9500

• UCREFRP Catalog Number: 9500
• Author: Pitlick, J. and R. Cress
• Title: Downstream Changes in the Channel Geometry of a Large Gravel Bed River
• USFW Year: 2002
• USFW - Doc Type: American Geophysical Union
• Copyright Material: YES

34 - 6 PITLICK AND CRESS: DOWNSTREAM CHANGES IN CHANNEL GEOMETRY
Table 3. Parameter Estimates for Regression Relations Between
In Transfonmed Values of Grain Size, Width, Depth, Shear Stress,
Shields Stress, and Distance'
n a b SE,, r' F p
In surface D84 78 57.6 0.0015 0.00050 0.11 9.4 0.003
In surface D5), 78 33.4 0.0015 0.00049 0.11 9.1 0.003
In surface Die 78 18.4 0.0013 0.00041 0.12 10.8 0.002
In subsurface Ds, 27 45.9 0.0021 0.00075 0.24 8.0 0.009
In subsurface D5() 27 16.5 0.0023 0.00081 0.25 8.3 0.008
In subsurface D16 27 0.8 0.0034 0.00202 0.10 2.9 0.10
In width 132 167.0 -0.0011 0.00036 0.07 9.7 0.002
In depth 132 7.8 -0.0035 0.00026 0.58 180 <0.001
In shear stress 132 27.6 0.0014 0.00039 0.08 12.0 <0.001
In Shields stress 132 0.048 -0.00005 0.00026 <0.01 0.03 0.858
"Here a is the number of observations; a and b are parameters in the
relation In r = /n a + h.r. will ix measured in km; SE,, is the standard error of
the coefficient h: r' is the coerficient of detennination, F is the value of the
F distribution: andp is the significance probability.
Table 4 indicate that the trends in surface D50 are not
significantly different from zero (p > 0.05), except in the
segment between DeBeque Canyon and Westwater Canyon.
We would be surprised if this was not the case, given that
the segment is 100-km long, and includes a 40% increase in
discharge from the Gunnison River. The other segments fail
the test of significance because the standard error of the
regression SEb is of the same order as the coefficient b itself.
To determine if fining is indeed stronger within the DeBe-
que-Westwater segment, we then performed an analysis of
covariance (ANCOVA), using a binary predictor variable
for the separate segments (DeBeque-Westwater vs. the
remainder of the data). The results of the ANCOVA indicate
that there is a marginal difference in the slopes of the
separate regression relations for InD50 (p = 0.08), suggest-
ing that the rate of downstream fining within the DeBeque-
Westwater segment is not much different from the trend
defined by the remainder of the data. What is perhaps more
important to the analysis and the main hypothesis of this
study is the correlation between gain size and shear stress,
which we pursue later in the section on channel geometry.
fix] Trends in the percentiles of the subsurface sediment
(Figure 5) indicate that the bulk bed material of the
Colorado River also fines systematically downstream.
Regression analysis of these data indicates that the subsur-
face D,ua and Dso are modeled reasonably well by exponen-
tial relations that parallel each other (Table 3); the relation
for D16 is not as strong (p = 0.10), and the trend is slightly
steeper. Comparison of the fining coefficients b for surface
and subsurface D50 (Table 3) suggests that the bulk bed
material fines downstream at slightly higher rates than the
pavement. The difference reflects an increase in the pro-
portion of sand and granules in the bed, and implies that the
surface coarsens downstream relative to the subsurface.
However, a plot of the ratio of surface D50 to subsurface
D50 derived from paired samples at the same locations
(Figure 6) shows that this trend is not very strong (r2 =
0.22, p = 0.02). On average the surface D50 is about 1.5
times the subsurface D50-
4.3. Channel Geometry
[I9] The downstream trends in bank-full channel width
and depth, derived from individual cross section measure-
ments, are plotted in Figure 7. These data are further
subdivided according to reach type (alluvial or quasi-
alluvial), and fit with separate regression equations. To
assess the influence of reach type on overall trends, we
compared the regression estimates of the intercept a and
slope b of the separate relations using an analysis of
covariance (ANCOVA), with distance as a covariate and
reach type as a factor. The purpose of these tests was to
establish whether changes in channel geometry are driven
more by one reach type than the other, and to examine
potential interactions between reach type and distance.
[20] The results of this analysis are summarized in Table
5, which lists the regression estimates of a and b for each
relation, standard measures of the strength and significance
of the relation, and a summary of the ANCOVA results with
different levels of complexity. A test of the regression
equations for In bank-full width indicates that there is no
significant difference in the slopes of the separate relations
(p = 0.44); therefore reach type does not appear to affect
downstream trends in bank-full width. Removing the inter-
action term (distance x reach type) results in a significant
difference in adjusted means (p < 0.001), thus bank-full
widths are consistently higher in alluvial reaches than in
quasi-alluvial reaches. Tests of the regression equations for
In bank-full depth likewise indicate no significant difference
in the slopes of the separate relations (p = 0.53); thus
downstream trends in bank-full depth do not appear to be
affected by reach type. Removing the interaction term
results in a significant difference in adjusted means (p =
0.01) suggesting that bank-full depths are, on average,
lower in alluvial reaches than in quasi-alluvial reaches.
[21] Previous studies of downstream changes in channel
geometry have shown that, when discharge is used as the
Table 4. Parameter ',Estimates and Measures of Statistical
Significance of Within-Segment Relations Between Individual In
Transformed Variables and Distance'
n a b SE,, r2 F p
rkm 365- 315
surface D511 17 20.1 0.0029 0.0049 0.02 0.35 0.565
width 31 7.8 0.0075 0.0029 0.19 6.84 0.014
depth 31 14.7 -0.0051 0.0024 0.14 4.73 0.038
tau 31 15.9 0.0031 0.0021 0.07 2.13 0.155
tau*. 31 0.039 0.00075 0.0023 <0.01 0.11 0.743
rkm 300- 200
surface D50 36 14.69 0.0048 0.0016 0.20 8.69 0.006
width 57 107.03 0.0010 0.0016 0.01 0.39 0.536
depth 57 9.16 -0.0044 0.0013 0.18 11.79 0.001
tau 57 15.70 0.0034 0.0012 0.14 8.96 0.004
tau* 57 0.054 -0.00066 0.0012 <0.01 0.29 0.592
rkm 180- 140
surface D50 16 24.14 0.0027 0.0026 0.07 1.04 0.325
width 24 86.20 0.0029 0.0048 0.02 0.37 0.550
depth 24 17.07 -0.0082 0.0032 0.23 6.68 0.017
tau 24 17.66 0.0026 0.0037 0.02 0.48 0.497
tau* 24 0.045 -0.000067 0.0035 <0.01 <0.01 0.985
rkrrt 139- 105
surface D50 9 22.94 0.0062 0.0216 0.01 0.08 0.782
width 20 19.50 0.0164 0.0084 0.17 3.81 0.067
depth 20 12.86 -0.0074 0.0057 0.08 1.66 0.213
tau 20 0.20 0.0452 0.0104 0.51 18.86 0.0004
tau* 20 0.015 0.0106 0.0056 0.17 3.61 0.074
'The notation is the same as in Table 3