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define the valley-system boundaries and a loose
bed of natural or synthetic bed material. Typical
model scales are in the order of 1:10
−3
or 10
−4
.
At this horizontal scale microscale models dif-
fer from traditional loose bed hydraulic models
because in order to ensure that sediment trans-
port occurs in the model, water depths are
exaggerated and as a consequence vertical scale
distortion is inherent. Also shallow depths lead
to surface tension effects and laminar flows,
which do not occur in the real river. The success
of microscale models, however, is not judged
on the basis of hydraulic similarity but more so
on how well overall the model reproduces the
gross features of the prototype river morpho-
logy (Gaines & Maynord 2001). In this sense
the approach is useful in that it provides an
initial assessment method for rapidly simulating
river behaviour at large scales.
The technique has been used by Davies et al.
(2003) to examine anthropogenic aggradation
of the Waiho River, Westland, New Zealand.
Long-term aggradation of the Waiho River
alluvial fan over much of the past 100 years
has raised the fanhead to an unprecedented high
level. This now poses an unacceptable flood
risk to the adjacent village of Franz Josef Glacier
and the main State Highway 6, which is a key
tourist corridor. The behaviour of this fan has
puzzled geomorphologists for some time and
has led to a number of hypotheses regarding
the evolution of the fan system in relation to
river control measures (Davies 1997; Davies
& McSaveney 2001). The only suitable way
of testing these ideas, however, was to construct
a model capable of simulating river behaviour
for a variety of imposed boundary conditions.
A 1:3333 microscale physical hydraulic model
was used to study the problem (Fig. 2.17a). In
the model an alluvial fan was generated and
allowed to develop to equilibrium with steady
inputs of water and sediment. The fan was later-
ally constrained by rigid boundaries which were
geometrically similar to the natural unrestricted
Waiho River. The boundaries were then reset to
reflect the presence of stopbanks (river control
structures) and the fan allowed to evolve under the
same water and sediment feed rates. The model
fanhead aggraded in a similar spatial pattern
to that observed in the real river. Figure 2.17b
shows a comparison between relative changes
in bed level in the model and those measured
in the Waiho River. The correspondence in the
spatial pattern of aggradation was very similar.
This implies that the reduction of the flow area
at the fanhead caused by the river stopbanks
is sufficient to cause the observed aggradation
in the Waiho.
This example clearly demonstrates the advant-
ages of using microscale modelling for under-
standing large-scale sedimentation problems in
mountain environments where rates of sedi-
mentation are relatively rapid and topography
exerts a major control on the spatial patterns
of cut and fill. Although there are constraints in
using this type of model (e.g. hydraulic condi-
tions cannot be truly scaled) a formal physical
model would require a planform of 50 m by
50 m which is beyond the scope of most physical
model investigations.
2.7
CONCLUDING COMMENTS
The aim of this chapter has been to show how
the functions of active sedimentary processes
are altered by human actions and recent climate/
environmental change in mountain environ-
ments. It has been demonstrated that mountain
environments are characterized by high relief,
steep slopes and local climates that vary over
altitude. These environmental constraints create
a distinctive set of mountain sedimentological
processes. Figure 2.18 is a simple conceptual
model that summarizes the relationship between
mountain sedimentation zones and dominant
process regimes. The diagram distinguishes sedi-
mentation zones in terms of a sediment-cascade
continuum which links slopes and valley-floor
sediment systems along a gradient of downslope/
valley sediment fining. Dominant process regimes
map on to the sedimentation zones but these
overlap to differing degrees dependent on the
extent of their spatial influences (broad boxes
show the main zone of operation and the arrows
show the maximum extent). The large overlap