The chemistry, mineralogy, and rates of transport of sediments in the ...

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This computation will seriously underestimate most sediment additions
to streams, since coarse silt, sand, and gravel will not be measured in
SSmax , and bedload transport is not considered . Results of the - calculation
(Eq . 6) can then be compared to known relationships between
sedimentation and the well-being of stream benthic organisms and fish
(Rosenberg and Snow, 1975) . Rosenberg and Snow (1975, and unpublished
data) found that experimentally increased sedimentation (of 25, 50, 25%
sand, silt, clay sediment, respectively) at rates of 0 .060-3 .9 kg m -2
of , stream bottom'hr 1 caused resident zoobenthic organisms in the stream
bed of Harris River to leave the site of sediment addition . If, by further
research, a level of sediment addition is found below which little or no
effect on zoobenthos, phytobenthos, and fish is observed, then that level
of sediment addition should be considered an upper limit on sediment supply
to streams from terrain disturbance .
We wish to emphasize that the regression lines in Fig . 1 are not based
on sufficiently long records, nor on sufficient details, to allow precise
use of the lines to establish "individual stream standards for sediment
concentrations" . For example, for a given Qi on Fig . 1, the variation of
SSi can be from ± 2x to ± 10 x the indicated value on the vertical axis,
depending on the river type 'and the number of Qj and SSj data points available
to us . Verification, stabilization, and an increase in confidence in
the regression lines in Fig . 1 will result from continued monitoring of
normal and natural extreme events . Greater confidence in such regression
lines could result from subdivision of the yearly hydrograph (Q • Vs time)
into a) the ascending limb of the peak flow hydrograph (May-early June in
the Mackenzie Valley), b)' the descending limb of the peak flow hydrograph,
and c) low flow periods (late summer, fall and winter) . For example, we
were able to improve the significance of the regression of SSi on Qj for
the Harris River from r - 0 .50 (a - >0 .001) for all data points, to r - 0 .72
(a - >0 .001) for only data points in the high Q . period of the year in
April, May and June (using data from Davies, 194) . We therefore stress
that our purpose is to present this method of data treatment and to illusstrate
general trends in the data . The absolute values of the slopes and
intercepts can be improved . b y more intensive sampling' over longer periods
of time .
We propose that the slopes (b) and intercepts (a) of regression lines
in Fig . 1, (see Eq . 1, Table 2a) relating the concentrations of suspended
sediment and discharge, are general indices of erosional characteristics
of each river and each watershed, respectively . A similar interpretation
was made briefly by MUller and Forstner (1968) for European and North
American rivers .
We propose that b is an index of the ability or energy of a river
to transport suspended sediment, and is a function of the seasonal and
annual distribution of river water mass, velocity, gradient, bed roughness,
and cross-sectional area . We further propose that a is an index of the
susceptibility of the terrestrial portion'of the watershed to erosion by
the river or stream, and is a function of watershed surficial geology,
relief, soil properties, vegetation, active layer thickness, seasonal