Geography Reference
In-Depth Information
advantages, the technology to collect information to the
full potential an experiment can offer has only recently
become readily available, mainly in the form of inex-
pensive digital cameras. Today it is common to conduct
experiments in which imaging is the only method of
data collection.
We present several imaging techniques that offer a
broad range of applications related to river management
(Table 13.1). These techniques are based on the use of
cameras ranging from simple digital cameras and video
recorders to more sophisticated CDD (charge-coupled
device) cameras and high-speed video recorders. The
experiments presented were conducted in a wide range
of flumes and stream tables and thus provide an idea of
the diversity of setups and methods used in experimental
geomorphology (Table 13.1). Our focus is on imagery
techniques used in studies of river channels and deltas
to measure (a) mass flux of sediment: sediment grain-
size distribution, bedload transport rate, trajectories and
velocities of individual particles, (b) local and regional
properties of the flow field: depth, width, migration rates,
sinuosity, braiding index, and (c) bed topography in river
channels and deltas (Table 13.1). This chapter is not an
exhaustive review of imagery techniques used in the labo-
ratory. We concentrate on a few key examples which illus-
trate how the powerful combination of laboratory exper-
iments and imagery can be used to advance our under-
standing of river processes and inform management.
(Commercial software and brand names of equipment
used in the studies presented here are included purely as
examples based on the authors' experience. The method-
ologies described do not depend on any specific software
packages or equipment and references to these do not
constitute endorsement).
yield imprecise estimates due to the inherent spatial and
temporal variability in the processes of bedload transport
(Diplas et al., 2008). Flume experiments have been used
extensively to improve our understanding of sediment
transport processes (e.g., Parker et al., 1982) and many of
the most widely used bedload transport equations were
derived from experimental data (e.g., Meyer-Peter and
M uller, 1948; Wilcock and Crowe, 2003). Experimentally,
measuring bedload transport rate and obtaining a grain-
size distribution (GSD) of the material transported (in
the case of non-uniform bed mixtures) typically consists
of collecting the sediment at the flume outlet, manu-
ally sieving the sample, and weighing the individual size
fractions. Needless to say, this is a cumbersome and
time-consuming task.
Even more difficult to measure than sediment trans-
port in the field is bed surface size distribution, which
directly affects the observed transport (Wilcock, 2001).
As in the case of sediment transport, the bed surface
in natural rivers can often be sampled under low flow
conditions, but is almost impossible to sample during
high transport conditions. Several methods for auto-
mated grainsize estimation from images exist (Rubin,
2004; Graham et al., 2005; Buscombe et al., 2009, 2010).
These techniques were developed for field applications
but can be adapted to laboratory experiments. Because
flow in a flume can be instantaneously shut off, experi-
ments offer a unique opportunity to study the bed surface
associated with active transport. This makes flume experi-
ments particularly useful for addressing questions such as
what happens to surface armour layers during high flow
and improving our understanding of fractional transport.
In a well-known set of experiments conducted in the 'bed
of many colours' (BOMC), imagery was used in an inno-
vative way to estimate bed surface grainsize distribution
(and from this variations in grain mobility) during active
transport in a way that was non-destructive to the bed
(details in Wilcock and McArdell, 1993; Wilcock, 2001).
In these experiments each size fraction in the sediment
bed was painted a different colour. Photographs of the
bed surface when the flow was turned off were used to
measure the grainsize distribution using point counts.
Here we present two techniques for studying sedi-
ment transport dynamics in experimental channels. The
first is an image-based technique which enables con-
tinuous in-line measurement of size and velocity of all
transported particles at the downstream exit of a flume.
This information is then used to determine the GSD
and total sediment discharge. The second technique uses
imagery to reconstruct 2D trajectories of individual grains
13.2 Bedload transport
Fundamental to the study of the dynamics of any river is
characterising the rate (mass or volume per unit time) of
sediment transported as bedload and the size distribution
of the transported material. In addition, detailed data
about bedload transport at the grainscale under differ-
ent flow conditions are needed in order to improve our
understanding of the physics governing bedload trans-
port and derive physically based transport equations and
models. However, direct measurements of bedload trans-
port in rivers are difficult and can be dangerous during
larger flows, which account for most of the sediment
flux (Wilcock, 2001). In addition, direct measurements
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