downstream variability of fluvial form, process, and character in a
TRANSCRIPT
Downstream Variability of Fluvial Form, Process, and Character in a Small
Deglaciated Watershed, Southern Ontario
By
James Benjamin Thayer
A thesis submitted in conformity with the requirements
for the degree of Master of Science
Graduate Department of Geography
The University of Toronto
© Copyright by James Benjamin Thayer, 2012
ii
Downstream Variability of Fluvial Form, Process, and Character in a Small
Deglaciated Watershed, Southern Ontario
James Benjamin Thayer
Master of Science, 2012
Department of Geography, The University of Toronto
Abstract
Many deglaciated watersheds possess complex longitudinal profiles and spatially
variable sediment sources derived from the last glaciation. Accordingly, downstream
patterns in fluvial forms and characteristics of the channel and floodplain may diverge
from conventional ‘graded’ watershed models where channel slope decreases
downstream. Within a small, deglaciated watershed, five distinct fluvial forms were
identified and it was found that the watershed is organized in a spatially variable, but
generally inverted arrangement with stable, low-energy forms dominating the upper
watershed and more dynamic, high-energy forms in the lower watershed. As a
consequence of this inverted and variable downstream succession, and the spatially
erratic organization of glacial sediment sources, downstream trends in channel and
floodplain characteristics are poorly defined, and in many cases, deviate from expected
trends. This is most true for sedimentological variables where multiple co-dominant
controls exist, while morphological and hydrological variables better conform to
expected downstream trends.
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Acknowledgements
This thesis wouldn’t have come to fruition if it weren’t for the support that I
received over the past two years from various people. I’d first like to thank my advisor,
Dr. Joe Desloges, for generously funding this project. His critiques and suggestions on
various drafts have improved upon the final version of this thesis, and our discussions,
where he challenged many of the ideas presented here, helped me gain a stronger grasp of
the various facets of fluvial geomorphology. I thank my committee members, Drs. Joe
Desloges, Jing Chen, and Carl Mitchell, for providing valuable comments on areas that I
neglected during my writing. Vicki MacDonald of Rouge Park and Lori Colussi and
Edlyn Wong, both of the Toronto and Region Conservation Authority, provided
assistance in gaining and permitting access to the various study sites.
I extend my deepest gratitude to my various field assistants who helped me collect
way too much (though never enough!!) data that I gleefully got to spend months sifting
through. I’d especially like to thank Joyce Arabian and Betty Opalinska who bore the
brunt of the fieldwork and had to contend with leaky chest waders that were many sizes
too large and all of my wonderful idiosyncrasies over the course of the summer. I’d like
to thank my brother, Thomas, a.k.a., rock-skipper extraordinaire, for coming up to
Toronto for a week to help me with fieldwork for the second time in three summers.
Quite the enjoyable experience as usual…except for the part where we were out in the
middle of a field with a 4-metre tall lightning rod with a thunderstorm quick on our heels,
and the 2 hour (at least!) long downpour where we had to spend it in the car, and then the
intermittent downpours when we were out on a gravel bar and just had to sit through it,
and then the ESP kept sticking. Oh, what joyous times indeed! Lastly, Jen Henshaw
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bravely crawled into the leaky chest waders and into barely-above-freezing water to
collect some more data in October. Thank you all.
I’d like to thank my officemates Roger Phillips and Jen Henshaw for giving me
people to bother from time-to-time. I’d especially like to thank Roger for giving me
helpful advice these past couple years and for our various fluvial and non-fluvial related
discussions. He enthusiastically helped me with my initial ArcGIS inquiries, trying to get
Arc onto my computer, and sending me a lot of data for this project.
Lastly, I’d like to thank my parents for financially supporting me this past year,
without which I wouldn’t have been able to complete my second year and you wouldn’t
be able to read this thesis.
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Table of Contents Abstract ............................................................................................................................. ii Acknowledgements .......................................................................................................... iii Table of Contents ............................................................................................................... v List of Figures ................................................................................................................. vii List of Tables ..................................................................................................................... x List of Appendices ........................................................................................................... xi Chapter One: Introduction .................................................................................. 1
1.1 Definition of the Problem .......................................................................... 1 1.2 Research Questions .................................................................................... 2
Chapter Two: Equilibrium and Downstream River Adjustment .................... 4
2.1 The Concept of Equilibrium in River Systems .......................................... 4 2.1.1 Scales of Equilibrium ..................................................................... 5
2.2 Adjustment of the Equilibrium Channel Form .......................................... 7 2.2.1 Predictive Methods of Channel Adjustment in Gravel-Bed Rivers 8 2.2.2 Controls on Channel Morphology: Direction and Magnitude ..... 10
2.2.2.1 Channel Cross-Sectional Adjustment .............................. 11 2.2.2.2 Controls on the Braiding Threshold ................................. 16 2.2.2.3 Controls on Channel Sinuosity ........................................ 19
2.3 Downstream Variation in Channel and Floodplain Character ................. 20 2.3.1 Downstream Variation in Channel Morphology .......................... 20 2.3.2 Downstream Variation in Bed Material ....................................... 22 2.3.3 Downstream Variation in Floodplain Character .......................... 23 2.3.4 The Case for Non-Alpine Deglaciated Watersheds ......................24
2.4 Research Objectives ................................................................................. 26 Chapter Three: Little Rouge River Watershed .................................................. 27
3.1 Introduction .............................................................................................. 27 3.2 Location ................................................................................................... 28 3.3 Land-use ................................................................................................... 28 3.4 Climate and Hydrology ............................................................................ 28 3.5 Physiography ............................................................................................ 37
3.5.1 Physiographic Regions ................................................................. 37 3.5.2 Watershed Stratigraphy ................................................................ 40
3.6 Study Sites ............................................................................................... 45 Chapter Four: Methods ....................................................................................... 51
4.1 Fieldwork ................................................................................................. 51 4.1.1 Surveying and Bed-Augering ...................................................... 51 4.1.2 Grain Size Analysis ...................................................................... 51 4.1.3 Floodplain and Channel Bank Sampling ..................................... 53
4.2 Lab Analysis of Floodplain Sediments .................................................... 54 4.3 Determination of Morphological Bank-full Discharge ............................ 54
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Chapter Five: Watershed-Scale Variability of Fluvial Form and Process .... 57
5.1 Introduction .............................................................................................. 57 5.2 Low Energy Mixed-Load Type ............................................................... 60 5.3 Low Energy Bed-Load Type ................................................................... 66 5.4 Mixed Energy Type ................................................................................. 69 5.5 Medium Energy Type .............................................................................. 74 5.6 High Energy Type .................................................................................... 81 5.7 Equilibrium Morphology Prediction ........................................................ 86
Chapter Six: Downstream Organization of Fluvial Form, Process, and Character .................................................................................... 94
6.1 Spatial Distribution of Channel-Floodplain Types .................................. 94 6.2 Downstream Organization of Watershed Zones ...................................... 95 6.3 Downstream Trends in Channel and Floodplain Character ................... 100
6.3.1 Channel Morphology ................................................................. 101 6.3.2 Channel Hydrology .................................................................... 102 6.3.3 Channel Bed Material Size ........................................................ 102 6.3.4 Overbank Alluvium Thickness .................................................. 105 6.3.5 Summary and Controls .............................................................. 107
Chapter Seven: Discussion and Conclusions .................................................... 111
7.1 Reappraisal of the ‘Graded’ River Model for Non-Alpine Deglaciated Watersheds ............................................................................................. 111
7.2 Summary of Findings ............................................................................. 112 7.3 Future Research Considerations ............................................................ 113
References ..................................................................................................................... 115 Appendices .................................................................................................................... 129 Curriculum Vitae ......................................................................................................... 204
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List of Figures Figure Page 2.1 Conceptual diagram illustrating channel equilibrium, disequilibrium, and
nonequilibrium as function of time ........................................................................ 5 2.2 Schematic representation of the stages of a geomorphic system’s response to a
disturbance ............................................................................................................. 6 2.3 Classification of gravel-bed channels based on bank erodibility and bed material
supply rate from upstream relative to the transport capacity of the channel ....... 18 2.4 Schematic diagram of the typical ‘graded’ fluvial system and downstream trends
in major system characteristics partitioned by zones ........................................... 21 2.5 Theoretical qualitative characteristics of the production, transport, and deposition
zones .................................................................................................................... 25 3.1 Variation in channel slope along the Little Rouge River ..................................... 27 3.2 Location of the Little Rouge watershed within southern Ontario ........................ 29 3.3 Land-use classification for the Rouge River watershed ...................................... 30 3.4 Mean monthly discharge values for the gauging stations on the Little Rouge River
............................................................................................................................... 31 3.5 Locations of active hydrometric gauging stations operated by the Water Survey of
Canada and the Environment Canada weather station within the watershed ...... 32 3.6 Flood frequency curves for the Locust Hill gauging station ................................ 34 3.7 A comparison of annual patterns in mean discharge between the Little Rouge
watershed and two neighbouring urbanized basins over 40 years ....................... 35 3.8 Decadal variation in average annual mean discharge in the Little Rouge watershed
............................................................................................................................... 36 3.9 Seasonal proportions in annual discharge between the Little Rouge, Rouge, and
Highland watersheds for two time periods .......................................................... 36 3.10 Physiographic regions of the Rouge River watershed ......................................... 38
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3.11 Surficial geology deposits within the Rouge River watershed ............................ 39 3.12 Generalized stratigraphic diagram for the Rouge River watershed ..................... 41 3.13 Whitby Formation shale exposed in an outcrop of the Little Rouge River
approximately 1 km upstream of the Rouge River confluence ............................ 42 3.14 Sunnybrook Drift exposed in a terrace downstream of Meadowvale Road ........ 42 3.15 Halton Till exposed in a low-lying terrace downstream of 14th Avenue ............. 43 3.16 Geologic cross-section through the Rouge River watershed ............................... 45 3.17 Location of study sites within the watershed ....................................................... 46 3.18 Location of study sites in the context of the longitudinal profile ........................ 47 3.19a Imagery of sites 1-3 ............................................................................................. 49 3.19b Imagery of sites 4-6 ............................................................................................. 50 5.1 Field image and idealized schematic cross-section of the low energy, mixed-load
channel-floodplain type ....................................................................................... 61 5.2 Plan-form discrimination of channel-floodplain types based off of potential
specific stream power and median bed material size ........................................... 62 5.3 Characteristic floodplain stratigraphy of the low energy, mixed-load type ......... 64 5.4 Field image and idealized schematic cross-section of the low energy, bed-load
channel-floodplain type ....................................................................................... 66 5.5 Characteristic floodplain stratigraphy of the low energy, bed-load type ............. 68 5.6 Field image and idealized schematic cross-section of the mixed energy channel-
floodplain type ..................................................................................................... 70 5.7 Characteristic floodplain stratigraphy of the mixed energy type ......................... 73 5.8 Development of an avulsion channel around an active debris dam ..................... 74 5.9 Field image and idealized schematic cross-section of the medium energy channel-
floodplain type (Site 4d) ...................................................................................... 76
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5.10 Field image and idealized schematic cross-section of the medium energy channel-floodplain type (Site 6) ........................................................................................ 77
5.11 Characteristic floodplain stratigraphy of the medium energy type (Site 4d) ....... 78 5.12 Characteristic floodplain stratigraphy of the medium energy type (Site 6) ......... 79 5.13 Extended floodplain stratigraphy of Site 6 .......................................................... 82 5.14 Field image and idealized schematic cross-section of the high energy channel-
floodplain type ..................................................................................................... 83 5.15 Characteristic floodplain stratigraphy of the high energy type ............................ 85 5.16 Comparison of field-derived channel widths and depths against predicted regime
dimensions ........................................................................................................... 89 5.17 Relationship between relative bank strength and dimensionless shear stress ...... 91 6.1 Downstream variation in specific stream power in relation to glacial landforms 96 6.2 Dominant glacial and post-glacial controls on the longitudinal profile ............... 97 6.3 Spatial distribution of inferred watershed zones for each study site ................... 99 6.4 Downstream variation in bank-full width, depth, and cross-sectional area ....... 101 6.5 Downstream variation in bank-full discharge .................................................... 103 6.6 Downstream variation in bank-full velocity ...................................................... 103 6.7 Downstream variation in grain size sorting coefficient and various size fractions .. ..............................................................................................................................104 6.8 Downstream variation in floodplain overbank alluvium thickness ................... 107
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List of Tables Table Page 2.1 A compilation of exponents predicting channel dimensions from various studies
on gravel-bed rivers ............................................................................................. 13 2.2 A compilation of exponents from various studies predicting how the threshold
channel slope for braiding responds to various controls ...................................... 17 2.3 Classification of genetic floodplain types based on specific stream power ......... 23 3.1 Description of the active hydrometric gauging stations within the Little Rouge
watershed ............................................................................................................. 31 3.2 Return periods for the mean annual flood discharges at the Locust Hill gauging
station ................................................................................................................... 33 3.3 Study site characterization prior to fieldwork ...................................................... 48 5.1 Bank-full channel and floodplain characteristics of the study sites ..................... 58 5.2 Description of the channel-floodplain types identified within the Little Rouge
River watershed ................................................................................................... 59 5.3 Facies classification of the study sites ................................................................. 60 5.4 Radiocarbon dates from the study sites ............................................................... 65 5.5 Relative bank strength values and associated vegetation conditions of the study
sites ...................................................................................................................... 90 6.1 Observed downstream trends in various channel and floodplain characteristics
compared against their expected trends ............................................................. 108
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List of Appendices
Appendix Page A Channel Morphology and Sedimentology ............................................. 129 B Floodplain Sedimentology ..................................................................... 135 C Bank-full Discharge Formulae Analysis ................................................ 139 D Flood Frequency Analysis ..................................................................... 143 E Downstream Trends in Channel and Floodplain Characteristics ........... 156 F Glacial Control on Downstream Trends ................................................ 162 G Statistical Tests ...................................................................................... 200
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Chapter One: Introduction
1.1 Definition of the Problem
It is well understood that rivers adjust their equilibrium morphology to a given
discharge, slope, sediment load, and sediment size (Leopold and Bull, 1979), and the
downstream variation of these control variables dictates the downstream progression of
channel morphology, plan-form, and floodplain characteristics. In conventional alluvial
systems, discharge is expected to increase downstream while channel slope and bed
material size decline (Knighton, 1987). How sediment supply changes downstream is less
certain. These trends often produce a predictable downstream succession of fluvial forms
and characteristics related to high-energy (ie. specific stream power) conditions in the
headwaters and low-energy conditions at the river outlet.
In watersheds composed of mixed alluvial and non-alluvial boundaries, like
southern Ontario, however, such downstream trends do not necessarily apply, as channel
slope, sediment supply, and bed material size are highly variable. The pervasive effects of
the last glaciation in Canada and southern Ontario are obvious. Longitudinal profiles in
these contexts are often composed of both convexities and concavities as a result of
topographic variations imposed by remnant glacial landforms, bedrock outcroppings, and
fluctuations in base-level. Campo and Desloges (1994) studied the sediment budget of a
medium sized southern Ontario watershed and found that up to 68% of the incoming
sediment is derived from fine-grained glacial sources that are transported through the
system as wash load, while gravel inputs, which dominate much of the bed material in
southern Ontario streams, are comparatively small. Furthermore, contrary to typical
models for alluvial rivers (ie. Jiongxin and Yunxia, 2005, their Figure 1), it was found
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that due to progressive downstream incision into glacial deposits and an increase in
channel-hillslope coupling, specific sediment yield tends to increase with drainage area
(Campo and Desloges, 1994). Finally, bed material does not conform to the expected
downstream fining described in the literature (Knighton, 1987), but instead, coarse gravel
and cobble deposits derived from nearby glacial sources typically dominate the bed
material along the entire channel length with variable amounts of glacial clay exposed in
the channel perimeter. Such morphology has typically been referred to as semi-alluvial
for its superficial resemblance to alluvial channels without being fully alluvial in nature
(Foster, 1998).
Based on the observed departure in controlling variables from traditional models,
it is not clear whether southern Ontario streams exhibit similar downstream trends in
fluvial form, and channel and floodplain characteristics, as seen in their conventional
counterparts. Nor is it clear how glacial inheritance influences downstream channel
adjustment. Moreover, Ferguson (1981) suggests that many semi-alluvial channels may
be in a state of persistent passive disequilibrium due to the imbalance between sediment
supply, sediment calibre, and transport capacity, such that these streams are incapable of
modifying their channel morphology and slope to the contemporary hydrologic and
sediment regimes. However, such a hypothesis has yet to be fully tested.
1.2 Research Questions
The research presented herein aims to address three primary questions:
1. What are the downstream trends in fluvial form, processes, and characteristics in
watersheds that have been conditioned by past glaciation?
2. To what extent does glacial inheritance influence these trends?
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3. To what extent are these rivers in equilibrium with respect to the prevailing
hydrological and sediment regimes?
4
Chapter Two: Equilibrium and Downstream River Adjustment 2.1 The Concept of Equilibrium in River Systems
While the concept of channel equilibrium was studied prior to the twentieth
century, significant focus on the topic was not undertaken until the mid-twentieth century
with the influential papers of Mackin (1948) and Langbein and Leopold (1964).
However, despite this and subsequent research, there remains discrepancies on what
equilibrium is in the geomorphic context as different workers adopt different definitions
(Thorn and Welford, 1994). Generally though, the consensus is that river channels are
adjusted to a ‘dynamic equilibrium’ or ‘quasi-equilibrium’ state whereby the channel
characteristics fluctuate around a static or dynamic mean value (Langbein and Leopold,
1964; Renwick, 1992; Thorn and Welford, 1994).
Renwick (1992) provides a very useful review of equilibrium, disequilibrium, and
nonequilibrium fluvial landforms in geomorphology with particular emphasis on river
systems. He defines disequilibrium as a state trending towards equilibrium but has not
had sufficient enough time to reach it, while a nonequilibrium state is characterized by a
state not migrating towards any identifiable mean form over any length of time (Fig. 2.1).
Ferguson (1981) introduced a subset of disequilibrium, which he termed persistent
passive disequilibrium. Here, the channel appears to be stable under the present hydro-
climate but would not have formed under it. This is to imply that the present channel has
inherited many of its characteristics (ie. slope and grain size distribution) from a previous
channel formed under different hydro-climatic conditions, but is unable to adjust these
characteristics. In essence, a channel under these conditions may be considered ‘frozen’.
However, persistent passive disequilibrium may be a misnomer, as the channel may not
5
be trending towards an equilibrium state since it is unable to adjust itself fully under
present conditions. This idea put forth by Ferguson (1981) may be more akin to a
threshold-dominated nonequilibrium state (Fig. 2.1c), whereby the channel adjusts during
high magnitude but low frequency discharge events.
Figure 2.1 - Conceptual diagram illustrating equilibrium (a), disequilibrium (b), and various states of nonequilibrium (c-e) as functions of time (after Renwick, 1992).
2.1.1 Scales of Equilibrium
In his review, Renwick (1992) emphasizes the importance of both the spatial and
temporal scales to equilibrium landforms. Implicit in the definition of dynamic
equilibrium is the time-scale at which the ‘mean condition’ is defined. Hickin (1983)
supplies three time-scales applicable to geomorphic processes: the geological time-scale
defined as a time period greater than 106 years, the geomorphic time-scale, which falls
between 102 to 106 years, and the engineering time-scale, which is defined as anything
less than 102 years. Whether or not a geomorphic system reaches equilibrium is
6
dependent on the time-scale of the response and the time passed since the initial
disturbance to the system. The response time is the combination of the reaction time (the
period of time where the system absorbs the disturbance) and the relaxation time (where
the system adjusts to the disturbance). If the response time is greater than the time passed
since the initial disturbance, then equilibrium may not be fully attained and the landform
can be considered to be in a state of disequilibrium (Fig. 2.2) (Renwick, 1992). This
relationship holds particular significance in light of global environmental change that has
occurred during and since the last glaciation to which many river systems may still be
adjusting.
Figure 2.2 - Schematic representation of the stages of a geomorphic system's response to a disturbance. The reaction time occurs where the system absorbs the disturbance and changes are imperceptible. The relaxation time is defined by visible changes to the system as it adapts to the disturbance and reaches a new equilibrium. Equilibrium and disequilibrium can be defined in the context of the diagram where disequilibrium occurs before the relaxation period is complete (after Charlton, 2008).
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Moreover, the time-scale of relaxation is dependent on the size of the landform,
such that larger landforms may have longer relaxation periods then smaller landforms.
This is illustrated through the study by Church et al. (1989), who show that for
watersheds in British Columbia between 10 km2 and 30 000 km2, specific sediment yield
tends to increase with drainage area – a trend does not follow conventional alluvial
models – and has been attributed to the downstream remobilization of glacial valley fill
sediments. It has been concluded that the sediment yield within these basins is still out of
phase with the present-day climate and that the time-scale necessary to remove the glacial
sediments from the river system is many tens of thousands of years (Church and
Slaymaker, 1989). This pattern in specific sediment yield is not restricted to alpine
environments either, as Ashmore (1993), Campo and Desloges (1994), and Church et al.
(1999) have all described similar increasing or stable trends in non-alpine regions of
Canada. Conversely, reach-scale morphology, in some cases, may have adjusted to
present-day conditions as Dury et al. (1972) show that the bed-morphology of the River
Severn is scaled to the current channel discharge while Phillips and Robert (2007)
demonstrate that wave-lengths on a small meandering stream in southern Ontario are
strongly controlled by the present-day discharge regime.
2.2 Adjustment of the Equilibrium Channel Form
The Lane Balance (Charlton, 2008) states that river channels adjust themselves to
a balance between discharge (Q), median grain size of the bed material (D50), channel
slope (SC), and sediment supply (Qs) such that
C 50 s.Q·S D ·Q 2.1
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In theory, should one of these variables change then the others would need to
adjust accordingly to maintain balance. Mackin (1948) introduced the idea that an
equilibrium channel is one that is ‘graded’, whereby the slope is adjusted in order to
convey the imposed sediment load with the minimum velocity for a given discharge. Any
changes in the above-mentioned variables will elicit a change in channel slope. While
Mackin’s (1948) model of channel adjustment is attractive, it has since been shown to be
only partially correct as Leopold and Bull (1979) re-state a graded channel as one where
the channel dimensions (width and depth), slope, grain size, bed roughness, and plan-
form mutually adjust to each other. In responding to changes in the driving variables,
river channels have at least eight variables to which channel morphology can adjust
(Hickin, 1983), which underlines the complexity in understanding and predicting channel
response, as one must account for all of these potential directions of change – a task
which has proven quite difficult.
2.2.1 Predictive Methods of Channel Adjustment in Gravel-Bed Rivers
While Mackin’s (1948) graded river concept is purely qualitative in nature,
subsequent researchers have aimed to quantify channel adjustment through empirical
relationships based on field and flume data, and theoretical models based on physical
relations. Empirical relationships were pioneered by Leopold and Maddock (1953) in
their classical study on hydraulic geometry. Channel dimensions were individually
plotted against bank-full discharge and a power trend-line was fitted to the data.
Hydraulic geometry relationships have since evolved to incorporate other variables such
as grain size and bank characteristics. A primary criticism aimed at hydraulic geometry is
that it is only a statistical relation describing what is there and does not have much
9
explanatory power in regards to the underlying fluvial processes (Hickin, 1983).
However, Parker et al. (2007) show that the exponents and coefficients of hydraulic
geometry relations can be physically explained. Empirical relationships have also been
useful in the establishment of plan-form thresholds by plotting channels of different
patterns on a plot based on two governing characteristics (typically discharge or
dimensionless discharge and channel slope) and manually fitting a line that separates the
plan-forms. Again, while this method gives inferential evidence on why different plan-
forms exist, little physical rationale can be extended. Moreover, empirical relationships
suffer from the fact that they can only be reliably used within the region that they were
developed in and for the range of data that they were derived from.
Theoretical, ‘rational’, relationships, on the other hand, use physical relations to
establish equilibrium morphology. These relationships come in two forms; the first of
which determines the channel width by the simultaneous solution of the flow continuity
relation, a flow resistance relation, and dimensionless shear stress (Griffiths, 1981).
These relations are designed to be used on threshold channels, which are defined as
gravel-bed channels that marginally exceed the threshold for sediment transport at bank-
full flow and which transport minor amounts of bed-load (Ferguson, 1986).
The second type of rational relation uses physical relations combined with an
extremal hypothesis constraint, which purport to explain the underlying behaviour of
river channels, to model the morphology. Examples of these hypotheses include
Minimum Stream Power, Minimum Unit Stream Power, Maximum Friction Factor, and
Maximum Sediment Transport Capacity (Davies and Sutherland, 1983; Bettess and
White, 1987). Despite their differing names, these hypotheses tend to suggest that rivers
10
minimize their channel slopes to convey the imposed sediment load. Extremal
hypotheses, however, have been tepidly received, as they are not regarded as physically
sound. Griffiths (1984) notes that extremal hypotheses predict a constant Shield’s value,
which is a trend observed in neither natural channels nor flume studies. Early models
neglected to include some measure of bank resistance, which often resulted in inaccurate
channel dimension predictions (Ferguson, 1986). Eaton and Millar (2004) addressed this
by applying a bank stability constraint to a model employing the Maximum Transport
Efficiency extremal hypothesis and found that when this constraint was applied, the
agreement with field derived data was considerably higher than that predicted by the
unconstrained model. The success experienced by Eaton and Millar (2004) has been
echoed in other studies where their model was employed (Eaton et al., 2004; Eaton and
Church, 2007). However, despite being shown as a promising avenue of research going
forward, extremal hypotheses continue to be relatively inaccessible due to their
computational demands.
2.2.2 Controls on Channel Morphology: Direction and Magnitude
As mentioned, there are four dominant controls on channel morphology
represented in the Lane balance with bank strength being subsequently added (Millar,
2005). These variables, however, disproportionately control channel morphology in both
the negative and positive directions. Thus, a wide variety of morphologies may exist
depending on the combination of the control variables. Generally speaking though, the
morphology of the channel is dictated by the relationship between the erosive force of the
flow and the resisting forces of the bed and channel banks.
11
Comprehensive reviews on early accounts of the controls on channel morphology
and plan-form have been given elsewhere (Carson, 1984b; Ferguson, 1987; Knighton,
1987). Thus, the intention of the following discussion is to provide a general review of
the present knowledge on the direction and relative magnitude of the dominant
morphologic controls with reference to various predictive relations for predominantly
gravel-bed rivers. Furthermore, while several types of channel patterns have been
identified, the transition between meandering and braided channels will be emphasized
here, as they represent the two most common plan-forms.
2.2.2.1 Channel Cross-Sectional Adjustment
The earliest hydraulic geometry relations related changes in channel dimensions
to the downstream change in discharge. Leopold and Maddock (1953) originally
proposed that for a specific set of alluvial rivers, downstream adjustments in channel
form take on the relations of
0.50w = aQ 2.2
0.40d = cQ 2.3
for the width (m), and depth (m), respectively where Q is a representative discharge
value, typically bank-full, in m3s-1, and a and c are constants. Their analysis suggests that
much of the adjustment to changes in discharge is taken up almost evenly by width and
depth. Subsequent research has revealed a high degree of consistency of the exponents in
Equations 2.2 and 2.3 from other physiographic regions (Table 2.1; Knighton, 1987).
However, Park (1977) has demonstrated that despite the tendency to adopt these
exponents, there exists some scatter about these values. The width exponent was found to
vary between 0.03 and 0.89, and depth between 0.09 and 0.70. These discrepancies are
12
thought to be a result of climatic differences between the study regions in addition to, and
perhaps secondarily to, other local controls on channel morphology.
Grain size has since been acknowledged to exert control over the channel
morphology, though the direction of change and relative magnitude are not fully
resolved. Parker (1979), Andrews (1984), and Parker et al. (2007), for example,
developed dimensionless hydraulic geometry relations, which, when dimensionalized,
show that channel width inversely varies with the D50 between the powers of -0.17 and
-0.25 while depth is less sensitive and directly varies between 0 and 0.08 (Table 2.1).
These values are confirmed by Millar (2005) when sediment concentration is used. While
Parker (1979) and Griffiths (1981) found much larger exponents in their relations, the
same inverse relation with grain size is observed. The implication here is that as grain
size becomes larger for gravel-bed rivers, channels become narrower and slightly deeper,
which is in direct contrast to what Davidson and Hey (2011) found in their study where,
after removing sediment load from their relations, the width and depth vary with D50 to
the powers of 0.17 and –0.16 respectively, such that the channel becomes wider and
shallower. The inclusion of sediment load in their relations reduces the D50 exponents to
–0.05 for width and –0.20 for depth. Hey and Thorne (1986) observed similar values for
depth. While the observations of Davidson and Hey (2011) are typical of what is
observed for gravel-bed rivers, the inverse trend reported by Parker (1979), Griffiths
(1981), Andrews (1984), Millar (2005), and Parker et al., (2007) does have a physical
rationale. Since the ability to transport sediment of a given size depends on the channel
slope and depth of the channel, an increase in grain size necessitates an increase in one of
these two variables. However, for a fixed slope and discharge, the channel can only
Regime Equation Variables Method Study Dimension Qbf D50 Qs SC Bank Strength
Empirical Leopold & Maddock (1953) Width Depth
0.50 0.40
- -
- -
- -
- -
Ferguson (1971)† Width 0.58* - - - -0.66 Parker (1979)‡ Width 0.50 -0.25 - - - Andrews (1984)‡ Width
Depth
0.48 0.48 0.38 0.37
-0.20 -0.20 0.06 0.08
- - - -
- - - -
2.54 (Thin Veg) 2.00 (Thick Veg) 0.288 (Thin Veg) 0.29 (Thick Veg)
Hey & Thorne (1986) Width
Depth
0.52
0.39
-
-0.15
-0.01
-0.02
- -
3.98 (Type I) 3.08 (Type II) 2.52 (Type III) 2.17 (Type IV) 0.16 (Type I)
0.19 (Types II/III)0.20 (Type IV)
Parker et al. (2007)‡ Width Depth
0.47 0.40
-0.17 -0.00
- -
- -
- -
Davidson & Hey (2011) Width
Depth
0.52
0.38
-0.05
-0.20
-0.05
-0.01
-0.26***
0.08***
1.48 (Type I) 1.13 (Type II) 0.82 (Type III) 0.53 (Type IV) 0.27 (Type I) 0.28 (Type II) 0.32 (Type III) 0.39 (Type IV)
Semi-Theoretical Parker (1979) Depth 0.42 -0.04 - - - Theoretical Parker (1979) Width 1.00 -1.50 - 1.22 -
Griffiths (1981) Width 1.00 -1.50 - 1.26 - Millar (2005)‡ Width
Depth Width Depth
0.50 0.37 0.70 0.16
-0.25 0.08 -0.75 0.60
1.12** -1.16**
- -
- -
0.60 -0.62
-1.66 1.22 -1.10 0.64
14
Table 2.1 (previous page) - A compilation of exponents for predicting channel dimensions from various studies on gravel-bed rivers where Qbf is the bank-full discharge, D50 is the median bed material size, Qs is the sediment discharge, and SC is the channel slope. † - data from sand-bed rivers; ‡ - data from dimensionless discharge analysis; * - discharge as the mean annual flood; ** - exponents presented as negative in the original paper for dimensionless sediment concentration defined as the –log(sediment concentration); *** - valley slope. Values italicized represent coefficients instead of exponents.
change its dimensions and thus, the channel must narrow in order to accommodate the
requisite increase in depth (Chew and Ashmore, 2001). In terms of magnitude though,
grain size seems relatively ineffective at forcing much channel change, especially in
regard to channel depth, and is over-shadowed by the control of discharge on channel
morphology. Moreover, the discrepancy between Hey and Thorne (1986), Davidson and
Hey (2011), and the other studies in Table 2.1 perhaps alludes to other, stronger controls
on channel morphology.
Bed-sediment load is not often included in regime relations due to its difficulty in
accurate quantification in both space and time. As a substitute, channel slope is often
employed, as it has been shown to scale with bed-sediment load (Schumm and Khan,
1972; Eaton and Church, 2004). However, slope has only been included in theoretical
relations and just recently in empirical relations. In terms of bed-sediment load, there
exists a marked disparity in its importance to the channel dimensions. Both Hey and
Thorne (1986) and Davidson and Hey (2011) found that sediment load has no effect on
width or depth, a fact attributed to co-linearity with discharge. Millar (2005), however,
shows that sediment load has a profound morphological impact, where an increasingly
wide and shallow channel exists with an increasing sediment load. If we believe that
channel slope is an apt surrogate for sediment load, then the regime relations of Parker
(1979) and Griffiths (1981) add further credence to sediment load’s positive effect on
channel width. Moreover, it is suggested that the positive relationship between channel
slope and width is due to the greater erosive power of the channel (Chew and Ashmore,
15
2001). The regime relations of Davidson and Hey (2011), on the other hand, suggest that
as valley slope increases, depth is unaffected and channels become narrower, which may
be attributed to higher flow velocities that necessitate a decrease in width, in light of
constant depth, to maintain continuity.
It is also important to note the morphological implications on the relative amount
of suspended-load to bed-load. Schumm and Khan (1972) found that channel width
decreased and depth increased in response to a concomitant increase in suspended
sediment transport and reduction in bed-load sediment transport as a proportion of the
total sediment load.
Finally, bank cohesion, which consists of the combined effects of bank vegetation
density and the silt/clay percentage, has been shown to exert varying degrees of control
over channel morphology. In general though, increases in bank strength tend to result in
narrower and deeper channels as shown in Table 2.1 due to the cohesive nature of the
sediment buffered by the roots of trees, which resist the erosive forces of the flow. Millar
(2005) has demonstrated in his theoretical relations that this variable may possess the
greatest amount of control over the channel dimensions. However, since Andrews (1984),
Hey and Thorne (1986), and Davidson and Hey (2011) used coefficients in their analyses,
the relative importance of bank strength cannot be assessed outside of Millar (2005) and
Ferguson’s (1971) studies.
The foregoing review suggests that the two strongest controls on channel cross-
sectional adjustment are the sediment supply and bank strength. However, these findings
are not universal, as Hession et al. (2003) and Allmendinger et al. (2005) have observed
increasing width with an increase in forest cover, opposite of what is suggested here.
16
Moreover, inaccurate representation of the relative magnitude and direction each variable
has on the channel dimensions could occur if important variables were neglected in
empirical formulae or if multi-collinearity exists. This effect is illustrated in the relations
of Millar (2005) where the exponents radically adjust when channel slope is substituted
for sediment supply (Table 2.1).
2.2.2.2 Controls on the Braiding Threshold
Discrimination between meandering and braided plan-forms has historically been
accomplished through the use of a slope threshold. This idea is predicated on the idea that
once a meandering channel crosses a critical slope, it will begin to braid. To this end,
research has been focused on determining what variables influence the critical slope
(Table 2.2).
Originally, discharge was thought to be the dominant controlling variable such
that an increase in discharge decreases the critical channel slope for braiding (Leopold
and Wolman, 1957). Although a range of values has been achieved, channel slope
typically increases to the –0.25 or –0.50 power of discharge. However, median grain size
of the channel bed has been shown to possess 2.5 times the power of discharge over the
critical slope in the opposite direction suggesting that as the channel bed becomes coarser
for a given discharge, the slope, and thus energy necessary for sediment transport, must
increase as well. Bank strength is the final variable included in braiding thresholds and
appears to exert the most control over the threshold being 2 times more impactful than
grain size and almost 5 times more so than discharge (Table 2.2).
Not explicitly stated in Table 2.2 but nevertheless paramount to the initiation of
braiding is the sediment supply of bed-calibre sediment to the river channel. This is
Braiding Threshold Variables Method Study Channel
Slope Qbf D50 Bank Strength
Empirical Leopold & Wolman (1957) -0.44 - - Kleinhans & van den Berg (2011) -0.50 0.42 -
Semi-Theoretical Henderson (1963) -0.46 1.15 - Carson (1984b) -0.33 1.00 - Ferguson (1987) -0.21 0.52 - Ferguson (1987)† -0.24* - 1.00
Theoretical Millar (2000) -0.25 0.61 1.75 Millar (2005)‡ -0.25 0.63 1.00 Eaton et al. (2010)‡
SC
-0.43 1.08 1.41
Table 2.2 - A compilation of exponents from various studies predicting how the threshold channel slope for braiding responds to various controls where Qbf is the bank-full discharge and D50 is the median bed material size. † - data from sand-bed rivers; ‡ - data from dimensionless discharge analysis; * - discharge as the mean annual flood.
18
implicit in the strong control exhibited over the threshold slope by bank strength. Carson
(1984a) provides a qualitative diagram relating the importance of bank stability and
sediment supply from upstream to channel plan-form in gravel-bed rivers (Fig. 2.3).
Braided rivers occur where highly erodible banks deliver bed-calibre sediment to the
channel whereas meandering rivers exist due to low bank erodibility and sediment
supply. Furthermore, the link between sediment supply and braiding is emphasized in the
study by Smith and Smith (1984) where braiding was induced after a 400% increase in
bed-load sediment along the William River.
Figure 2.3 - Classification of gravel-bed channels based on bank erodibility and bed material supply rate from upstream relative to the transport capacity of the channel (after Carson, 1984a).
19
2.2.2.3 Controls on Channel Sinuosity
Much like the preceding discussion on channel dimensions and the braiding
threshold, the controls on channel sinuosity are seemingly diverse. An oft-cited control is
that of Schumm’s (1963) account that sinuosity is positively related to the weighted
percent silt/clay in the channel perimeter. However, this conclusion is marred by the fact
that his weighting is based on the width-depth ratio such that the coefficient of
determination between sinuosity and the width-depth ratio is 0.79 while the correlation
with the weighted silt/clay percentage is 0.83. Clearly, the addition of the silt/clay content
only marginally improves the correlation. Nevertheless, Schumm (1963) inferred that
higher sinuosity is a consequence of channels transporting a greater proportion of
suspended/wash load sediment versus bed-load sediment. This inference has been
reinforced by the flume studies of Schumm and Khan (1972) where, when kaolinite was
introduced into the sediment load with a concomitant decrease in bed-load supply,
cohesive sediment deposition began to stabilize submerged bars and the channel sinuosity
consequently increased. Furthermore, the width-depth ratio of the channel decreased,
which accounts for the strong correlation between sinuosity and the width-depth ratio
found by Schumm (1963) earlier. Eaton and Church (2004; 2009) parallel Schumm and
Khan (1972) in showing that for a fixed valley slope and discharge, sinuosity of the
thalweg can be increased by decreasing the bed-load supply, however, bank-cohesion
may retard this.
Lastly, valley slope has often been thought to be a dominant control on sinuosity
(Schumm, 1993). The rationale here is that as valley slope increases, the channel has
more potential energy for erosion, and in order to reduce this energy, the channel erodes
20
the outer banks of meander bends, thereby decreasing the channel slope and increasing
sinuosity. This idea was, in part, borne out of flume studies where the thalweg sinuosity
increases with increasing valley gradient before the channel begins to braid at a critical
slope (Schumm and Khan, 1972). However, empirical analysis demonstrates no
correlation between sinuosity and valley slope (Kleinhans and van den Berg, 2011) and
the most convincing explanation for sinuosity remains the proportion of suspended/wash
load to bed-load sediment.
2.3 Downstream Variation in Channel and Floodplain Character
The downstream variation of channel and floodplain characteristics is dictated by
the downstream variation in grain size, sediment supply, valley slope, and discharge as
well as bank vegetation. In conventional ‘graded’ fluvial systems, the watershed can be
divided into three contiguous zones related to the production, downstream movement,
and deposition of sediment (Fig. 2.4). These zones are very much a qualitative abstraction
of watersheds with no quantitative definition or distinct boundaries. However, each zone
is typically characterized by specific channel and floodplain morphologies reflective of
the control variables within the zone.
2.3.1 Downstream Variation in Channel Morphology
The production zone is often characterized by steep valley slopes and high
sediment supply from extensive hillslope-channel coupling (Fig. 2.4). Where sediment
supply is particularly high, such as in recently deglaciated regions, braided patterns can
typically develop, while in non-glaciated mountainous and piedmont regions, step-pool
and cascade morphologies typically dominate with debris and log jams being of major
geomorphic significance (Montgomery and Buffington, 1997). Local sections of bedrock
21
Figure 2.4 - Schematic diagram of the typical ‘graded’ fluvial system and downstream trends in major system characteristics partitioned by zones. Erosion typically happens in production (Zone 1) and sediment is transferred down-valley (Zone 2) to the depositional zone (Zone 3) (after Charlton, 2008).
may outcrop in the riverbed where channels are supply limited. With an increase in
downstream distance, the degree of hillslope-channel coupling diminishes and with it a
decrease in sediment supply. As a consequence of this, the dominant supply of sediment
is from upstream and bank erosion. Channels in the transportation and depositional zones
22
are characterized by meandering riffle-pool channels. The channel bed in these zones is
entirely alluvial in nature as sediment supply typically is equal to or exceeds transport
capacity. The width-depth ratio of the channel has historically been thought to increase
marginally downstream but due to the complicating factors of other controls, this may not
entirely be the case as is explored further in the next section.
2.3.2 Downstream Variation in Bed Material
The downstream variation in bed material is typically complex due to tributary
inputs (Knighton, 1980), but the general trend is that bed material fines downstream (Fig.
2.4) (Sambrook Smith and Ferguson, 1995). Downstream fining has been shown to be a
result of dominantly size-selective transport, while abrasion is of less importance
(Brierley and Hickin, 1985; Ferguson et al., 1996). Since valley slope often decreases
downstream faster than channel depth can increase, shear stresses tend to decrease
downstream. As a result, the competence of the channel wanes downstream and only
smaller particles can be transported. This mechanism accounts for the observed
downstream increase in sediment sorting of some rivers (Knighton, 1980; Brierley and
Hickin, 1985). Once the median grain size reaches about 10 mm, there exists an abrupt
gravel-sand transition, which reflects a threshold decrease in valley slope where the fall
velocity of the suspended sediment becomes greater than the shear velocity of the flow
(Sambrook Smith and Ferguson, 1995). As a result, much of the suspended load falls out
onto the bed creating a sand-bed channel. The downstream change in bed material size,
particularly at the gravel-sand transition, has implications for channel morphology.
Reflecting on Schumm and Khan’s (1972) experiment with kaolinite, increases in the
percent load transported in suspension results in a sinuous, narrow, and deep channel.
23
Thus, channels in the production zone are expected to be relatively wide, straight, and
shallow due to their predominance of bed-load transport. Conversely, channels occupying
the depositional zone tend to have a greater suspended load component and, as a result,
should be more sinuous, narrower, and deeper.
2.3.3 Downstream Variation in Floodplain Character
Reinfelds et al. (2004) show that the peak of specific stream power corresponds to
the peak in channel gradient. In conventional fluvial systems, this often occurs in the
headwaters with specific stream power decreasing downstream. As such, it is possible to
classify landforms based on specific stream power and arrange them in their expected
downstream trend. Nanson and Croke (1992) devised a classification scheme of
floodplain types based on specific stream power and bed-sediment type that permits this
(Table 2.3).
Order
Type
Specific Stream Power (Wm-2)
Class A: High Energy Non-Cohesive Floodplains A1 Confined coarse-textured floodplains >1000 A2 Confined vertical accretion floodplains 300-1000 A3 Unconfined vertical accretion sandy floodplains 300-600 A4 Cut and fill floodplains ~300
Class B: Medium Energy Non-Cohesive Floodplains B1 Braided river floodplains 50-300 B2 Wandering gravel-bed river floodplains 30-200 B3 Meandering river, lateral migration floodplains 10-60
Class C: Low Energy Cohesive Floodplains C1 Laterally stable, single thread channel floodplains <10 C2 Anastomosing river floodplains <10
Table 2.3 - Classification of genetic floodplain types based on specific stream power (modified after Nanson and Croke, 1992).
Class A floodplains are often formed through catastrophic stripping of the
floodplain by floods, which leave behind a cobble-boulder lag and is followed by
reconstruction of the floodplain through vertical accretion during flood recession. Such
24
floodplains occur in steep headwater reaches with confined floodplains that prevent
floodwaters from extensive lateral flow. Floodplains are typically poorly developed and
may be turned over frequently. Where channels and floodplains are less confined, Class
B type floodplains dominate and occupy the upper part of the production zone through to
the deposition zone. This class of floodplain is the most prevalent in most watersheds and
forms through lateral accretion of gravels and sands with vertically accreted sands, silts,
and clays. Due to wider floodplains, sediment storage is typically larger than upstream,
which is reflected in floodplain thickness and age.
Lastly, Class C type floodplains dominate the deposition zone. These floodplains
form primarily through vertical accretion of silts and clays as lateral migration is
restricted by low erosive energy relative to cohesive riverbanks. Low channel energy
leads to slow turnover rates and high sediment storage on wide floodplains
Reduction of stream energy is also correlated with an increase in floodplain
thickness, such that Class A floodplains have the thinnest floodplains and Class C
floodplains are the thickest (see stored sediment in Fig. 2.4). This was partially shown on
the Squamish River where the downstream succession of river plan-form resulted in a
downstream increase in maximum floodplain thickness of 3.5 m, 4.5 m, and 6 m for a
type B1 braided channel floodplain, B2 wandering channel floodplain, and B3
meandering channel floodplain respectively (Brierley and Hickin, 1991). These
relationships are summarized in Figure 2.5.
2.3.4 The Case for Non-Alpine Deglaciated Watersheds
The preceding discussion presented a stereotypical ‘graded’ model for the
downstream variability in channel and floodplain characteristics, and is predicated on the
25
Figure 2.5 - Theoretical qualitative characteristics of the production, transport, and deposition zones. Arrow directions give downstream direction.
notion that channel slope decreases downstream. In recently deglaciated non-alpine
watersheds however, channel slope is often spatially inconsistent suggesting that fluvial
forms, and channel and floodplain characteristics may be just as spatially variable.
Studies by Brown (1990) and Croke (1994) demonstrate that the erratic downstream
variability in floodplain properties and formative processes in two recently deglaciated
basins are related to the shape of the longitudinal profiles, which were inherited from the
Pleistocene infilling of bedrock basins and bedrock valley confinement. Brewer et al.
(2009) note that the patterns of floodplain sedimentation in Wales are related to glacial
landforms, particularly relict alluvial fans and cross-valley moraines, which act to restrict
channel migration. Upstream of these constrictions the channel is sinuous and inactive
while the channel is more energetic within the valley constrictions. Additionally, the
spatial distribution of glacial sediments is such that sediment inputs are highly variable,
particularly when the degree of hillslope-channel coupling fluctuates downstream. As a
result, lateral inputs from glacial sediments tend to disrupt downstream fining (Foster,
1998). Since channel geometries and plan-forms depend on the interaction between
26
sediment supply, grain size, and channel slope, it seems logical to surmise that river
patterns within deglaciated basins are highly variable in the downstream direction and do
not conform to traditional notions of watershed characteristics as alluded to by previous
studies (Croke, 1994).
2.4 Research Objectives
The specific objectives of the research are as follows:
1. To describe various fluvial forms and the physical processes that shape them in a
deglaciated watershed and to describe downstream trends of various morphologic,
hydrologic, and sedimentologic characteristics of the river channel and floodplain.
2. To relate how glacially inherited slopes and sediment inputs dictate the spatial
distribution of fluvial forms and the downstream progression of the observed
characteristics.
3. To infer whether the channel is in equilibrium based on rational or empirical
relations.
27
Chapter Three: Little Rouge River Watershed
3.1 Introduction
Various southern Ontario watersheds were initially screened based on channel
longitudinal profiles, constructed from topographic maps with a contour interval of 10
metres. Ideal profiles contained at least one or two pronounced convexities and
concavities, such that a complex longitudinal profile was attained. The Little Rouge River
was selected as it meets this criterion, is located fairly close-by, and does not suffer from
heavy urbanization. Figure 3.1 shows the longitudinal profile of the Little Rouge River,
derived from a 10-metre digital elevation model, and the downstream variation in channel
slope, which varies downstream by approximately two orders of magnitude. Specifically,
there exist four peaks in channel slope separated by four areas of low slope. Presumably,
these peaks and valleys contain contrasting fluvial forms and were a primary
consideration for site selection discussed further on.
0.0000
0.0020
0.0040
0.0060
0.0080
0.0100
0.0120
0.0140
0 5 10 15 20 25 30 35 40 45
Distance Downstream (km)
Ch
ann
el S
lop
e (-
)
0
50
100
150
200
250
300
350
Ele
vati
on
(m
ab
ove
sea
leve
l)
Channel Slope
Longitudinal Profile
Figure 3.1 - Variation in channel slope along the Little Rouge River (data provided by R. Phillips).
28
3.2 Location
The Little Rouge River watershed is located in south-central Ontario and
encompasses portions of the cities of Toronto and Pickering, and the towns of
Whitchurch-Stouffville and Markham. The drainage basin is approximately 115 km2 in
area and occupies the eastern third of the Rouge River watershed, which drains south into
Lake Ontario (Fig. 3.2).
3.3 Land-use
While land-use percentages for the Little Rouge River sub-watershed are not
available, they can be inferred from data for the greater Rouge River watershed and
Figure 3.3. Presently, 40% of the Rouge River basin is composed of agriculture and
another 24% is forests, wetlands, and meadows. 35% of the basin is urban land-use with
the remaining 1% as water bodies (TRCA, 2007a). Based on Figures 3.2 and 3.3, it is
apparent that the vast majority of the Little Rouge basin is characterized by non-urban
land-uses and is predominantly agricultural with the downstream portion of the basin
dominated by Rouge Park. The town of Stouffville in the upper northeast corner of the
watershed constitutes the greatest urban land-surface.
3.4 Climate and Hydrology
Based on data from the Environment Canada weather station in Stouffville (ID#
6158084), the average annual temperature between 1971 and 2000 is 6.9ºC. The daily
maximum and minimum are 26.2ºC and –11.6ºC respectively. The average annual
precipitation for the 30-year period is 869 mm. Of this, 85% falls as rain and the
remainder as snow. However, snowfall storage over the winter months means that much
of the runoff is generated by snowfall melt in the months of March and April (Fig. 3.4). A
Figure 3.2 - Location of the Little Rouge watershed within southern Ontario.
30
Figure 3.3 - Land-use classification for the Rouge and Little Rouge (outlined in red) watersheds (modified after TRCA, 2007a).
31
second flood peak is experienced in the late autumn and early winter months, which is
associated with rainstorms and early snowmelt events. Rain-on-snow events typically
produce the highest discharge events and occur in spring. While snowmelt is responsible
for producing the annual flood discharge, the relatively low amount of snowfall
compared to other regions of southern Ontario means that flood peaks are comparatively
low, which is reflected in the analysis by Javelle et al. (2003) who show that watersheds
in south-central Ontario are characterized by low to medium intensity floods that occur
over short time periods.
Station Name Station ID Record Period Record Length (years)
Drainage Area (km2) (% Total Area)
Dicksons Hill 02HC053 2002-2010 9 59.3 (51.7%) Locust Hill 02HC028 1963-2010 48 83.8 (73.2%)
Table 3.1 - Description of the active hydrometric gauging stations within the Little Rouge watershed. Drainage areas are derived from a 10m-resolution digital elevation model.
0.00
0.50
1.00
1.50
2.00
2.50
Jan Feb Mar Apr May Jun Jul Aug Sept Oct Nov Dec
Month
Mea
n M
on
thly
Dis
char
ge
(m3 s-1
)
Locust Hill (1964-2010)
Dicksons Hill (2003-2010)
Figure 3.4 - Mean monthly discharge values for the gauging stations on the Little Rouge River. Periodsof record are indicated beside each station name.
32
Figure 3.5 - Locations of active hydrometric gauging stations operated by the Water Survey of Canada (WSC) and the Environment Canada (EC) weather station within the watershed.
The Water Survey of Canada presently operates two gauging stations on the Little
Rouge River (Fig. 3.5 and Table. 3.1). Since the gauging station near Dicksons Hill is
relatively recent, spatial analyses on the hydrology of the watershed is restricted to the
33
last decade. The mean annual runoff at each station between the years 2003-2010 is 370
mm and 363 mm for the Dicksons Hill and Locust Hill stations respectively, which
suggests a decrease, albeit small (6.2%), in run-off contribution downstream of the
Dicksons Hill station. Figure 3.4 shows that the annual hydrologic regime at both stations
behaves similarly suggesting that major downstream changes in the timing of the annual
flood hydrograph are not significant.
A flood frequency analysis on the Locust Hill station was performed using the
General Extreme Value distribution on the maximum instantaneous and maximum daily
discharges for the annual maximum series (AMS), and the General Pareto distribution on
the maximum daily discharges for the partial duration series (PDS) (Kidson and
Richards, 2005). The cut-off discharge for the PDS was 5.38 m3s-1, which represents the
lowest peak discharge on the AMS (Langbein, 1949). The results (Fig. 3.6) indicate that
the watershed has had a modest history of flooding where the maximum discharge on
record is 36 m3s-1 using maximum instantaneous values and has a recurrence interval of
18.5 years. The mean annual flood is approximately 22 m3s-1 using the maximum
instantaneous values and has a recurrence interval of 2.10 years (Table 3.2).
Max Daily (AMS) Max Instantaneous Max Daily (PDS) Mean Annual Flood (m3s-1) 15.36 21.75 15.36 Return Period (years) 2.16 2.10 2.44
Table 3.2 – Return periods for the mean annual flood discharges at the Locust Hill gauging station. Return period values were derived from the flood frequency curves in Figure 3.5.
While the neighbouring watersheds to the west have experienced increased
urbanization over the last several decades, the Little Rouge watershed has been left
dominantly rural, which is reflected in a comparison of the annual mean discharges of the
Rouge and Little Rouge rivers with Highland Creek since the 1960s (Fig. 3.7). While the
34
0
5
10
15
20
25
30
35
40
0.1 1 10 100
Return Period (years)
Dis
char
ge
(m3s-1
)
Max Daily - PDS (1964-2010)
Max Daily - AMS (1964-2010)
Max Inst. - AMS (1966-2007)
Figure 3.6 - Flood frequency curves for the Locust Hill gauging station. Periods of record are indicated beside each curve label. PDS = partial duration series, AMS = annual maximum series. Little Rouge River does show a modest increase in discharge, the slope of the regression
is not significant at the 90% confidence level, which is in contrast to the other, more
urbanized basins. An analysis of the decadal variation in discharge shows that much of
the observed increase in the Little Rouge basin occurred between the 1960s and 1980s,
remaining relatively constant since (Fig 3.8). In terms of seasonal variation, there has
been no change in the proportion of the annual flow occurring in winter/spring and
summer/fall since the 1960s within the Little Rouge basin (Fig. 3.9). However, this
cannot be said for the Rouge and Highland watersheds, which show decreases in
winter/spring discharge percentages and increases in summer/fall percentages. Further
inspection reveals that much of the summer/fall increases in these two basins occur
35
Figure 3.7 - A comparison of annual patterns in mean discharge between the Little Rouge watershed and two neighbouring urbanized basins over 40 years (after TRCA, 2007b).
36
0.50
0.60
0.70
0.80
0.90
1.00
1960s 1970s 1980s 1990s 2000s
Decade
Ave
rag
e A
nn
ual
Mea
n D
isch
arg
e
(m3s-1
)
Figure 3.8 - Decadal variation in average annual mean discharge in the Little Rouge watershed (data from the Locust Hill station between 1964 and 2009). Error bars represent +/- 1 standard error.
Figure 3.9 - Seasonal proportions in annual discharge between the Little Rouge, Rouge, and Highland watersheds for two time periods. Winter is defined as January-March, Spring as April-June, Summer as July-September, and Fall as October-December (after TRCA, 2007b).
37
almost exclusively in the summer, which is rationalized as an effect of the impervious
nature of urban structures contributing greater run-off during summer convective storms
(TRCA, 2007b). While the summer and fall flow percentages in the Little Rouge basin
are unchanged between the two time periods, the winter discharges appear to have
increased at the expense of the spring discharges (Fig. 3.9). This, however, may be
related to regional climatic changes causing an earlier melt period compared to past
decades.
3.5 Physiography
The highest point within the Little Rouge watershed is 370 meters above sea level
along the Oak Ridges Moraine from where the headwater channel descends nearly 300
meters over a distance of 45 kilometres to the confluence with the Rouge River. Along
the way it passes over an array of glaciogenic sediments within several different
physiographic regions.
3.5.1 Physiographic Regions
The watershed can be divided into four primary physiographic regions that
represent past depositional environments. From north to south, these are the Oak Ridges
Moraine, the South Slope, the Peel Plain, and the Lake Iroquois Sand Plain (Fig. 3.10).
Though not directly within the Little Rouge basin, but still within the greater Rouge
River basin, the Lake Iroquois Clay Plain physiographic region occupies the lowest
portion of the Rouge River basin. Each of the four regions is composed of a variety of
surficial sediments ranging from clay to gravel (Fig. 3.11).
At over 300 metres above sea level, the Oak Ridges Moraine acts as the drainage
divide between channels draining north to Lake Simcoe and south towards Lake Ontario.
38
Figure 3.10 - Physiographic regions of the Rouge River watershed. The Little Rouge watershed is outlined in red (modified after TRCA, 2007a).
39
Figure 3.11 - Surficial geology deposits within the Rouge River watershed. The Little Rouge watershed is outlined in red (modified after TRCA, 2007a).
40
Due to a mixture of relatively permeable sediments, the moraine is an important
source for groundwater recharge, which helps maintain the channel discharge in the
summer (TRCA, 2007a). The South Slope is a relatively flat till plain (Halton Till) that
slopes from the southern flanks of the Oak Ridges Moraine southward towards Lake
Ontario. Overlying portions of the South Slope is the Peel Plain, which is generally more
horizontally angled than the South Slope and consists of glaciolacustrine sands, silts, and
clays deposited in remnant glacial ponds.
Aside from the Oak Ridges Moraine, the Lake Iroquois shoreline is perhaps the
most well known physiographic feature within the watershed and separates the South
Slope to the north from the Sand and Clay plains to the south. This shoreline is composed
of beach gravels and sands deposited by proglacial Lake Iroquois (Fig. 3.11) (Eyles and
Boyce, 1991; TRCA, 2007a).
3.5.2 Watershed Stratigraphy
While the spatial distribution of the surface deposits is complex in nature, the
underlying glacial stratigraphy is similarly complex. Underlying the watershed is a
succession of glacial sediments of varying thickness and granular composition, which
records the Illinoian and Wisconsin glaciations over the last ~100 thousand years (Fig.
3.12). These deposits, however, are not all exposed within the Little Rouge watershed
and only those that are will be discussed here.
The basement bedrock underlying the glacial deposits is the Whitby Formation,
which is a highly fissile bluish-grey shale deposited during the Ordovician Period (Eyles
and Boyce, 1991). The spatial extent of bedrock exposure is quite limited and restricted
41
to brief outcroppings downstream of Twyn Rivers Drive (Fig. 3.13) (Karrow, 1967; Eyles
and Boyce, 1991).
Figure 3.12 - Generalized stratigraphic diagram for the Rouge River watershed (after TRCA, 2007a).
The Scarborough Formation developed during an interstadial period within the
early Wisconsin glaciation and is thought to represent a delta complex prograding into a
proglacial lake (Eyles and Boyce, 1991). The deposits consist of a fining upward
sequence with basal silts and clays capped by fluvial sands and vary in thickness but
typically are several tens of metres thick. Within the Little Rouge watershed, these
deposits outcrop in the bluffs between the confluence with the Rouge River and several
hundred metres upstream of Twyn Rivers Drive (Karrow, 1967). Overlying the
42
Scarborough Formation is the Sunnybrook Drift, which is a clast-poor clayey-silt till
formed during the early Wisconsin stadial with an ascribed thickness of 5 to 10 metres
(Eyles and Boyce, 1991). Sunnybrook Drift can be seen to outcrop in the valley sides,
terraces, and the channel bed between Meadowvale Road and its downstream contact
with the Scarborough Formation, downstream of which it seems to be absent (Fig. 3.14)
(Karrow, 1967).
Figure 3.13 - Whitby Formation shale exposed in an outcrop of the Little Rouge River approximately 1 km upstream of the Rouge River confluence.
Figure 3.14 - Sunnybrook Drift exposed in a terrace downstream of Meadowvale Road.
43
The Halton Till, and its correlatives the Northern and Newmarket Till, represent
the most spatially extensive glacial unit within the watershed having been deposited
during the late Wisconsin period and forms the vast majority of surficial sediments within
the South Slope and Peel Plain physiographic regions. The till is generally regarded to be
stone and sand-rich compared to the Sunnybrook Till, and incorporates sand and gravel
inclusions derived from the underlying glacial deposits (Fig. 3.15) (Eyles and Boyce,
1991). Much of the river channel between Meadowvale Road and 14th Avenue is cut into
this till as documented in bluff analysis by Karrow (1967) and Eyles and Boyce (1991)
and it seems likely that this is the case for the channel farther upstream. Drift thickness is
variable but likely ranges between a couple meters to at least 40 meters (Eyles and
Boyce, 1991).
Figure 3.15 - Halton Till exposed in a low-lying terrace downstream of 14th Avenue.
44
Overlying the Halton Till are superficial lacustrine sands, silts, and gravels. The
most prominent of which are those in the south deposited by Lake Iroquois. Sediment
thickness of the near-shore gravel deposits typically does not exceed 5 meters but reduces
to less than a meter for the offshore silts and clays, which only sporadically drape Halton
Till (Eyles and Boyce, 1991). Though their spatial extent is not known, outwash gravels
upstream of the Lake Iroquois shoreline have been documented overlying Halton Till in a
valley bluff and seem to be several meters thick (Mahaney and Hancock, 1993).
Lacustrine deposits above the Iroquois shoreline are typically patchy and composed of
clays to sands reaching a maximum thickness of several meters (TRCA, 2007a). The
complexity of the Oak Ridges Moraine sediments in the northernmost part of the
watershed is significant, but, in brief, much of the surficial sediments are composed of
silts and sands with pockets of gravel deposited through glaciofluvial and glaciolacustrine
sedimentation (Barnett et al., 1998).
The overall drift thickness within the watershed tends to decline downstream from
a thickness of around 170 metres within the Oak Ridges Moraine complex to 5 metres
near the confluence with the Rouge River (Fig. 3.16). In many cases the glacial units tend
to thin down-valley, which combined with progressive incision means valley bluffs tend
to be composed of several stratigraphic units with the number increasing downstream. In
general, and as alluded to in the previous paragraphs, the channel appears to be down
cutting into older glacial deposits with increasing distance downstream.
45
Figure 3.16 - Geologic cross-section through the Rouge River watershed. Overall drift thickness tends to decrease downstream while channel incision increases exposing multiple glacial units in valley bluffs. Note: valley sections are for the Rouge River and not the Little Rouge, though they should be fairly similar (after Eyles and Boyce, 1991).
3.6 Study Sites
As channel slope appears to be a dominant control on fluvial form (ie. Ferguson
and Ashworth, 1991; Nanson and Croke, 1992) and is easily determined through maps
and GIS software, channel slope was the primary basis for selecting study sites. A
longitudinal profile of the channel was created from a 10-metre digital elevation model
and 1-metre contour interval data of the drainage basin, and sites that represented various
gradients along the longitudinal profile were selected (Figs. 3.17 and 3.18). Site selection
was supplemented by field reconnaissance, land accessibility, and digital imagery
analysis of river plan-form to ensure a variety of fluvial forms were chosen. Due to time
constraints, only a handful of sites could be chosen, which represent only a portion of the
variability within the watershed. However, they are thought to be representative of the
range of slope and boundary conditions. Table 3.3 provides an overview of major site
characteristics prior to data collection and imagery of each site are given in Figures. 3.19a
and b.
46
Figure 3.17 - Location of study sites within the watershed.
Figure 3.18 - Location of study sites in the context of the longitudinal profile. Selected road names are given for reference. The longitudinal profile was derived from combining a 10-metre digital elevation model (first 3.145 kilometres) with 1-metre contour interval data (rest of the profile). Both datasets were created by the Ontario Ministry of Natural Resources. Approximate boundaries of the physiographic regions are given. Vertical exaggeration = 78x.
Site Drainage Area (km2)
Slope Channel Confinement
Plan-form Sinuosity Bed Structure
1 16.99 0.0024 Unconfined Single-thread, no bars
High Plane Bed
2 21.70 0.0071 Unconfined Single-thread with medial bars and poorly developed lateral bars
Low Run/Riffle-Pool
3 73.14 0.0004 Unconfined Single-thread, no bars
Moderate-High
Plane Bed
4 86.60 0.0027 Semi-confined to Unconfined
Single-thread with poorly developed lateral and point bars
Low-Moderate
Riffle-Pool
5 107.42 0.0057 Confined to Semi-confined
Single-thread with variably developed lateral, medial, and
point bars
Low-Moderate
Riffle-Pool
6 114.12 0.0044 Unconfined Single-thread with well developed lateral, medial, and point bars
Low-Moderate
Riffle-Pool
Table 3.3 - Study site characterization prior to fieldwork. Channel slopes were derived from the longitudinal profile in Figure 3.18.
49
Figure 3.19a - Imagery of sites 1-3. Images on the left are field images, while images on the right are Google Earth™ imagery. Dense forest canopy prevented an aerial image of Site 4 from being obtained.
50
Figure 3.19b - Imagery of sites 4-6. Images on the left are field images, while images on the right are Google Earth™ imagery.
51
Chapter Four: Methods 4.1 Fieldwork
Fieldwork was carried out at the study sites during the months of June to August
2011 with supplemental data collected in October. Data collection consisted of levelling
surveys of the channel, channel-bed augering, grain size analysis, and floodplain
sampling.
4.1.1 Surveying and Bed Augering
At each site, 5 to 11 cross-sections of the channel were taken in addition to the
longitudinal profile, using a Sokkia™ engineering level and stadia rod, over a distance
equivalent to approximately 9 to 32 bank-full channel widths with a mean of 20.5
channel widths. Cross-sections were split nearly even between riffles and pools. Intervals
between elevation measurements in each cross-section were typically on the order of 50
cm or less in order to characterize the cross-sectional shapes as best as possible.
Following surveying, up to four points were selected evenly spaced across the alluvial
section of the channel to be manually drilled into using a Dutchfield auger until glacial
clay or bedrock was reached, or refusal due to cobbles. Depth to clay or refusal was then
recorded with the distance along the cross-section. Lateral changes in bed composition
(ie. glacial clay, gravel, sand) were also noted.
4.1.2 Grain Size Analysis
At each riffle, the Wolman (1954) pebble count method was employed to
characterize the distribution of the surface bed material. A clast was selected every 50 cm
along the cross-section and placed through a template with square holes equivalent to b-
axis diameters ranging from 4 mm up to 256 mm spaced in half-phi intervals. Several
52
lines parallel to the cross-section were taken until a sample size of at least 100 clasts was
attained. This sample size was chosen because it is expected that the sample variance will
begin to stabilize at this point (Wolcott and Church, 1990). Boulders (b-axis diameters
>256 mm) that were included within the sample were measured with a measuring tape.
Bulk sampling was employed at sites 1 and 3 as bed material here consisted of a
considerable amount of sand, which is beyond the limits of the template. Since obviously
defined riffles did not exist at these sites, samples were taken from shallow locations
within the channel that were felt to be analogous to riffles. At each site, 3-4 buckets were
filled with 10-15 kg of sediment taken from the channel bed to a depth of approximately
half the blade length of the shovel. The samples were taken back to the lab,
disaggregated, and dry sieved through screens of diameters between 0.045 mm up to 64
mm in half-phi increments for 15 minutes. The a, b, and c axes of the largest sediment
clast within each study site were also measured.
Grain size distributions were pooled together to give site-average distributions, as
advocated by Wolcott and Church (1990). Where pebble counts were used, this resulted
in sample sizes between 200 to 600 particles, but typically at least 300. Rice and Church
(1996) suggested that precision in the distribution at the 95% confidence level does not
get appreciably greater beyond 400 particles. Therefore, the site-averaged distributions
derived are expected to be reliable. Combination of the individual bulk samples from
sites 1 and 3 yielded total weights of 32 and 46 kg respectively, with the largest particle
class representing, respectively, 3.2% and 1.7% of the distribution by weight. Church et
al. (1987) have advocated that the largest class should not constitute more than 1% by
53
weight. Therefore, the precision of the upper end of the distributions may not be as strong
as desired.
4.1.3 Floodplain and Channel Bank Sampling
Floodplain data were collected from bank exposures, manually dug pits, auger
holes, and sediment cores. Banks were initially cleared of slumped material in order to
reveal the entire stratigraphy. Individual strata that were distinct from one another based
on apparent grain size and/or colour were identified and their respective thickness
measured and recorded. Each stratum was then described making note of features such as
colour, weathering, grain size, the presence of organics, sedimentary structures (ie. cross-
beds, imbrication, and grading), and the nature of the contact with the overlying stratum.
Sediment samples of strata composed of sediment in the sand fraction or finer were taken
for laboratory particle size analysis. In instances where the sand stratum was particularly
thick, two samples were taken – one from near the bottom and one from near the top – to
discern differences in the sediment sizes upward through the deposit. Organic samples
were also taken where appropriate.
Pits were selectively dug on the inside of meander bends where the overbank
thickness was less than 50 cm. Where overbank thickness exceeded 50 cm, a hand-driven
Oakfield Auger was used until refusal, typically defined by the gravel surface, and the
sediment laid out onto a tray for examination. The same procedure described for the
cutbanks above was used to characterize the sediments, and samples of organic material
and representative grab samples of the strata were collected. At selected locations at Site
6, a hand-driven JMC Environmentalist’s Soil Probe was used to take narrow-diameter
54
sediment cores of the floodplain for further lab analysis. Refusal was fluvial gravel,
though these deposits were not often reached.
4.2 Lab Analysis of Floodplain Sediments
For fine floodplain analysis, selected floodplain sediments from each site were
dried at 100°C overnight, disaggregated using a mortar and pestle, weighed, and left to sit
in 100 mL of 5% sodium hexametaphosphate and then topped up with 400 mL of
distilled water for 24 hours. The samples were wet sieved through a 63 μm screen. The
sand fraction was retained, dried, and weighed in order to determine the percent silt and
clay in each sample. Loss-on-ignition was also performed on selected floodplain samples
for organic content. Samples were first dried, weighed, and heated to 550°C for an hour
(Dean, 1974). Following this, the samples were cooled to room temperature and re-
weighed, from which percent organics was derived. Sediment cores were analyzed for
major lithostratigraphic breaks, sediment structures, colouration, and grain size based on
hand texturing.
4.3 Determination of Morphological Bank-full Discharge
The determination of morphological bank-full discharge has many important
implications for morphological, sediment transport, and flood frequency relations
(Navratil et al., 2006). Indeed, an accurate representation of morphological bank-full
discharge forms a major component of this study, as it is necessary for equilibrium
relations, stream power computations, plan-form analysis, and bank-full discharge
frequency analysis. Thus, it was imperative to determine the best indicator(s) of
morphological bank-full stage and how best to calculate the corresponding discharge.
55
In any given river reach, there usually is not a single feature that indicates bank-
full stage. More often, multiple indicators exist and it is up to the researcher to determine
which is the correct one at any given cross-section. It is for this reason that Williams
(1978) and Navratil et al. (2006) advise that a reach-average bank-full estimate be
calculated incorporating the measurements from multiple cross-sections. The
morphological bank-full indicators used within the study were the minimization of the
width-depth ratio, bar-top elevation, the limits of vegetation (ie. shrubs or trees), and the
elevation of the active floodplain (see Williams (1978) for a full list). It was often the
case that the minimization of the width-depth ratio (or a close approximation of it)
coincided with the elevation of the active floodplain and this indicator appears to have
been reliable in a regional study conducted in nearby watersheds (Annable et al., 2010).
Each cross-section was viewed graphically to assess bank-full stage in the context of the
four indicators and compared to orthoimagery where possible. A portion of Site 5
experienced localized down cutting of 70 cm above bar-top surfaces and 90-130 cm
above summer low-flow stage. Since many of the aforementioned indicators do not work
for entrenched channels, the stage at these cross-sections needed to be critically assessed
in order to not over-estimate bank-full stage and thus discharge. Once a stage was
determined, bank-full width and average depths were calculated for each cross-section
and compiled to form a reach average cross-section.
Discharge was estimated through the use of four relations. In his analysis,
Williams (1978) formulated a regression relation using cross-sectional area (Abf, m2) and
channel slope (SC, - ) given as
1.28 0.28bf bf CQ = 4A S 4.1
56
The other three relations use an estimate of velocity (Vavg) multiplied by the
cross-sectional area. Bray (1979) reviewed the velocity calculation problem and
determined that the two best performing relations are (1) the Limerinos-Manning relation
0.67 0.5h C
avg
R SV =
n 4.2
where Rh is the bank-full hydraulic radius (m) and n is the Manning’s roughness value
estimated as
0.17h
-1h 84
0.113Rn =
1.16+2log(R D ) 4.3
where D84 is the grain size that represents the coarsest 84th percentile of the grain size
distribution (m), and (2) the Lacey relation
0.67 0.33avg h CV = 10.8R S 4.4
The final velocity relation utilized was developed by Hey (1979) and uses the
Darcy-Weisbach relation defined as
0.5
h Cavg
8gR SV =
ff
4.5
where g is the gravitational acceleration (9.81 ms-2) and ff is the friction factor given by
Hey (1979) as
2
h
84
13.4R = 2.03log
3.5Dff
4.6
Before these relations were used to calculate bank-full discharge at each study
site, they were first tested on independent field data in order to assess the reliability of
each relation. The results of this analysis are presented in Appendix C.
57
Chapter Five: Watershed-Scale Variability of Fluvial Form and Process
5.1 Introduction
The study sites were divided into five channel-floodplain types based primarily on
specific stream power, accretionary style, and channel plan-form. Accretionary styles are
a reflection of the energy conditions and sediment size within each channel-floodplain
type. Using data acquired from cross-sectional surveys, floodplain sampling, and
stratigraphic profiles, these channel-floodplain types are described with reference to
important physical and sedimentary controls. The derivation and rationale for these
controls are too extensive to be explained here but are analyzed in detail in Appendix F.
Bank-full specific stream power, based on data from the study sites, is assigned to each
type for comparison to other channel and floodplain classification schemes.
The primary bank-full morphological, hydrological, and sedimentological
characteristics of each site along with floodplain characteristics are presented in Table
5.1. A more detailed set of characteristics, including the full data-set, and the derivation
of the bank-full discharges and return periods are provided in appendices A, B, C, and D.
Major characteristics of the channel-floodplain types are summarized in Table 5.2.
To characterize floodplain stratigraphy at each site, a selected group of bank
exposures, auger holes, and pits were analyzed based on sediment structures, colour,
texture, and other relevant properties. Grain size variations shown are derived from data
presented in Appendix B and from hand texturing of sediment cores. Facies units were
assigned to each core and bank log based on Table 5.3 and broad depositional
environments are interpreted.
Site Site Characteristics 1 2 3 4u 4d 5 6 Drainage Area (km2) % Total Area
16.99 14.84
21.70 18.96
73.14 63.88
86.53 75.57
86.65 75.67
107.42 93.82
114.12 99.67
Distance Downstream (km) 6.45 8.29 21.77 27.80 28.00 38.42 43.36 Channel Slope 0.0002* 0.0072 0.0002 0.0017 0.0043 0.0069 0.0035 Channel Morphology Width (m) 5.64 0.51 9.42 0.77 9.11 0.80 13.38 0.23 13.64 0.74 17.45 1.67 20.51 1.77 Depth (m) 0.68 0.04 0.65 0.03 1.04 0.09 0.73 0.12 0.73 0.08 0.70 0.05 0.81 0.10 Width:Depth 8.29 14.49 8.76 18.33 18.68 24.93 25.32 Area (m2) 3.86 0.42 6.07 0.62 9.75 1.63 9.78 1.55 10.09 1.37 12.11 1.82 16.14 1.95 Sinuosity 1.71 1.14 1.70 1.15 1.18 1.17 1.26 Channel Hydrology Velocity (ms-1) 0.49 1.47 0.59 1.08 1.41 1.68 1.48 Discharge (m3s-1) 1.87 8.95 5.57 10.59 14.02 20.55 24.64 Return Period (years) 0.50 20.00 0.50 1.10 2.00 3.00 5.00 Channel Sedimentology Bed Thickness (cm) 38 2 45 1 58 3 37 1 26 2 50 1 91 3 Percent Clay (%) 15.03 7.50 4.19 4.19 5.20 5.20 0.76 0.76 25.98 9.53 16.02 4.60 4.26 4.26 D50 (mm) 8 36 3 62 56 54 31 Sorting () 3.09 1.67 2.80 0.94 0.78 1.14 0.82 Floodplain Sedimentology Overbank Thickness (cm) ~ 45† 82 8 145 12 63 11 64 9 20 5 ~ 112† Silt/Clay Content (%) 63.41 5.87 59.91 5.31 76.62 2.96 49.82 5.83 47.11 4.71 38.51 3.49 52.31 6.09 Organic Content (%) 6.70 0.69 4.88 0.74 4.28 1.06 4.46 1.08 3.65 0.73 1.47 0.17 1.58 0.21
Table 5.1 - Bank-full channel and floodplain characteristics of the study sites. Drainage areas derived from 10-m digital elevation model provided by the Ontario Ministry of Natural Resources. Downstream distances derived from Figure 3.18. Error ranges represent one standard error. * - the water surface slope at the time of survey is substituted for channel slope as a better measure of the energy condition at the study site. Channel slope is an order of magnitude higher. † - values are estimates of overbank thickness based on floodplain logs.
Type Plan-form Specific
Stream Power (Wm-2)
Floodplain Accretion
Style
Channel Accretion
Style
Width-Depth Ratio
Dominant Bed
Material
Representative Study Sites
Low Energy Mixed-Load
Sinuous single-thread with no bar-forms
<2 Oblique Lateral and oblique
8 Sandy-gravel
1 and 3
Low Energy Bed-Load
Low sinuosity single-thread with no to weakly developed bar-forms
13 Oblique Lateral 18 Gravel-cobble
4u
Mixed Energy
Low sinuosity single-thread with variously developed bar-forms
12-70 Oblique Lateral and vertical
15 Gravel-cobble
2
Medium Energy
Low sinuosity single-thread with weakly to well-developed bar-forms
40-45 Vertical Lateral and vertical
18-25 Gravel-cobble
4d and 6
High Energy Low sinuosity single-thread with well-developed bar-forms
80+ Vertical Lateral and vertical
25 Gravel-cobble
5
Table 5.2 - Description of the channel-floodplain types identified within the Little Rouge River watershed.
60
Facies Code Facies Description Interpretation Gcm Massive clast-supported gravel/cobble;
not imbricated
Lag deposits
Gh Massive or weakly horizontally-bedded clast-supported gravel; often imbricated
Bed-load deposits
Gms Massive matrix-supported gravel with coarse sandy-matrix; weakly imbricated
Bed-load and suspended-load mixture
Sm Massive sand or silt; no visible structures
Deposited out of suspension or as bed-load
Pi Incipient soil development; roots common; very similar to facies Sm
Minimal sediment deposition
P Well developed soil profile or paleosol; roots prevalent; likely similar to facies Sm
Minimal to no sediment deposition
Table 5.3 - Facies classification of the study sites (adapted after Miall, 1996).
5.2 Low Energy Mixed-Load Type
Low energy, mixed-load channels are characterized by sites 1 and 3. A
representative cross-section illustrating floodplain sediments and their depositional
mechanisms are shown in Figure 5.1. Characteristic specific stream powers are very low
(<2 Wm-2), which is primarily driven by very low channel slopes. As a result of
transport-reduced conditions, sand is often deposited on the channel bed blanketing
gravels inherited from past channel states, resulting in very poorly sorted channel beds.
The increase in the importance of sand to sediment transport relative to the generally
immobile gravel results in an increase in the importance of suspended sediment transport
in addition to bed-load transport. Consequently, channels have low width-depth ratios
(<10) and are generally sinuous in plan-form. Bed-forms were not observed and the
structure of the channel bed seems to take on a lower regime plane-bed morphology.
Plotting sites 1 and 3 on a plan-form discrimination plot developed by Kleinhans and van
61
Figure 5.1 - Field image taken during the summer (a) and idealized schematic cross-section (b) of the low energy, mixed-load channel-floodplain type. The diagram is based on cross-sectional surveys, lateral bed material identification, augering into the channel bed with a Dutchfield auger, and channel bank stratigraphy. The flow direction is given by the white arrow and the direction of channel migration is the same as depicted in the cross-section. Elevation given on the cross-section is in metres above an arbitrary datum.
den Berg (2011) that uses potential specific stream power and median grain size of the
bed material shows that Site 3 plots in the laterally immobile with no bars domain, which
is congruent with the plan-form style observed in the field (Fig. 5.2). Site 1 however,
plots in the meandering domain, which is a consequence of beaver dams along the
channel. While the channel is naturally at a higher energy state, the presence of beaver
62
dams lowers the water surface slope (and thus energy slope) of the channel enough to
change the channel behaviour.
Figure 5.2 - Plan-form discrimination of channel-floodplain types based off of the model provided by Kleinhans and van den Berg (2011) relating potential specific stream power to median bed material size.
Individual sites are labelled. Potential specific stream power (pv) is defined as bf Vpv 0.5
bf
ρgQ Sω =
aQ, where
is the density of water (1000 kgm-3), g is gravitational acceleration (9.81 ms-2), Qbf is the bank-full discharge (m3s-1), SV is the valley slope (-), and ‘a’ is a coefficient that is different for sand-bed (4.7) and gravel-bed (3.0) rivers.
According to the classification scheme presented by Nanson and Croke (1992),
these low energy, mixed-load channels are comparable to the laterally stable, single-
channel types that develop their floodplains through vertical accretion of overbank
sediments forming low-lying levees proximal to the channel with distal backswamps.
However, levees are absent at sites 1 and 3 suggesting that, despite multiple overbank
flooding events per year, vertical accretion is not likely a significant depositional process
63
at these sites, which likely explains why post-settlement alluvium was absent on the
floodplains.
Page et al. (2003) offer a model of floodplain development for low energy
migrating channels with negligible floodplain relief and pervasive overbank flooding,
much like the low energy sites presented here, where the dominant floodplain formative
process is the progressive erosion of the outer channel bank and lateral accretion of
suspended sediments against the inner channel bank (termed oblique accretion). It is
believed that this process is active at sites 1 and 3.
Floodplain formation at sites 1 and 3 is achieved initially through the lateral
accretion of coarse pebbly sand transported as bed-load over an immobile gravel lag,
which form steeply dipping (17), structureless sub-aqueous point bars (Figs. 5.1b and
5.3). These point bars may fine upwards to silty-sand, which represents a lateral gradation
of grain size, and they often contain small shells and abundant wood pieces at, or just
below, the low water surface. A sample of these wood deposits yields a radiocarbon age
of 3050 30 years BP at Site 3 indicating floodplain formation during at least the mid- to
late-Holocene and likely very slow sedimentation and channel migration (Table 5.4).
Suspended sediments are accreted to the inner bank above the point bar forming
steeply dipping (up to 25) banks. In this way, sedimentation is limited to the inner bank
of the channel and slow, progressive migration produces a relatively flat floodplain.
These overbank deposits have a diffuse contact with the underlying channel sands and
consist of massive sandy-silts that show no strong indication of upward fining. In some
cases, distinguishing between channel and overbank deposits is difficult. Soil profiles are
very well developed owing to the lateral stability of the channel.
Figure 5.3 – Characteristic floodplain stratigraphy of the low energy, mixed-load type based on S3-B1.
65
Site Lab Number Material 14C Age Two-Sigma Calibrated Range 3 Beta-315421 Wood 3050 30 BP 3360-3210, 3180-3170 BP 6 Beta-315420 Wood 140 30 BP 280-170, 150-60, 50-0 BP
Table 5.4 - Radiocarbon dates from the study sites. Uncalibrated dates are reported with one standard deviation. Dates calibrated using INTCAL09. Before present (BP) = before 1950 AD.
Based on sediment logs, laterally accreted channel deposits consist of
approximately half of the fine floodplain sediment while obliquely accreted deposits
account for the other half. Where point bars do not form, obliquely accreted deposits
dominate the entire fine sediment sequence. Vertical accretion, if it does occur, typically
makes up less than 5% of the floodplain stratigraphy (Page et al., 2003). The thickness of
the fine floodplain deposits is controlled by the quantity of incoming fine sediment from
upstream. Upward fining trends in the sediment may also occur.
The channel and floodplain morphology and sedimentology described for sites 1
and 3 are very similar to that reported for other low-energy fine-grained channels
(Jackson, 1981; Miall’s (1996) Model 7; Page et al., 2003) suggesting that these
accretionary processes may be pervasive amongst low energy migrating rivers. However,
differences exist between these studies and the floodplain sedimentology described here.
Primarily, the floodplain stratigraphy for sites 1 and 3 are more simplistic than that
reported in the literature. Page et al. (2003) report that obliquely accreted sediments often
consist of couplets of fine sand and silt, which have been similarly described by Jackson
(1981) and Miall (1996). These couplets are absent at sites 1 and 3 giving the sediment a
structureless appearance. The sand thickness of a couplet tends to take on approximately
a 3:1 ratio with the silt (Page et al., 2003). Conversely, the obliquely accreted deposits at
sites 1 and 3 have a far greater silt component by weight than sand (~3:1), suggesting that
the paucity of sand within the deposits precludes couplets from forming. Even still, any
66
couplets that may form would be very thinly laminated and would likely be destroyed due
to bioturbation.
5.3 Low Energy Bed-Load Type
The low energy, bed-load channel-floodplain type is based on Site 4u and shown
schematically in Figure 5.4. The channel plan-form takes on a low-sinuosity course with
a riffle-pool bed structure. Bar-forms are generally absent but are weakly developed
when visible. Specific stream power is low (~13 Wm-2) due to low channel slopes,
Figure 5.4 - Field image taken during the summer (a) and idealized schematic cross-section (b) of the low energy, bed-load channel-floodplain type. The flow direction is given by the white arrow and the direction of channel migration is the same as depicted in the cross-section.
67
however, is high enough to prevent significant sand deposition as in the low energy,
mixed-load type. The channel bed is composed of glacially derived gravel-cobble for
which the channel is competent to transport only a small fraction. Due to the lack of
transport capacity within the channel, glacial clay is not often exposed. However, Figure
5.4 does show that there is a tendency for the channel to plane off the underlying glacial
surface as it progressively migrates, which means that the lag deposits must be mobilized
at some point, perhaps during exceptionally large magnitude flood events.
Plan-form discrimination predicts that this type is a laterally immobile channel
with no bars, which is in agreement with field observations (Fig. 5.2). The well-
developed soil profiles characterized by relatively high organic contents provide
inferential evidence that the channel is very laterally stable, which is gained through low
stream power and resistant, root-stabilized banks.
The Nanson and Croke (1992) floodplain classification scheme suggests that the
floodplain developed by this channel-floodplain type is created through progressive
lateral accretion of point bars capped with vertically accreted deposits, which is broadly
confirmed here. It is suggested, though, that the floodplain is formed through the oblique
accretion of sandy-silt, similar to that described above for low energy, mixed-load
channels. Initial floodplain development involves the lateral accretion of fine-medium
gravel over an immobile coarse gravel-cobble lag producing a vertical fining trend (Fig.
5.5). Deposition appears to be reduced to the inner third of the channel while the
remaining two-thirds are dominated by the immobile lag. The laterally accreted gravel
may be intermixed with small shells, wood pieces, and sand that increases in thickness
towards the inner channel margin. The depositional surface is sub-aqueous at low flow
Figure 5.5 – Characteristic floodplain stratigraphy of the low energy, bed-load type based on S4-B2 (a) and S4-AH5 (b).
69
and tends to dip shallowly (6º) towards the channel centre, which contrasts with the
steeply dipping laterally accreted surface described for the low energy, mixed-load
system.
As mentioned, it is believed that suspended-load sediment is accreted to the side
of the inner bank-face, which dips sharply into the channel while the floodplain is
relatively flat beyond the bank-full channel limits. Furthermore, recent (ie. post-
settlement) deposition on the floodplain surface is absent despite annual to sub-annual
overbank flooding, which argues against vertical accretion and may be indicative of the
capacity of overbank flows to carry coarse sands onto the floodplain. Fining upward
trends within the sandy-silt are commonly observed. The proportion of fine, obliquely
accreted sediments to coarse, vertically accreted sediments is about 1:1, similar to that of
the low energy, mixed-load system. Silt-sand couplets are absent due to a lack of
significant sand in the system, bioturbation, and pedogenic processes.
5.4 Mixed Energy Type
The mixed energy channel-floodplain type is very similar to the low energy, bed-
load type described above in terms of channel and floodplain deposition. Indeed the
schematic illustrations in Figures 5.4 and 5.6 are nearly identical. However, the primary
difference between the two types is the energy level within the channel. In the mixed
energy type, the channel tends to alternate between a low energy state (~12 Wm-2) and a
high energy state (~70 Wm-2) brought on by the presence of debris dams, where low
energy conditions prevail upstream of dams and high energy conditions prevail
downstream. Since the presence of large woody debris is an important characteristic, it is
70
likely that this channel-floodplain type is restricted to the upper portion of the watershed
where fallen trees easily span the width of the channel.
Figure 5.6 - Field image taken during the summer (a) and idealized schematic cross-section (b) of the mixed energy channel-floodplain type. The flow direction is given by the white arrow. Since the image in a is not the same as the cross-section in b, the direction of channel migration is not the same.
Plan-form predictions predict a meandering or weakly braided channel with bars
and chute cut-offs (Fig. 5.2), which is not entirely congruent with field observations.
Overall, the plan-form of the channel is fairly straight with occasional bar-forms of
various degrees of development. Most bar-forms develop downstream of debris dams or
behind fallen debris within the channel. The disparity between predicted and observed
71
plan-forms arises from the occurrence of low energy states along the channel, which are
more comparable to laterally immobile channels, in addition to bank reinforcement by
extensive tree rooting, which acts to prevent erosion and channel migration.
Sediment transport is strongly conditioned by debris dams and the hydrological
regime of the basin. Upstream of dams, only the finest gravels can be entrained. Due to
damming of the flow, bank-full stage is often reached several times throughout the year
meaning the finest gravel and granules are entrained frequently. Downstream of the
dams, much more of the gravel is entrained during bank-full events creating thinly
bedded mid-channel bars and gravel sheets. However, due to enlarged cross-sectional
dimensions, and the low and often quick peak flows, bank-full discharge is rarely
reached, and large-scale sediment transport is consequently not common. The structure of
the channel bed is typically riffle-pool, however, aggradation of fine gravel and granules
under low energy conditions creates a bed structure more akin to run-pool. The mixing of
fine gravels and granules with glacially derived coarse gravels and cobbles leads to a
poorly sorted, bimodal channel bed. Following the return to high energy conditions
through either breaching of the debris dam or diversion of the channel, the accumulated
fine gravel and granules can be quickly mobilized, which may result in a pulse of bed-
load under bank-full conditions. Alternatively, under sub-bank-full conditions, the
deposits may be gradually winnowed. Glacial clay is not readily exposed in the channel
due to aggradation of the channel bed or slow reworking of aggraded deposits. However,
glacial clay was observed downstream of debris dams where the gradient is steeper and
turbulence greater, and downstream of steep riffles.
72
Floodplain development is very similar to that described for the low energy, bed-
load dominated type and will be reiterated here (Figs. 5.4 and 5.6). Under high energy
conditions, the channel bed is composed of coarse-gravels and cobbles that are mobile
during infrequent bank-full conditions but less mobile or immobile during sub-bank-full
conditions. As a result they are considered lag deposits. Proximal to the inner margins of
the channel are laterally accreted fine to medium gravels and sandy-gravels that are
mobile under more frequent, but smaller discharges. Under low energy conditions, the
same general lateral gradation of sediments exists, however the proportion of proximal
sand increases while the proportion of fine gravel and granules increases towards the
outer, eroding channel bank. The lateral accretion of the fine gravels over coarse gravels
creates a fining upward sequence (Fig. 5.7). Wood deposits and small shells may be
found proximal to the inner bank.
Sandy-silt deposits carried in suspension are accreted obliquely to the inner bank
of the channel in much the same fashion as that described for the low energy, bed-load
type, which may result in an upward fining trend from silty-sand to sandy-silt. Channel
migration appears to be very slow, inferred from very well developed soil profiles (Fig.
5.7), which is a consequence of root-stabilized banks and generally low energy conditions
either through debris dams or infrequent bank-full flooding. It is of note that abandoned
channels were observed, which may indicate that, in addition to progressive lateral
migration, channel avulsion is important as well. Such avulsions may have been induced
by flow diversion around debris dams. A large scour pool adjacent to the present debris
dam and perpendicular to the active channel was observed indicating that headward
Figure 5.7 - Characteristic floodplain stratigraphy of the mixed energy type based on S2-B1 (a) and S2-AH1 (b).
74
incision of a new channel is in progress (Fig. 5.8), though the rate of incision is not
known.
Figure 5.8 - Development of an avulsion channel (outlined in black) around an active debris dam (to the bottom left of image). The active channel is shown in the top of the image with the flow direction given. The flow direction through the avulsion channel is given, as is the direction of headward incision. Standing water can be seen in the scour pool.
5.5 Medium Energy Type
The medium energy channel-floodplain type is characterized by sites 4d and 6,
and is associated with a specific stream power of about 40-45 Wm-2. The channel plan-
form between the two sites is strikingly different despite having similar energy levels.
This is due to the grain size of the bed material relative to the channel slope. Bed material
at Site 4d consists of glacially derived gravel and cobble-sized sediment, only half of
which can be transported during bank-full events, while at Site 6, the bed material is
75
dominantly gravel derived from size-selective transport from upstream, such that 90% of
the sediment is mobile at bank-full stage. The effect that sediment mobility has on the
channels’ plan-form is illustrated in Figure 5.2 where Site 6 is predicted to be weakly
braided while Site 4d is not. This prediction is broadly conformable with observed plan-
forms where occasional medial bars and extensive lateral and point bars are seen at Site 6
while Site 4d lacks these features (compare Figs. 5.9a and 5.10a). The overall structure of
the channel bed is riffle-pool. The width-depth ratio of the bank-full channel varies
between 18-25 and scales with the bed-load concentration. Under supply-limited
conditions, glacial clay or bedrock is readily exposed in channel pools and may make up
the majority of the channel bed. Channel stability was not examined in detail for this
study, but based on aerial imagery, Site 6 appears to be much more active than Site 4d.
This is evident in Figures 5.9 and 5.10 where vegetation along the channel grows almost
up to the low-flow level at Site 4d but a large unvegetated buffer exists at Site 6. The
suspected reasoning behind this is that the channel at Site 6 is cut into relatively erodible
alluvium, which allows the channel to migrate more easily than at Site 4d, which is
bound by resistant glacial clay. Consequently, vegetation has sufficient time to colonize
the channel margins.
Floodplains developed by this channel type tend to form through a combination of
lateral and vertical accretion (Figs. 5.9 and 5.10). At Site 4d, large-scale sediment
mobility exposes glacial clay along the outer half of the channel where a patchy coarse
gravel and cobble lag forms. Advancing overtop of the lag is a moderately dipping (13)
sandy, fine-medium gravel point bar that tends to gently fine upwards reflecting a lateral
76
fining trend towards the inner bank of the channel (Fig. 5.11). The surface of the point
bar tends to be exposed at low-flow revealing a dominantly sandy to fine gravely texture.
Figure 5.9 - Field image taken during the summer (a) and idealized schematic cross-section (b) of the medium energy channel-floodplain type (Site 4d). The flow direction is given by the white arrow and the direction of channel migration is the same as the cross-section.
77
Figure 5.10 - Field image taken during the summer (a) and idealized schematic cross-section (b) of the medium energy channel-floodplain type (Site 6). The flow direction is given by the white arrow and the direction of channel migration is the same as the cross-section.
Similarly, point bars and lateral bars at Site 6 possess a comparable accretionary
angle, though typically less than Site 4d, and exhibit a lateral gradation of sediment
consisting of medium gravel near the channel floor that fines towards the inner margin of
the channel. Bar surfaces at Site 6 consist of a mixture of gravel and sand, and are often
much more extensively sub-aerially exposed during low-flow, which is a result of higher
sediment supply and channel mobility than at Site 4d. Medial bars, though observed, are
rare, and form through vertical accretion onto stalled gravel slugs (Miall, 1996).
Overlying bar deposits at both sites are vertically accreted massive sands
deposited during overbank flooding that may weakly fine upwards. Return periods for
overbank flooding varies between 2-5 years. Where return periods are long, such as at
Site 6, individual flood layers may be evident separated by thin incipient soils with
rootlets, which represent periods of little flooding (Fig. 5.12b). Overbank deposits may
Figure 5.11 - Characteristic floodplain stratigraphy of the medium energy type based on S4-B3 (a) and S4-P1 (b).
Figure 5.12 - Characteristic floodplain stratigraphy of the medium energy type based on S6-B1 (a) and S6-C2 (b).
80
contain shells and occasional small pebbles. The thickness of the deposits varies with
sediment supply such that Site 6 has thicker overbank deposits than Site 4d.
The style of floodplain development described for this type is in good agreement
to that suggested by Nanson and Croke (1992), and exemplifies the overall point bar
morphology and sedimentology of other gravel-bed meandering rivers described in the
literature (Wolman and Leopold, 1957; Bluck, 1971; Jackson, 1976). Nevertheless,
differences between the sites described here and observations along other rivers exist.
Most notably, the lack of observed sedimentary structures compared to conventional
point bar models (Bluck, 1971; Jackson, 1976; Miall, 1996). Whether sedimentary
structures exist and were destroyed during the falling stages of floods or were just not
apparent during the field campaign remains uncertain.
Post-settlement alluvium (PSA) was observed at both sites, though is thicker and
more extensive at Site 6 due to a greater fine sediment supply from upstream. PSA was
distinguished from paleosols based on its light tan or grey colour, which is indicative of
lower organic contents, compared to the organic-rich brown colour of paleosols. The
presence of rootlets also indicates paleosol formation. Mahaney et al. (1989) documented
paleosols farther downstream of Site 6 but at approximately the same stratigraphic
position as that shown in Figure 5.12a. Radiocarbon dates for these paleosols are not
precise but are thought to have developed within the last one hundred radiocarbon years
(Mahaney et al., 1989). This is confirmed by an underlying radiocarbon date retrieved
from the lower sand unit (140 30 BP, Table 5.4), which indicates that the paleosol at
Site 6 had formed shortly before European settlement and that the floodplain is quite
young compared to the previously described sites.
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Of particular interest is the difference in boundary conditions between sites 4d
and 6. As shown in Figures 5.9 and 5.10, Site 4d is underlain by glacial clay while Site 6
is underlain by alluvium. A sediment core taken from the floodplain of Site 6 allows for a
much more extensive interpretation of the underlying floodplain deposits, which may
provide an explanation on why alluvium, instead of glacial clay exists (Fig. 5.13).
Though basal gravels were never reached to a core sampling depth of 3.7 metres, the
bottommost part of the core is believed to represent a relic floodplain surface on the basis
of its brown colour. A small pebble was found within these deposits, which may indicate
high-energy conditions. Overlying this surface is a succession of three, possibly four,
coarse sand and granule deposits representing a channel environment separated by graded
silt-sand deposits indicative of overbank deposition. The basal contact of the inferred
channel deposits with the underlying overbank deposits are abrupt and perhaps erosional
in nature, while the contacts within individual overbank-channel couplets tend to be
either abrupt or diffuse. The uppermost channel-overbank sequence underlies the pre-
settlement paleosol and post-settlement alluvium discussed previously. The present day
floodplain surface is approximately 4 metres above present day Lake Ontario water levels
suggesting that the thick, multi-story floodplain deposits underlying the present-day
channel may be a result of aggradation following lake level rise during the mid- to late-
Holocene (Weninger and McAndrews, 1989; Anderson and Lewis, 2012).
5.6 High Energy Type
The high energy channel-floodplain type is characterized by Site 5 and shown
schematically in Figure 5.14. Characteristic specific stream powers are approximately 80
Wm-2 but higher values (~100 Wm-2) are expected in the steeper sections of the channel
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Figure 5.13 – Extended floodplain stratigraphy of Site 6 based on S6-C1.
83
downstream of Site 5. Much like Site 6, this channel type is dominated by well-defined
lateral, point, and medial bars along the channel, which is a product of widespread bed
sediment mobility. The spatial extent of the bar-forms is dictated by the supply of the
coarse gravel from valley sides and upstream. Bed material is dominantly gravel-cobble
derived from valley sides. The bed structure is dominantly riffle- pool, however in higher
energy sections not studied here, segments of run-pool morphology were observed.
Figure 5.14 - Field image taken during the summer (a) and idealized schematic cross-section (b) of the high energy channel-floodplain type. The flow direction is given by the white arrow and the direction of channel migration is the same as the cross-section.
The plan-form of the channel takes on a low sinuosity course with variable lateral
and point bars, while medial bars are less prominent. The plan-form is comparable to
gravel meandering and wandering type 1 channels reported in the literature (Lewin, 1976;
Forbes 1983; Carson, 1986; Miall, 1996) and predictions agree well with observations
(Fig. 5.2). While bar-forms within this type are the most spatially extensive and
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developed within the watershed, they are generally smaller than other gravely
meandering channels owing to the limited sediment supply inherent in semi-alluvial
basins. Due to pervasive bed-load sediment mobility and comparatively large supply,
bank-full width-depth ratios are around 25, which are comparable to the meandering
gravel-bed rivers described by Carson (1986). The channel is often confined within a
narrow (<40-50 metres wide) floodplain bound by terraces 2-6 metres high composed of
glacial clay. As a result, channel migration is limited and likely gradual.
Glacial clay often floors the low-flow channel and is composed of patchy gravels
and cobbles, though the degree to which clay is exposed is dependent upon sediment
supply and the angle of the channel bend. Sandy gravel point bars described previously
for Site 4d (medium energy) were observed at Site 5, though it is not clear how
prominent they are, and likely decrease in importance with increasing stream power.
Large gravel bar-forms are typically horizontally-bedded and consist of a coarse gravel-
cobble framework from which imbricated gravel of various sizes are deposited over,
producing a weakly defined upward fining trend (Fig. 5.15). Gravel point bars and lateral
bars often possess low accretionary angles (5º) dipping towards the channel and in some
places across the entire channel. Clay till rip-up clasts from the channel bed may also be
found within bar deposits. Overbank deposits tend to be much thinner than bar deposits
and consist of massive sand vertically accreted onto the bars during overbank flooding,
which recurs about 3 years. Upward grain size trends are inconsistent as both normal and
inverse grading conditions were documented. The existence of the occasional gravel clast
within the sand stratum indicates periodic energetic overbank flows onto the floodplain.
Figure 5.15 - Characteristic floodplain stratigraphy of the high energy type based on S5-B1 (a) and S5-P2 (b).
86
Based on the bank-full specific stream power, floodplain development here
should be comparable to that of wandering and braided channels as per Nanson and
Croke’s (1992) classification scheme. Braided and wandering rivers develop their
floodplains predominantly through channel avulsion and abandoned channel accretion,
and vertical accretion of fine overbank sediment. Additionally, wandering rivers also
experience lateral accretion of gravely point bars. The inferred floodplain formative
processes at Site 5 diverge from those described for braided and wandering rivers. While
accretion of abandoned slough channels may occur episodically, floodplain development
at Site 5 is thought to occur through the progressive lateral accretion of gravel point bars
behind the laterally migrating channel and vertical accretion of overbank sand. The
incidence of channel avulsion is not known but may be limited due to floodplain
confinement, vegetated floodplains, infrequent bank-full flooding, and observed channel
down-cutting.
Comparisons of the stratigraphy for Site 5 with Miall’s (1996) idealized
stratigraphic logs for gravel meandering, wandering, and braided channels reveal broad
similarities in sediment facies, though his models include structured sand facies, often
seen in such rivers (e.g. Forbes, 1983; Desloges and Church, 1987; Brierley, 1989), that
were not observed here. Floodplain stratigraphy for a braided gravel-bed river described
by Reinfelds and Nanson (1993) conforms well with the floodplain deposits at Site 5 in
terms of sediment facies, lack of structures in the overbank fines, alluvial thickness, and
relative thickness of the overbank fines to the bar deposits suggesting that depositional
processes are similar.
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5.7 Equilibrium Morphology Prediction
One method in assessing whether the channels have reached an equilibrium form
with the controlling variables is to predict the channel dimensions using regime relations
and analyze why the channels deviate from the predicted values. An important
consideration is the selection of regime relations to be used. As discussed in Chapter
Two, empirical relations are often used but lack the physical justification to explain the
resulting channel forms and are often developed under limiting constraints, such as
specific hydro-climatic regions. Moreover, if the goal is to predict equilibrium
dimensions, then empirical relations introduce the uncertainty that the data the relations
were derived from are, themselves, in equilibrium. Rational regime relations do not suffer
these issues as they are developed from physical relations instead of empirical data.
A second consideration is the appropriateness of using bank-full discharge for the
determination of channel dimensions. Since the bank-full discharge was determined from
the dimensions themselves, predicting the dimensions based off of bank-full discharge
would be circular. This argument has been raised by Ferguson (1986) and it has been
suggested that a frequency-based discharge be used instead since such a discharge would
be independent of the channel dimensions. In spite of this concern, however, many
regime relations developed still utilize bank-full discharge in their formulation.
Millar (2005) developed a set of theoretical rational regime relations based upon
the Maximum Transport Efficiency extremal hypothesis, which states that under the
constraints of discharge, grain size, bank vegetation, and channel slope, the channel will
adopt a preferential pair of stable dimensions in order to transport the given sediment
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supply without long-term deformation of the channel bed through erosion or deposition.
His relations for bank-full width (wbf, m) and depth (dbf, m) are given as
0.70 -0.75 0.60 -1.10bf bf 50 Cw = 6.23Q D S μ’ 5.1
0.16 0.60 -0.62 0.64bf bf 50 Cd = 0.10 Q D S μ’ 5.2
where Qbf is bank-full discharge (m3s-1), SC is the channel slope (-), D50 is median bed-
material size (m), and μ’ is a dimensionless index value for bank strength relating the
relative resistance of the bank to the channel bed. A value of 1 indicates equal resistance,
while any value greater than 1 represents the effects of increasing vegetation density.
Theoretically, values cannot be below 1. Since bank strength cannot easily be measured
in the field, it was set to 1 and the other variables substituted into the relations to derive
the theoretical equilibrium channel morphology.
The results of this analysis show that there is a fairly even split between under–
prediction and over-prediction for both width and depth for the study sites (Fig. 5.16). In
their analysis on gravel-bed rivers, Parker et al. (2007) attributed deep and narrow
channels to dense bank vegetation and/or a decrease in sediment supply to the channel
from upstream or from eroding banks, though the two are often inter-related. Back-
calculating the bank strength indices using bank-full discharge, channel slope, median
grain size, and the field-measured width-depth ratio of the channel (as per Millar’s (2005)
guidelines) reveals values varying between 0.42 and 1.94 (Table 5.5). The values
calculated for sites 2, 3, 5, and 6 are in agreement with field-observed vegetation patterns
where Site 3 is dominated by grass (low bank strength) and Site 2 consists of root-
dominated banks (high bank-strength). Sites 5 and 6 are in between with more grasses
than trees lining the banks. The remaining sites, however, are in disagreement with their
89
Figure 5.16 - Comparison of field-derived channel widths (a) and depths (b) against predicted rational regime dimensions. Error bars around the field-derived measurements are one standard error. Site numbers given for reference.
calculated indices and sites 1 and 4u are drastically different. While it could be argued
that the poor prediction achieved at Site 1 is a result of the channel bed having a mixed
sand-gravel composition, which the relations were not necessarily designed for, Site 3
possesses a finer median bed grain size and was well predicted. Since, in theory, bank
strength values cannot be below 1, the calculated bank strength values in Table 5.5 may
90
indicate the presence of disequilibrium forms at sites 1 and 4u, and perhaps less so for
Site 4d.
Site Bank Strength Index Vegetation Conditions 1 0.43 Grasses, shrubs, and minimal trees 2 1.93 Thick forest canopy, shrubs, and dense rooting 3 1.07 Grasses
4u 0.42 Thick forest canopy, shrubs, and dense rooting 4d 0.94 Grasses, shrubs, and trees on outside bank 5 1.29 Grasses, shrubs, and some trees 6 1.28 Grasses, shrubs, and some trees on outside bank
Table 5.5 - Relative bank strength values and associated vegetation conditions of the study sites.
The dimensions predicted by Equations 5.1 and 5.2 are based on the discharge,
vegetation, grain size, and slope constraints inputted into them. More fundamentally,
however, these dimensions are based on maintaining the capacity to transport the
sediment supply at bank-full discharge. Since the capacity to transport a given supply of
sediment depends upon the channel slope and discharge, the predicted and observed
dimensions can be viewed as a balance between the erosional resistance of the channel
bed versus the erosional resistance of the channel banks. The erosional resistance of the
channel bed can be represented by the dimensionless shear stress (τ*), defined as
* h C
s 50
ρgR Sτ =
(ρ - ρ)gD 5.3
where ρ is the density of water (1000 kgm-3), ρs is the density of sediment (2650 kgm-3),
g is the gravitational acceleration (9.81 ms-2), Rh is the hydraulic radius of the channel
(m), SC is the channel slope (-), and D50 is the median grain size of the channel bed (m).
When relative bank strength values are plotted against the dimensionless shear stress a
strong positive correlation is observed where μ’ values of 1 or greater are associated with
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dimensionless shear stresses above 0.03 (Fig. 5.17), which is often regarded as the lower
limit for sediment mobility (Buffington and Montgomery, 1997).
Figure 5.17 - Relationship between relative bank strength and dimensionless shear stress of the study sites.
The rationale behind this trend is that as the banks become increasingly resistant
to erosion due to increasing vegetation density, the channel is able to maintain high
dimensionless shear stresses without widening (Parker et al., 2007). Should the
vegetation be removed, the banks would become more erodible than the bed and the
channel would widen and shallow, lowering the erodibility (ie. dimensionless shear
stress) of the channel bed and reducing the relative bank strength to a value closer to 1.
This control that vegetation exerts on the channel dimensions explains why sites 2, 5, and
6 are deeper and narrower than predicted.
Bank strength values below 1, however, suggest that the channel banks are more
erodible than the channel bed and coincide with a dimensionless shear stress 67% less
than critical. As the dimensionless shear stresses are less than critical under the present
channel depths at sites 1 and 4u, the necessary channel depths to transport the bed
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material given the present discharges and channel slopes must be much higher, and
consequently, the channels must be narrower. The calculated dimensions, however, have
not been attained, perhaps due to the dimensions not being physically stable enough, and
preferential erosion of the channel banks (despite being root-reinforced at Site 4u)
maintains wider and shallower channels than predicted, and ultimately results in a
mismatch between the transport capacities and the bed material at these two sites.
Based on the preceding analysis, it is suggested here that since the channel
dimensions at sites 2, 3, 5, and 6 can be well predicted, they are in equilibrium with the
prevailing hydrological and sediment conditions, while sites 1 and 4u are not. These two
sites are presently experiencing a mismatch between the sediment size along the channel
bed and the capacity to transport it, which stems from flatter slopes than necessary for
transport. Ferguson (1981) has classified this state as ‘persistent passive disequilibrium’.
Such channels have inherited their bed material and slopes from past channel states but
are incapable of modifying them under present hydrological conditions.
Using a classification scheme presented by Renwick (1992), persistent passive
disequilibrium may be comparable to a threshold-dominated non-equilibrium state,
whereby the channel is inactive until a threshold is crossed, rejuvenating the channel. In
the case of sites 1 and 4u, rejuvenation may be achieved through either a drastic increase
in discharge or an increase in channel slope. Site 4d may have undergone rejuvenation
through channel slope steepening, as the channel slope increases by 150% downstream of
Site 4u. This steepening is reflected in the dimensionless shear stress at Site 4d, which is
higher than upstream. However, the relative bank strength value is below 1, while the
93
vegetation conditions suggest it should be closer to sites 5 and 6. It is thought that Site 4d
is adjusting towards an equilibrium state but has not had enough time to reach it.
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Chapter Six: Downstream Organization of Fluvial Form, Process, and Character 6.1 Spatial Distribution of Channel-Floodplain Types
Using the specific stream power values associated with each channel-floodplain
type, it is possible to broadly assess their spatial distributions within the watershed. A
map of the downstream variation in specific stream power (ω2) was constructed (R.
Phillips, personal communication) based on the relation
2 C2
bf
ρgQ Sω =
w 6.1
where ρ is the density of water (1000 kgm-3), g is gravitational acceleration (9.81 ms-2),
Q2 is the 2-year discharge (m3s-1), SC is the channel slope (-), and wbf is the bank-full
channel width (m). Bank-full width and discharge were estimated using regional rating
curves with drainage area (Ad, km2) given respectively as
0.50bf dw = 1.20A 6.2
0.912 dQ = 0.25A 6.3
Channel slope was derived by extracting the longitudinal profile from a 10-metre
digital elevation model and applying a moving window to smooth out artefacts within the
data. Drainage area was calculated through the D8 flow accumulation algorithm, which
measures the number of contributing upstream cells at any given point along the flow
path. Each cell represents 100 m2 of drainage area and the lower limit of the flow path
(and thus the start of the longitudinal profile) was 2 km2. While these values are not an
entirely accurate representation of bank-full specific stream power, the downstream
variation within the values are expected to be a reasonable reflection of the variation in
bank-full values.
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The downstream variation in calculated specific stream power shows that the
highest values are located in the downstream end of the watershed while the upper half
possesses the lowest values (Fig. 6.1). From this, it is apparent that the upper half of the
watershed upstream of Site 4 is dominantly low energy and mixed energy channel-
floodplain types though the medium energy type may exist, while the lower half
downstream of Site 4 is dominated by the medium and high energy types. This pattern is
opposite to what is typically found in watersheds and, since channel slope largely drives
the spatial distribution of specific stream power, this is a reflection of the large increase
in slope along the downstream half of the longitudinal profile (Fig. 6.2).
The role that glacial landform inheritance and geomorphic history plays in
influencing the channel slope, and thus the distribution of fluvial form, is illustrated in
Figures 6.1 and 6.2. The low stream powers characterizing the upper half of the
watershed seem to largely stem from the prevalence of glaciolacustrine plains, which the
channel flows over. Low discharges, however, are largely responsible for maintaining
moderate to low stream power values where slopes are steeper, which are a consequence
of the channel passing over moraines or through ridges (possibly small moraines)
separating successive glaciolacustrine deposits. Conversely, high stream powers
downstream are driven by channel incision due to post-glacial isostatic rebound and
prehistoric lake level fluctuations in Lake Ontario (Anderson and Lewis, 2012).
6.2 Downstream Organization of Watershed Zones
The study sites were broadly classified as production, transport, and deposition
zones according to the qualitative criteria presented in Chapter Two (Fig. 2.5). To
measure channel confinement, a simple ratio of the width of the channel to the width of
96
Figure 6.1 - Downstream variation in specific stream power in relation to glacial landforms (courtesy of R. Phillips). Channel-floodplain types are listed with the study sites.
Figure 6.2 - Dominant glacial and post-glacial controls on the longitudinal profile. Selected well logs are given along the longitudinal profile to illustrate the downstream variability in glacial sediments and the relative degree of incision along the channel. Well logs were selected from the Ontario Ministry of Natural Resources Borehole Database Version 1.2 and supplemented with log descriptions of valley sides described by Karrow (1967) and Mahaney and Hancock (1993). The tops of the logs represent valley side topographic variations. Vertical exaggeration = 78x.
98
floodplain was used. Higher values mean that the channel is wide compared to the
floodplain. As a result, more opportunities for coupling with valley/terrace sides exist.
Overbank alluvium thickness and grain size values were taken from Table 5.1 and
floodplain ages were assigned based on radiocarbon dates presented in Chapter Five and
relative ages based on an analysis presented in Appendix F, section F.3.2. It should be
emphasized that the site classifications are subjective but do tend to conform to the broad
qualitative descriptions of each zone. For instance, low specific stream powers, sandy bed
material, and long term sediment storage on thick and old floodplains suggest that the
deposition zone is an appropriate classification for sites 1 and 3. Conversely, high
specific stream power coupled with high channel confinement, and a thin, poorly
developed floodplain suggest that Site 5 likely represents a production zone. The
remaining sites were classified as transport zone. These sites are more subjective since
they fall within the poorly defined area between the end member classifications.
However, their classification is based on low hillslope-channel coupling and moderate
specific stream powers. Channel beds are gravel to gravel-cobble indicating that sand is
carried through the system. Floodplain thickness is variable, indicative of variations in
upstream sediment sources.
The spatial distribution of the zones tends to suggest that both transport and
deposition zones exist in the upper watershed while the production zone exists in the
lower watershed (Fig. 6.3), which is the opposite of traditional watershed models. Since
high specific stream power and channel confinement are two dominant characteristics of
the production zone, there is no reason to suggest that the upper watershed has a
Figure 6.3 - Spatial distribution of inferred watershed zones for each study site. SSP = specific stream power; Con. Ratio = confinement ratio (bank-full channel width/floodplain width, both in metres); Bed Mat. = channel bed material composition; OB Thickness = overbank alluvium thickness; Fp Age = floodplain age. Vertical exaggeration = 78x.
100
production zone. If one does exist, it is likely very inefficient. Only along one stretch of
the channel length is the traditional production zone-transport zone sequence inferred and
that is the lowermost 8 kilometres of the river. Whether by coincidence or not, both of the
study sites (sites 5 and 6) within this stretch are suggested to be in equilibrium, while
many of the remaining sites are not. The inferred inverted and spatially variable
arrangement of watershed zonation likely explains the increasing or stable trends in
specific sediment yields with drainage area described in some southern Ontario
watersheds (Ashmore, 1993; Campo and Desloges, 1994; Church et al., 1999). The
following is proposed as a potential cause for these patterns. In the headwaters, due to
low stream power and little to no channel-hillslope coupling, sediment recruitment is
generally low. However, as the channel moves downstream and progressively becomes
more energetic and incised, the level of sediment recruitment increases. If the degree of
incision and channel slope steepening is faster than drainage area can increase
downstream, it is probable that specific sediment yield increases. Otherwise, a stable
trend might be observed indicating consistent downstream recruitment of sediment and/or
limited floodplain storage.
6.3 Downstream Trends in Channel and Floodplain Character
The inverted and spatially variable organization of the watershed zones raises the
question as to how channel and floodplain characteristics vary downstream and whether
they conform to expected downstream trends. Using data presented in Table 5.1, the
characteristics were plotted against downstream distance. Only the characteristics that
can be reliably compared against prior knowledge are reported in detail here. The
remaining characteristics are presented in Appendix E.
101
6.3.1 Channel Morphology
Standard hydraulic geometry relations for alluvial rivers suggest that bank-full
channel width, depth, and cross-sectional area increase downstream, with width
increasing marginally faster than depth (Leopold and Maddock, 1953). For the Little
Rouge River, bank-full channel width tends to show a strong increase downstream (Fig.
6.4). However, variation within this trend is evident, particularly between sites 2 and 3
where there is a downstream decrease in width, though this decrease is not significant (p
= 0.855). Depth, on the other hand, shows a lack of a downstream trend. Though a slight
deepening trend is detected, the relation is rather weak and the regression slope is not
significantly different from zero. Site 3, which is significantly deeper (p < 0.05) than the
other study sites, plots above the best-fit line. Channel adjustment at Site 3 appears to be
accommodated by a deepening of the channel rather than widening, which is in contrast
to the other study sites.
Figure 6.4 - Downstream variation in bank-full channel width, depth, and cross-sectional area. Error bars are given as one standard error. Study sites labelled for reference. Site 4 represents two data points (sites 4u and 4d).
102
The product of width and depth yields bank-full cross-sectional area, for which
the downstream trend is strongly positive. Variation exists within this relation with Site 6
showing a significantly larger (p < 0.05) channel area over a relatively small increase in
drainage area compared to Site 5. Sites 2, 3, and 6 all plot above the trend-line, which is
driven by large channel widths for sites 2 and 6, and a large channel depth for Site 3.
6.3.2 Channel Hydrology
It has conventionally been thought that bank-full discharge recurs at a periodicity
of 1-2 years on the annual maximum daily series (Wolman and Leopold, 1957). Since the
mean annual flood, which is the discharge approximated by the 2.33 year return period,
increases downstream in humid and temperate climates (Knighton, 1987), it logically
follows that bank-full discharge should increase downstream as well.
Overall, there is a moderate trend towards increasing morphological bank-full
discharge with distance downstream (Fig. 6.5). However, a 38% decrease in
morphological bank-full discharge exists between sites 2 and 3 despite a 237% increase
in drainage area. Since Figure 6.4 demonstrated that cross-sectional area increases in the
downstream direction, the trend in morphological bank-full discharge is necessarily
controlled by flow velocity, which was calculated by dividing the bank-full discharge by
the average cross-sectional area. Flow velocity shows an overall weak downstream
increase with the downstream decrease in bank-full discharge between sites 2 and 3
explained by a 61% decrease in bank-full velocity (Fig. 6.6).
6.3.3 Channel Bed Material Size
It is useful to view the downstream variation in channel bed material size as a
single measure, which is done using the sorting coefficient. Grain size sorting was
103
Figure 6.5 - Downstream variation in bank-full discharge.
Figure 6.6 - Downstream variation in bank-full velocity. calculated for each site based on the Inclusive Graphic Standard Deviation presented by
Folk and Ward (1957) and plotted on Figure 6.7a. In conventional grain size models,
whether through abrasion or size selective transport, the coarsest grain sizes decrease
104
Figure 6.7 - Downstream variation in grain size sorting coefficient (a) and various size fractions (b-g). Sites labelled for reference.
downstream quicker than the finest, which results in a downstream tightening of the grain
size distribution. Less dispersion within the distribution means that the grain sizes are
105
better sorted and one should expect to see a downstream decrease in the sorting
coefficient. Sorting coefficients along the Little Rouge River tend to exhibit this
downstream pattern where distributions evolve from very poorly sorted towards
moderately sorted (Folk and Ward, 1957), though considerable scatter is observed in the
upstream portion of the watershed and the slope of the regression is not significantly
different from zero at the 95% confidence interval. This trend is realized, however, not
from a decrease in the coarse fractions, which exhibit little downstream trend, but instead
a downstream increase in the fine fractions (Fig. 6.7b-g). Considerable scatter exists
within each fraction though, leading to poorly defined relationships and regression slopes
not significantly different from zero at the 95% confidence interval for any fraction. The
observed downstream trends in sorting and grain size fractions are a result of the presence
of sites 1 and 3, which consist of sandy-gravel bed material. Whether or not these trends
would persist with the inclusion of more sites in the upper portion of the watershed is not
certain.
6.3.4 Overbank Alluvium Thickness
The thickness of floodplain overbank alluvial deposits is typically thought of as
the boundary between gravel and sand. This discrimination may be true for higher energy
sites but is less true for sites where sand forms a component of the channel bed. In these
sites, the boundary between channel and overbank deposits is less obvious. As such,
overbank deposits may be over-estimated in some cases. Based on bank exposure S4-B2,
Site 4 may be over-estimated by up to 20%. At sites 1 and 6, where over-estimation
interferes with the accurate representation of the downstream trend, overbank estimates
are based on the inferred depositional environments shown for their respective sediment
106
logs. At Site 1, the boundary between channel and floodplain deposits could only be
distinguished in one sample. Accordingly, a value of 45 cm was assigned to the site so as
to not over-estimate the overbank thickness, which otherwise may have been over-
estimated by up to 100%.
Due to its complex geomorphic history, perhaps more so than the other sites, the
sub-2mm thickness at Site 6 ranges from 95 cm to over 380 cm. While the latter value is
believed to be more representative of the site based on auger holes, cores, and banks
analyzed, closer inspection of sediment cores taken from the floodplain reveal that much
of this sediment includes several fining upward trends thought to be indicative of
multiple episodes of channel and floodplain aggradation (Fig. 5.13). In order to be
comparable to the other sites for analysis, only the overbank deposits deposited under the
present energy conditions of the channel (ie. specific stream power) were included in the
analysis. The uppermost overbank sequence was chosen for this purpose, which was
estimated to be approximately 112 cm based off of S6-C2 (Fig. 5.12b) and a cut-face not
presented here.
Plotting overbank thickness against distance downstream reveals no overall
downstream trend and a large degree of scatter about the trendline (Fig. 6.8). The
floodplain tends to become thicker downstream, consistent with conventional thought,
peaking at Site 3. However, downstream of Site 3 there is an 86% reduction in thickness,
which is followed by a second peak at Site 6.
107
Figure 6.8 - Downstream variation in floodplain overbank alluvium thickness. Error bars represent one standard error. Error bars for sites 1 and 6 are not reported due to a lack of suitable data.
6.3.5 Summary and Controls
The downstream trends described above, including those in Appendix E, are
summarized in Table 6.1. While there appears to be some agreement with the expected
downstream trends, in many cases the agreement is rather tenuous as indicated by the r2
values of the trendlines and regression slopes are often not significantly different from
zero. This is a consequence of both the variation within the watershed and the emphasis
on sampling sites of contrasting characteristics instead of systemic downstream sampling.
Despite this latter point, these trends are believed to be representative of the watershed. In
more than half of the variables, the observed trend is opposite of what is expected.
Morphological and hydrological variables appear to most generally conform to expected
downstream trends while sedimentological variables tend to exhibit the most departure.
At a very broad scale, the downstream trends reflect the assertion that the watershed is
arranged in a spatially variable but generally inverted manner.
Characteristic Expected Trend (Source) Observed Trend (r2) Controls Channel Morphology Bank-full Width Increasing (Knighton, 1987) Increasing (0.91)** Discharge (+), channel slope (+), large woody debris (+),
boundary resistance (-) Bank-full Depth Increasing (Knighton, 1987) Increasing (0.05) Discharge (+), channel slope (-), large woody debris (+),
boundary resistance (-) Bank-full Cross-sectional Area Increasing (Knighton, 1987) Increasing (0.93)** Discharge (+), boundary resistance (-), large woody debris
(+) Bank-full Width-Depth Ratio Decreasing? (n.a.) Increasing (0.74)* Channel slope (+), discharge (+/-), bed material size (+/-),
bed-load sediment supply (+), boundary resistance (-) Channel Sinuosity Increasing? (n.a.) Decreasing (0.19) Channel slope (-), discharge (+/-), bed material size (-) Channel Hydrology Bank-full Discharge Increasing (Knighton, 1987) Increasing (0.81)** Not analyzed Bank-full Discharge Return
Period Increasing (Petit & Pauquet, 1997)
Decreasing (0.12) Channel slope (+), large woody debris (+), boundary resistance (-), hydrological regime (+/-)
Bank-full Velocity Increasing (Knighton, 1987) Increasing (0.35) Not analyzed Channel and Floodplain Sedimentology
Channel Bed Alluvium Thickness
Increasing? (n.a.) Increasing (0.28) Channel slope (-), discharge (-), sediment supply (+), geomorphic history (+/-), large woody debris (+)
Exposed Clay Percentage Decreasing (Montgomery & Buffington, 1997)
None (0.00) Channel slope (+), discharge (+), sediment supply (-), geomorphic history (+/-), large woody debris (-)
Bed Material Size Decreasing (Knighton, 1987) Increasing (0.02-0.37) Channel slope (+), glacial inheritance (+), large woody debris (-)
Sorting Coefficient Decreasing (Knighton, 1980) Decreasing (0.51) Channel slope (-), glacial inheritance (+/-), large woody debris (+)
Overbank Alluvium Thickness Increasing (Church, 2002) None (0.00) Channel slope (-), sediment supply (+), large woody debris (+)
Silt/Clay Percentage Increasing? (n.a.) Decreasing (0.35) Channel slope (-), large woody debris (+) Organic Content (Fp age) Increasing (Brown, 1990) Decreasing (0.86)** Channel slope (-), large woody debris (+), boundary
resistance (+)
109
Table 6.1 (previous page) - Observed downstream trends in various channel and floodplain characteristics compared against their expected trends. N.A. – No study was found suggesting any preferential downstream trend. Accordingly, a trend is indicated based on theoretical expectations. * – Regression slope significant at the 95% confidence interval. ** – Regression slope significant at the 99% confidence interval. Controls are listed with most important control first. + – An increase in the control variable results in an increase in the response variable. - – An increase in the control variable results in a decrease in the response variable. +/- – An increase or a qualitative change in the control variable results in either an increase or decrease in the response variable. See Appendix F for a full explanation of the controls.
The conventional controls on each of the characteristics in Table 6.1 were
examined in detail, the results of which are presented in Appendix F. To summarize that
analysis, channel slope acts as either a primary or secondary control for all of the
variables except bank-full cross-sectional area. The morphological and hydrological
variables tend to show the most conformity with expected downstream trends due to
discharge acting as a strong control, which increases downstream in watersheds of humid
and temperate climates regardless of how the watershed zones are organized. Increasing
channel slope along the lower half of the channel results in a reinforcement of channel
width and counteracts the positive effect that discharge has on depth. As a result, channel
width tends to show a strong downstream increase while channel depth shows no trend.
The effect of increasing channel slope downstream can be seen in the width-depth ratio
and channel sinuosity, which are strongly related to channel slope. Channel boundary
resistance and large woody debris play smaller roles in morphological and hydrological
control.
Sedimentological variables, on the other hand, show the most scatter and
departure from expected trends due to a suite of various co-dominant controls including
channel slope, upstream sediment supply, and geomorphic history, among others. The
complexity in the spatial arrangement of sediment sources, the degree to which the
channel is incised into them, and the variability of channel slope can easily be seen in
Figure 6.3. The effect of these various co-dominant controls is most pronounced in the
110
channel bed alluvium thickness and exposed glacial clay percentage. The remaining
variables are more dominantly controlled by channel slope, such that the channel bed
becomes coarser and the floodplain becomes thinner, coarser, and younger with
increasing channel slope, though scatter remains in some variables due to secondary
controls, such as upstream sediment supply, glacially inherited bed material, and large
woody debris.
111
Chapter Seven: Discussion and Conclusions 7.1 Reappraisal of the ‘Graded’ River Model for Non-Alpine Deglaciated
Watersheds
The traditional exponentially decreasing channel slope characteristic of graded
river channels is based on the idea that river channels originate in steep, mountainous
terrain and flow towards the ocean or some other spatially extensive base-level. This
rather generalized model is most applicable for large, high-relief watersheds where such
features often exist at the upper and lower ends of the watershed respectively, but not
applicable for many small, non-alpine, deglaciated watersheds where watershed relief is
often much lower and the channel slope is controlled by the spatial distribution of glacial
and geological landforms, bedrock outcroppings, and post-glacial processes, such that a
variety of non-graded longitudinal profile shapes are possible.
As the findings of this study reinforce the importance of channel slope in
controlling the spatial distribution of fluvial forms and the downstream trends of various
channel and floodplain characteristics, many of the results presented here may not be
easily transferable to watersheds within southern Ontario with different longitudinal
profiles than that of the Little Rouge River. Such watersheds likely exhibit their own
downstream trends in accordance with variations in channel slope, which may be further
confounded by watershed-specific variations in glacial sediment sources and other
controls. Analysis of other southern Ontario watersheds may reveal different downstream
trends and different channel and floodplain forms, but it is probable that the variability
within the watershed would be directly proportional to the complexity of the longitudinal
profile.
112
7.2 Summary of Findings
The existence of five channel-floodplain types are proposed for the Little Rouge
River watershed based on specific stream power and bed sediment calibre. Laterally
stable, low energy types tend to develop their floodplains through lateral accretion of
sandy and/or gravely bed-load accompanied by oblique accretion of sandy-silt deposits.
More dynamic, higher energy types are dominated by lateral accretion of sandy-gravel
point bars and vertical accretion of lateral and medial gravel bars, overlain by vertically
accreted sand. Their spatial distribution is broadly related to the distribution of specific
stream power, which is highest in the lower half of the watershed and lowest in the upper
half, counter to what is expected in conventional ‘graded’ rivers. Variations in specific
stream power are a result of high slopes downstream driven by base-level fluctuations
and low slopes upstream where the channel flows over glaciolacustrine deposits. The
spatial distribution of specific stream power and progressive downstream channel
entrenchment suggests that the watershed is organized in a spatially variable, but
generally inverted manner with the production zone near the lower end of the watershed
and the transport and deposition zones dominating the upper half of the watershed.
As a consequence of this inverted organization, downstream trends in various
channel and floodplain characteristics are found to be highly variable, but are more
conformable with expected trends for morphological and hydrological variables, whereas
sedimentological variables are inconsistent with conventional downstream trends.
Morphological and hydrological variables are strongly controlled by channel slope in
addition to discharge, though large woody debris and boundary resistance play smaller
roles. The large scatter observed for sedimentological variables is attributed to the highly
113
variable nature of glacial sediment sources and the variable degree to which the channel
is incised into these deposits, on top of the conventional relationships with channel slope.
Lastly, using a rational regime relation, it is suggested that the channel is in
various states of equilibria with the present hydrological regime, channel slope, and bed
material size. Four sites were found to be in equilibrium, while two are thought to be in a
state of persistent passive equilibrium where the bed material is too coarse for the channel
slope.
7.3 Future Research Considerations
Compiling data from additional study sites, with particular emphasis on the upper
half of the watershed, would allow for increased interpretative power for many of the
relationships and inferences made here. Furthermore, the longitudinal profile of the Little
Rouge River exhibits three incidences of the conventional graded profile separated by
two prominent inflection points. By increasing the number of data points, downstream
trends within each sub-profile can be assessed in addition to the full profile, which would
allow insight into how the various characteristics respond under graded conditions in
deglaciated watersheds. By adding additional sites, the range of, and variability within,
the channel-floodplain types may be broadened, which would allow for relative
abundances of each type to be calculated for the watershed to see if any particular types
are dominant. Examination of other southern Ontario watersheds may broaden the
inventory of fluvial styles in deglaciated watersheds.
Reconstruction of channel response to environmental change remains poorly
detailed for southern Ontario watersheds, particularly for smaller watersheds like the
Little Rouge. Reconstructing the chronologies of the Little Rouge River in both the
114
downstream and upstream ends of the watershed would be useful considering the variety
of depositional environments observed.
As has been described here previously, downstream fining trends in the bed
material are often thought to be disrupted by lateral inputs from glacial sediment sources.
However, the contribution of tributary inputs relative to glacial inputs in this disruption
remains unresolved for non-alpine, deglaciated watersheds. A further research
consideration might investigate how the grain size distribution of the bed material
changes downstream of confluences under various slope, drainage area, and bed material
conditions, and to what extent glacial valley side inputs alter these trends.
115
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Appendix A: Channel Morphology and Sedimentology
A.1 Bank-full Channel Width
Site Cross-Section 1 2 3 4u 4d 5 6
1 4.77 10.46 10.60 13.20 13.10 15.36 18.48 2 5.67 8.93 9.00 13.20 14.75 11.60 19.26 3 6.60 6.70 8.90 14.06 14.70 14.97 24.41 4 7.60 10.06 7.94 13.04 10.97 13.40 19.66 5 4.39 13.00 7.25 14.70 28.87 12.41 6 4.83 10.35 10.06 15.65 22.52 7 11.06 13.26 15.89 26.80 8 6.20 5.90 16.04 9 8.60 15.00 10 8.80 27.57 11 17.60
Average 5.64 9.42 9.11 13.38 13.64 17.45 20.51 Standard Deviation 1.24 2.03 2.25 0.46 1.65 5.55 4.67
Table A.1 - Bank-full channel width measurements in metres for each site.
A.2 Bank-full Channel Depth
Site Cross-Section 1 2 3 4u 4d 5 6
1 0.78 0.55 1.43 1.02 0.85 0.36 1.2 2 0.71 0.54 1.22 0.45 0.78 0.86 0.86 3 0.66 0.63 1.00 0.67 0.89 0.72 0.56 4 0.70 0.66 1.03 0.79 0.46 0.82 0.97 5 0.51 0.70 0.63 0.66 0.61 0.74 6 0.72 0.64 1.26 0.62 0.91 7 0.71 1.00 0.65 0.44 8 0.85 0.73 0.54 9 0.56 0.97 10 0.64 0.78 11 0.77
Average 0.68 0.65 1.04 0.73 0.73 0.70 0.81 Standard Deviation 0.09 0.09 0.27 0.24 0.18 0.17 0.26
Table A.2 - Bank-full channel depth measurements in metres for each site.
130
A.3 Channel Bed Alluvium Thickness
Site 1 2 3* 4u 4d 5 6*
# of Points 112 259 120 230 91 370 185 Total
Thickness 4238.66 11596.51 7017.7 8421.57 2378.95 18571.56 16820.45
Average 37.85 44.77 58.48 36.62 26.14 50.19 90.92 Standard Deviation
24.31 15.97 32.88 18.51 21.22 24.42 36.29
Maximum Value
122.00 85.00 143.30 84.30 80.40 104.97 164.60
Minimum Value
1.30 1.98 7.20 0.20 0.65 1.05 1.31
Table A.3 - Alluvium thickness measurements in centimetres for each site. 'Total thickness' refers to the sum of all points for all cross-sections at a site. Sites marked with an asterisk are known to possess large under-estimates.
A.4 Channel Bed Gravel Thickness
Site 1 2 3* 4u 4d 5 6
# of Points 112 259 120 230 91 370 155 Total
Thickness 3434.86 11596.51 7017.7 8421.57 2378.95 18571.56 5717.35
Average 30.67 44.77 58.48 36.62 26.14 50.19 36.89 Standard Deviation
21.97 15.97 32.88 18.51 21.22 24.68 22.63
Maximum Value
94.00 85.00 143.30 84.30 80.40 104.97 86.70
Minimum Value
1.30 1.98 7.20 0.20 0.65 1.05 1.18
Table A.4 - Gravel thickness measurements in centimetres for each site. Sites marked with an asterisk are known to possess large under-estimates.
A.5 Miscellaneous Alluvium Strata Thickness
Site (Sediment Unit) 1 (Organic Sand) 3 (Sandy Gravel) 3 (Gravel)* 6 (Sand)*
Number of Points 73 116 32 185 Total Thickness 803.80 5644.40 1268.40 11103.1
Average 11.01 48.66 39.64 60.02 Standard Deviation 11.48 25.13 5.47 37.00 Maximum Value 59.20 98.60 44.70 164.60 Minimum Value 0.20 1.00 33.90 1.31
Table A.5 - Alluvium thickness for strata that appear above or below the channel gravels, or channel gravels that can be differentiated. Sites marked with an asterisk are known to possess large under-estimates.
131
A.6 Percent Glacial Clay in Bank-full Channel
Site Cross-Section 1 2 3 4u 4d 5 6
1 37.74% U
0.00% U
0.00% U
3.79% P
15.27% P
0.00% R
0.00% R
2 0.00% U
0.00% U
0.00% U
0.00% R
0.00% R
42.59% P
0.00% P
3 15.15% U
0.00% U
41.57% U
0.00% R
53.74% P
5.08% R
0.00% R
4 0.00% U
0.00% U
0.00% U
0.00% P
20.05% R
26.64% P
0.00% P
5 0.00% U
0.00% U
0.00% U
0.00% R
40.82% P
0.00% R
0.00% R
6 37.27% U
0.00% U
0.00% U
40.52% P
29.84% P
7 0.00% U
0.00% U
9.44% R
0.00% R
8 41.95% P
0.00% U
24.28% P
9 0.00% R
6.67% R
10 0.00% P
7.98% P
11 13.07% R
Average 15.03% 4.19% 5.20% 0.76% 25.98% 16.02% 4.26% Standard Deviation
18.37% 13.26% 14.70% 1.69% 21.31% 15.25% 11.28%
Table A.6 - Percentage of the bank-full channel that is occupied by glacial clay/bedrock.
R = riffle, P = pool, and U = undifferentiated bed-form.
A.7 Channel Bed Material Grain Size Characteristics Site
1 2 3 4u 4d 5 6 Dmax 1110 940 340 960 1260 2500 670 D95 55.72 157.59 36.00 142.02 132.51 187.4 61.82 D84 29.04 97.01 19.84 102.54 93.70 107.63 48.84 D50 7.46 35.51 3.36 61.82 56.10 53.82 30.91 D16 0.32 8.00 0.30 30.06 32.90 24.25 17.15 D5 0.07 4.76 0.10 14.83 21.11 12.13 8.00
Table A.7 - Grain size characteristics of the bed material. Values are in millimetres.
132
A.8 Grain Size Distribution of the Channel Bed Material
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
0.01 0.1 1 10 100
Grain Size (mm)
Per
cen
t F
iner
Composite
Sample 1
Sample 2
Sample 3
Figure A.1- Grain size distribution for Site 1 showing individual sample distributions and the composite distribution.
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
1 10 100 1000 10000
Grain Size (mm)
Per
cen
t F
iner
Composite
Sample 1
Sample 2
Sample 3
Sample 4
Sample 5
Figure A.2 - Grain size distribution for Site 2 showing individual sample distributions and the composite distribution.
133
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
0.01 0.1 1 10 100
Grain Size (mm)
Per
cen
t F
iner
Composite
Sample 1
Sample 2
Sample 3
Sample 4
Figure A.3 - Grain size distribution for Site 3 showing individual sample distributions and the composite distribution.
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
1 10 100 1000
Grain Size (mm)
Per
cen
t F
iner
Downstream
Upstream
Sample 1
Sample 2
Sample 3
Sample 4
Sample 5
Figure A.4 - Grain size distribution for Site 4d and 4u showing individual sample distributions and the composite distribution.
134
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
1 10 100 1000 10000
Grain Size (mm)
Per
cen
t F
iner Composite
Sample 1
Sample 2
Sample 3
Sample 4
Sample 5
Sample 6
Figure A.5 - Grain size distribution for Site 5 showing individual sample distributions and the composite distributions.
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
1 10 100 1000
Grain Size (mm)
Per
cen
t F
iner
Composite
Sample 1
Sample 2
Sample 3
Sample 4
Figure A.6 - Grain size distribution for Site 6 showing individual sample distributions and the composite distribution.
135
Appendix B: Floodplain Sedimentology
B.1 Floodplain Overbank Alluvium Thickness
Site Pit/Auger Hole 1 2 3 4u 4d 5 6
1 103* 100 111 54 51 33 95 2 94* 51 157 82* 31 36 292* 3 97* 72 165 41 68 19 4 92* 98 41 81 25 5 120* 97 13 6 88* 8 7 9 8 5 9 10
Bank Section 1 72 145 97* 58 44 262*† 2 94 22 255*†
Core 1 372*† 2 372*†
Average 99.00 81.67 144.50 63.00 64.00 20.36 274.67Standard Deviation 11.45 19.83 23.8 25.33 22.31 15.56 102.05
Table B.1 - Thickness of overbank sediments from pits, auger boreholes, bank analyses, and sediment cores in centimetres. Values marked by an asterisk give probable over-estimates for overbank thickness as overbank deposits here are often indistinguishable from channel deposits or represent multiple channel-overbank sequences. Refusal, which formed the cut-off for what was considered possible overbank sediment, for these values was medium gravel, which is too large to be recovered in the ESP cores. † - refusal not reached.
B.2 Grain Size Analysis of Floodplain Samples
Sample Depth from Floodplain Surface % Gravel % Sand % Silt S1-AH1-A1 2.0 0.00% 26.49% 73.51% S1-AH1-A2 93.5 0.00% 53.19% 46.81% S1-AH3-A1 13.5 0.00% 14.53% 85.47% S1-AH3-A2 48.0 0.00% 37.30% 62.70% S1-AH3-A3 91.0 0.00% 66.29% 33.71% S1-AH5-A1 4.5 0.00% 33.81% 66.19% S1-AH5-A2 67.5 0.00% 23.41% 76.59% S1-AH5-A3 113.0 0.00% 37.72% 62.28%
Site 1 Average 0.00% 36.59% 63.41% Standard Deviation 0.00% 16.60% 16.60%
S2-B1-A1 30.0 0.00% 38.38% 61.62% S2-B1-A2 56.0 0.00% 50.57% 49.43%
S2-AH1-A1 4.5 0.00% 44.02% 55.98%
136
S2-AH1-A2 50.0 0.00% 41.86% 58.14% S2-AH1-A3 79.5 0.00% 63.31% 36.69% S2-AH5-A1 4.0 0.00% 19.53% 80.47% S2-AH5-A2 43.0 0.00% 18.46% 81.54% S2-AH5-A3 93.0 2.61% 41.99% 55.40%
Site 2 Average 0.33% 39.76% 59.91% Standard Deviation 0.92% 14.95% 15.03%
S3-B1a 47.0 0.00% 34.07% 65.93% S3-B1b 87.0 0.00% 28.85% 71.15% S3-B1c 130.0 0.00% 27.71% 72.29%
S3-AH3-A1 4.5 0.00% 14.18% 85.82% S3-AH3-A2 79.5 0.00% 13.75% 86.25% S3-AH3-B1 127.5 0.00% 18.02% 81.98% S3-AH3-C1 192.0 0.00% 32.76% 67.24% S3-AH3-C2 259.0 0.00% 17.73% 82.27%
Site 3 Average 0.00% 23.38% 76.62% Standard Deviation 0.00% 8.36% 8.36%
S4u-B2-A1 13.0 0.00% 37.90% 62.10% S4u-B2-A2 40.0 0.00% 29.98% 70.02% S4u-B2-B 73.0 0.00% 56.44% 43.56%
S4u-AH4-A1 4.5 0.00% 38.32% 61.68% S4u-AH4-A2 51.5 4.48% 67.96% 27.56% S4u-AH5-A1 8.0 0.00% 52.25% 47.75% S4u-AH5-A2 78.0 0.00% 63.94% 36.06%
Site 4u Average 0.64% 49.54% 49.82% Standard Deviation 1.69% 14.41% 15.43%
S4d-P1-A1 14.0 2.12% 69.79% 28.09% S4d-P1-A2 43.0 0.27% 66.83% 32.90% S4d-B1-A1 14.0 0.00% 34.02% 65.98% S4d-B1-A2 50.0 0.18% 60.72% 39.11%
S4d-AH2-A1 4.5 0.43% 46.58% 52.99% S4d-AH2-A2 64.0 18.43% 33.65% 47.92%
S4d-B3-A 18.0 0.00% 36.56% 63.44% S4d-B3-B 51.0 0.00% 40.70% 59.30% S4d-B3-C 78.0 0.32% 65.43% 34.25%
Site 4d Average 2.42% 50.48% 47.11% Standard Deviation 6.04% 15.11% 14.14%
S5-B1-A1 9.0 0.00% 49.55% 50.45% S5-B1-A2 41.0 3.51% 64.71% 31.78% S5-AH8 4.0 1.24% 56.30% 42.46%
S5-P2-A1 8.0 0.00% 61.63% 38.37% S5-P2-A2 26.0 0.42% 67.36% 32.22% S5-P4-A1 10.0 0.00% 74.35% 25.65% S5-P4-A2 34.0 1.04% 50.30% 48.66%
Site 5 Average 0.89% 60.60% 38.51% Standard Deviation 1.27% 9.12% 9.23%
S6-1a 13.0 0.00% 34.27% 65.73% S5-1b 50.0 0.00% 53.26% 46.74% S6-1c 73.0 0.00% 15.51% 84.49% S6-1d 101.0 0.00% 30.83% 69.17%
137
S6-1e 137.0 0.00% 66.15% 33.85% S6-1f 162.0 0.00% 41.17% 58.83% S6-2a 18.0 0.00% 69.18% 30.82% S6-2b 90.0 0.00% 62.13% 37.87% S6-2c 124.0 0.00% 56.74% 43.26%
Site 6 Average 0.00% 47.69% 52.31% Standard Deviation 0.00% 18.26% 18.26%
Table B.2 - Crude grain size distribution of selected floodplain samples. Depth values are in centimetres.
B.3 Percent Organics in Floodplain Samples
Sample Depth from Floodplain Surface % OrganicsS1-AH1-A1 2.0 7.64% S1-AH1-A2 93.5 5.11% S1-AH3-A1 13.5 8.29% S1-AH3-A2 48.0 4.65% S1-AH3-A3 91.0 4.96% S1-AH5-A1 4.5 8.54% S1-AH5-A2 67.5 5.04% S1-AH5-A3 113.0 9.35%
Site 1 Average 6.70% Standard Deviation 1.94%
S2-B1-A1 30.0 5.42% S2-B1-A2 56.0 4.73%
S2-AH1-A1 4.5 8.19% S2-AH1-A2 50.0 4.42% S2-AH1-A3 79.5 2.49% S2-AH5-A1 4.0 6.91% S2-AH5-A2 43.0 5.07% S2-AH5-A3 93.0 1.79%
Site 2 Average 4.88% Standard Deviation 2.10%
S3-B1a 47.0 5.32% S3-B1b 87.0 2.94% S3-B1c 130.0 1.86%
S3-AH3-A1 4.5 11.30% S3-AH3-A2 79.5 3.71% S3-AH3-B1 127.5 3.05% S3-AH3-C1 192.0 2.83% S3-AH3-C2 259.0 3.25%
Site 3 Average 4.28% Standard Deviation 3.00%
S4u-B2-A1 13.0 6.78% S4u-B2-A2 40.0 5.10% S4u-B2-B 73.0 1.32%
S4u-AH4-A1 4.5 9.09%
138
S4u-AH4-A2 51.5 1.62% S4u-AH5-A1 8.0 4.80% S4u-AH5-A2 78.0 2.51%
Site 4u Average 4.46% Standard Deviation 2.86%
S4d-P1-A1 14.0 2.10% S4d-P1-A2 43.0 2.39% S4d-B1-A1 14.0 7.89% S4d-B1-A2 50.0 2.01%
S4d-AH2-A1 4.5 4.43% S4d-AH2-A2 64.0 2.59%
S4d-B3-A 18.0 6.42% S4d-B3-B 51.0 3.56% S4d-B3-C 78.0 1.48%
Site 4d Average 3.65% Standard Deviation 2.20%
S5-B1-A1 9 1.52% S5-B1-A2 41 1.15% S5-P2-A1 8 1.72% S5-P2-A2 26 1.71% S5-P4-A1 10 0.81% S5-P4-A2 34 1.92%
Site 5 Average 1.47% Standard Deviation 0.41%
S6-1a 13.0 2.65% S6-1b 50.0 1.17% S6-1c 73.0 2.38% S6-1d 101.0 1.74% S6-1e 137.0 0.84% S6-1f 162.0 1.95% S6-2a 18.0 1.24% S6-2b 90.0 1.09% S6-2c 124.0 1.19%
Site 6 Average 1.58% Standard Deviation 0.63%
Table B.3 - Percent organic content in selected floodplain samples based on loss-on-ignition method. Depth values are in centimetres.
139
Appendix C: Bank-full Discharge Formulae Analysis
The formulae presented in Chapter Four were tested against meandering gravel
and cobble-bed river data from Bray (1979), Church and Rood (1983), and Annable
(1996) to analyze how well each relation estimated bank-full discharge and if there was
any relation that was consistently better than the others. The results of this analysis are
presented in Tables C.1 – C.3. It should be noted that for the Bray (1979) data, D90 was
used instead of D84 and the values were tested against the 2-year discharge.
Williams (1978)
Lacey Limerinos-Manning
Darcy-Weisbach
Mean Error 15.08% 10.16% -5.25% 3.42% Standard Deviation 29.54% 31.25% 27.17% 27.70% Mean Absolute Error 22.25% 22.52% 22.67% 22.49% Standard Deviation 24.51% 23.80% 15.65% 16.29% Median Error 8.07% 1.32% -9.36% 7.66% Median Absolute Error 13.26% 13.98% 21.26% 20.54% Maximum Error 94.62% 121.21% 62.74% 61.98% Minimum Error -64.92% -59.57% -62.17% -65.79% 20% Error 67.16% 64.18% 46.27% 46.27% Underestimation 29.85% 47.76% 67.16% 34.33% Overestimation 70.15% 52.24% 32.84% 65.67%
Table C.1 - Statistics on errors for Bray (1979) data (n = 67).
Williams
(1978) Lacey Limerinos-
Manning Darcy-
Weisbach Mean Error 3.28% 12.38% 12.86% 15.09% Standard Deviation 29.93% 34.74% 46.93% 47.83% Mean Absolute Error 21.72% 27.19% 34.41% 35.15% Standard Deviation 20.73% 24.79% 34.24% 35.63% Median Error 0.02% 10.00% 1.92% 4.08% Median Absolute Error 14.76% 23.35% 25.77% 25.13% Maximum Error 105.47% 116.56% 190.60% 196.32% Minimum Error -52.52% -64.74% -79.51% -79.07% 20% Error 59.34% 46.15% 42.86% 42.86 Underestimation 49.45% 37.36% 48.35% 48.35% Overestimation 50.55% 62.64% 51.65% 51.65%
Table C.2 - Statistics on errors for Church and Rood (1983) data (n = 91).
140
Williams (1978)
Lacey Limerinos-Manning
Darcy-Weisbach
Mean Error 23.35% 33.36% 25.24% 27.71% Standard Deviation 37.44% 44.58% 51.88% 52.92% Mean Absolute Error 31.18% 38.76% 39.39% 40.56% Standard Deviation 30.94% 39.83% 41.83% 43.56% Median Error 15.48% 17.16% 8.53% 10.50% Median Absolute Error 20.41% 20.69% 22.90% 23.96% Maximum Error 118.42% 137.67% 157.41% 162.37% Minimum Error -30.90% -39.04% -54.00% -53.09% 20% Error 48.57% 48.57% 45.71% 42.86% Underestimation 22.86% 22.86% 40% 40% Overestimation 77.14% 77.14% 60% 60%
Table C.3 - Statistics on errors for Annable (1996) data (n = 35).
The data in all the tables have been stratified to determine which relation is the
best predictor. Bolded black numbers represent the best value, followed by blue, and
green. Red represents the worst value. It is a necessary requirement that the predictor
relation possesses the lowest errors in its estimates. Since mean and median errors can be
deceiving in that the underestimates tend to cancel out the overestimates, it was opted to
use the mean absolute error as a criterion for choosing the best relation. In all three
databases the Williams (1978) bank-full relation has the lowest error. However, only the
Church and Rood (1983) database demonstrates significant differences in mean absolute
errors between the four relations at the 95% confidence level, with the Williams (1978)
relation being significantly different from all the relations with the exception of the Lacey
relation (Tables C.4-C.7). Consequently, despite being the best predictor in this regard,
the Williams (1978) relation is not appreciably better consistently. Moreover, using the
median absolute errors in order to remove the effects of outliers reveals that the median
value in all three databases is 20% or less for the Williams (1978) relation, which is
comparable to the Lacey relation and less than the Limerinos-Manning and Darcy-
Weisbach relations.
141
Sum of Squares df Mean Square F Sig. Level Between groups 0.001 3 0.000 0.005 1.000 Within groups 11.069 264 0.042
Total 11.070 267
Table C.4 - Results of an analysis of variance test on the Bray (1979) dataset based on mean absolute error.
Sum of Squares df Mean Square F Sig. Level
Between groups 1.109 3 0.370 4.244 0.006 Within groups 31.367 360 0.087
Total 32.476 363
Table C.5 - Results of an analysis of variance test on the Church and Rood (1983) dataset based on mean absolute error.
Sum of Squares df Mean Square F Sig. Level Between groups 0.191 3 0.064 0.410 0.746 Within groups 21.050 136 0.155
Total 21.240 139
Table C.6 - Results of an analysis of variance test on the Annable (1996) dataset based on mean absolute error.
Relation 1 Relation 2 Significance Level
Williams (1978) Lacey 1.000 Limerinos-Manning 0.024 Darcy-Weisbach 0.014
Lacey Limerinos-Manning 0.599 Darcy-Weisbach 0.419
Limerinos-Manning Darcy-Weisbach 1.000
Table C.7 - Results of a Bonferroni post-hoc test on Church and Rood (1983) dataset.
Furthermore, one must take into consideration the variability in the errors with the
lowest variability being the most desirable. Many possible variables could be looked at
from the tables including standard deviation, the estimate extremes, or the percentage of
the values that are under-predicted versus over-predicted. The criterion selected for
variability was the percentage of the values within 20% of the reported discharge. On
average, between the three databases, 58% of the values for the Williams (1978) relation
fall within 20% above or below the reported discharge value, which is higher than the
other relations (Lacey: 53%, Limerinos-Manning: 45%, Darcy-Weisbach: 44%). In
142
regards to the other categories on variability mentioned above, the Williams (1978)
relation tends to, but not always, possess the best values such as the lowest extremes, the
lowest standard deviations, and the lowest under-/over-estimates, which help to further
solidify the selection of this relation. Moving forward with the Williams (1978) relation
as the bank-full discharge estimator for the current study, it should be considered that the
estimates will most likely be over-predictions given that the relation in all three databases
has a positive mean error and the majority of the distribution is overestimated. Using the
Williams (1978) relation, the average bank-full width and depth, and the surveyed
channel slope, the following bank-full discharge estimates were obtained, which compare
favourably with those predicted using the other relations (Table C.8).
Site 1 2 3 4u 4d 5 6 Width (m) 5.64 9.42 9.11 13.38 13.64 17.45 20.51 Depth (m) 0.68 0.65 1.04 0.73 0.73 0.70 0.81 Channel Slope 0.0002 0.0072 0.0002 0.0017 0.0043 0.0069 0.0035 Discharge (m3s-1) 1.87 8.95 5.57 10.59 14.02 20.55 24.64 Lacey Relation 1.66 8.85 5.47 9.73 13.45 19.14 22.95 Manning Relation 1.32 8.89 4.79 8.04 12.37 19.76 26.68 Darcy Relation 1.34 9.07 4.88 8.20 13.63 20.15 27.18
Table C.8 - Bank-full discharge estimates for the study sites. The channel slope of 0.0028 for Site 1 was found to be unacceptable as an estimate of the energy conditions and was replaced by an estimate of 0.0002 based on the surveyed water level, which was near bank-full stage.
143
Appendix D: Flood Frequency Analysis After initially screening 46 gauging stations in watersheds between the Niagara
Escarpment, Peterborough, Lake Ontario, and Lake Simcoe, 11 stations were chosen
within the vicinity of the Little Rouge watershed that were believed to produce similar
hydrological responses to the Little Rouge River. These 11 stations were chosen by
regressing their 2-year return period discharge, selected from a distribution-fitted annual
maximum series curve, against drainage area and selecting stations that form a trend with
the Little Rouge station. The chosen stations form the nucleus of the flood frequency
analysis and their basic characteristics are summarized in Table D.1.
Water Survey of Canada (WSC) Station Name
WSC Station ID
Drainage Area (km2)
Record Period Length (years)
Lynde Creek near Whitby 02HC018 106.0 1959 – 2010 52 Duffins Creek above Pickering 02HC019 93.5 1960 – 2009 50 Rouge River near Markham 02HC022 186.0 1961 – 2010 50 West Duffins Creek at Green River 02HC026 98.1 1963 – 1988 26 Little Rouge Creek at Locust Hill 02HC028 77.7 1963 – 2010 48 West Duffins Creek above Green River 02HC038 52.0 1974 – 2010 37 Duffins Creek at Ajax 02HC049 251.0 1989 – 2010 22 Bowmanville Creek at Bowmanville 02HD006 82.9 1959 – 2010 52 Oshawa Creek at Oshawa 02HD008 95.8 1959 – 2010 52 Wilmot Creek near Newcastle 02HD009 82.6 1965 – 2010 46 Harmony Creek at Oshawa 02HD013 41.6 1980 – 2010 31
Table D.1 - Gauging stations used in the flood frequency analysis.
Annual discharge data for each of the above stations were ordered from highest to
lowest and then fitted to the General Extreme Value (GEV) distribution for the annual
maximum series (AMS) daily and instantaneous values and the General Pareto (GP)
distribution for the partial duration series (PDS) maximum daily values (Kidson and
Richards, 2005). The formulae for each distribution are outlined below, summarized from
Glaves and Waylen (1997) and Adamowski et al. (1998).
144
General Extreme Value Distribution
The General Extreme Value distribution estimates discharge quantiles based on
the cumulative probability function and three site-specific parameters that characterize
the shape (skew), scale (variation), and the location (mean) of the distribution. The
formula for the distribution is outlined as
k
GEV
β 1- -ln pQ = ζ +
k
for k 0 D.1a
= ζ - βln 1 - ln(p) for k = 0 D.1b
where QGEV is the discharge, is the location parameter, is the scale parameter, k is the
shape parameter, and p is the cumulative probability of the quantile (ie. 1-exceedance
probability). The parameters can be estimated using L-moments, which are linear
combinations of ranked data (ie. annual floods) that are stated to be unbiased estimates
compared to product-moments since they do not need to be cubed or squared
(Adamowski et al., 1998). The formulae for calculating the parameters through L-
moments are
1
β Γ 1 + k - 1ζ = λ +
k
D.2
2-k
λ kβ =
1 - 2 Γ 1 + k D.3
2k = 7.859c + 2.9554c D.4
where 1 is the first L-moment, 2 is the second L-moment, is the gamma function, and
c is equal to
3 2
2 log(2) -
λ /λ + 3 log(3) D.5
145
with 2 and 3 representing the second and third L-moments respectively. The four L-
moments can be summarized as follows:
1 0λ = b D.6
2 1 0= 2b – bλ D.7
3 2 1 0= 6b – 6b + bλ D.8
4 3 2 1 0λ = 20b – 30b + 12b – b D.9
where 1-4 are respectively the mean, standard deviation, skewness, and kurtosis and, b0-3
are the probability weighted moments for the sample data. The probability-weighted
moments can be defined as:
n
jj=1
0
x
b = n
D.10
n - 1
1 jj = 1
n - jb = x
n n - 1
D.11
n - 2
2 jj = 1
n - j n - j - 1b = x
n n - 1 n - 2
D.12
n - 3
3 jj = 1
n - j n - j - 1 n - j - 2b = x
n n - 1 n - 2 n - 3
D.13
where xj is a value from the sample with rank j when the sample values are ranked from
highest to lowest, and n is the total number of values in the sample.
146
General Pareto Distribution
The General Pareto distribution is very similar to the GEV distribution above in
that it estimates discharge quantiles based on a cumulative probability function and three
parameters that characterize the distribution. The difference between the two is that the
General Pareto distribution is useful for partial duration series data as opposed to the
annual maximum series. In defining the database for the partial duration series, it is
necessary to establish a cut-off point for the inclusion of discharge values, which was
taken as the lowest discharge occurring on the annual maximum series. In this way, at
least one discharge value from each year in the record period will appear in the database
(Langbein, 1949). The General Pareto distribution can be defined as:
k
GP
α 1 - 1 - pQ = μ +
k
for k ≠ 0 D.14a
= μ – αln 1 – p for k = 0 D.14b
where QGP is the discharge estimate, μ is the location parameter, α is the scale parameter,
k is the shape parameter, and p is the cumulative probability of the discharge occurring
(ie. 1 – exceedance probability). The three parameters can be defined as:
12
2 + kμ = λ –
λ D.15
2α = 1 + k 2 + k λ D.16
3 2
3 2
1 - 3 λ /λk =
1 + λ /λ D.17
where λ1-3 are the first, second, and third L-moments from Equations D.6-D.8.
147
Following this, discharges for various return periods ranging from 0.5 years to 20
years were calculated for each station based on their maximum instantaneous (AMS) and
maximum daily (AMS and PDS) distributions. These values were then compiled and
regressed against drainage area to formulate regional discharge-drainage area rating
curves for each return period. The coefficients and exponents are listed in Table D.2.
The relations were tested against the Little Rouge at Locust Hill (used in the
development of the relations) and Duffins Creek at Pickering (not used in the
development; station ID 02HC006) stations to see how they performed. The results of the
gauging station analysis are mixed at best with the discharges of the Little Rouge River
being better predicted by the relations than for Duffins Creek (Tables D.3 and D.4).
Generally, the relations under-predict the discharges with the only exception being the
maximum instantaneous values for the Little Rouge. For the Little Rouge data, the best
predictor was the partial duration series relations, which had the lowest error values while
the maximum instantaneous relations generated the highest errors. While all three series
relations had very similar average error values for the Duffins Creek data, the partial
duration series relations tended to be more consistent than the other two. Despite the
predictions, the Little Rouge data typically lay within one standard error of the estimate
while the Duffins Creek data lay outside, particularly for values between 20 and 80 m3s-1
(Figs. D.1 and D.2). Whether or not the Duffins Creek station is an anomalous occurrence
is not known, but the results from this station are not as encouraging.
As to which series should be used for the estimate of bank-full discharge return
period, one must consider the reliability of the series and the range of return periods that
can be estimated. The preceding discussion already alluded to the partial duration series
148
as likely the most reliable. The value of the partial duration series over the annual series
is increased when the range of available return periods is considered, such that three extra
return periods are gained using the partial duration series. Furthermore, it was discovered
Series Return Period a b Standard Error of Estimate r2 AMS-MD 1.05 0.699 0.463 0.246 0.499
1.10 0.520 0.580 0.180 0.745 1.50 0.393 0.754 0.140 0.890 2.00 0.407 0.793 0.143 0.897 2.50 0.433 0.807 0.144 0.898 3.00 0.460 0.812 0.145 0.898 5.00 0.557 0.813 0.150 0.892 7.50 0.659 0.805 0.157 0.880 10.00 0.745 0.796 0.165 0.868 15.00 0.893 0.780 0.179 0.842 20.00 1.017 0.767 0.191 0.819
PDS-MD 0.50 0.279 0.697 0.255 0.677 0.75 0.296 0.749 0.198 0.800 1.00 0.318 0.770 0.182 0.834 1.05 0.322 0.773 0.181 0.837 1.10 0.326 0.775 0.179 0.840 1.50 0.356 0.789 0.172 0.856 2.00 0.389 0.797 0.168 0.863 2.50 0.417 0.801 0.166 0.868 3.00 0.442 0.803 0.164 0.871 5.00 0.520 0.806 0.161 0.876 7.50 0.592 0.804 0.159 0.877 10.00 0.649 0.802 0.160 0.876 15.00 0.738 0.798 0.163 0.871 20.00 0.808 0.794 0.167 0.864
AMS-MI 1.05 0.159 0.852 0.524 0.427 1.10 0.053 1.153 0.499 0.600 1.50 0.018 1.506 0.551 0.678 2.00 0.015 1.593 0.593 0.670 2.50 0.014 1.630 0.621 0.660 3.00 0.014 1.652 0.641 0.651 5.00 0.014 1.689 0.694 0.625 7.50 0.014 1.705 0.733 0.604 10.00 0.015 1.712 0.759 0.589 15.00 0.016 1.717 0.794 0.568 20.00 0.017 1.718 0.818 0.554
Table D.2 - Exponents and coefficients for the discharge-area rating curves of various return periods (years). AMS = annual maximum series, PDS = partial duration series, MD = maximum daily values, MI = maximum instantaneous values. The rating curves take on the form of Q = aAd
b, where Q is the discharge for the chosen return period (m3s-1), Ad is the drainage area (km2), and a and b are the values from the table that correspond to the chosen series and return period. Standard error of the estimate values are in ln units.
149
% Difference % Absolute Difference Return Period
AMS–MD AMS–MI PDS–MD AMS–MD AMS–MI PDS–MD
0.5 6.70% 6.70%0.75 -5.31% 5.31%
1 -8.99% 8.99%1.05 -27.75% 11.25% -9.31% 27.75% 11.25% 9.31%1.1 -24.62% 10.39% -9.62% 24.62% 10.39% 9.62%1.5 -17.36% 10.25% -11.42% 17.36% 10.25% 11.42%2 -13.48% 12.42% -12.06% 13.48% 12.42% 12.06%
2.5 -11.11% 13.65% -12.19% 11.11% 13.65% 12.19%3 -8.83% 15.04% -12.11% 8.83% 15.04% 12.11%5 -2.88% 19.32% -10.48% 2.88% 19.32% 10.48%
7.5 2.05% 22.60% -9.15% 2.05% 22.60% 9.15%10 5.31% 25.13% -7.59% 5.31% 25.13% 7.59%15 10.52% 29.04% -5.02% 10.52% 29.04% 5.02%20 14.10% 31.91% -3.24% 14.10% 31.91% 3.24%
Average -6.73% 18.27% -7.84% 12.55% 18.27% 8.80%Standard Deviation 13.83% 7.82% 5.04% 8.24% 7.82% 2.87%
Table D.3 - Relative error values as a percent difference between the predicted and observed discharges for the Little Rouge gauging station.
% Difference % Absolute Difference Return Period
AMS–MD AMS–MI PDS–MD AMS–MD AMS–MI PDS–MD
0.5 14.06% 14.06%0.75 -9.68% 9.68%
1 -16.01% 16.01%1.05 24.54% -57.98% -16.64% 24.54% 57.98% 16.64%1.1 -17.49% -43.68% -17.20% 17.49% 43.68% 17.20%1.5 -30.75% -23.97% -20.48% 30.75% 23.97% 20.48%2 -28.81% -18.17% -22.16% 28.81% 18.17% 22.16%
2.5 -26.89% -15.93% -22.98% 26.89% 15.93% 22.98%3 -24.75% -14.35% -23.48% 24.75% 14.35% 23.48%5 -18.86% -11.00% -23.39% 18.86% 11.00% 23.39%
7.5 -13.92% -9.42% -23.36% 13.92% 9.42% 23.36%10 -10.66% -8.38% -22.78% 10.66% 8.38% 22.78%15 -5.68% -6.96% -21.63% 5.68% 6.96% 21.63%20 -2.34% -6.00% -20.94% 2.34% 6.00% 20.94%
Average -14.15% -19.62% -17.62% 18.61% 19.62% 19.63%Standard Deviation 15.87% 16.62% 9.93% 9.55% 16.62% 4.25%
Table D.4 - Relative error values as a percent difference between the predicted and observed discharges for the Duffins Creek gauging station.
that beyond the 1.5-year return period, the values between the partial duration series and
annual series (both using maximum daily values) are quite similar (Fig. D.3), which
150
means that the difference between the two series lies in the discharges occurring more
frequently than 1.5-years. Since the same cut-off value was used in constructing both the
partial duration and annual series, the values below a return period of 1.5 years have to fit
into five return period categories for the partial duration series versus two for the annual
series, which suggests that the discharges for return periods below 1.5 years on the annual
series may be under-estimated compared to the same return period on the partial duration
series.
0
10
20
30
40
50
60
70
0 5 10 15 20 25 30 35 40
Observed Discharge (m3s-1)
Pre
dic
ted
Dis
char
ge
(m3 s
-1)
AMS - MD AMS - MI PDS - MD 1:1 Line
Figure D.1 - Plot of observed discharges from the Little Rouge River gauging station against the predicted discharges for the various series. Error bars represent one standard error of the estimate.
Given that the partial duration series is generally more accurate, is very similar to
the annual series for return periods over 1.5-years, and has greater predictive capacity
below 1.5-years leading to more accurate representation of the return period, the partial
duration series is advocated as being the best predictor of the bank-full discharge return
periods for this study. However, it should be noted that as the partial duration series is for
maximum daily values, it over-estimates the return period of a given discharge.
Maximum instantaneous values should be considered in conjunction with the
151
0
20
40
60
80
100
120
140
0 20 40 60 80 100 120
Observed Discharge (m3s-1)
Pre
dic
ted
Dis
char
ge
(m3 s
-1)
AMS - MD AMS - MI PDS - MD 1:1 Line
Figure D.2 - Plot of observed discharges from the Duffins Creek gauging station against the predicted discharges for the various series. Error bars represent one standard error of the estimate.
0.8
1
1.2
1.4
1.6
1.8
2
2.2
0 5 10 15 20 25
Return Period (years)
Dis
char
ge
(PD
S -
MD
) :
Dis
char
ge
(AM
S -
MD
)
Figure D.3 - Average ratio of the discharge from the partial duration series and the annual series for a given return period for the 11 gauging stations. On average, for a given return period below 1.5-years, discharges are 1.5-2 times larger on the partial duration series than the annual series. Discharges on the two series are about equal at the 1.5-year return period and stabilize at between 0.90 and 0.98 by the 2-year return period. Error bars represent one standard error. partial duration series, but the lower limit of its usefulness is likely reached at the 1.5-
year return period. The rating curves presented in Table D.2 for the partial duration series
and maximum annual series (instantaneous values) were applied to the study sites to
152
estimate the return period of bank-full discharge. The results of this are displayed
graphically in Figures D.4-D.10 and summarized in Table D.5.
1
10
100
0.1 1 10 100
Return Period (years)
Dis
char
ge
(m3 s-1
)
PDS - MD Bank-full Discharge AMS - MI
Figure D.4 - Bank-full discharge flood frequency estimate for Site 1. Error bars represent one standard error of the estimate.
1
10
100
0.1 1 10 100Return Period (years)
Dis
char
ge
(m3s-1
)
PDS - MD Bank-full Discharge AMS - MI
Figure D.5 - Bank-full discharge flood frequency estimate for Site 2. Error bars represent one standard error of the estimate.
153
1
10
100
0.1 1 10 100Return Period (years)
Dis
char
ge
(m3s-1
)
PDS - MD Bank-full Discharge AMS - MI
Figure D.6 - Bank-full discharge flood frequency estimate for Site 3. Error bars represent one standard error of the estimate.
1
10
100
0.1 1 10 100Return Period (years)
Dis
char
ge
(m3 s-1
)
PDS - MD Bank-full Discharge AMS - MI
Figure D.7 - Bank-full discharge flood frequency estimate for Site 4u. Error bars represent one standard error of the estimate.
154
1
10
100
0.1 1 10 100Return Period (years)
Dis
char
ge
(m3 s-1
)
PDS - MD Bank-full Discharge AMS - MI
Figure D.8 - Bank-full discharge flood frequency estimate for Site 4d. Error bars represent one standard error of the estimate.
1
10
100
0.1 1 10 100Return Period (years)
Dis
char
ge
(m3 s-1
)
PDS - MD Bank-full Discharge AMS - MI
Figure D.9 - Bank-full discharge flood frequency estimate for Site 5. Error bars represent one standard error of the estimate.
155
1
10
100
0.1 1 10 100Return Period (years)
Dis
char
ge
(m3 s-1
)
PDS - MD Bank-full Discharge AMS - MI
Figure D.10 - Bank-full discharge flood frequency estimate for Site 6. Error bars represent one standard error of the estimate.
Site 1 2 3 4u 4d 5 6 Drainage Area (km2)
16.99 21.70 73.14 86.53 86.65 107.42 114.12
Discharge (m3s-1) 1.87 8.95 5.57 10.59 14.02 20.55 24.64 PDS-MD Return Period (years)
0.5 20 0.5 1.1 2 3 5
Range <0.5-0.5 10->20 <0.5-0.5 1-1.5 1.5-3 2.5-5 5-7.5 AMS-MI Return Period (years)
<0.5 1.5 <0.5 <1.1 <1.5 <1.5 1.5
Range <0.5 <1.5-2.5 <0.5 <1.1 <1.5 <1.5-1.5 <1.5-2
Table D.5 - Summary of bank-full return periods for the maximum daily partial duration series and the maximum instantaneous annual series rating curves for each site.
156
Appendix E: Downstream Trends in Channel and Floodplain Characteristics
E.1 Width-Depth Ratio and Sinuosity
The interaction between bank-full width and depth is reflected in the width-depth
ratio (Fig. E.1), which shows a moderate downstream increase. Sites 1 and 3 possess the
lowest width-depth ratios, which, in the case of Site 3, is a result of increased bank-full
depth and a concomitant decrease in width (see Chapter Six, section 6.3.1). The higher
values in the downstream end of the watershed are brought on by channel width
increasing against a constant to slightly decreasing channel depth.
Figure E.1 - Downstream variation in bank-full width-depth ratio (w:d) and channel sinuosity (P).
Channel sinuosity (P) shows a very weak downstream decrease. All values are
below 1.30 except for sites 1 and 3, which are coincident with the lowest width-depth
ratios. It should be noted that sinuosity is a somewhat arbitrary value as the start and end
points for measurements can vary between users. Moreover, sinuosity does not stay
constant over a selected distance and can change quite rapidly over a short horizontal
distance. Taking these realities into consideration, the sinuosity values discussed above
represent general approximations for each site.
157
E.2 Bank-full Discharge Return Period
It is often expected that return periods of bank-full discharge along a channel
fluctuate between 1 and 2 years on the annual maximum series (Wolman and Leopold,
1957). This, however, has been shown to be a general approximation at best with return
periods in the data compilation of Williams (1978) ranging from one year to over 50
years on the annual series. When the partial duration series is considered, the range is
even larger. The downstream variability in return periods has not been well studied, but
has been shown to possess a positive relationship with drainage area by Petit and Pauquet
(1997). The opposite is observed as an overall trend in the Little Rouge watershed using
maximum daily flow values from the partial duration series, which is driven by the
comparatively high value at Site 2 (Fig. E.2) (for derivation of these values and possible
ranges, see Appendix D). The remaining sites exhibit the expected positive trend.
Figure E.2 – Downstream variation in bank-full discharge return period.
158
E.3 Channel Bed Alluvium Thickness
Channel bed alluvium thickness shows a very weak downstream increase, though
the slope of the regression line is not significantly different from zero (Fig. E.3).
Thickness values generally fall within the range of 25-60 cm with the only departure
from this being Site 6 (91 cm), which is responsible for the impression of a downstream
increasing trend. In half of the cross-sections at Site 6 basal bedrock was never reached.
Thus, the actual alluvial thickness at this site is under-estimated. Site 3 is also under-
estimated but not likely to the same extent. Based on the limited data, two smaller trends
can be discerned from the overall trend where the average alluvial bed thickness
increases between sites 1 and 3, and 4 and 6. These two smaller trends are separated by a
decrease in thickness of up to 55%. The maximum alluvial thickness tends to follow the
trend observed for average alluvium thickness and values vary between 80 and 165 cm,
though sites 3 and 6, which represent the thickest sites, are under-estimates.
The average percentage of glacial clay (or clay-bedrock in the case of Site 6) that
outcrops within the bank-full channel varies between 0% and 24%, and appears to show
no relationship with distance (Fig. E.4). Since the values in Figure E.6 are site-averages
based on riffle and pool cross-sections, the large error bars about each average are a
reflection of the variability in clay exposure within the two bed-forms. Clay was most
often exposed in channel pools where the channel became coupled with valley or terrace
sides, though instances were also observed when the channel was decoupled from the
valley sides, while riffles were fully composed of gravel in many cases.
159
Figure E.3 - Downstream variation in maximum and average channel bed alluvium thickness. Error bars represent one standard error.
Figure E.4 - Downstream variation in exposed glacial clay/bedrock within the bank-full channel. Error bars represent one standard error.
160
E.4 Silt/Clay Content and Organic Content
The general downstream pattern of the depth-averaged silt/clay content within the
floodplain is similar to that described for overbank thickness (Fig. E.5). Overall, there is a
weakly defined negative trend with a slope not significantly different from zero. Silt/clay
percentages are above 45% in all of the sites except for Site 5 where silt and clay
compose 39% of the floodplain sediment. Sites upstream of Site 4 tend to be finer with
silt/clay percentages about 60% or greater, while the other sites have less than 55%
silt/clay indicating slightly sandier floodplains downstream.
Depth-averaged organic content tends to show a strongly decreasing downstream
trend (Fig. E.6). This trend is realized because sites 5 and 6 possess significantly less
organic-rich floodplains than at Site 4 and farther upstream.
Figure E.5 - Downstream variation in depth-averaged silt/clay content. Error bars represent one standard error.
161
Figure E.6 - Downstream variation in depth-averaged organic content. Error bars represent one standard error.
162
Appendix F: Glacial Control on Downstream Trends F.1 Introduction
The objective of the following analysis is to explain the downstream trends
described in the preceding appendix in relation to the relevant physical controls (ie.
discharge, valley slopes) and sediment inputs. While it is most desirable to explain the
downstream trends as a function of these variables, it is understood that fluvial systems
often involve more complicated interactions with intrinsic and extrinsic influences. In
some instances, discharge, valley slope, and sediment inputs may not be the only
controlling parameters behind the observed trends. In which case, other intrinsic or
extrinsic forces may be sought to explain these occurrences.
F.2 Channel Morphology, Hydrology, and Sedimentology
F.2.1 Channel Dimensions and Cross-Sectional Area
In equilibrium channels, the bank-full dimensions represent a balance between the
prevailing hydrological regime (often represented by bank-full discharge), channel slope,
supply rate of bed-load sediment, the bed material size, and bank-strength (see Table
2.1). Separating these variables apart is difficult since their inherent downstream
variation makes controlling for them unrealistic in many situations. However, by dividing
the bank-full dimensions by the upstream drainage area at each site and plotting these
‘relative dimensions’ against bed material size, discharge, and channel slope, some
inferences can be made on the downstream adjustment in the channel dimensions.
It is often regarded that bank-full discharge exerts the strongest control over the
channel dimensions (refer to Table 2.1), but since bank-full discharge was derived from
the dimensions themselves, plotting the dimensions per unit drainage area (hereafter
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referred to as relative width, depth, and area) against bank-full discharge would lead to
spurious correlations (Ferguson, 1986). Instead, as it is theoretically thought that river
channels are adjusted to a flow of a return frequency of 1-2 years (Wolman and Leopold,
1957), the 2-year discharge as derived from the relations in Appendix D is used to replace
bank-full discharge. If the 2-year discharge is the strongest control over the bank-full
channel dimensions, then the downstream variation in the relative channel dimensions
can be modelled using simple power relations. Leopold and Maddock (1953) show that
bank-full channel width (wbf) and depth (dbf) vary with bank-full discharge (Qbf)
respectively as
0.50bf bfw Q F.1a
0.40bf bfd Q F.1b
with bank-full cross-sectional area (Abf) necessarily varying with discharge as
0.90bf bfA Q F.1c
A relation that relates the 2-year discharge (Q2) as a function of drainage area (Ad)
is given as (R. Phillips, personal communication)
0.912 dQ A F.2
Substituting Equation F.2 into Equation F.1 yields
0.82
bf dA A F.3a
0.46
bf dw A F.3b
0.36
bf dd A F.3c
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Dividing each relation by drainage area yields the theoretical downstream adjustment of
relative width, depth, and cross-sectional area as a function of drainage area (Eq. F.4) and
the Q2 (Eq. F.5), given as
-1 -0.18bf d dA A A F.4a
-1 -0.54bf d dw A A F.4b
-1 -0.64bf d dd A A F.4c
-1 -0.20bf d 2A A Q F.5a
-1 -0.59bf d 2w A Q F.5b
-1 -0.70bf d 2d A Q F.5c
Any deviation from Equation F.5 can be interpreted in the context of grain size, channel
slope, bank strength, and other controlling variables.
The exponent for relative cross-sectional area plotted against the 2-year discharge
is –0.53, which is steeper than predicted by Equation F.5a by 165% (Fig. F.1a) and
implies that cross-sectional area is increasing slower downstream than discharge, which
may be a result of relatively wide and deep channels upstream or narrow and shallow
channels downstream. Multiplying the regime relations developed by Millar (2005),
bank-full cross-sectional area (Abf) can be expressed as
0.86 -0.15 0.02 -0.46bf bf 50 CA Q D S μ’ F.6
where Qbf is the bank-full discharge (m3s-1), D50 is the median bed grain size (m), SC is
the channel slope (-), and ’ is the relative bank strength compared to the channel bed (-).
Equation F.6 suggests that discharge exerts the most control over cross-sectional area and
that increasing grain size results in a decrease in cross-sectional area and channel slope
165
has no effect, both of which are reflected, albeit very poorly, in Figure F.1b and c. The
effects of bank vegetation cannot be quantitatively assessed here. The fact that bank-full
cross-sectional area cannot adequately be explained by discharge, grain size, or channel
slope alludes to external controls.
Figure F.1 - Relative cross-sectional area as a function of discharge (a), grain size (b), and channel slope (c). Sites are given for reference.
Wohl and Achyuthan (2002) demonstrate how channels flowing over resistant
substrates tend to possess smaller cross-sectional areas than channels flowing over
alluvium. The sites in Figure F.1 can be segregated into glacial clay and alluvium, which
represent the two dominant substrate types. Site 6 is carved into a thick sequence (>2 m)
of sand, while all sites upstream of Site 6 are cut into glacial clays (tills or
glaciolacustrine clays), which possess varying erodibilities that resist morphological
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adjustment (Shugar et al., 2007) compared to the relatively erodible alluvium. As a result,
the cross-sectional area of the channel at Site 6 is larger per unit drainage area than the
upstream sites (Fig. F.1), and may be manifest as a wider and deeper channel.
While differential substrate erodibility adequately explains the downstream
increase in cross-sectional area between sites 5 and 6, this rationale cannot be extended to
sites 1 or 2, which are underlain by glacial clay and possess very large relative cross-
sectional areas. It is believed that the large channel area present at Site 2 is the result of
bed and bank scouring caused by the presence of debris dams along the channel, which
are absent in the downstream sites (Fig. F.2). Keller and Swanson (1979) note that flow
deflection caused by debris dams can cause bank erosion citing a study in which such a
scenario induced a 230% increase in channel width. Furthermore, flow deflection towards
the banks by mid-channel bars accreted downstream of dams may also widen the
channels (Fig. F.3). Local scouring in the pool immediately downstream of the dam and
scouring of the bed when the dam breaks may cause increases in channel depth as well,
such that, after the dam breaks, the legacy of the debris dam remains as an over-widened
and deepened channel.
Additionally, and perhaps equally important, the large width relative to the
drainage area at Site 2 may be a result of the vegetation lining the banks. Hession et al.
(2003) and Allmendinger et al. (2005) note that channels flowing through forested
floodplains are wider than channels flowing through grassy floodplains, which
Allmendinger et al. (2005) attribute to the trapping of sediment by grassy vegetation
along the inner banks of the channel. Such vegetation is typically absent on forested
floodplains due to the forest canopy blocking out much of the sunlight necessary for
167
grasses to grow. The channel at Site 2 flows through a dense forest of coniferous trees
with a ground cover consisting of sparse and low-lying herbaceous scrubs and minimal
grasses. Due to the lack of light along the floodplain, the over-widened channel cannot be
reclaimed by colonizing vegetation, and, as a result, the wide channel and large cross-
sectional area persists.
Lastly, as Site 1 flows through a grass-dominated floodplain, the preceding
explanation may not necessarily apply to this site. Instead, it is believed that the
occurrence of several relic beaver dams along the channel has caused the channel to
become wider and deeper (Fig F.4). Little empirical information is available on the
effects of beaver dam construction on channel dimensions to support why this might be.
However, since beaver dams are, in essence, debris dams (Gurnell, 1998), it is
conceivable that the widening effects of debris dams mentioned previously may be
extended to Site 1.
Figure F.2 - Debris dam at Site 2 during low-water stage. Flow direction given by the arrow.
168
Figure F.3 – Bar-form developed behind fallen trees in the channel. Notice the downstream gradation of sediment along the bar and lack of colonizing vegetation. Coarse gravel is at the bar-head while sand is at the bar-tail. Flow direction given by the arrow.
Figure F.4 - Beaver dam looking downstream at Site 1. The crest of the dam is at approximately bank-full stage.
169
Figure F.5a and b show how relative channel width and depth vary downstream as
a function of the 2-year discharge. The exponents are –0.65 and –1.14 for width and
depth respectively. While the width exponent is comparable to that in Equation F.5b,
scatter remains about the trend line. Moreover, there appears to be an increasing trend
between sites 3 and 6, meaning that the channel width is increasing faster downstream
than the 2-year discharge. The large apparent gap between sites 2 and 3 is a consequence
of the structure of the watershed where almost half of the total drainage area enters
between these two sites raising the 2-year discharge. The downstream trend in channel
depth shows very little scatter but the exponent of the trendline is 63% steeper than that
predicted in Equation F.4c, meaning that channel depth is increasing much slower than
discharge is downstream. These deviations from the expected relations, through either
scatter or different exponents, allude to other controls on bank-full channel morphology.
The trends in Figure F.5a and b have been described by the variation in channel
slope (Fig. F.5c and d) and median grain size of the bed material (Fig. F.5e and f). In
Figure F.5c-f, the relations are poorly defined with no relationship being statistically
significant, which is a consequence of sites 1 and 2 plotting well above the other sites.
Nevertheless, despite the lack of statistically defined relations, basic visual trends can be
discerned from the data. Considering sites 1 and 2 as their own group (affected by debris
dams) and sites 3-6 (not affected by debris dams) as another, it appears that when channel
slope increases, relative width also increases while relative depth decreases. In addition,
channels with median grain sizes above 10 mm are typically wider and shallower than
channels with median sizes below 10 mm, though these grain size trends are not
particularly well defined.
170
Figure F.5 - Relative width and depth as a function of discharge (a and b), channel slope (c and d), and bed material size (e and f). Sites numbers are given for reference.
The slope-width and slope-depth relations are in agreement with rational regime
relations (Parker, 1979; Griffiths, 1981; Millar, 2005) but are in disagreement with the
semi-theoretical relations of Lee and Julien (2006) and the empirically derived hydraulic
geometry relations of Davidson and Hey (2011). Results from a study by Nanson and
171
Young (1981) support the relationships between slope and width, and slope and depth
described here. Since slope is traditionally thought to be proportional to bed-load
concentration (Schumm and Khan, 1972), the observed increase in width and decrease in
depth may be related to increasing bed-load concentration within the channel. Channels
with high bed-load concentrations are typically reported to be wide and shallow
compared to low bed-load concentration channels, which are narrow and deep (Leopold
and Maddock, 1953; Schumm and Khan, 1972). Furthermore, since sand-sized particles
can be more easily transported in suspension than gravel, the positive and inverse
relationships grain size has with relative width and depth respectively may be indicative
of increasing bed-load transport relative to the total sediment load.
Since channel slope increases between sites 3 and 5, based on Figure F.5c and d,
the relative channel width should increase while the relative depth should decrease.
Given width and depth increase with discharge downstream, the increase in channel slope
should magnify the downstream increase in channel width and counteract the increase in
depth. This phenomenon broadly explains why relative channel width increases
downstream of Site 3 (Fig. F.5a), while channel depth decreases faster than predicted
(Fig. F.5b).
F.2.2 Width-Depth Ratio and Sinuosity
Dividing the width and depth relations of Millar (2005), the width-depth ratio can
be expressed as,
0.13 -0.33 2.28 -2.88bf 50w:d Q D C* μ’ F.7
where C* is the concentration of bed-load sediment discharge per unit water discharge.
From this relation, bed-load sediment concentration and relative bank-strength exert the
172
greatest control over the width-depth ratio. By contrast, bank-full discharge and median
bed-material size are relatively ineffective. The implication of this relation is that as bed-
load concentration increases the width-depth ratio will increase, but can be impeded by
increasingly resistant banks, which is consistent with past studies (Schumm, 1963;
Schumm and Khan, 1972; Eaton and Church, 2004; Eaton and Church, 2009). While
there is no physical relation describing the controls on sinuosity, based on the work of
Schumm (1963) and Schumm and Khan (1972), it is probable that sinuosity is controlled
in much the same way as width-depth ratio is.
The degree to which the bed-material composition can be divided into bed-load
and suspended-load sediment is presented in Table F.1, and was calculated using the
dimensionless shear stress (τ*) given as,
* h C
s
ρgR Sτ =
(ρ - ρ)gD F.8
where ρ is the density of water (1000 kgm-3), ρs is the density of sediment (2650 kgm-3),
g is the gravitational acceleration (9.81 ms-2), Rh is the hydraulic radius of the channel
(m), SC is the channel slope (-), and D is a grain size of a given calibre on the channel bed
(m). The initiation of suspended sediment transport is given as a dimensionless shear
stress of 1 (Dade, 2000; Church, 2006) and using the slope and hydraulic radius of each
site, the maximum grain size that can be transported in suspension at bank-full flow is
calculated (Table F.1).
The suspended sediment data is poorly detailed with many of the sites not capable
of transporting any bed material sediment in suspension, which may be a result of the
methods employed to sample the bed material. Bulk sampling was undertaken at sites 1
and 3, which tends to emphasize the fine tail of the distribution while the remaining sites
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Site Max. Grain Size Transported in Suspension (mm)
% of Grain Size Distribution
Width-Depth Ratio
Sinuosity
1 0.07 5 8.31 1.71 3 0.10 5 8.81 1.70 2 2.49 0 14.55 1.14
4u 0.68 0 18.30 1.15 4d 1.72 0 18.72 1.18 5 2.71 0 24.89 1.17 6 1.59 0 25.29 1.26
Table F.1 - Percent of the bed material of the study sites mobilized in suspension compared to the width-depth ratio and sinuosity.
were sampled using a pebble count that emphasizes the coarser tail. Nevertheless, there
does appear to be an emerging trend where the two sites with the highest sinuosities and
lowest width-depth ratios do transport some of their bed-material in suspension, albeit a
very low amount. The reason for such a low percentage is that these beds are poorly
sorted and consist of sediments that the river is incompetent to transport. Mobile
sediments represent between 33% and 51% of the grain size distribution at sites 1 and 3
respectively. As a percentage of the total mobile sediment distribution, the sediment in
Table F.2 represents, respectively for the two sites, 15% and 10%, with the remainder
being transported as bed-load, though saltation is probably pervasive at these sites due to
the fine-calibre nature of the bed material. The results agree with the notion that narrow,
deep, and sinuous channels transport a greater proportion of their sediment load in
suspension than wide and shallow channels.
To further explain the various width-depth ratios, bank-full bed-load
concentration data were sought. While bed-load data were not collected at the sites,
volumetric discharges can be estimated from a bed-load formulae and related to bank-full
discharge to estimate a bed-load sediment concentration. A modified Meyer-Peter and
Müller equation was used (Wong and Parker, 2006) given as,
174
bi*i 3
i
=q
q(G-1)gD
F.9
* * * 1.6i i Crq =4.93(τ -τ ) F.10
where qi* is the dimensionless unit bed-load transport rate for a given grain size fraction i,
qbi is the bed-load transport rate of a given grain size fraction i per unit channel width
(m2s-1), G is the specific gravity of sediment taken as 2.65, g is the gravitational
acceleration (9.81 ms-2), Di is the grain size of a given grain size fraction i (m), τi* is the
dimensionless shear stress for a given grain size fraction i (Eq. F.8), and τCr* is the critical
dimensionless shear stress taken as 0.03, which is generally regarded as the lower limit
for sediment mobility (Buffington and Montgomery, 1997). Using Equations F.9 and
F.10, the fractional volumes for the D95, D90, D84, D75, D50, D25, D16, D10, and D5 were
calculated and summed to give the total bank-full transport rate per unit channel width.
This, in-turn, was multiplied by the active gravel width to yield bank-full volumetric
transport rates (in m3s-1). Active gravel widths were chosen instead of bank-full widths
since bank-full widths incorporate glacial clays, bare sand exposures, and vegetated
surfaces, in addition to the active gravel surfaces. Thus, including these surfaces would
over-estimate the transport volumes. Bed-load concentrations (logC*) were derived by
dividing the bank-full bed-load discharge by the bank-full discharge (Table F.2). Since
hiding and protrusion effects, which are important in sediment transport were not
considered here, these estimates are considered high.
The results of this analysis are shown in Figure F.6. While there is considerable
scatter within the plot, there appears to be a positive correlation between bed-load
sediment concentration and width-depth ratio. Since bed-load transport is a function of
175
the channel slope, discharge, and sediment inputs from banks and valley sides, the scatter
in Figure F.6 is a reflection of the interactions between these variables.
Site qb Wg Qb Qbf LogC* w:d 1 0.0000224 5.64 0.000126 1.87 -4.17 8.31 3 0.000051 9.11 0.000465 5.57 -4.08 8.81 2 0.008694 9.11 0.079202 8.95 -2.05 14.55
4u 0.0000605 10.11 0.000612 10.59 -4.24 18.30 4d 0.001423 5.99 0.008524 14.02 -3.22 18.72 5 0.006765 10.58 0.071574 20.55 -2.46 24.89 6 0.002904 10.75 0.031218 24.64 -2.90 25.29
Table F.2 - Bed-load concentration (logC*) estimates for each study site compared against width-depth ratios (w:d). qb is the bed-load transport rate per unit width (m2s-1), Wg is the average active gravel width (m), Qb is the bank-full bed-load transport rate (m3s-1), and Qbf is the bank-full discharge (m3s-1).
Figure F.6 – Bank-full width-depth ratios of the study sites as a consequence of bed-load concentration segregated by dominant sediment sources. Sites are labelled for reference.
To reflect the variability in sediment inputs, the data points were segregated by
the dominant source of bed-load sediment. Sites that derive all of their bed-load sediment
from glaciolacustrine clays or gravel-poor tills possess the lowest bed-load
176
concentrations, which is a result of the lack of sediment supply (Site 4d), the lack of
transport capacity manifest as low channel slopes relative to the bed material size (Site
4u), and the size of the bed material (sites 1 and 3). Site 2 is an exception since its
estimated bed-load concentration is comparatively high but still maintains a low width-
depth ratio. This may be a reflection of both the strength of the channels banks, which are
root stabilized, and the bimodal grain size distribution of the channel bed, where much of
the sediment load comes from the finer mode. The reason for the bimodality and why the
bed-load sediment concentration may likely not be an accurate reflection of the channel’s
sediment transport regime is explored in section F.2.4.3.
Site 4u is an interesting case, as it possesses the lowest bed-load concentration,
yet maintains a width-depth ratio similar to that of Site 4d, which has a bed-load
concentration an order of magnitude higher. The speculated reason for this is that the
banks at Site 4u are relatively more erodible than the channel bed, which results in
preferential erosion of the banks with minimal bed-load transport as was suggested in
Chapter Five.
Sites 5 and 6 exhibit the highest width-depth ratios and coincide with the highest
bed-load concentrations after Site 2, which are a result of the high transport capacity (ie.
high slopes versus grain size) of the channel and the coarse glaciofluvial sediments and
gravel-rich tills exposed in the valley sides, which act to increase the active gravel widths
compared to gravel-starved sites upstream (ie. Site 4d). It is speculated that the reason
why Site 6 has a similar width-depth ratio as Site 5 but a smaller bed-load concentration
is that the banks at Site 5 may be stronger due to the presence of glacial clay resisting
further widening compared to the more erodible alluvial boundaries of Site 6.
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F.2.3 Bank-full Discharge Return Period
The return period of bank-full discharge is a function of the hydrological regime
of the watershed, the bank-full cross-sectional area, and the average bank-full velocity,
which is proportional to channel slope. Figure F.7 shows how return period, using
maximum daily flow values on the partial duration series, varies with the channel slope
and the relative cross-sectional area. Generally, there appears to be a statistically
significant positive relationship between channel slope and return period, which is in
accordance with Williams’ (1978) findings. Though Nanson and Young (1981) did not
explicitly look at return periods in their study, they found that a downstream decrease in
channel slope was in part responsible for a downstream decrease in bank-full discharge,
which, in watersheds where discharge of a given frequency increases downstream, would
result in a downstream decrease in return period as well. This relationship between slope
and return period can be explained as follows: high slopes typically result in high
velocities and high discharges for a given cross-sectional area. Thus, a large magnitude
discharge would need to occur in order to overtop the banks. Such a discharge, however,
would be expected to occur infrequently. Conversely, the low slope present at Site 3 leads
to low velocities and hydraulic damming, which causes the water to backup and over-
flow the banks with higher frequencies. In the case of Site 1, the over-bank flows are
driven by the presence of beaver dams that reduce the water surface slope. Over-bank
flows are common at this site after summer convective storms.
The relationship between relative cross-sectional area and return period is much
weaker, but its importance can be summarized by comparing sites 4d, 5, and 6, where
Site 6 has a larger return period than the other two sites despite having a lower channel
178
slope, and can be attributed to its larger relative cross-sectional area. This suggests that
channels with fully alluvial boundaries (Site 6) may be less prone to overbank flooding
than channels with mixed alluvial-non-alluvial boundaries (sites 4d and 5) due to its
ability to more freely adjust the channel dimensions to accommodate peak flows.
The nature of the hydrological regime plays an important role in determining the
return periods, which are different depending on whether maximum daily or maximum
instantaneous flow values are used. Table F.3 gives the return periods using the
maximum instantaneous flow values and the maximum daily flow values.
Figure F.7 - Return period of bank-full discharge (max. daily) plotted against relative cross-sectional area and channel slope. Sites are labelled for reference.
In all of the sites, the return period for bank-full discharge is either 1.5 years or
less using instantaneous values. This is particularly interesting for Site 2 considering its
return period for maximum daily values is much higher. Javelle et al. (2003) report that
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rivers within south-central Ontario are dominated by spring floods characterized by
moderate flood peaks that occur over short time periods. Accordingly, flood peaks are
high enough to reach bank-full stage with a high degree of regularity. However, they are
not high enough, nor are they persistent enough, to generate a daily average equivalent to
bank-full discharge (hereafter referred to as sustained bank-full discharge). This
reasoning is less true for sites with low slopes since they reach bank-full frequently
regardless of which set of data is used.
Site Return Period (Maximum Instantaneous) Return Period (Maximum Daily) 1 <0.5 years 0.5 years 2 1.5 years 20 years 3 <0.5 years 0.5 years
4u <1.1 years 1.1 years 4d <1.5 years 2 years 5 <1.5 years 3 years 6 1.5 years 5 years
Table F.3 - Return periods for the study sites (see Appendix D for full derivation of these values).
It is interesting to note the disparity between sites 2 and 6. Both have maximum
instantaneous values of 1.5 years, however, their maximum daily values differ by a factor
of 4, which may have to do with their locations within the watershed. As Site 2 is located
in the upper portion of the watershed, it is limited in the catchment size from which its
floodwaters are supplied. As a result, flood-waves are likely to be very flashy and given
the size of the channel cross-sectional area, sustained bank-full flows are not probable.
Site 6, on the other hand, has a smaller relative cross-sectional area and larger drainage
area, which permit a sustained bank-full discharge to occur more frequently.
F.2.4 Bed Material Size and Sorting
Bed sediment size typically varies with channel slope since channels with high
slopes are competent to carry larger sediment particles while channels with low slopes
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are able to only transport small sediment particles. Grain size and sorting data were re-
plotted against channel slope and segregated by the dominant non-alluvial sediment
sources at each site (Fig. F.8). In general, grain size tends to correlate well with channel
slope and the expected direct relationship is apparent in all of the size fractions. However,
scatter is visible within each fraction, and there is no apparent relationship with channel
slope on slopes above 0.001, indicative of glacial conditioning of the bed material.
F.2.4.1 Size-Selective Transport of the Bed Material
The direct relationship between channel slope and grain size is predicated on the
notion that channels of a given slope can transport the majority of the sediment along the
channel bed. Theoretically, any increase in channel slope will result in an increase in
transport capacity and coarsening of the grain size composition of the channel bed. This
idea is tested on the data to see how effective size selective transport is as an explanation
for the observed relationships in Figure F.8.
Using Equation F.8 and a dimensionless shear stress of 0.03, the maximum grain
size entrainable at each site were calculated and are presented in Table F.4. At the various
study sites, the channel is competent to transport between 10% and 87% of the bed
material at bank-full flow. However, these are estimates, as hiding and protrusion effects
have not been taken into account. Sites 2, 5, and 6 are the most competent sites capable of
transporting over three-quarters of the bed material. The remaining bed sediment not
mobilized during bank-full flows can be considered to be glacially inherited lag deposits.
From a sediment transport perspective, those sites with the most mobile sediment can be
thought of as the least affected by the last glaciation.
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Figure F.8 - Sorting and grain sizes of various fractions of the bed sediment plotted against channel slope. Datapoints are segregated based on dominant sediment sources and site numbers are given for reference.
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Site Max. Grain Size Transported (mm) % of Grain Size Distribution 1 2.21 33 2 83.08 79 3 3.42 51
4u 22.60 10 4d 57.28 51 5 90.33 77 6 53.08 87
Table F.4 - Percent of the bed material of the study sites potentially mobilized during bank-full flows.
Of particular note is Site 6, which transports the most amount of sediment of the
study sites and nearly all of its bed material. Figure F.8a-d show that the coarse fractions
at Site 6 are comparatively finer than the other gravel-cobble based sites, with the
disparity increasing with the size fraction. In addition, between sites 5 and 6 there is a
downstream decrease in the sorting coefficient coinciding with a downstream decrease in
channel slope. These two patterns are consistent with conventional size-selective
transport models (Knighton, 1980; Brierley and Hickin, 1985) and it is proposed that this
site has derived its bed-load sediment almost exclusively from downstream transport with
little non-alluvial sediment input or reworking of previously laid-down deposits.
In support of this, the very recent radiocarbon date retrieved for this site (Table
5.4 and Fig. 5.12a) and the thick sand deposits underlying the present channel suggest
that gravel did not exist at the current channel elevation several hundred years ago, which
means that the gravel had to have been transported in from upstream within this recent
time period or supplied directly from the valley sides. Since valley slope-channel
coupling is not extensive and the valley slopes are stable and forested, it is unlikely that
much of the gravel deposits have been derived from them. Size-selective transport
remains the best explanation for the grain size characteristics at Site 6.
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F.2.4.2 Glacial Inheritance of the Bed Material
The remaining sites are reworking previously laid-down deposits derived from
incision into glacial sediments along the channel length, which account for much of the
variance within Figure F.8a-f. Following the data in Table F.4 and the preceding
discussion on size-selective transport, it is interesting to compare the sorting values and
the channel competence between sites 4d, 4u, and 6. The sorting values for these sites are
respectively 0.78, 0.94, and 0.82, which show a high degree of similarity, especially
between sites 4d and 6 (Fig. F.8g). However, their capacities to move the bed material are
quite different. As mentioned, Site 6 is capable of moving 87% of the bed material at
bank-full discharge. Sites 4u and 4d, on the other hand, can only transport approximately
10% and 51% respectively. It is speculated that the vast disparity between competence
with relatively similar sorting values between sites 4 and 6 may be indicative of a past
discharge regime at Site 4, which would necessarily be larger than present such that the
channel could transport most of the bed material. Paleochannels with discharges 8-10
times larger than present have been identified in studies in southern Ontario (Phillips and
Robert, 2005) and Michigan (Arbogast et al., 2008), while large paleochannels were
observed in the upper Little Rouge watershed. Subsequent waning discharge with climate
change appears to have led to a largely immobile channel bed.
Compared to the other gravel-cobble based sites, Site 5 is coarser in terms of the
Dmax and the D95 and D84 fractions, which result in a higher sorting coefficient (Fig. F.8a-
c, and g). This likely results from the channel receiving sediment from gravel-rich glacial
outwash deposits exposed in the valley sides (Mahaney and Hancock, 1993) while the
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other sites derive their gravel from gravel-poor silty-clayey tills and glaciolacustrine silts
(Fig. F.9).
The high sorting coefficient at Site 3 results from the low channel slope, which
forces deposition of sand previously passed through the channel at higher slopes. These
sands are mixed with gravel, which account for 57% of the bed material by weight,
deposited from lateral inputs and left over from more competent prior channel states. It is
this combination of sand and gravel that results in the inverse relationship between
sorting and channel slope, counter to what is typically expected in conventional
downstream fining models.
F.2.4.3 External Controls on the Bed Material
On top of the glacially inherited sediment, sites 1 and 2 experience external
controls that dictate the grain size distribution of the bed material. In the case of Site 1,
the presence of beaver dams reduces the water surface slope of the bank-full channel to
approximately 0.0002 (the channel bed slope is an order of magnitude higher) causing
sand to be trapped and deposited out over gravel and cobbles inherited from the pre-dam
channel state. The result is the same as Site 3, where the mixed composition of the
channel bed leads to a very high sorting coefficient and the inheritance of a grain size
distribution from a prior channel state leads to low channel competence.
The high sorting coefficient for Site 2 exists due to bimodality in the grain size
distribution, which is the result of the presence of debris dams along the channel. Several
grain size analyses were done above a debris dam and compared against an analysis done
on a mid-channel bar downstream of the dam (Fig. F.10). Comparing the two
distributions shows that the upstream distribution is strongly bimodal while the
Figure F.9 - Bed material characteristics at each study site in relation to the channel slope and sediment inputs along the channel length. Processes of bed sediment origin are listed and elaborated on in the text. Vertical exaggeration = 78x.
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downstream distribution is unimodal and far better sorted. The reason for this
phenomenon is the bank-full water surface slope upstream of the debris dam is about 70-
75% lower than that of the channel bed slope, which results in a lower transport capacity.
Using Equation F.8, a critical dimensionless shear stress of 0.03, and inputting the
hydraulic radius (0.57 m) and a slope of 0.002 (based on the water surface slope
measured in the field), the maximum grain size that can be entrained upstream of the
debris dam is 23 mm or 52% of the bed material. Conversely, using a gradient of 0.0072
yields a maximum entrainable grain size of 83 mm or about 95% of the bed material on
the mid-channel bar. A grain size of 23 mm or less represents 16% of the bed material on
the mid-channel bar meaning that there is an excess of this finer material upstream of the
debris dam. The upper half of the upstream grain size distribution is immobile, while the
smaller grain size fractions are brought in from farther upstream and stored on the
channel bed. Overtime, these smaller fractions progressively make up a greater
proportion of the bed material until the debris dam breaks or the channel is diverted and
the water surface slope steepens up flushing out the smaller fractions and remobilizing
the larger fractions. This process of sediment trapping and expulsion has implications for
the bed-load concentration data presented in Figure F.6. The calculation was made using
the combined upstream and downstream grain size distribution for which the upstream
distribution dominates due to more sampling locations, and a slope of 0.0072. In essence,
the datapoint for Site 2 in Figure F.6 represents a rare scenario after the debris dam
breaks or the channel is diverted around it where the excess fine sediment is flushed
through the system. The processes described in the preceding paragraphs and their spatial
distributions are summarized in Figure F.9.
187
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
1 10 100 1000 10000
Grain Size (mm)
Per
cen
t F
iner
Upstream of Debris Dam
Downstream of Debris Dam
With damWithout dam
Figure F.10 - Grain size distributions for Site 2 above (n = 405) and below (n = 128) the debris dam. Red dots represent the limits of competence at bank-full flow. F.2.5 Channel Bed Alluvium Thickness and Exposed Clay Percentage
Massong and Montgomery (2000) have shown that for mountain drainage basins,
alluvial and bedrock reaches can be discriminated through the use of a simple slope-
discharge plot (Fig. F.11). For a given discharge, bedrock channels occur on higher
slopes unless the channel is forced into an alluvial state by wood debris or through high
sediment supply relative to the transporting capacity of the channel. Likewise, a bedrock
channel that falls below the threshold line may be caused by a low sediment supply
relative to the transport capacity. The implication here is that these two substrates are
segregated based on their transport capacities relative to their sediment supply.
Since the dimensionless shear stress is a ratio between the transport capacity of
the channel and the grain size of the channel bed, it was compared against the average
percentage of glacial clay or bedrock exposed in the channel (Fig. F.12) and the average
channel bed alluvium thickness (Fig. F.13) to see if similar trends appear to that reported
by Massong and Montgomery (2000). It is expected that channels with dimensionless
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shear stresses above critical (0.03) will possess high exposed clay percentages (under
supply-limited conditions) and low alluvium thickness values unless forced into an
alluvial state by excess sediment or external forces (transport-limited conditions). In
determining the dimensionless shear stress (Eq. F.8), the grain size was set as the D50.
Figure F.11 - Theoretical discrimination between alluvial and bedrock channels based on slope and drainage area (after Massong and Montgomery, 2000).
Figures F.12 and F.13 show that the expected trends do not appear to hold, as a
positive trend is observed between both dimensionless shear stress, percent clay exposed,
and alluvium thickness, though the relationships are quite poor and in neither case is the
regression slope significant. For percent clay exposed, the data were subdivided into four
classifications based on sediment mobility and sediment supply conditions. The boundary
between immobile and mobile sediment is given as a dimensionless shear stress value of
0.03 above which sediment is often considered mobile. The boundary between supply-
and transport-limited conditions is arbitrarily defined but given the separation between
sites 1, 4d, and 5 from the other sites, the approximate location of the boundary is
justified. Despite exhibiting up to 5% clay exposure, on average, the lower sites are
considered transport-limited because clay was only exposed in one cross-section at each
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site. Thus, an alluvial (transport-limited) state was considered the average condition for
these sites.
While the data in Figures F.12 and F.13, in general, do not support the hypothesis
that increasing transport capacity (ie. dimensionless shear stress) results in thinner
channel bed alluvium and more exposed glacial clay, this is a consequence of the diverse
channel conditions and geomorphic histories within the watershed. Consider Site 4,
which is split into two sub-reaches on the basis of differing channel slopes. Within both
sub-reaches, all relevant controlling conditions (glacial inputs and discharge regime) are
held constant with channel slope varied from 0.0017 at the upstream sub-reach (4u) to
0.0043 at the downstream sub-reach (4d). As a consequence of this change in slope, the
Figure F.12 - Average percent clay exposed in the bank-full channel as a function of dimensionless shear stress. Critical dimensionless shear stress of 0.03 is shown as the lower limit of sediment mobility. Sites are given for reference.
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Figure F.13 - Average channel bed alluvium thickness as a function of dimensionless shear stress.
dimensionless shear stress increases from 0.011 to 0.031 and the channel moves from an
immobile bed state to a mobile state. This increase in transport capacity given a low
sediment supply strips away bed material and increases the percent clay exposed in the
channel from 0.76% to 26% and decreases the average thickness of the channel bed from
37 cm to 26 cm (Figs F.12 and F.13). A t-test revealed that these values are significantly
different at the 90% confidence level.
The role that glacial sediment inputs have on the exposure of clay and channel
bed alluvium thickness is evident when comparing sites 4d and 5. While the channel at
Site 5 has a more mobile bed, the contribution of sediment from outwash gravel deposits
exposed in the valley sides and terraces helps to conceal the glacial clay substrate and
increase the alluvium thickness. Conversely, Site 4d derives its alluvium from a silt-clay
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till and thus does not have the necessary sediment supply to form a thick alluvial layer,
nor hide as much of the underlying clay.
Despite having a dimensionless shear stress below critical and similar to that of
Site 4u, glacial clay is exposed in 15% of the surveyed channel cross-sections at Site 1. It
is proposed that this site represents a condition where the majority of the bed sediment is
immobile (Table F.4) while possessing a limited supply of bed sediment. As the channel
bed slope is an order of magnitude higher than the present bank-full water surface stage,
the presence of glacial clay may be indicative of a former channel state (and transport
capacity) in existence prior to the initiation of beaver dam construction along the channel,
where the channel may have been in a mobile-bed supply-limited state competent to
transport at least half of its coarse (> 2 mm) bed material.
Sites 2, 3, and 6, despite being competent to transport at least half of the channel
sediment, are transport limited due to a greater influx of sediment than transport capacity.
This is particularly true for Site 3, which, due to a reduced channel slope, and thus
transport capacity, much of the fine sediment derived from upstream settles out,
blanketing the channel bed and concealing much of the exposed clay (see Fig. F.9). In
addition, the newly deposited sand covers relic channel gravels increasing the thickness
of the channel bed alluvium compared to the other study sites (Fig. F.13).
While the same general process of deposition described for Site 3 happens in Site
1, the build up of fine alluvium within the channel is not to the same extent, which may
be due to Site 1’s location farther upstream where fine sediment recruitment is less
available due to the channel’s smaller erosive power upstream and lack of valley sides to
contribute sediment. Conversely, Site 3 is located downstream of a large glaciolacustrine
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sand deposit that the channel has cut into, which supplies the site with more bed-calibre
sediment (Fig. F.9).
Site 2 is forced into an alluvial state due to the presence of a debris dam. Figure
F.14 shows the effect that the observed debris dam has on the alluvium thickness and
exposure of glacial clay within the channel. Upstream of the dam, fine gravel and
granules are transported in, increasing the thickness of the gravel deposits and smoothing
out the channel bed resulting in a bed structure more comparable to a run than a riffle-
pool morphology. Immediately downstream of the dam, the increased gradient and
turbulence leads to greater bed scouring and, as a result, gravel thickness is reduced and
glacial clay is exposed in the bed. Farther downstream the channel remains fully alluvial
with a thick (approximately 40 cm) layer of gravel, which is thought to be due to the
recurrence period of bank-full discharge. According to the flood frequency analysis
presented in Appendix D, bank-full discharge has an exceedance probability of
approximately 67% in any given year using maximum instantaneous values, which is
comparable to other sites. However, instantaneous measurements only reflect a 15-minute
interval and do not transport much sediment within this time period. While a sustained
bank-full discharge (ie. bank-full discharge averaged over a day) is capable of much
greater sediment transport, it has a probability of occurring in any given year between 5-
10%. Thus, competent discharges necessary to erode into the accumulated sediment are
either too short or too infrequent to expose clay.
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Figure F.14 - Longitudinal profile of Site 2 showing the effects the debris dam has on the downstream variation in gravel thickness and exposed clay. Clay surface inferred based on selected auger points that reached the surface (beige circles) and points that did not (grey circles). Note the reduced water surface slope upstream of the debris dam compared to the channel bed slope, which results in preferential transport and deposition of fine gravel leading to a bimodal grain size distribution and thick gravel deposits.
Lastly, as previously mentioned, the channel at Site 6 flows over thick sand deposits
such that bedrock is only exposed during channel-valley side coupling. These thick sand
deposits account for the high datapoint for channel bed alluvium thickness shown in
Figure F.13.
F.3 Floodplain Sedimentology
F.3.1 Overbank Alluvium Thickness and Silt/Clay Content
Overbank alluvium thickness and the silt content of floodplains are typically
thought to increase downstream as sediment is conveyed from upstream, high gradient
source regions and deposited along low gradient reaches (Church, 2002). The
relationships between channel slope, overbank alluvium thickness, and the silt content are
tested and shown in Figures F.15 and F.16. There appears to be good agreement in the
two trends as the floodplain tends to get finer and thicker as channel slope decreases,
which conforms to conventional knowledge that increasingly erosive overbank flows
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prevent deposition of fine sediment. Overbank alluvium thickness tends to show far more
scatter than the silt content though, suggesting that factors other than channel slope are
important in determining the thickness of overbank deposits. One such factor is the
sediment supply from upstream. While fine-grained glacial sediments are contributed to
the channel along much of its length, the amount of fine sediment is determined by the
degree to which the channel is incised into the glacial sediments and the type of sediment
the channel is incised into. Incision exposes more surface area for weathering and erosion
and the steep valley slopes transfer the sediment to the valley floor. Moreover, incised
channels often experience more coupling with the valley sides than channels that are not
incised. As a result, sediment can be directly transferred to the channel instead of sitting
on the valley floor.
In the context of the Little Rouge River, the channel is incised into glacial
deposits by up to 30-40 metres in its lower 20 kilometres. The middle reach (10-25 km) is
still incised, but to a more limited degree, while the upstream-most 10 km are not incised
at all (Fig. F.17). The impact of this is that fine sediment production is limited in the
upper watershed and active in the lower watershed. This explains the difference in
sediment storage between sites 1 and 3. Site 3 is downstream of glaciolacustrine sand
deposits that the channel is cut into while Site 1 is downstream of glaciolacustrine clay
deposits that the channel flows over but is not directly cut into. Moreover, as the erosive
potential of the channel is lower upstream than it is downstream, the ability to recruit
sediment is further hindered above Site 1.
The importance of sediment supply is again demonstrated when comparing sites 4
and 6. Site 6 is downstream of a highly energetic and deeply incised channel cut into sand
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diamicts (Fig. F.17). As a result, sediment is recruited from the valley sides and
transported downstream with little storage on the floodplain (which explains the thin
nature of Site 5) and deposited at Site 6. Conversely, Site 4 is downstream of a major
sediment sink in Site 3 where fine sediment is prevented from moving farther
downstream. Consequently, starvation of sediment leads to thinner overbank deposits at
Site 4.
Figure F.15 – Average floodplain overbank alluvium thickness as a function of channel slope.
Figure F.16 - Depth-averaged silt/clay content of the floodplain as a function of channel slope.
Figure F.17 - Spatial variation of floodplain sedimentological characteristics and their relation to the longitudinal profile and glacial sediment sources. See text for discussion. Vertical exaggeration = 78x.
197
It is interesting to note that despite possessing a channel slope an order of
magnitude higher, Site 6 has an overbank thickness comparable to that of Site 3. This is
likely caused by a combination of greater sediment supply from the valley sides upstream
of Site 6 and a greater efficiency of downstream sediment conveyance towards Site 6.
Lastly, despite having similar channel slopes, Site 2 is significantly thicker and
finer than Site 5 at the 99% confidence interval. Jeffries et al. (2003) describe a case
where sediment deposition on the floodplain of a low-order gravel-bed stream is strongly
conditioned by the presence of in-channel debris dams. They observe that impoundment
of water behind debris dams forces much of the would-be channelized discharge onto the
floodplain. Suspended sediment is then transferred onto the floodplain through diffusion
and deposited due to low overbank velocities. The frequency of overbank flows, and thus
sediment deposition, increases upstream of these dams as well. Jeffries et al. (2003) note
that during the period of their study, overbank flows occurred 41.5% of the time upstream
of the dam, while only occurring 0.22% of the time downstream. It is suspected that Site
2 may behave in much the same manner. Indeed, since debris dams force low-energy
conditions upstream by ponding water, assuming a bank-full water surface slope of 0.002
upstream of the debris dam (based on survey measurements) is an appropriate value to
characterize upstream energy conditions, the observed overbank alluvium thickness and
the silt/clay content of Site 2 plot much closer to the trendlines in Figures F.15 and F.16.
Given that sites 1 and 2 both possess similar sediment supplies due to their close
proximity and both possess woody dams spanning their channels, why their overbank
alluvium thickness differ so dramatically remains uncertain. It is speculated that some of
the sediment, which is considered overbank alluvium at Site 2, is stored on the channel
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bed at Site 1. The average thickness of the sub-2mm sequence at Site 1 is 99 cm, which is
not statistically different from the overbank alluvium thickness at Site 2 at the 95%
confidence level.
F.3.2 Floodplain Age
Absolute ages of floodplain surfaces could not be attained for all sites due to the
lack of suitable dating material available. As a substitute, relative ages are proposed
based on depth-averaged percent organics sampled from multiple points within the
floodplain. The premise behind this is that as soils increase in age and become more
mature, the organic content increases as well such that older floodplain surfaces will
contain greater organic levels (Mahaney and Sanmugadas, 1986). While this method is
very limited in terms of dating control, it can help elucidate relative trends in floodplain
age, and thus channel stability. Figure F.18 shows organic content against channel slope
and Figure F.17 divides the Little Rouge River into two zones with sites 5 and 6
potentially being significantly younger than the other sites. This inference is supported by
statistical tests and two radiocarbon dates retrieved from sites 3 and 6. An analysis of
variance and subsequent Fisher’s Least Significance Difference post-hoc test reveals that
the data can be partitioned into three groups. Sites 2, 3, and 4, and 5 and 6 represent two
distinct groups while Site 1 represents a third group. The radiocarbon dates suggest that
the floodplain at Site 4u and upstream may be at least 3100 years old, while sites 5 and 6
are modern in age (Fig. F.17). The value for Site 4d is over-estimated because of mixing
between old low-lying terraces (organic content of floodplain surface between 6% and
8%, comparable to Site 4u in age) and newer inset floodplain surfaces (organic content =
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2-4%, comparable to Site 6 in age if not older). Whether Site 1, which possesses the
highest organic content, is significantly older than Site 3 is unknown.
Since the radiocarbon dates were acquired from the outer bends of the channel,
the dates can be thought to represent the residence period of floodplain sediments.
Floodplain sediments at, and upstream of Site 4u appear to be recycled more than an
order of magnitude slower than sites 5 and 6, which imply a more laterally active channel
downstream of Site 4 and a very stable channel upstream.
Organic content was plotted against channel slope demonstrating a weak inverse
relationship (Fig. F.18). The results suggest energetic channels are more capable of
floodplain turnover, thus being younger, than less energetic channels. Brown (1990) drew
similar conclusions. It is thought that the reason Site 2 plots much higher (ie. more stable)
than Site 5 given similar slopes is a combination of low total stream power due to low
discharge and debris dams reducing the water surface slope, as well as root-stabilized
banks that resist floodplain erosion.
Figure F.18 - Depth-averaged organic content of the floodplain in relation to channel slope. Sites are given and uncalibrated radiocarbon dates are attached for reference.
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Appendix G: Statistical Tests
Sum of Squares df Mean Square F Sig. Level Between groups 1188.348 6 198.058 16.435 0.000 Within groups 530.232 44 12.051
Total 1718.580 50
Table G.1 - Analysis of variance test results of differences in bank-full channel width.
Site Site Significance Level
1 2 0.041 3 0.071 4u 0.001 4d 0.000 5 0.000 6 0.000
2 3 0.855 4u 0.060 4d 0.031 5 0.000 6 0.000
3 4u 0.051 4d 0.027 5 0.000 6 0.000
4u 4d 0.909 5 0.051 6 0.002
4d 5 0.048 6 0.002
5 6 0.075
Table G.2 - Fisher's least significance difference post-hoc test results on bank-full channel width.
Sum of Squares df Mean Square F Sig. Level
Between groups 0.846 6 0.141 3.910 0.003 Within groups 1.587 44 0.036
Total 2.433 50
Table G.3 - Analysis of variance test results of differences in bank-full channel depth.
Site Site Significance Level
1 2 0.746 3 0.001 4u 0.671 4d 0.678 5 0.837 6 0.220
2 3 0.000
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4u 0.456 4d 0.446 5 0.534 6 0.088
3 4u 0.012 4d 0.006 5 0.000 6 0.026
4u 4d 0.972 5 0.771 6 0.511
4d 5 0.786 6 0.457
5 6 0.231
Table G.4 - Fisher's least significance difference post-hoc test results on bank-full channel depth.
Sum of Squares df Mean Square F Sig. Level
Between groups 690.748 6 115.125 9.395 0.000 Within groups 539.194 44 12.254
Total 1718.580 50
Table G.5 - Analysis of variance test results of differences in bank-full channel area.
Site Site Significance Level
1 2 0.227 3 0.003 4u 0.012 4d 0.005 5 0.000 6 0.000
2 3 0.032 4u 0.080 4d 0.042 5 0.000 6 0.000
3 4u 0.990 4d 0.865 5 0.155 6 0.001
4u 4d 0.895 5 0.261 6 0.006
4d 5 0.292 6 0.005
5 6 0.022
Table G.6 - Fisher's least significance difference post-hoc test results on bank-full channel area.
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t-statistic df Significance Level 4.293 319 0.000
Table G.7 - T-test results of differences in channel bed alluvium thickness between sites 4u and 4d.
t-statistic df Significance Level
-2.638 4.051 0.057
Table G.8 - T-test results of differences in exposed clay percentage between sites 4u and 4d.
t-statistic df Significance Level
7.761 15 0.000
Table G.9 - T-test results of differences in overbank alluvium thickness between sites 2 and 5.
t-statistic df Significance Level
3.259 13 0.006
Table G.10 - T-test results of differences in silt/clay percentage between sites 2 and 5.
t-statistic df Significance Level
1.854 10 0.093
Table G.11 - T-test results of differences in sub-2 mm floodplain alluvium thickness between sites 1 and 2.
Sum of Squares df Mean Square F Sig. Level
Between groups 157.850 6 26.308 5.953 0.000 Within groups 212.133 48 4.419
Total 369.982 54
Table G.12 - Analysis of variance test results of differences in organic content.
Site Site Significance Level
1 2 0.090 3 0.026 4u 0.045 4d 0.004 5 0.000 6 0.000
2 3 0.574 4u 0.703 4d 0.236 5 0.004 6 0.002
3 4u 0.871 4d 0.540 5 0.017 6 0.011
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4u 4d 0.450 5 0.014 6 0.009
4d 5 0.055 6 0.042
5 6 0.920
Table G.13 - Fisher's least significance difference post-hoc test results on organic content.
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Curriculum Vitae
Name James Benjamin Thayer Place of Birth Newmarket, Ontario Year of Birth 1988 Post-Secondary Education 2010-2012 The University of Toronto Master of Science in Geography
2006-2010 The University of Western Ontario Honours Bachelor of Science in Geography and Geology
Honours and Awards 2011 John Horner Graduate Scholarship in Geography
2010 The University of Toronto Fellowship Award 2010 The Canadian Association of Geographers Prize 2010 Certificate of Merit of Excellence 2010 NSERC USRA 2010 Dean’s Honour List 2009 NSERC USRA 2009 Dean’s Honour List 2008 NSERC USRA 2008 Dean’s Honour List 2007 Dean’s Honour List 2006 Western Scholarship of Distinction
Related Work Experience September 2010 – May 2012
Research Assistant to Dr. Joe Desloges at The University of Toronto
September 2010 – May 2012 Teaching Assistant at The University of Toronto May 2010 – September 2010
Research Assistant to Dr. Peter Ashmore at The University of Western Ontario
May 2009 – September 2009
Research Assistant to Dr. Peter Ashmore at The University of Western Ontario
May 2008 – September 2008
Research Assistant to Dr. Peter Ashmore at The University of Western Ontario
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Publications & Thayer, J.B. (2010). Floodplain development for a semi- Conference Abstracts alluvial river. Canadian Association of Geographers
Ontario Division, 2010 Annual Meeting, October 15-16, 2010. Ryerson University, Toronto, Canada.
Thayer, J.B. (2010). Floodplain development for a semi- alluvial river. Undergraduate thesis manuscript. The University of Western Ontario, 73 pp.