auel & Boes 2011). Gravels are released into the test
flume by hand just after the jetbox. These gravels aretransported along the flume, detected by the plate andcaught by a basket. A constant sediment weight of 50 g
for both grain sizes, Ds = 2 mm and 5 mm was supplied. For Ds = 10 mm, 50 mm, and 100 mm, a fixed
number of 20 stones was added manually to the flow
every five seconds. Every case was repeated 50 times,
therefore in total 1000 tests were carried out.

3

RESULTS AND DISCUSSIONS

3.1 Results
3.1.1 Sound and vibration waveform
Figure 8 and Figure 9 are examples of the results ofwaveforms. Figure 8 is a result of case 10 (V = 4.5 m/s,
Ds = 100 mm), and Figure 9 of case 6 (V = 4.5 m/s,
Ds = 2 mm). The top wave is the sound waveform andthe bottom is the vibration waveform. According to
Figure 8, both devices detect the impinging of gravels. The forms of them are, however, not the same. It
is observed that the wave length caused by a gravel

Sediment

Case
No.

Q
[m3 /s]

V
[m/s]

Ds
[mm]

W
[g]

1
2
3
4
5
6
7
8
9
10

0.10
0.10
0.10
0.10
0.10
0.18
0.18
0.18
0.18
0.18

2.5 (Low)
2.5 (Low)
2.5 (Low)
2.5 (Low)
2.5 (Low)
4.5 (High)
4.5 (High)
4.5 (High)
4.5 (High)
4.5 (High)

2
5
10
50
100
2
5
10
50
100

50
50
50
20 stones
20 stones
50
50
50
20 stones
20 stones

hit measured by the plate microphone is much longer
than the vibration sensor. To consider this difference,the plate vibration has an advantage to avoid the overlap of waves when high amount of sediment passes
over it. On the other hand, it is also observed that theoutput voltage sometimes saturates. To confirm the
problem, more experiments to cralify the muximum
grain size which does not saturate is needed. Whereas,
Figure 9 clearly explains the difference of the bothdevices when the fine sediment hit. The plate microphone can not detect Ds = 2 mm sediment obviously
but the plate vibration sensor detects them. Actually,
to expand the y-axis of the plate microphone’s waveform, there is a successive wave. However, these waves
appear in the water flow without sediment. Therefore these are noises of water flow and the waves ofsediment concealed under the noise are hard to be
confirmed.
3.1.2 The number of pulses
Figure 10 shows the relationship between the amplitude and the number of pulses for high flow conditions.
This graph reveals that the number of pulses increases
with increasing amplitude. The reason is that more particles exceed the threshold voltage, thus more particles
are detected. Even though the number of pulses of theplate vibration sensor is much higher than the plate
microphone one’s due to the reason mentioned in 2.2.2,
a significant difference is not found. The difference isthat the plate microphone cannot detect Ds < 2 mm
and 5 mm, respectively.
3.1.3 Acoustic energy and vibration energy
Figure 11 shows the acoustic energy (E s ) and thevibration energy (E v ) versus the BTR using low flow
conditions. Here, the BTR is the weight used for eachexperiment divided by the observed time. The figure
clearly depicts that the sediment of sizes Ds = 2 mm,
5 mm and 100 mm vary widely between zero and about
100 mV with a positive correlation of increasing E v
and E s with increasing diameter. Even though the dataof 5 mm and 10 mm gravels are distinguishable, 50 mm
and 100 mm are not as they area in the same energy

1041

Figure 8. Waveform
Ds = 100 mm).

of

case

10

(V = 4.5 m/s,

Figure 10. Results of the number of pulses (V = 2.5 m/s).

Figure 9. Waveform of case 6 (V = 4.5 m/s, Ds = 2 mm).

range. It can be concluded that the waves overlap whenlarge sediment is transported. The results of acoustic
energy also reveals that, by the plate microphone, only
few of the Ds = 2 mm grains were detected. On theother hand, E v of fine sediment has an almost constantvalue. This means that notwithstanding the detectionof fine sediment are confirmed in the waveform data,
were not reflected in the results of E v . As the cause ofthis problem, it is possible that the threshold to measure
E v. is too low for fine sediment to exceed. Therefore,
this problem may be resolved by device adjusting.

3.2

Discussions

3.2.1 Detection rate
To know, how much sediment is detected by the devices
compared to the total sediment amount, the detection
rate Rd was defined as the number of detected pulsed
divided by the number of particle used in one experiment (Pn ). Figure 12 shows the relationship between
Rd and the amplitude (V = 2.5 m/s). In general, Rd

Figure 11. The acoustic energy (E s ) and the vibrationenergy (E v ) versus the bedload transport rate (BTR)(V = 2.5 m/s).

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Figure 13. Parameters which compose saturation rate.

The saturation rate Rs is the number of particles
transported over the plate at the same time representing
a bulk density as:

Figure 12. The relationship between the detection rate (Rd )and the amplitude. (V = 2.5 m/s).

increases with amplitude. The results of the plate
microphone reveal that Rd of Ds = 2 mm and 5 mm
are low, making it hard to estimate an accurate sediment transport rate. Especially, Rd of Ds = 2 mm with
2, 4, 16, and 64 times amplitude, Ds = 5 mm with 2,
4, and 16 times amplitude, and Ds = 10 mm with 2
times amplitude are zero. However, the detection rate
for particles with Ds > 10 mm is good in general. On
the other hand the results of the plate vibration sensor revealed that fine sediment less than 10 mm can bedetected when the amplitude is high. Moreover, focusing on the amplitude larger than 4, Rd is increasing for
all diameter of gravels.
3.2.2 Saturation rate
The detection rate can be calculated using the flow andsediment conditions. The number of sediment passing over the devices can be calculated by dividing
the detected number of pulses by Rd. Therefore, twoparameter governing Rd , namely the saturation rate Rs
and hit probability P(Lp ) are introduced.

Here, t: impact time caused by one particle hiton the plate microphone [s], T : The time between firstcollision of first particle to the last of the last particle in
one experiment. Figure 13 explains these parameters.
Figure 14 shows the relationship between Rd andRs using amplitude larger than 4 for Ds = 50 mm at
the low flow conditions. As Rs increases, Rd tends todecrease. When Rs rises, both the waveforms whichinterfere each other and the sediment transported without hitting on the plate microphone increase leading
to a decreased value of Rd . This is confirmed for bothdevices but the results of the plate vibration sensor withthe low amplitudes does not show the negative correlation well. The reason of this can be expected that thepulses registered by the plate microphone tend to overlap because the each wave’s length is generally longer
than the plate vibration sensor’s one as mentioned in
3.1.2.
3.2.3 Hit probability
It is obvious that the particle saltation length affects therelationship with Rd . Saltation length Ds for supercritical flows can be calculated as follows (Auel2014):

Where, Lp : saltation length. θ: Shields parameter. θis calculated by:where Gs : relative density, g: gravitational accelerationand shear stress τb iswhere ρ: density of water and u∗ : shear velocity:1043

Figure 14. The relationship between the detection rate(Rd ) and the saturation rate (Rs ). (Ds = 50 mm, V = 2.5 m/s,
amplitude of (a) = 1024, (b) = 256, (c) = 64 and (d) = 16).

With ib = gradient of channel or energy line gradient. Since ib of the flume in this experiment is 0◦ , ib
is represented by the energy gradient. Thus, probability based on saltation length p(Lp ) was calculated asfollows:

Figure 15. The relationship between the detection rate (Rd )and the hit probability (P(Lp )). (Amplitude = 256 times).

also the height has to be considered to calculate thehitting probability.

with B = plate length. Calculation results of Eq. (6) are
shown in Figure15, where Rd is given as a function ofP(Lp ). The amplitude is 256 times and filled triangles
meanV = 4.5 m/s, and filled circles mean V = 2.5 m/s.
Figure15 reveals that P(Lp ) increases with decreasing fluid velocity for both devices as the arrows show.
According to the result of the plate microphone, at highflow velocities, particles tend to jump very long andhence do not hit the plate often, whereas at low flow,
particles tend to roll or only jump short distances andtherefore show a higher detection rate Rd . However,particles Ds = 50 mm show satisfying Rd = 1 even forthe high flow. That means that in average every particle hits the plate once although P(Lp ) is only about
20%. Consequently not only the saltation length but

4

CONCLUSION

In this paper, two new systems to measure bedloadtransport rates, namely a plate microphone and aplate vibration sensor are introduced and comparedexperimentally. Both systems are developed based on
existing systems, the Japanese hydrophone and Swissgeophone, in order to get over their weak points. As aconsequence of the laboratory experiments, the following features of them are revealed. 1) The plate
vibration sensor can detect fine sediment with theDs smaller than 10 mm, which cannot be detected by
the geophone. However, the plate microphone cannot
detect fine sediment. 2) Rd is effective to calculate
the bedload transport rate from the measured outputs.

1044

3) Both devices outputs saturate when bedloadtransport rate is large. 4) In order to calculate the Rdfrom a given flow condition, Rs and the P(Lp) are suggested and good correlation between the Rd and theparameters was found.
As a future study, more experiments to quantify
the Rd by using the Rs and P(Lp) are needed. At thesame time, not only the minimum detectable grain size
but also the maximum detectable grain size should beclarified. Moreover, these measuring methods are supposed to be installed at the outlet of Koshibu SBT in
Nagano Prefecture in Japan. The SBT will start theoperation from 2016 and in-situ experiments using
Koshibu river sediments are planned before the commencement of the operation. Therefore, in the future,
on site experiments and observations will be carriedout in addition to the laboratory experiment to proceeda more pragmatic study.
ACKNOWLEDGEMENTS
The authors acknowledge the support of the VAWof ETH Zurich for excellent collaboration during theexperimental calibration tests. Many thanks also go
to the Ministry of Land, Infrastructure, Transport, andTourism (MLIT) by sharing the information about the
Koshibu SBT. This work was also supported by JSPS
KAKENHI Grant Number 26257304 and by regional
research project of river and sediment management
technology development by MLIT. The second author
acknowledges the support of the Japanese Society for
the Promotion of Science.
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