**DEVELOPMENT OF AN IMPROVED BEDLOAD TRAP FOR SAMPLING GRAVEL AND COBBLE
BEDLOAD IN COARSE MOUNTAIN STREAMS**

Kristin Bunte^1^, John P. Potyondy^2^ and Steven R. Abt^3^

^1^ Colorado State University, Fort Collins, Colorado,
kbunte@engr.colostate.edu

^2^ USDA Forest Service, Rocky Mountain Research Station,
jpotyondy@fs.fed.us

^3^ Colorado State University, Fort Collins, Colorado,
sabt@engr.colostate.edu

**Keywords:** coarse bedload sampling, rating curve, flow competence,
incipient motion,

**ABSTRACT**

Bedload traps are portable, cost-effective, and appropriate samplers for
gravel bedload. They are easy to install and operable in wadable flow.
Their long sampling time reduces variability in sampled transport rates
and avoids sampling bias; sampling efficiency is generally satisfactory.
Bedload rating curves for total and fractional gravel transport as well
as flow competence curves obtained from bedload traps are generally
steep and relatively well-defined. The ability to sam­ple marginal
transport rates permits direct measurement of incipient motion. Bedload
traps also appear suitable as calibration tools for electronic devices.

**INTRODUCTION**

Gravel- and cobble-bed streams are formed by the transport of coarse
bedload. However, accu­rate measurements of gravel and cobble transport
rates and particle sizes are still difficult to ob­tain. Electronic
devices are not (yet) advanced enough to provide a reliable conversion
between recorded signals and the number and the size of particles moved.
A physical sampler is therefore needed to provide accurate and sievable
samples of coarse bedload that can be related to instanta­neous flow and
used for calibration of signals rates.

Vortex samplers (e.g., Milhous 1973, Hayward and Sutherland 1974,
Tacconi and Billi 1987) and continuously weighing pit samplers (e.g.,
Lewis 1991; Powell et al. 1998; Sear et al. 2000; Reid et al. 2002) can
provide representative measurements of instantaneous transport rates of
gravel and cobble bedload in mountain streams. However, substantial
streambed construction is in­volved in the installation, which makes
these devices difficult, time-comsuming and costly to de­ploy and also
unsuitable for remote sites.

Small non-recording pit trap samplers (e.g., Church et al. 1991; Wathen
et al. 1995; Bunte 1997; Hassan and Church 2001; Sterling and Church
2003) can be installed in a streambed by a small field crew with shovels
and buckets. However, trap operation is limited to flows in which an
op­erator can reach down to the stream bottom to empty the traps. Pit
traps also have highly variable sampling efficiency. During high flow,
sand and fine gravel may travel in suspension, and given a sufficiently
high energetic flow, even mid-sized gravel particles may skip over the
trap opening. Together with the problem of resuspending particles
already captured in the trap and losing them from the sample, both
processes lead to diminishing trap efficiency and underprediction of
trans­port rates at high flows. The sampling efficiency may vary
spatially as well, because flow energy often increases at an uneven rate
over a cross-section.

Net-frame bedload samplers have openings several square feet large and
collect gravel and cob­ble particles in long and relatively
coarse-meshed, trailing fishing nets. These large samplers have been
successfully used to sample gravel and cobble bedload over a wide range
of flows (Bunte 1996; Whitaker and Potts 1996; Whitaker 1997). However,
applicability of net-frame samplers is limited because they require a
bridge with sturdy vertical bars for support, a sill on the stream
bottom for good ground contact, and the strength of several people to
operate.

Bedload traps discussed in this paper overcome many of the deficiencies
listed above and were developed under a cooperative agreement between
the USDA Forest Service's Stream Systems Technology Center and the
Engineering Research Center at Colorado State University. The pri­mary
motivating force behind development was a need by the Forest Service to
accurately and easily measure the onset of gravel and cobble bedload
transport in remote mountain streams for the purpose of quantifying
channel maintenance instream flows on National Forest land. While the
original intent was limited to the determination of incipient motion,
subsequent analysis has demonstrated that data collected with the
bedload traps in coarse-bedded streams can also be used to determine
cross-sectional transport rates and establish bedload transport rating
curves.

To achieve the objective of accurately measuring the onset of gravel and
cobble bedload trans­port, bedload traps had to representatively collect
all mobile gravel particle sizes, cause minimal stream bed disturbance,
and be easy to operate in wadable flow.

A suitable bedload trap would therefore have to meet the following
design criteria:

-   Have a sufficiently large sampler entrance to allow cobbles to
    easily enter,

-   Be stationary to allow for long sampling times to increase the
    probability of sampling infre­quently moving particle sizes,

-   Have a large bag to collect a large sample volume without reducing
    sampling efficiency,

-   Have a comparatively large mesh width to keep flow resistance at a
    minimum,

-   Be lightweight for portability,

-   Be operable in flow depths and velocities as long as the stream
    remained wadable, and

-   Require no more than two persons to operate in the field.

**BEDLOAD TRAPS: DESIGN AND OPERATION**

![](media/image1.wmf){width="3.149212598425197in"
height="2.4283464566929136in"}

Given the above design criteria, a sampler was designed consisting of
the following parts (Fig. 1):

-   Sturdy aluminum sampler frame,

-   Sampling bag made of fishing net,

-   Nylon straps with friction buckles,

-   Aluminum ground plate, and

-   Two smooth iron holding stakes.

Bedload traps developed for collecting gravel (\> 4 mm) and small cobble
bedload consist of an aluminum frame, 0.3 by 0.2 by 0.1 m in size that
is temporarily strapped onto a ground plate anchored into the stream
bottom by metal stakes. Bedload is collected in a trailing net of
ap­proximately 25 liter volume (6.4 gal.), 0.9 m long and with a 3.5 mm
mesh width (Figs. 1 and 2). Sampling capacity is estimated as 40% of the
sampler volume (i.e., 10 liters or 20 kg of gravel). Several bedload
traps are typically installed in roughly 1-m spacing across the stream
on a riffle ![](media/image2.jpeg){width="2.9216535433070865in"
height="2.0456692913385828in"}![](media/image3.jpeg){width="3.161023622047244in"
height="2.046456692913386in"}or a stream widening that will be wadable
to flows of bankfull or more (Fig. 3). During the

sampling period (which is usually one hour), the end of the net is tied
shut with a piece of cotton covered rope. The net can be untied and
emptied with the traps in place, or the traps can be re-moved from the
ground plates and brought to the bank for emptying. Operation of the
bed­load traps is easy in wadable flow but becomes more difficult as flow
reaches the limit of wadability (Fig. 4) (Abt et al. 1989) and may
require a 3-person team and/or the use of safety de­vices (e.g., safety
ropes, belaying, temporary footbridge).

![](media/image4.jpeg){width="3.149212598425197in"
height="2.122047244094488in"}![](media/image5.png){width="2.9200787401574804in"
height="2.1244094488188976in"}Bedload trap samples may contain large
amounts of coarse organic material, particularly when sampling in
forested watersheds during the rising limb of snowmelt highflow (Fig.
5). These or­ganics need to be separated from the gravel before bedload
transport can be analyzed.

***Sampling time***

Bedload traps are designed for sampling times of about one hour. A
1-hour sampling time is usually feasible up to moderately high flow but
fast changing flow or high transport rates may necessitate shorter
times. A long sampling time (or a large number of short-duration
samples) is necessary for representative sampling of fluctuating
transport rates for several reasons: (1) Long deployment averages
transport rates and reduces the measured variability. (2) It decreases
the undersampling bias that occurs when short (or only a few) samples
are collected from lognormal-ly- or Hamamori-distributed transport rates
which are skewed towards large rates (i.e., mode and median rates are
smaller than the mean). (3) When particles of the size classes just
becoming mobile move infrequently (e.g., once per hour), a long sampling
time prevents an overprediction of transport rates that occurs when an
infrequently moving particle is collected by chance and al­lotted to a
short sampling time (Bunte and Abt, submitted). Avoiding these sampling
biases, bedload traps deployed for one hour provide steeper and more
well-defined bedload rating curves than those obtained from a 2-minute
deployment (Fig. 6a), even if legitimate zero-samples (i.e., those that
occurred at flows larger than the smallest non-zero sample) are included
in the power function regression
![](media/image6.wmf){width="3.386220472440945in"
height="2.6133858267716534in"}![](media/image7.wmf){width="3.425196850393701in"
height="2.633464566929134in"}

***Sampling efficiency***

Bedload traps appear to have a satisfactory sampling efficiency within
the limitations posed by the design. The presence of a ground plate
under the sampler prevents inadvertent particle en-train­ment and thus
oversampling. The long-duration deployment reduces positive and negative
bias in samples at low and high flow typically associated with short
collection times (see above). However, if the traps are allowed to fill
beyond their capacity (which may happen during a 1-hour sample when
large amounts of coarse organic material is transported or when gravel
trans­port rates are high), transport may be underestimated. To prevent
this bias, several shorter dura­tion samples need to be collected. With
the current size and mesh width of the bag, small cob­bles are the
largest particles that can be sampled representatively, although larger
ones fit into the sampler opening. This limitation arises because
transport rates are usually so high when cobbles start to become mobile
that the bag fills beyond capacity before enough time has elapsed to
per­mit infrequently moving medium and large cobbles to be properly
sampled.

Detailed field measurements of velocity profiles at the trap entrance,
along the ground plate, and on the bed upstream of the plates, showed
that bedload traps do retard the mean flow velocity in the water column,
particularly when the net is filled to capacity. However, this
retardation is counteracted by an acceleration of the bottom flow
velocity due to the smooth aluminum surface of the ground plates.
Particles that moved onto the ground plate are usually transported
immedi­ately into the sampler. A delay in particle capture may occur if a
small recirculating eddy devel­ops at the transition between the bed and
the ground plate. Small particles may swirl around in this eddy for a
while before entering the trap. However, significant sediment build-up
or a scour trough has not been observed in this location. Flume studies
to fully evaluate the sampler's in­flow velocity distributions and
hydraulic efficiency are being planned.

**RESULTS**

These bedload traps have been used to collect gravel and small cobble
bedload in several coarse-bedded Rocky Mountain streams. Study streams
have gradients of 0.093 to 0.012, basin areas of 8 to 55 km^2^, bankfull
flows of 0.8 to 5.7 m^3^/s (26-200 cfs), and surface *D~50~* particle
sizes of 49 to 108 mm. Some of the results obtained from these field
measurements are summarized below.

***Steep bedload transport rating curves***

Transport rates computed from bedload trap samples can cover a wide
range. The smallest measurable non-zero sample comprises one particle
4-5.6 mm in size in one of the traps during a 1-hour sampling time. This
corresponds to a transport rate on the order of 0.0001 g/s. Con­versely,
samples may be as large as 20 kg in 6 minutes per trap and produce
transport rates of 100 g/s or more. Transport rates that span up to 6
orders of magnitude over a 2- or 3-fold range of flow with relative
little variability produce steep and relatively well-defined rating
curves of total and fractional gravel bedload transport rates (Bunte et
al. 2001; Bunte et al., in revision; Bunte and Abt, in press). Power
function bedload rating curves fitted to measured transport rates
yielded exponents between 8 and 16 in the five studied mountain streams
(Fig. 7). Similarly high expo­nents were reported e.g., by Hassan and
Church (2001) and Wilcock (2001) who also used long sampling times.

![](media/image8.wmf){width="3.188976377952756in"
height="2.45748031496063in"}![](media/image9.wmf){width="3.188976377952756in"
height="2.4515748031496063in"}

***Steep flow competence curves***

Samples from the bedload traps also show a strong coarsening of the
bedload particle-size distri­bution with increasing flow. The bedload
*D~max\ ~*(size class of the largest particle size per sample) increases
from 4 mm at flows 30-50% of bankfull to between 22 and 128 mm at flows
70-130% of bankfull. A 2- or 3-fold increase in flow thus also produces
a strong increase in the largest bedload particle size, spanning up to
10 size classes of 0.5 phi. Power function regres­sions fitted to the
relationships between *D~max~* and flow (flow competence curves) are
therefore comparatively steep and well-defined when based on bedload
trap samples (Fig. 8, above).

***Incipient motion***

![](media/image10.wmf){width="3.2744094488188975in"
height="2.538976377952756in"}Incipient motion can be determined from the
largest bedload particle-size per sample (flow com­petence method) or
from the exceedence of a small preset fractional transport rate (small
trans­port rate method). Measured field results are usually not
compatible between the two methods which lead to the opinion that
incipient mo­tion is better calculated from flow and bed­material data
than directly measured (Wil­cock 1988). However, as bedload traps quite
accurately sample infrequently moving parti­cles, critical flow for
incipient motion com­puted from the flow compe­tence curve corre­sponds to
the critical flow required for the transport of two particles/m·hr per
size class (Fig. 9). This similarity suggests that bedload traps are
suitable for direct meas­ure­ments of incipient motion, an advantage that
bypasses assumptions necessary in a computational approach (Bunte et
al., in revi­sion).

***Comparison of bedload trap sampling results ith results from a
Helley-Smith sampler***

At each of the streams sampled, bedload was also collected with a 3-inch
Helley-Smith sampler for 2 minutes per vertical spaced 0.5-1 m apart.
This sampler is not designed for collecting gravel \> 10 mm but is
frequently used in gravel/cobble beds due to its portability and ease of
use. Bedload trap rating curves are considerably steeper and orders of
magnitude lower at low flow than rating curves obtained for gravel \> 4
mm from a Helley-Smith sampler (Bunte et al. 2001; Bunte and Abt, in
press; Bunte et al., in revision). Transport rates from both samplers
become similar at flows near or above bankfull. Bedload traps deployed
for two-minutes (a sampling pe­riod similar to that often used for a
Helley-Smith sampler) produced rating curves only moder­ately less steep
than those obtained from bedload traps in a 1-hour deployment (Fig. 5a
and b). Thus, sampling time contributes, but cannot explain, the large
differ­ence between rating curves from bedload traps and Helley-Smith
samples at low flow.

***Bedload traps as a calibration tool for electronic devices***

To date, few if any electronic devices developed for measuring gravel
and cobble transport pro­duce signals from which the mass and the size of
a bedload particle can be accurately determined. Bedload traps provide
physical and sievable samples of gravel bedload transport that appear to
be representative and measured transport results are in tune with
theoretical knowledge of bedload transport mechanisms. This suggests
that bedload traps are a suitable device with which to cali­brate signals
obtained from electronic devices that detect gravel transport. There is
a calibration dilemma, though. While very close proximity of two
sampling devices may cause disturbance in transport patterns around each
of the two devices, the high spatial and temporal variability of gravel
transport can cause unequal results if two devices are deployed further
apart (Downing et al., in press). Multiple repetitions of a side-by-side
comparison may be required to average out spatial and temporal
variability and thereby overcome this calibration dilemma.

**SUMMARY AND CONCLUSION**

Bedload traps were designed for sampling gravel and small cobble
transport in wadable coarse- bedded streams. Within the range of design
conditions, bedload traps appear to provide accurate measurements of
gravel transport. The long sampling time reduces variability in measured
trans­port rates and largely eliminates sampling biases due to short-time
sampling. Trap placement on ground plates avoids inadvertent particle
pick-up. Obtaining representative samples of particles \> 128 mm and of
very high transport rates requires a larger net or larger mesh width to
avoid overfilling the net. Bedload trap rating curves and flow
competence curves are comparatively steep and well-defined and both have
larger exponents than curves obtained from a Helley-Smith sampler. The
ability to obtain representative samples during marginal transport rates
for particle size fractions that are just becoming mobile permits direct
measurements of incipient motion. Collection of representative samples
of gravel and cobble bedload combined with portability and ease of use
appear to make bedload traps suitable for calibration tools for
electronic devices.

**ACKNOWLEDGEMENTS**

This research would not have been possible without the help of Kristin
Bunte's husband Kurt Swingle and others in the field. Larry Schmidt
supported this ongoing study in many ways. The study was funded by the
Stream Systems Technology Center, Rocky Moun­tain Research Station, USDA
Forest Service, Fort Collins, CO.

**REFERENCES**

Abt, S.R., R.J. Wittler, A. Taylor, and D.J. Love, 1989. Human stability
in a high flood hazard zone: *Water Resources Bulletin* Vol. 25 (4): pp.
881-890.

Bunte, K., 1996. Analyses of the temporal variation of coarse bedload
transport and its grain size distribution (Squaw Creek, Montana, USA):
*U.S.D.A., Forest Service, Rocky Mountain For­est and Range Experiment
Station, General Technical Report* RM-GTR-288, 123 pp.

Bunte, K., 1997. Development and field testing of a bedload trap for
sand and fine gravel in mountain gravel-bed streams (South Fork Cache la
Poudre Creek, CO): Report prepared for the Stream Systems Technology
Center, USDA Forest Service, Rocky Mountain Forest and Range Experiment
Station, Fort Collins, CO, 53 pp.

Bunte, K. and Abt, S.R., (in press), Sampler size and sampling time
affect measured bedload transport rates and particle sizes in gravel-bed
streams. In: *Erosion and Sediment Transport Measurement in Rivers:
Technological and Methodological Advances*. IAHS-Publ.

Bunte, K. and Abt, S.R., (submitted), Bias in measured transport rates
due to sampling time and implications for annual load computations.
*Geomorphology*.

Bunte, K., Abt, S.R. and Potyondy, J.P., 2001, Portable bedload traps
with high sampling inten­sity for representative sampling of gravel
transport in wadable mountain streams: *Seventh Interagency
Sedimentation Conf.*, Reno, Nevada, p. III-24 to III-31.

Bunte, K., Abt, S.R., Potyondy, J.P. and Ryan, S.E., (in revision),
Measurement of coarse gravel and cobble transport using a portable
bedload trap: *Journal of Hydraulic Engineering*.

Church, M., Wolcott, J.F. and Fletcher, W.K., 1991, A test of equal
mobility in fluvial sediment transport: behavior of the sand fraction:
*Water Resources Research* Vol. 27(11): pp. 2941-2951.

Downing, J.A., Fraley, P.J., Bunte, K., Swingle, K., Ryan S.E. and
Dixon, M., in press. Acoustic gravel-transport sensor. In: *Erosion and
Sediment Transport Measurement in Rivers: Tech­nological and
Methodological Advances*. IAHS-Publ.

Hassan, M.A. and Church, M., 2001, Sensitivity of bedload transport in
Harris Creek: Seasonal and spatial variation over a cobble-gravel bar:
*Water Resources Research* 37 (3): 813-825.

Hayward, J.A. and Sutherland, A.J., 1974, The Torlesse stream
vortex-tube sediment trap: *Jour­nal of Hydrology* (N.Z.) Vol. 13(1): pp.
41-53.

Lewis, J., 1991. An improved bedload sampler: Proceedings of the Fifth
Federal Interagency Sedimentation Conference, Las Vegas, Nev.,
Subcommittee of the Interagency Advisory Committee on Water Data, p.
6.1- 6.8.

Milhous, R., 1973. Sediment transport in a gravel-bottomed stream: Ph.D.
thesis, Oregon State University, Corvallis, USA.

Powell, D.M., Reid, I., Laronne, J.B., and Frostick, L.E., 1998, Cross
stream variability of bed­load flux in narrow and wide ephemeral channels
during desert flash floods. In: *Gravel-Bed Rivers in the Environment.*
P.C. Klingeman, R.L. Beschta, P.D. Komar, and J.B. Bradley, eds.,
177-196, Water Resources Publications LLC, Highlands Ranch, Colorado.

Reid, I., Laronne, J.B. and Powell, M., 2002, The Nahal Yatir bedload
database: sediment dy­namics in a gravel-bed ephemeral stream: *Earth
Surface Processes and Landforms* Vol. 20: pp. 845-857.

Sear, D.A., Damon, W., Booker, D.J. and Anderson, D.G., 2000, A load
cell based continuous recording bedload trap: *Earth Surface Processes
and Landforms* Vol. 25: pp. 689-672.

Sterling, S.M. and Church, M., 2002, Sediment trapping characteristics
of a pit trap and the Helley-Smith sampler in a cobble gravel-bed river:
*Water Resources Research* 38(6), 10.1029/2000WR000052, 2002.

Tacconi, P. and Billi, P., 1987, Bed load transport measurement by a
vortex-tube trap on Virginio Creek, Italy. In: *Sediment Transport in
Gravel-Bed Rivers.* C.R. Thorne, J.C. Bathurst, and R.D. Hey (eds.),
John Wiley, Chichester, pp. 583-615.

Wilcock, P.R., 1988, Methods for estimating the critical shear stress of
individual fractions in mixed-sized sediment: *Water Resources Research*
Vol. 24 (7): pp. 1127-1135.

Wilcock, P.R., 2001, Toward a practical method for estimating sediment
transport rates in gravel-bed rivers: *Earth Surface Processes and
Landforms* Vol. 26: pp.1395-1408.

Wathen, S.J., Hoey, T.B. and Werritty, A., 1995, Unequal mobility of
gravel and sand in weakly bimodal river sediments: *Water Resources
Research* Vol. 31 (8): pp. 2087-2096.

Whitaker, A.C. and Potts, D.F., 1996, Validation of two threshold models
for bedload initiation in an upland gravel-bed stream. In: *Watershed
Restoration Management - Physical, Chemi­cal, and Biological
Considerations*. American Water Resources Association, Proceedings of
the Annual Symposium 1996, pp. 85-94.

Whitaker, A.C., 1997, *The initiation of coarse bed load transport in
gravel bed streams*. Ph.D. Dissertation, University of Montana,
Missoula, 148 pp.