sedimentary processes and environmental signals …
TRANSCRIPT
SEDIMENTARY PROCESSES AND ENVIRONMENTAL SIGNALS FROM PAIRED HIGH ARCTIC LAKES
by
Jaclyn Mary Helen Cockburn
A thesis submitted to the Department of Geography
In conformity with the requirements for
the degree of PhD
Queen’s University
Kingston, Ontario, Canada
(September, 2008)
© Copyright, Jaclyn Cockburn, 2008
ii
Abstract
Suspended sediment delivery dynamics in two watersheds at Cape Bounty,
Melville Island, Nunavut, Canada were studied to characterize the hydroclimate
conditions in which laminated sediments formed. Process work over three years
determined snow-water equivalence was the primary factor that controlled
sediment yield in both catchments. Cool springs (2003, 2004) enhanced runoff
potential and intensity because channelized meltwater was delayed as it
tunneled through the snowpack and reached the river channel (sediment supply)
within 1-2 days. In warm springs (2005), meltwater channelized on the
snowpack and did not immediately reach the river bed (7-10 days). Sediment
transport was reduced because flow competence was lower and sediment
supplies limited.
Sediment deposition in the West Lake depended on surface runoff
intensity. Short-lived, intense episodes of turbid inflow generated underflow
activity which delivered the majority of seasonal sediment. In 2005, runoff was
less intense and few underflows were detected compared to the cooler,
underflow dominated 2004 runoff season. As well, grain-size analysis of trapped
sediment indicated that deposition rates and maximum grain-size were
decoupled, indicative of varied sediment supplies and delivery within the fluvial
system. These decoupled conditions have important implications for
paleohydrological interpretations from downstream sedimentary records.
iii
Two similar 600-year varve records were constructed from the lakes at
Cape Bounty. Although these series were highly correlated throughout, time-
dependent correlation analysis identified divergence in the early 19th century.
Because the varve records were from adjacent watersheds and subject to the
same hydroclimatic conditions, the divergence suggests watershed-level
changes, such as increased local active layer detachments. The varve record
from West Lake was highly correlated with lagged autumn snowfall and spring
temperature. Similar relationships between these variables and East Lake were
not as strong or significant.
Long-term climatic interpretations should be carefully assessed. A single
record from either of these lakes might lead to autumn snowfall and/or spring-
melt intensity reconstructions, given the process work and weather record
correlations. The recent divergence reveals potential changes likely to occur as
warming increases variability within the Arctic System. Multidisciplinary
monitoring and observations should continue in order to quantify future variability
and evaluate the impact on these systems.
iv
Co-Authorship
Lake trap collection and instrument deployment was planned and coordinated by
the author with assistance by Scott Lamoureux and all Cape Bounty field camp
members in 2003, 2004 and 2005. River sample collection was planned and
coordinated by the author, with major assistance by Scott Lamoureux, Andrew
Forbes, Dana McDonald and Elizabeth Wells (2004), along with collection
assistance from all Cape Bounty field camp members in 2003, 2004 and 2005.
Snow water equivalence measurements were collected by Andrew Forbes
(2003), Krys Chutko (2004), Melissa Lafrenière and Brock Macleod (2005).
Analysis of the snow data was carried out by Melissa Lafrenière, Brock Macleod,
Elizabeth Wells and Scott Lamoureux. Meteorological data were collected by
Scott Lamoureux with assistance from the Cape Bounty field teams. Long
sediment cores and bathymetric data were collected in 2003 with major
assistance from Scott Lamoureux and Andrew Forbes. Several more sediment
cores and bathymetric data sets were collected in 2004 with the assistance of
Krys Chutko, Dana McDonald and Elizabeth Wells and in 2005 with the
assistance of Scott Lamoureux and Jessica Tomkins.
All laboratory and data analyses for Chapters 2 - 4 were carried out by the
author. Members of the EVEX laboratory in the Geography Department and
PEARL group in the Biology Department at Queen’s University assisted in the
timely completion of the analyses.
v
Acknowledgements
I have many people to thank for all the encouragement and support I have
received through my time at Queen’s and in the Geography Department. I
cannot possibly do everyone justice here, but know that you have made a
difference, and without your support this would not have been possible.
I would like to thank Scott Lamoureux for his supervision and
encouragement through my PhD. His knowledge and expertise seem endless
and his enthusiasm for all things cold and muddy is contagious. I am a better
scientist and a better teacher for having known him. Through my umpteen years
as a student at Queen’s I also became close to his family and would like to thank
Linda, Mackenzie and Brenna for always welcoming me and making me smile.
To Bob Gilbert – thanks for taking a chance back in 1999 and hiring me as
a summer student. I look back on that summer with fondness and know that I
wouldn’t be where I am today without that opportunity. Your passion and
imagination for the physical environment are inspiring.
To the Polar Continental Shelf Project in Resolute – the high Arctic is an
amazing place, with your support, expertise and good humour, you made this
work possible and fun. Thanks to all the staff through the years that have helped
and continue to help the work at Cape Bounty.
To Jess, Krys and David – I can’t thank you guys enough. There is
something to say for safety in numbers. Whether it was a coke, more coffee or a
chat over backgammon you helped make this a great experience for me.
vi
To everyone who has been to Cape Bounty, shipped stuff to Cape Bounty
or had to find it on the map, thanks. I would especially like to thank the members
of the Cape Bounty field campaigns in 2003, 2004 and 2005. To members of the
EVEX, LARSEES and PEARL research groups, thank you for your assistance in
field and sample prep.
To my family and friends – words are not enough to describe my gratitude.
Thank you for being there and supporting me always.
vii
Statement of Originality
I hereby certify that all of the work described within this thesis is the original work
of the author. Any published (or unpublished) ideas and/or techniques from the
work of others are fully acknowledged in accordance with the standard
referencing practices.
Jaclyn Cockburn
(September, 2008)
viii
Table of Contents Abstract ............................................................................................................................. ii Co-Authorship .................................................................................................................. iv Acknowledgements ........................................................................................................... v Statement of Originality................................................................................................... vii Table of Contents............................................................................................................viii List of Figures.................................................................................................................... x List of Tables.................................................................................................................... xi Chapter 1 Introduction.......................................................................................................1 Chapter 2 Hydroclimate controls over seasonal sediment yield in two adjacent High
Arctic watersheds..............................................................................................................5 2.1 Abstract ...................................................................................................................5 2.2 Introduction..............................................................................................................6 2.3 Study Site ................................................................................................................9 2.4 Methods.................................................................................................................11
2.4.1 Meteorology ....................................................................................................12 2.4.2 Hydrology........................................................................................................13
2.5 Results...................................................................................................................17 2.5.1 Hydrometeorology...........................................................................................17 2.5.2 Sediment Delivery...........................................................................................24
2.6 Discussion .............................................................................................................25 2.6.1 Hydroclimate controls over seasonal runoff ....................................................25 2.6.2 Hydroclimate controls on seasonal sediment delivery ....................................29 2.6.3 Sensitivity of sediment yield to climate variability in high arctic watersheds...35 2.6.4 Interpreting hydroclimatic variability from downstream sedimentary records..37
2.7 Conclusions ...........................................................................................................41 Chapter 3 Inflow and lake controls on short-term mass accumulation and particle size in
a High Arctic lake: implications for interpreting varved lacustrine sedimentary records..44 3.1 Abstract: ................................................................................................................44 3.2 Introduction............................................................................................................45 3.3 Study Site ..............................................................................................................46 3.4 Methods.................................................................................................................49
3.4.1 Hydrometeorology...........................................................................................49
ix
3.4.2 Limnology........................................................................................................51 3.5 Results...................................................................................................................54
3.5.1 Hydrometeorology...........................................................................................54 3.5.2 Sediment deposition rates and patterns .........................................................63 3.5.3 Sedimentary grain size characteristics............................................................70
3.6 Discussion .............................................................................................................74 3.6.1 Short-lived deposition patterns in mass accumulation and vertical distribution
.................................................................................................................................74 3.6.2 Implications for sedimentary grain size interpretations ...................................82 3.6.3 Interpreting the sedimentary record from West Lake and similar settings ......84
3.7 Conclusions ...........................................................................................................86 Chapter 4 Snowfall variability and post-19th century arctic landscape disturbance
revealed by paired varved sedimentary records .............................................................87 4.1 Abstract .................................................................................................................87 4.2 Introduction............................................................................................................88 4.3 Study Site and Methods ........................................................................................90 4.4 Results...................................................................................................................93 4.5 Discussion .............................................................................................................99
4.5.1 Divergent varve records..................................................................................99 4.5.2 Hydroclimatic record .....................................................................................102
4.6 Conclusion...........................................................................................................104 Chapter 5 Conclusions and Future Work ......................................................................106
5.1 Summary .............................................................................................................106 5.2 Future Work.........................................................................................................109 5.3 Conclusion...........................................................................................................110
References....................................................................................................................112 Appendix A Correlation between Mould Bay and Rea Point weather stations..............129 Appendix B Suspended sediment trapping in limnological process studies .................130
x
List of Figures Figure 2.1: Location map of Cape Bounty on the southern coast of Melville Island in the
Canadian High Arctic. ..............................................................................................10
Figure 2.2: The effect of sample density on estimating total seasonal suspended
sediment yield in the East River, 2005.....................................................................16
Figure 2.3: Daily mean temperature at Rea Point, Mould Bay and Cape Bounty ...........19
Figure 2.4: Cumulative melting degree days at Cape Bounty ........................................20
Figure 2.5: Hourly hydrometeorological summaries...................................................21-23
Figure 2.6: Cumulative discharge and suspended sediment yield compared to
cumulative melting degree days ..............................................................................27
Figure 2.7: Mean monthly June,and July air-temperature records from Mould Bay and
Rea Point weather stations ......................................................................................40
Figure 3.1: Cape Bounty, Melville Island, Nunavut, and locations of meteorological and
hydrological stations ................................................................................................47
Figure 3.2: Schematic of the suspended sediment trap system .....................................52
Figure 3.3: West Lake seasonal inflow and depositional summaries for 2003...............56
Figure 3.4: West Lake seasonal inflow and depositional summaries for 2004...............58
Figure 3.5: West Lake seasonal inflow and depositional summaries for 2005...............60
Figure 3.6: Ratios of lower trap sedimentation rates to upper trap sedimentation ..........65
Figure 3.7: The ratio of Proximal to Mid site sedimentation rates ...................................67
Figure 3.8: West Lake inflow and deposition between June 28 and July 10, 2004........69
Figure 3.9: Mean grain size and deposition rates in the lower traps..............................72
Figure 3.10: Deposition rates versus mean grain size in traps .......................................73
Figure 3.11: Schematic representation sediment delivery and deposition.....................81
Figure 4.1: Coring sites in West and East Lakes at Cape Bounty...................................91
Figure 4.2: West and East varve thickness records........................................................95
Figure 4.3: Time-dependent Pearson correlation coefficients........................................96
Figure 4.4: West and East varve thickness records for the 20th century ........................97
xi
List of Tables Table 2.1: Differences in SSQ estimates based on spline curves...................................16 Table 2.2: Estimated snow water equivalence and total runoff for each watershed .......17 Table 2.3: Regression coefficients for daily discharge, suspended sediment yield and
melting degree days for each river...........................................................................33 Table 3.1 Mean June temperature at Cape Bounty, snow-water equivalence (SWE), total
discharge and suspended sediment yield................................................................55 Table 3.2 Total suspended sediment deposition in the upper and lower traps in the
Proximal and Mid stations in West Lake ..................................................................64 Table 3.3 Specific suspended sediment delivery and deposition (Mid lower trap) in West
River and Lake 2003-2005.......................................................................................70 Table 4.1: Pearson correlation coefficients between the varve thickness measurements
and weather variables..............................................................................................93 Table 4.2: Pearson correlation coefficient between the varve records............................96 Table 4.3: F-test statistic for selected time periods.........................................................97
1
Chapter 1 Introduction
It is widely understood that the Earth’s climate varies naturally due to large-scale
earth system processes. There is a consensus that human activities are altering
atmospheric composition, which in turn will alter the earth’s climate system (IPCC
2007). The impact of anthropogenic climate change on earth system processes
is wide in scope and in some cases not yet clearly understood, particularly in the
Canadian High Arctic. The Canadian High Arctic has limited instrumental climate
data available, which is problematic when considering long-term environmental
variability in this region (ACIA, 2005). Understanding current changes in a
broader context requires longer records of change.
Proxy indicators or natural archives record past climate and environmental
variations (Bradley, 1999) and when combined with modern climatological
measures, provide the means to quantitatively calibrate and assess proxies with
respect to present-day conditions. One common proxy, annually laminated lake
sediments, referred to as varves, has the potential to reconstruct annual
variations in hydroclimatic variability (e.g., Hardy et al., 1996; Overpeck et al.,
1997; Hughen et al., 2000; Hodder et al., 2007). Varve formation and
preservation occurs in a number of environmental circumstances, such as in
lakes where seasonal sediment delivery and deposition are driven by river inflow
and sediment transport (Sturm and Matter, 1978; Sturm, 1979; Smith, 1981). In
most cases, varve thickness reflects, in part, variation in hydroclimatic behaviour
2
that determines runoff and transport of available material (Gilbert, 1975;
Desloges, 1994; Desloges and Gilbert, 1994a,b; Lamoureux, 2002; Cockburn
and Lamoureux, 2007; Hodder et al., 2007).
Broadly, individual climate reconstructions based on one proxy have been
combined to produce indices to compare with climate forcing mechanisms (e.g.,
Overpeck et al., 1997; Mann et al., 1998; 1999). Each of these multi-proxy
paleoclimate reconstructions draws credibility from statistically significant signals
extracted from the compiled records and correlated with recent measures of
climate forcing mechanisms (e.g., solar irradiance, atmospheric CO2
concentrations: Overpeck et al., 1997; Mann et al., 1998; 1999). These multi-
proxy compilations demonstrate that there is a measurable common factor
influencing individual records, and given the geographical extent over which
these records correlate, it is assumed that the principle factor is related to
climate. Spatial variability in processes is often used to explain poor correlations
between different records. However, few studies attempt to demonstrate the
impact that spatial variability may have on records because most focus on single
records and thus preclude such analyses.
In general, it is anticipated that there is an underlying signal or pattern that
is reproducible at a high resolution (annual) from similar proxy records (e.g.,
varved lake sediments) from the same region. However, there are few studies
that have compared annual proxy records (e.g., varves: Desloges, 1994; Hughen
et al., 2000; Menounos et al., 2005; varves and tree-rings: Luckman, 2000) from
3
similar regions. In most cases, discrepancies between sedimentary records are
attributed to location-specific factors (e.g., physiography, weather). However,
there are rarely localized sedimentary process measurements that can
substantiate the character and magnitude of these discrepancies, and thus, the
impact of local differences on the individual records is unknown.
Proxy records with annual resolution afford the best opportunity to
compare the climate signal reproducibility from similar regions. The well-
constrained temporal resolution allows common forcing mechanisms (e.g.,
climate) to be identified. Furthermore, it allows available meteorological and
hydrological records to be used for calibration and comparison processes. As
well, seasonal process studies can be integrated into the calibration analyses to
better understand the record (Hardy et al., 1996; Lewis et al., 2002).
This study assesses annual reproducibility in two varve records from the
Canadian High Arctic in order to understand what environmental signal is
preserved. Through a combination of field process measures and available
meteorological records, the mechanisms by which varve sediments are
deposited in two lakes were assessed. Beyond the available instrument data,
the two records were used to independently verify and validate the signal
preserved in the varve record and identify anomalies due to geomorphic
processes or other differences rather than regional hydroclimatic controls.
4
It is hypothesized that there is a strong underlying climate signal,
reproducible at an annual scale between individual records from a similar region
for the entire length of the record (i.e., regardless of post-industrial anthropogenic
climate forcing mechanisms). In order to test the reproducibility of the dominant
annual signal in individual records, paired reconstructions based on clastic varve
deposition in two High Arctic lakes with adjacent watersheds were developed and
compared. Although evidence indicates that this is difficult to achieve and the
success of compilations tend to be at coarser temporal scales, previous studies
have not closely calibrated seasonal sediment deposition with hydroclimatic
measures or taken place in similar lake and watershed settings. Through
multiple seasons of observations, this study evaluated the seasonal fluvial and
lake sedimentary processes for each watershed. In doing so, the similarities
between the adjacent systems were compared through the last six centuries.
5
Chapter 2 Hydroclimate controls over seasonal sediment yield in two
adjacent High Arctic watersheds
In Press, Hydrological Processes
Authors:
Jaclyn M.H. Cockburn
Scott F. Lamoureux
Keywords: Nival melt; seasonal suspended sediment transfer; sediment delivery;
snow water equivalence, climate, erosion
2.1 Abstract
Interannual variations in seasonal sediment transfer in two High Arctic non-
glacial watersheds were evaluated through three summers of field observations
(2003-05). Total seasonal discharge, controlled by initial watershed snow water
equivalence (SWE) was the most important factor in total seasonal suspended
sediment transfer. Secondary factors included melt energy, snow distribution
and sediment supply. The largest pre-melt SWE of the three years studied
(2004) generated the largest seasonal runoff and disproportionately greater
suspended sediment yield than the other years. In contrast, 2003 and 2005 had
6
similar SWE and total runoff, but reduced runoff intensity resulted in lower
suspended sediment concentrations and lower total suspended sediment yield in
2005. Lower air temperatures at the beginning of the snowmelt period in 2003
prolonged the melt period and increased meltwater storage within the snowpack.
Subsequently, peak discharge and instantaneous suspended sediment
concentrations were more intense than in the otherwise warmer 2005 season.
The results for this study will aid in model development for sediment yield
estimation from cold regions and will contribute to the interpretation of
paleoenvironmental records obtained from sedimentary deposits in lakes.
2.2 Introduction
Spring snowpack and thermal conditions determine the magnitude and intensity
of runoff in Arctic rivers. Projected climate scenarios suggest that discharge in
arctic rivers will increase due to greater precipitation (ACIA, 2005) and seasonal
sediment discharge may also increase. These conclusions are consistent with
modeling studies based on ungauged Arctic rivers of varying basin area and
runoff magnitudes (Syvitski, 2002), but the sparseness of sediment delivery data
from these regions is acute. In addition to predicted increases in discharge due
to more precipitation, warmer temperatures may also increase sediment yield
through increased freeze-thaw processes and frozen ground dynamics (Woo et
al., 1992; Syvitski, 2002). Although models predict increased sediment yield,
there are few multi-year studies from Arctic catchments available for comparison
with model results.
7
In the Canadian High Arctic, non-glacial watersheds are characterized as
nival streamflow regimes, with short-lived flow (approximately 70-100 days; Woo
2000) and maximum discharge generated by spring snowmelt (Church, 1972).
Seasonal suspended sediment concentration (SSC) generally mirrors stream
discharge patterns; thus, high concentrations typically occur during or just prior to
the peak snowmelt runoff period (Woo and Sauriol, 1981; Lewkowicz and Wolfe,
1994; Forbes and Lamoureux, 2005). Furthermore, discharge magnitudes are
limited by total snowpack and melt intensity, since the primary source for surface
runoff is melting snow. Woo and Sauriol (1981) observed that cooler springs
prolonged snowpack melt processes and generated greater snowpack meltwater
storage within large snow banks and in channels filled with snow. The prolonged
melt period delays and ponds meltwater, which, once released, can generate
short-lived intense runoff that often accounts for a high proportion of the entire
seasonal discharge (Woo and Sauriol, 1981; Hardy, 1996). This brief period of
intense nival discharge generates high flow competence and fluid shear stress
and thus the potential for higher suspended sediment erosion, transport and
seasonal yield (Church, 1972; Lewkowicz and Wolfe, 1994; Forbes and
Lamoureux, 2005). Thus total suspended sediment discharge (SSQ) or seasonal
suspended sediment transported in a watershed is closely related to the intensity
and duration of nival discharge (Q) for catchments with abundant sediment
supply.
8
Multi-year studies (Lewkowicz and Wolfe, 1994; Priesnitz and Schunke,
2002; Forbes and Lamoureux, 2005) found that spring snow water equivalence
(SWE) explained the overall magnitude of total runoff better than spring melt
conditions (estimated by air temperature indices). This suggests that seasonal
suspended sediment yield appears to be closely linked to spring SWE;
consequently, snowpack exhaustion may limit total suspended sediment delivery
in nival streams. However, sediment supply variations that result in
intraseasonal sediment hysteresis can also play an important role in determining
yield (Nistor and Church, 2005; Hasholt and Mernild, 2006), although relatively
few studies of sediment yield hysteresis have been carried out in high latitude
watersheds. For example, at Hot Weather Creek, Ellesmere Island, sediment
supply appeared to be abundant and it was noted that sediment deposited in the
channel-bed after the previous day’s peak waned was subsequently remobilized
with increased discharge the following day (Lewkowicz and Wolfe, 1994).
This study presents three seasons of sediment yield observations from
two similar, adjacent watersheds in the Canadian High Arctic. This study aimed
to distinguish primary hydroclimate controls over seasonal sediment delivery in
similar watersheds. It was hypothesized that observed differences between the
watersheds subject to similar hydroclimatic forcings would reveal the nature and
magnitude of interseasonal suspended sediment yield hysteresis. In this manner
the results of this study provide the first analysis of paired watershed climate-
9
sediment yield dynamics with implications for assessing future climate sensitivity
and model verification.
2.3 Study Site
Cape Bounty (74º55’N, 109º35’W, Figure 2.1) is located on the south-central
coast of Melville Island, Nunavut, in the western Canadian High Arctic. The
landscape is characterized by relatively simple drainage patterns, sparse tundra
vegetation and continuous permafrost. The active layer varies between 20 and
70 cm depth and surface detachments and gullies are common features along
the river channels. The underlying bedrock of central Melville Island is
characterized by prominent syncline and anticline features (Harrison, 1994). The
dominant bedrock type in the headlands consists of upper Devonian Beverley
Inlet Formation and the middle Devonian Hecla Bay Formation is found in the
lowlands. Both formations are characterized by heavily weathered sandstones
and siltstones (Hodgson et al., 1984; Harrison, 1995).
10
Figure 2.1: Location map of Cape Bounty and the southern coast of Melville Island in the Canadian High Arctic. Inset map shows locations of Meteorological Service of Canada (MSC) stations at Rea Point, Mould Bay and Resolute (temperature only at Rea Point). Environmental monitoring stations and snow survey transect locations conducted each year are indicated. The transect network was expanded in 2004 and 2005. However, snow survey results presented in this study use the smaller 2003 subset for consistency.
11
Two adjacent watersheds with similar physiography were studied during
the 2003-2005 melt seasons. The West and East River1 watersheds are 8.0 km2
and 11.6 km2, respectively (Figure 2.1). The uplands of both watersheds reach
110-125 m above sea level (a.s.l.) and are characterized as gently sloped
plateaus covered in a veneer of glacial till and regressive Holocene marine
sediments (Hodgson and Vincent, 1984; Hodgson et al., 1984). The West River
has a slightly steeper gradient than the East River and as such, the West
catchment has more frequent and well-expressed gullies compared to the East
catchment.
This region is classified as a polar desert characterized by cold winters,
cool summers, and limited precipitation that occurs primarily as snowfall
(Maxwell, 1981). Mean summer (June, July, August) and winter (December,
January, February) temperatures at Rea Point (105 km northeast (Figure 2.1),
1969-1985) are 1.9 and –32.2ºC, respectively. Annual precipitation is dominated
by snow in winter months (< 150 mm, Mould Bay, NWT); whereas summers are
characterized by infrequent, low-intensity rainfall (< 10 mm/day).
2.4 Methods
A comprehensive watershed research program was established in 2003 to
monitor meteorological, hydrological and sediment transport conditions in both
watersheds at Cape Bounty. Prior watershed observations from the region are
1 All river names are unofficial
12
limited to short intervals (e.g., Wedel et al., 1977; McLaren, 1981) or
comprehensive data collection in small-scale slope studies (Lewkowicz and
Young, 1990).
2.4.1 Meteorology
Three seasonal meteorological stations were established in June 2003. The
primary station (MainMet) was located on the boundary between the two
watersheds and an additional station was located in the headwaters of each
watershed (Figure 2.1). Air temperature was measured 1.5 m above the ground
with thermistors (accuracy 0.4°C) and recorded at 10-minute intervals with either
Onset Hobopro (MainMet) or H8 loggers. Rainfall was measured with a Davis
industrial tipping bucket gauge (0.2 mm resolution) and an Onset Hobo event
logger at all three stations. Systematic wind, incoming solar and net radiation,
and relative humidity measurements were also recorded at MainMet, but results
are not described in this study.
Snow surveys were completed in early June of each season and
consisted of eleven depth measurements along 100-m transects with at least one
density measurement per transect. Transects were established at 15 locations in
2003 and expanded to 23 and 41 locations in 2004 and 2005, respectively
(Figure 2.1). Terrain classes were determined prior to the 2003 field season
based on topographic maps and aerial photographs. For purposes of
comparison between the three years, the results from the 2003 transect locations
13
are used in this study, although this necessarily reduces the available data. The
terrain index method (Yang and Woo, 1999) was used to estimate watershed
snow water equivalence (SWE) for each terrain class.
2.4.2 Hydrology
River gauging stations were established prior to runoff in each season at
locations with minimal channel snow cover and a single well-defined channel
(Figure 2.1). Stage was measured with a Sensym SCX vented differential
pressure transducer recorded at 10-minute intervals with an Onset Hobo H8
logger (accurate to 2 mm) in 2003 and Omega CP-Level101 (± 0.2%, 0.5 mm)
pressure transducer loggers with an Omega CP-PRTEMP101 (± 0.4%
atmospheric pressure) logger for barometric compensation in 2004 and 2005.
Manual discharge gauging was carried out with either a Columbia (± 4%) or
General Oceanics Flowmeter (± 1%) to rate the streams throughout each
season. A minimum of 12 points were used to develop rating curves each
season (r2 = 0.796 – 0.905) that were combined with recorded stage
measurements to construct seasonal hydrographs and calculate total season
discharge (estimated ± 10%). Due to unfamiliarity with the stream channels and
deep channel snowpack in 2003, the gauging station on the East River was
initially located in the middle of the channel. The resulting stage record, which
included the highest flow of the season, was deemed unusable because the
stilling well caused flow to back up.
14
Suspended sediment concentration (SSC) was determined from filtered
water samples collected with a DH-48 integrated water sampler at eight-hour
intervals in 2003 (West 0100, 0900, 1700h; East 0000, 0800, 1600h local time),
and hourly intervals during the peak snowmelt period, and two-hour intervals
thereafter in 2004 and 2005 from the West River. In East River, 2004 and 2005
SSC samples were taken less frequently due to personnel limitations. Between 4
and 10 samples per day were collected in 2004 and between 3 and 6 samples
per day in 2005. Volumetric samples were vacuum filtered with tared 0.45 µm
cellulose acetate (2003) and 1.0 µm glass fiber filters (2004 and 2005) and re-
weighed twice after drying at 50ºC in the laboratory to determine suspended
sediment concentration (± 0.1 mg·L). The filters were changed in 2004 to 1.0 µm
glass fiber filters to increase field process capacity and sample collection. To
evaluate the expected losses due to changing the type of filter after 2003, varying
sediment concentrations were filtered with tared 1.0 µm glass fiber filters, the
filtrate was then filtered with tared 0.45 µm cellulose acetate filters to estimate
the loss associated with using the 1.0 µm glass fiber filters. In all cases, the
difference between the 1.0 µm glass fiber and 0.45 µm cellulose acetate filters
was minimal and does not represent a significant difference in the concentrations
between years, but we are mindful that the SSC values obtained in 2003 may be
slightly higher.
The total suspended sediment discharge (SSQ) each season was
calculated from point SSC samples and total discharge in each river. In order to
15
estimate SSC between point samples, spline curves constrained by the SSC
point samples were used to construct an hourly sedigraph. From these values,
SSQ was calculated at one hour intervals as the sum of the product of SSC and
Q (± 20 kg·d-1). Limited sample processing capacity in 2003 restricted SSC
samples to three per day for each river, while increased capacity in the
subsequent years generated spline curves constrained by as many as 24 hourly
point samples.
In order to determine the bias induced by higher sampling resolutions in
2004 and 2005, alternative spline curves were fit with the minimum number of
sample points (three samples daily as collected in 2003) from the 2004 and 2005
data in order to compare the estimated SSQ values for each season (Table 2.1).
Due to the higher sampling frequency in 2004 and 2005, the 2003 SSC time
series represents a minima. As well, river turbidity was measured in East River
with an Analite NEP9500 turbidity sensor (± 10.0 NTU over the full range of SSC)
logged with a Hobo U12 logger at 30-second intervals in 2005. A comparison of
the turbidity time series with the point samples collected from the river
demonstrated that the point samples were comparable in most cases, but missed
short-lived periods of variability (Figure 2.2). This comparison indicates that point
samples likely underestimated the overall variability in SSC and thus suggests
that our estimates of SSQ are conservative. As well, given the stage
measurement problems encountered early in the 2003 East River runoff,
16
seasonal suspended sediment yield was determined to be a gross underestimate
in that year.
Table 2.1: Differences in SSQ estimates based on spline curves constrained by all available point SSC samples (SSQall) and a reduced number of point SSC samples to reflect the reduced sample interval undertaken in 2003 (SSQ2003). Specific sediment yields (Mg·km-2) are indicated in parentheses.
River, Year SSQall (Mg) SSQ2003 (Mg)
West 2003 134 (16.8) n/a
West 2004 413 (51.6) 410 (51.3)
West 2005 63 (7.9) 61 (7.6)
East 2004 433 (37.3) 425 (36.6)
East 2005 108 (9.3) 83 (7.2)
Date
Jun 12 Jun 14 Jun 16 Jun 18 Jun 20 Jun 22 Jun 24 Jun 26
Sus
pend
ed S
edim
ent
Con
cent
ratio
n (m
g. L)
0
200
400
600
800
1000
Point SamplesTurbidity Hourly Readings
Figure 2.2: The effect of sample density on estimating total seasonal suspended sediment yield in the East River, 2005. Point samples taken during short-lived high concentration periods induce over-estimates and likewise, point samples taken during short-lived low concentration periods generate under-estimates. The turbidity points shown represent the individual measurement taken on the hour, in conjunction with the manual point sample collected.
17
2.5 Results
2.5.1 Hydrometeorology
Snow surveys conducted prior to runoff in each watershed demonstrated that in
seasons with reduced estimated overall snowpack (2003 and 2005), SWE was
greater in the West catchment than the East catchment (Table 2.2). However, in
2004 when SWE was substantially higher, snowpack distribution was more
uniform across the two catchments. High winds throughout the winter in the High
Arctic result in large snowbanks and drifts on the lee slopes and in concave river
channels (Yang and Woo, 1999). Thus, the snow survey results likely
underestimate the total amount of snow in certain terrain classes. In particular, it
is highly likely that SWE was underestimated in the river channels as it was not
possible to obtain an absolute depth in many portions of the river channel (> 2.5
m probe length).
Table 2.2: Estimated snow water equivalence (SWE) and total runoff for each watershed at Cape Bounty compared to the total precipitation prior to each season (total, uncorrected Oct. – May) at Mould Bay, NWT (200 km west). The values from Mould Bay represent minimums as there are months with missing data, as well the precipitation gauge at Mould Bay malfunctioned during early 2005 (Meteorological Service of Canada, pers. Comm. 2005). The total runoff for the East River in 2003 is underestimated due to problems with the stilling well position during initial runoff.
West East
Year SWE (mm) ΣQ (mm) SWE (mm) ΣQ (mm)
Mould Bay
Precipitation (mm)
2003 43 69 20 >24 >89
2004 82 120 41 107 >68
2005 55 81 16 76 –
18
Daily mean air temperature data were highly correlated amongst the Cape
Bounty weather stations (r2 = 0.98 – 0.99, n ≥ 70, for all years). Correlation of
the Cape Bounty mean daily temperature records with the two closest
Meteorological Service of Canada (MSC) stations at Rea Point, Nunavut (r2 =
0.84 – 0.98, n ≥ 70, for all years) and Mould Bay, Northwest Territories (r2 = 0.85
– 0.98, n ≥ 70, for all years; Figure 2.3) was also high. Cumulative melting
degree days (MDD) indicate that 2005 was warmer earlier than the other two
years studied (Figure 2.4), but was similar to the long-term mean MDD values at
the nearby meteorological stations and not anomalously warm in the context of
the past 57 years. In addition, paired t-tests indicated that June 2005 was
significantly warmer than June temperatures in 2003 and 2004 at 95%
confidence. Furthermore, the t-test indicated that there were no significant
differences between June temperatures in 2003 and 2004 at the same
confidence level.
19
2003M
ean
Dai
ly
Tem
pera
ture
(o C)
-10-8-6-4-202468
1012
Rea PointMould BayCape Bounty
2004
Mea
n D
aily
Tem
pera
ture
(o C)
-10-8-6-4-202468
1012
Rea PointMould BayCape Bounty
2005
Date
06/01 06/06 06/11 06/16 06/21 06/26 07/01 07/06 07/11 07/16 07/21 07/26 07/31
Mea
n D
aily
Tem
pera
ture
(o C)
-10-8-6-4-202468
1012
Rea PointMould BayCape Bounty
Figure 2.3: Daily mean temperature at Rea Point, Mould Bay and Cape Bounty during June and July for the three years of this study.
20
2005
Date06/01 06/06 06/11 06/16 06/21 06/26 07/01 07/06 07/11 07/16 07/21 07/26 07/31
Mel
ting
Deg
ree
Day
s
020406080
100120140160180
2004
Mel
ting
Deg
ree
Day
s
020406080
100120140160180
2003M
eltin
g D
egre
e D
ays
020406080
100120140160180
June 15
June 15
June 15June 30
June 30
June 30
July 31
July 31
July 31Rea PointMould Bay
Cape Bounty
Mould Bay MeanRea Point Mean
Mould Bay MeanRea Point MeanRea Point
Mould BayCape Bounty
Mould Bay MeanRea Point MeanRea Point
Mould BayCape Bounty
Figure 2.4: Cumulative melting degree days (MDD) for each season at Cape Bounty and the long-term means determined on June 15, June 30 and July 31 from Rea Point and Mould Bay weather stations. Three reference lines (June 15, June 30 and July 31) show the cumulative thermal energy available prior to that date. The mean of the cumulative MDD at nearby weather stations are shown by triangles (Rea Point) and circles (Mould Bay) on June 15, June 30 and July 31. The means at Rea Point and Mould Bay are based on measurements between 1969–2005 and 1948–2005, respectively.
After initial ponding of meltwater in the streams in early to mid-June,
channelized flow was established at the gauging stations within 6-7 days in 2003
and 2004 and in less than 8 hours in 2005. Discharge was characterized by a
distinctive diurnal cycle that peaked at approximately 1700-1900h in both rivers.
Time to peak runoff was approximately a week in the first two years of the study,
21
and less than 2 days in 2005 (Figure 2.5). The date of initial and peak discharge
differed between the rivers by seven days in 2003, likely due to the reduced
snowpack in the East River watershed and channel, which required less time to
ripen and saturate with meltwater. In the West River, flow was rerouted through
a subnival channel after initial channelization in 2003 and 2004, but remained on
the snow surface channel in 2005 for the entire season (Lamoureux et al.,
2006a). Peak runoff duration and instantaneous peak discharge were similar
between the rivers in each respective season (Figure 2.5). Discharge responses
due to rainfall events during the summer were minor and short-lived (e.g., Figure
5a, July 28, 2003).
A comparison of the total runoff each season suggests that SWE was
significantly underestimated by the snow survey network and subsequent
surveys were expanded to improve representation (Table 2.2). Although SWE
underestimated total runoff, it predicted the relative difference between
watersheds and between years. Therefore it appeared reasonable to use these
data to relate hydroclimatological controls on seasonal sediment discharge at the
Cape Bounty study site. Estimates of seasonal snow accumulation from regional
weather stations were not comparable due to the unrepresentativeness of such
data (Woo et al., 1999; Yang and Woo, 1999). Furthermore, precipitation data
were not available for Rea Point, and missing data and instrument malfunction
(2004-5) at Mould Bay precluded comparable data from the station
(Meteorological Service of Canada, pers. comm. 2005).
Dat
e
Jun
20 Ju
n 25
Jun
30 Ju
l 05
Jul 1
0 Ju
l 15
Jul 2
0 Ju
l 25
Jul 3
0
024681012
010
020
030
040
050
0
Dat
e
Jun
01 Ju
n 06
Jun
11 Ju
n 16
Jun
21 Ju
n 26
024681012
Dat
e
Jun
20 Ju
n 25
Jun
30 Ju
l 05
Jul 1
0 Ju
l 15
Jul 2
0 Ju
l 25
Jul 3
0
024681012
Hourly SSC (mg/L)
0
500
1000
1500
2000
2003
Hourly AirTemperature (
oC)
-8-4048121620
04
-8-4048121620
05
-8-40481216
Hourly
Discharge (m3/s)
Hourly
Discharge (m3/s)
0.0
0.3
0.6
0.9
1.2
1.5
1.8
Hourly Discharge (m3/s)
0.0
0.3
0.6
0.9
1.2
1.5
1.8
0.0
0.3
0.6
0.9
1.2
1.5
1.8
Hourly SSC (mg/L)
0
500
1000
1500
2000
050
010
0015
0020
0025
0030
0035
0040
0050
0060
00Rainfall (mm)
0 4 8 12
Rainfall (mm)
0 4 8 12
No
rain
fall
010
020
030
040
050
0
010
020
030
040
050
0
Tota
l Q =
69
mm
Tota
l Q =
120
mm
Tota
l Q =
81
mm
SSQ
= 1
34 M
gSS
Q =
413
Mg
(4
10 M
g)SS
Q =
63
Mg
(61
Mg)
SSQ (Mg)
Q (x 105 m
3)
Q (x 105 m
3)
Q (x 105 m
3)
SSQ (Mg)
SSQ (Mg)
Hourly SSC (mg/L)Hourly AirTemperature (
oC)
Hourly AirTemperature (
oC)
22
Figu
re 2
.5a,
figu
re c
aptio
n fo
llow
s
Dat
e
Jun
01 Ju
n 06
Jun
11 Ju
n 16
Jun
21 Ju
n 26
02468101214
Dat
e
Jun
20 Ju
n 25
Jun
30 Ju
l 05
Jul 1
0 Ju
l 15
Jul 2
0 Ju
l 25
Jul 3
0
02468101214
010
020
030
040
050
0
010
020
030
040
050
0
Hourly SSC (mg/L)
0
500
1000
1500
2000
2500
3000
0.0
0.3
0.6
0.9
1.2
1.5
1.8 Hourly SSC (mg/L)
0
500
1000
1500
2000
2500
3000
Discharge (m3/s)
0.0
0.3
0.6
0.9
1.2
1.5
1.8
Dat
e
Jun
18 Jun
23 Jun
28 Jul 0
3 Jul 0
8 Jul 1
3 Jul 1
8 Jul 2
3 Jul 2
8
Hourly SSC (mg/L)
0
500
1000
1500
2000
2500
3000
Discharge (m3/s)
0.0
0.3
0.6
0.9
1.2
1.5
1.8
2003
Air Temperature (oC)
-40481216
Rainfall (mm)
0 4 8 12
2004
Air Temperature (oC) -8-40481216
Rainfall (mm)
0 4 8 12
2005
Air Temperature (oC) -8-40481216N
o R
ainf
all
SSQ
= 4
33 M
g
(425
Mg)
Tota
l Q =
107
mm
SSQ
= 1
08 M
g (8
3 M
g)
Tota
l Q =
67
mm
Figu
re 2
.5b,
Fig
ure
capt
ion
follo
ws
Q (x 105 m
3)
Q (x 105 m
3)
Discharge (m3/s) SSQ (Mg)
SSQ (Mg)
Poi
nt D
isch
arge
M
easu
rmen
ts
23
24
Figure 2.5: Hourly hydrometeorological summaries for (a) West and (b) East River catchments. Note that the time period shown is different for each year. Values in parentheses on the sedigraph are the total SSQ estimates based on a reduced sample set in order to be comparable to the dataset collected in 2003 (see text for description). The hydrograph at the beginning of 2003 in East River is unavailable because the channel where the gauging station was located was not free of snow at this time. The bottom panel for each year shows the cumulative discharge (m3) and cumulative suspended sediment yield (Mg).
2.5.2 Sediment Delivery
Suspended sediment concentration (SSC) reached seasonal maximums after
peak runoff in both rivers in all cases except in the East River 2005, when peak
SSC occurred prior to peak discharge (Figure 2.5). In general, SSC remained
low prior to peak discharge. However, as runoff and channelization progressed,
access to sediments and SSC increased. Maximum SSC varied considerably
each year, but was substantially higher in 2004 (5526 mg·l, West River). During
the same season, higher SSC was maintained over a longer duration in both
rivers compared to 2003 and 2005. In 2003 and 2004, the mean SSC after peak
discharge was substantially larger than the mean SSC during the same periods
in 2005 (Figure 2.5).
In 2003 and 2004 the majority of suspended sediment was transferred in
less than one week (Figure 2.5). After the nival peak, discharge and SSC
decreased substantially, and resulted in relatively minimal suspended sediment
discharge (SSQ). In 2005, SSQ (Figure 2.5) was more uniform over the entire
runoff season compared to the previous two years. Although the 2005 season
was comparatively short due to reduced snowpack and warm conditions, further
25
appreciable snowmelt-sourced discharge was unlikely when observations
ceased.
2.6 Discussion
2.6.1 Hydroclimate controls over seasonal runoff
Previous studies in the arctic have pointed to the short-lived, intense nival peak
as the most significant period for suspended sediment transport (Lewkowicz and
Wolfe, 1994; Hardy, 1996; Braun et al., 2000; Priesnitz and Schunke, 2002;
Beylich and Gintz, 2004; Forbes and Lamoureux, 2005). Hence, it is important to
consider the hydroclimatic controls that contribute to nival runoff. Seasonal
discharge in the Cape Bounty rivers was generated and sustained primarily by
snowmelt over three seasons (Figure 2.6). Runoff intensity was proportionate to
initial SWE and the rate at which snowmelt water was produced. The clearest
indication of the dominant control of SWE over discharge was the response of
both rivers in 2004, a year with relatively high SWE and low available melt
energy (Figures 2.5, 2.6). By comparison, reduced SWE in both 2003 and 2005
resulted in substantially lower peak discharge, duration of peak runoff and
sediment delivery, and lower total runoff and suspended sediment yield (Figure
2.6).
Total runoff is the net of winter snowfall, and losses due to ablation and
evaporation and infiltration and resultant soil storage. Losses due to ablation and
evaporation will be minimal in cool springs due to limited available thermal
26
energy (Woo and Sauriol, 1980; Woo and Young, 1997). In warm springs,
ablation losses may be greater, and the snowpack may become fragmented due
to rapid melting. In 2005 snowmelt began three weeks earlier than the previous
two springs (Figure 2.4). Combined with reduced SWE, the early warm spring in
2005 produced an accelerated melt period and rapid channelization. The
snowpack on slopes and uplands was fragmented and isolated earlier which
resulted in a reduction of the runoff contribution area. The reduced connectivity
of the fragmented slope snowpack further delayed meltwater runoff from
reaching the channel, and introduced greater potential for infiltration into newly
thawed soil and increased flow resistance. In 2003 and 2004, reduced available
melt energy slowed snow cover losses, particularly in areas with thin snowpack,
resulting in more extensive snow cover through the melt period. Thus, conditions
in these years maintained a larger contributing area to flow throughout the peak
snowmelt period that sustained high discharge for longer.
27
Cumulative Melting Degree Days0 20 40 60 80 100 120 140
Cum
ulat
ive
Dis
char
ge(x
104 m
3 )
0
20
40
60
80
100
Est
imat
ed S
WE
(mm
)
0
20
40
60
80
100
West 2003West 2004West 2005
Cumulative Melting Degree Days0 20 40 60 80 100 120 140
Cum
ulat
ive
Sus
pend
ed
Sed
imen
t Yie
ld (M
g)
0
100
200
300
400
500
Est
imat
ed S
WE
(mm
)
0
20
40
60
80
100
West 2003West 2004West 2005
(a) (b)
2004 SWE
2005 SWE2003 SWE
2004 SWE
2005 SWE2003 SWE
Cumulative Melting Degree Days0 20 40 60 80 100
Cum
ulat
ive
Dis
char
ge
(x10
4 m3 )
020406080
100120140
Est
imat
ed S
WE
(mm
)
0
10
20
30
40
50
East 2004East 2005
Cumulative Melting Degree Days0 20 40 60 80 100
Cum
ulat
ive
Sus
pend
ed
Sed
imen
t Yie
ld (M
g)
0
100
200
300
400
500
Est
imat
ed S
WE
(mm
)
0
10
20
30
40
50
East 2004East 2005
2005 SWE
2004 SWE
2005 SWE
2004 SWE
(c) (d)
Figure 2.6: Cumulative discharge (a and c) and suspended sediment yield (b and d) compared to cumulative melting degree days (MDD) for West (a and b) and East Rivers (c and d). Estimated SWE for each catchment and year it represents is indicated by horizontal dashed lines.
In addition to SWE magnitude, runoff intensity also depends on the rate of
snowmelt water production (Woo, 1983). A season with reduced thermal energy
inputs can generate a more intense runoff due to meltwater stored within
snowbanks and the snowpack. Woo and Sauriol (1980) observed that cooler
springs delayed peak runoff due to ponded meltwater, and consequently
increased runoff intensity in rivers near Resolute. Additionally, they also
observed that cooler springs reduced overall ablation losses when accompanied
by reduced solar radiation due to increased cloud cover (Woo and Sauriol, 1980;
Woo and Young, 1997). In 2003 and 2004, the snowmelt period at Cape Bounty
28
was prolonged due to cool conditions (Figure 2.4). Meltwater produced in early
spring was temporarily stored within the snowpack and in thick snow banks
within the channels for up to a week. In several instances ponding was observed
behind deep, near-saturated channel snow banks which increased the potential
meltwater runoff in the catchments. A prolonged period of ponding occurred in
West River in 2003 and 2004 (seven days) but once the channel was
established, runoff was intense. However, in 2005, ponding occurred for only
eight hours due to the small volume of snow and rapid snowpack melting during
the warm spring. Thus, runoff intensity was reduced in 2005 due to the lack of
water storage and limited meltwater production.
The secondary, but important links between runoff intensity and thermal
conditions are demonstrated through a comparison between 2003 and 2005.
Although 2003 and 2005 had similar SWE estimates and total discharge, the
delayed release of meltwater in 2003 generated more intense runoff compared to
2005. Melt energy available in 2003 was reduced compared to 2005 (estimated
by total melting degree days; Figure 2.4) and led to meltwater storage within the
snowpack and seven days of ponding in the channels. In this respect, 2003 was
quite similar to 2004 and both years exhibited increased runoff intensity.
The observations from Cape Bounty are consistent with and contribute to
a growing number of studies that indicate that the primary control over nival
runoff is through catchment snowpack. The increase in total seasonal discharge
associated with larger snowpacks is typically clear (e.g., Lewkowicz and Wolfe,
29
1994; Forbes and Lamoureux, 2005). However, the results from both this study
and previous work suggest that increased spring snowpack also appears to
lengthen the duration of high discharge during the spring (e.g., Forbes and
Lamoureux, 2005). These conditions are mediated by available melt energy and
in many instances, daily discharge is significantly correlated with temperature
(Hardy, 1996; Forbes and Lamoureux, 2005). However, these relationships
become more complex or weaken as snowpack is progressively exhausted
(Forbes and Lamoureux, 2005). Hence, while the relationship between melt
energy and daily discharge may be important for discharge generation during the
nival peak, seasonal discharge appears primarily governed by the amount of
snow available. Melt energy and snowpack distribution contribute as secondary
factors and are important in distinguishing between years with similar SWE (e.g.,
2003 and 2005). It is of particular note that increased discharge during the nival
peak may not necessarily result in higher instantaneous discharge. Rather, the
period of high discharge may be prolonged for several days and result in
substantially higher total discharge (Forbes and Lamoureux, 2005).
2.6.2 Hydroclimate controls on seasonal sediment delivery
Total runoff generated by snowmelt each spring was the most important
hydroclimatic factor controlling seasonal sediment delivery at Cape Bounty.
Runoff intensity appeared to be a secondary condition controlling seasonal
suspended sediment yield. Total seasonal sediment delivery was greatest in
2004 (Figure 2.5; Table 2.1; West 413 Mg, East 433 Mg) in response to the
30
largest spring snowpack, total runoff and runoff intensity. Additionally, increased
runoff resulted in a disproportionately larger increase in SSQ. Comparison
between 2003 and 2004 reveals that 2004 runoff was nearly double, but SSQ
increased by nearly four times. In 2003 and 2005 when SWE and total runoff
were similar (Figure 2.5) the corresponding seasonal SSQ was dissimilar
because each watershed responded differently. The disproportionate response
between the three seasons studied is likely reflected in the differences in runoff
intensity and possibly interannual sediment supply.
In the West River 2003 and 2005, SWE and total runoff were similar, but
SSQ was substantially reduced in 2005. The major difference between the two
seasons was that runoff was more intense in 2003 because snowmelt runoff was
prolonged due to reduced thermal energy (Figure 2.4). In 2005, runoff was
characterized by reduced peak instantaneous discharge and SSC and therefore
the stream competence was reduced (Figure 2.5a). Furthermore, cumulative
SSQ shows a gradual transfer of sediment in 2005 rather than rapid transfer over
a short period of time as observed in the preceding two years (Figure 2.5a, 2005
bottom panel). The East River responded similarly, with gradual sediment
transfer in 2005 compared to rapid sediment transfer over a few days in 2004
(Figure 2.5b, bottom panel).
These results demonstrate that seasonal SSQ does not proportionately
respond to total runoff and likely reflects the duration of maximum instanteous
discharge (intense runoff) and SSC during the season (Forbes and Lamoureux,
31
2005). In 2003 and 2004, the majority of suspended sediment transfer occurred
over a short period of time and reflects the importance of flow competence and
sediment availability during this period. These results are similar to the
responses reported in other arctic river systems. For example, in a study of two
watersheds on Ellesmere Island, Nunavut, 86 – 99% of the seasonal suspended
sediment load was transported during the main melt period (Lewkowicz and
Wolfe, 1994). Additionally, peak instantaneous discharge was substantially
higher in the year with greater SWE (~15 m3·s-1 (SWE 118 mm) and 3.8 m3·s-1
(SWE 43 mm); Lewkowicz and Wolfe, 1994), which in part, reflects the
differences in SWE between years and a delayed spring in the former (Woo et
al., 1991). In a multi-year study of two creeks in the Richardson Mountains,
northern Yukon, the greatest sediment delivery occurred at the transition into the
late nival flood phase, where 99% of the annual suspended load was delivered
during the five-day snowmelt period (Priesnitz and Schunke, 2002). Similarly,
Forbes and Lamoureux (2005) observed that the only time three middle arctic
rivers carried appreciable sediment was during the brief period (several days) of
maximum discharge and noted that increased catchment SWE sustained the
period of high discharge and effectively increased seasonal SSQ. Their results
showed that a SWE increase of approximately 1.7 times corresponded to 3.5
times greater total SSQ in the Lord Lindsay River (Forbes and Lamoureux,
2005).
32
Analysis of hydroclimatic controls on sediment delivery by Hardy (1996)
indicated that thermal indices could reasonably estimate total seasonal SSQ from
a mountainous watershed on northern Ellesmere Island, although SWE
information was not included in the study. Similar analysis at Cape Bounty with
daily melting degree days (MDD), total daily discharge and total daily SSQ (Table
2.3) demonstrate that the strongest correlations were during initial sediment
transfer only. Even though the strongest correlations were observed early in the
season, the relationship was not consistent each year, or between the rivers. In
the warmest season (2005) at Cape Bounty, discharge and suspended sediment
yield were poorly correlated with daily MDD (Table 2.3) unlike the previous years
when suspended sediment yield was more strongly correlated with daily MDD in
the early season. This suggests that despite warmer conditions, runoff from
snowmelt was the dominating control in sediment yield and cooler conditions led
to more intense runoff and sediment transfer. For example, 2005 was warmer
and correlations between daily suspended sediment yield in the West River and
temperatures suggest that the warmer conditions in 2005 did not have a positive
influence on the overall sediment yield. Furthermore, in each river, most of the
suspended sediment flux occurred prior to major accumulation of MDD. This
suggests that daily MDD may be a poor predictor of seasonal discharge and total
sediment yield in a given year, especially where there is a large spring snowpack
at Cape Bounty.
33
Table 2.3: Regression coefficients (r) for daily discharge, suspended sediment yield and melting degree days (MDD) for each river during the periods of highest and lowest daily runoff and sediment transfer rates. The 2003 East Season is not reported due to the stilling well problems at the beginning of the season. The 2005 season was not separated into high and low rate periods due to the short record available.
West River
High Rate
West River
Low Rate
West River
Total Season
East River
High Rate
East River
Low Rate
East River
Total Season
Year Q vs
MDD
(n)
SSQ
vs
MDD
(n)
Q vs
MDD
(n)
SSQ
vs
MDD
(n)
Q vs
MDD
(n)
SSQ
vs
MDD
(n)
Q vs
MDD
(n)
SSQ
vs
MDD
(n)
Q vs
MDD
(n)
SSQ
vs
MDD
(n)
Q vs
MDD
(n)
SSQ
vs
MDD
(n)
2003 0.47
(7)
0.98
(4)
-0.19
(29)
-0.18
(32)
-0.09
(36)
-0.14
(36) n/a n/a
2004 0.11
(15)
0.79
(9)
-0.03
(22)
-0.06
(28)
0.14
(37)
0.42
(37)
-0.10
(14)
0.73
(11)
0.03
(23)
0.29
(26)
0.08
(37)
0.42
(37)
2005 -0.43
(15)
-0.15
(15)
0.06
(18)
0.45
(17)
Despite the dominance of snowpack controls over total SSQ, thermal
conditions likely played an indirect role in suspended sediment delivery at Cape
Bounty through pre-runoff snow ablation. In 2005, conditions were substantially
warmer than the previous two years and caused rapid snowpack fragmentation
and melt that reduced runoff and limited sedimentation erosion from many first-
order channels. By contrast, 2003 had a similar SWE but the snowpack was
substantially less fragmented. Increased connectivity of first-order sediment
supplies may in part explain the higher sediment yields in 2003 compared to
2005.
34
Finally, in 2003 and 2004, the West River tunneled under thick channel
snowpacks to access sediment on the river bed. In 2005, the river did not tunnel
beneath the snowpack and thus the river had reduced access to sediment
supplies through the peak runoff period (Lamoureux et al., 2006a). Similar
tunneling was not apparent in the East River in any of the years studied, hence it
is difficult to know the extent to which isolation from the channel bed could have
affected the 2005 sediment yield (e.g., Woo and Sauriol, 1980; 1981).
In addition to snowpack meltwater production controls over total runoff and
runoff intensity in a season, these results suggest that a third factor may
influence seasonal sediment yield at Cape Bounty. Despite similar SWE and
total runoff, total SSQ in 2005 West River was less than half of the 2003 yield. A
key difference between the years was the lower overall SSC and reduced
instantaneous peak discharge in both rivers during 2005. It is possible that
reduced yields in 2005 were caused by some degree of reduced sediment
availability; essentially a form of interseasonal sediment hysteresis that may have
been caused by sediment exhaustion due to high sediment yields in 2004. As
well, observations suggested that some sediment supplies, available early in the
season during 2003 and 2004 and resulted in significant deposits of sediment on
channel snowpack, were unavailable in 2005 (Lamoureux et al., 2006a).
If sediment availability was reduced in 2005, the observed differences
between the West and East Rivers (Table 2.3) suggest that the West River was
more affected by interannual sediment exhaustion. The apparent difference in
35
sediment supply between the watersheds may be explained by differences in
watershed geomorphology. In general, the West watershed has narrower
channels and steeper slopes compared to the broader valley in the East
watershed. This potentially leads to more snow being trapped in depressions
and gullies in the West catchment. As well, snow cover was generally patchier in
the East catchment compared to the West catchment, likely due to prevailing
winter winds redistributing snow. Furthermore, Lamoureux et al. (2006a)
demonstrated that ponding in early spring can abandon a substantial amount of
sediment on multi-year channel snow banks in the West River, nearly 17% of the
annual sediment yield in 2003. Similar ponding in the East River was not
observed and potentially is less likely due to the broader channels. This
suggests that sediment source and channel storage mechanisms are more
complex in the West River watershed. Although these results suggest that the
West River is more sensitive to interannual sediment supply variations than the
East River, the available data are not sufficient to conclusively demonstrate the
extent to which hysteresis actually occurred and how consistent this differential
sensitivity would be with different snowpack and hydroclimatic conditions.
2.6.3 Sensitivity of sediment yield to climate variability in high arctic watersheds
The results from this study suggest that sediment transfer is most sensitive to
runoff conditions during the nival freshet which are primarily controlled by
catchment SWE, and to a lesser extent, melt energy and snow cover distribution.
36
Comparison of adjacent catchments with similar underlying bedrock, surficial
materials and vegetation cover suggests that interannual sediment yield
variations are also likely subject to localized, potentially important geomorphic
controls. Therefore, climate model results that predict future increased winter
precipitation have important implications on sediment transfer in nival-dominated
Arctic river systems.
Syvitski (2002) modeled sediment loads with respect to temperature and
discharge increases and concluded that 2ºC warming would increase sediment
loads by 22%. This was partially due to greater sediment availability due to
increased active layer thickness (Woo et al., 1992; ACIA, 2005), but also due to
larger snowpacks and nival freshets (Syvitski, 2002). Results from Cape Bounty
are in agreement with these results, although the short record prevents analysis
of the role of changing active layer thickness on sediment yield. The
disproportionate increase in sediment yield between 2003 and 2004 in response
to greater SWE suggests greater yield sensitivity than the model results,
although the modeling was based on much larger watersheds (Syvitski, 2002).
Moreover, the apparent sensitivity may reflect local sediment availability
characteristics, which vary widely across the Canadian Arctic (Lewkowicz and
Wolfe, 1994; Lamoureux, 2000). For example, Forbes and Lamoureux (2005)
also found disproportionate responses in watersheds approximately 100 times
larger than the Cape Bounty watersheds, suggesting that the response observed
at Cape Bounty may scale up in some cases. However, Forbes and Lamoureux
37
(2005) also reported low yields, so it is difficult to determine if the limitations are
due to scale issues or sediment supply.
Although temperature was not shown to be a primary control over
seasonal sediment transfer at Cape Bounty, the impact of warmer temperatures
in the future may influence sediment supply in the catchment through permafrost
degradation and surface disruption. The three years observed at Cape Bounty
are insufficient to observe any changes in sediment supply due to the impact of
warmer summers and perhaps increased permafrost degradation. However,
sedimentary records from lakes and ponds have been used to estimate past
sediment yield (e.g., Lamoureux, 2002; Verstraeten and Poesen, 2002). Lakes
and ponds that receive clastic sedimentary inputs can serve as natural archives
of seasonal sediment runoff from the catchment. Examination of the sedimentary
records from the downstream lakes at Cape Bounty is underway to quantify past
sedimentation patterns and provide additional means to evaluate sediment yield
departures and interannual hysteresis.
2.6.4 Interpreting hydroclimatic variability from downstream sedimentary records
Examination of the hydrometeorological measurements at Cape Bounty with
concurrent regional observations suggests none of the years monitored were
extremes with respect to temperature; thus, our observations may be considered
typical of these watersheds for the past 57 years (Figure 2.7). Interpretation of
the precipitation records over the region is problematic as wind re-distribution of
38
snow is significant in the Arctic, especially in years with low snow-cover (Yang
and Woo, 1999). As already discussed, the total precipitation and snowpack at
Cape Bounty do not correlate with precipitation from weather stations at Mould
Bay or Resolute which are located at sea level on the coast compared to the
snow survey results from Cape Bounty, which were carried out over a range of
elevations (20–120 m a.s.l.).
The multi-season study of sediment transfer at Cape Bounty has important
implications for the interpretation of the sedimentary records in lakes subject to
similar watershed processes. Catchment studies have been used to quantify the
relationships between hydrometeorological conditions and sedimentation
processes in order to infer the climate signal preserved within the sedimentary
record (e.g., Hardy et al., 1996; Gilbert and Butler, 2004). There are few studies
in the Arctic that pair paleoclimate reconstructions from a site with a catchment
process study, although there has been success in statistically interpreting the
paleoclimatic record from lake sediments without an associated process study
(e.g., Hughen et al., 2000; Francus et al., 2002; Hambley and Lamoureux, 2006).
In a pioneering study, Hardy et al. (1996) concluded that early summer
temperature was significantly correlated to annual sedimentary layer thickness in
a lake with a partially glacierized drainage basin on northern Ellesmere Island
based on a process study completed at the site (Hardy, 1996). In addition to
warmer temperatures, runoff was an order of magnitude larger in the warmer
spring and subsequently generated a greater sediment yield (Hardy, 1996).
39
Although there were no SWE data available and the site likely receives some
glacial-meltwater inputs each summer, the study established a strong
climatological (thermal) link with sediment delivery processes in the Arctic.
However, as in this study, there is a strong relationship between total discharge
and seasonal sediment delivery at Lake C2. In a recent study in the Canadian
Middle Arctic, Lamoureux et al. (2006b) interpret the annually laminated
sediments in Sanagak Lake, Boothia Peninsula, Nunavut as a record of spring
discharge controlled by SWE based on two years of process studies that
included characterization of SWE (Forbes and Lamoureux, 2005). The Boothia
study characterized the relationship between hydrological process and sediment
deposition and demonstrated the potential to explore the linkages between
climate and hydrology through laminated lake sediment records.
40
Mean June Temperature
Year AD1950 1955 1960 1965 1970 1975 1980 1985 1990 1995 2000 2005
Mea
n Te
mpe
ratu
re (o C
)
-6
-4
-2
0
2
4
Mould BayRea PointCape Bounty
Mean July Temperature
Year AD1950 1955 1960 1965 1970 1975 1980 1985 1990 1995 2000 2005
Mea
n Te
mpe
ratu
re (o C
)
0
2
4
6
8
Mould BayRea PointCape Bounty
(a)
(b)
Figure 2.7: Mean monthly (a) June, and (b) July air-temperature records from Mould Bay and Rea Point weather stations. Note that an equipment change (to automated measurement) at Mould Bay resulted in gap in the record.
Our results demonstrate that seasonal sediment transfer in nival
watersheds is dependent primarily on SWE and total runoff, and secondly, on
runoff intensity. Therefore, the sedimentary record in the downstream lakes may
also reflect nival melt magnitude and intensity. However, temperature can
indirectly mediate suspended sediment transfer through melt generation and
connectivity of runoff and sediment supply sources. Furthermore, warmer
temperatures may increase sediment availability through increased permafrost
degradation and potential sediment availability over longer time scales.
41
The indications of possible inter-annual sediment yield hysteresis at Cape
Bounty raise a critical issue for the interpretation of sedimentary records as
hydroclimatic proxies. Multi-year sediment yield exhaustion could conceivably
alter the sedimentary record by dampening sediment accumulation following high
yield years like 2004. To date, little work has been carried out to investigate this
issue. A study of a varve record from a nivally-dominated system identified
sediment supply effects that lasted multiple decades (Lamoureux, 2002). Annual
mass accumulation during the past 487 years revealed evidence for sustained
high sediment yields for up to 17 years after a year with an exceptional yield
(Lamoureux, 2002). The impact of this type of sediment availability is important
to consider as part of the hydroclimatic interpretation of the sedimentary record,
and varies substantially between lake systems. For example, in a study from
Sophia Lake, Cornwallis Island, Nunavut, sediment supply was limited to thin,
discontinuous surficial deposits and resistant carbonate bedrock. In this case,
the recurrence of high sediment yields after a large event was considered
unlikely (Braun et al., 2000). Further work to explore these effects is clearly
warranted, given the growing number of paleoenvironmental records derived
from sedimentary records.
2.7 Conclusions
Seasonal suspended sediment yield from two high arctic catchments was
controlled by SWE through total runoff and runoff intensity in a given season.
Interannual seasonal suspended sediment yield increased disproportionately in
42
response to higher total discharge through prolonged high instantaneous
discharge and SSC. Variable snowcover altered the production and intensity of
meltwater runoff, and influenced the sediment yield by isolating runoff from
sediment sources, particularly in the channel. Furthermore, comparison of the
two catchments suggests that increased SWE, and resultant large runoff and
suspended sediment yield in 2004 may have exhausted sediment supplies and
reduced yields in the subsequent year. Each watershed exhibited a different
degree of inferred sediment exhaustion, indicating the importance of watershed-
specific conditions.
Given the observed response to different snow years, it is likely that
sediment yields in this environment will increase in response to increased winter
precipitation predicted by current models. In addition, although increased
temperatures play a secondary role in controlling seasonal sediment yield in this
study, it is likely that warmer temperatures will also increase permafrost
degradation and potentially increase sediment supplies. The three years studied
were not anomalous with respect to temperature records for the last 57 years
from weather stations in the region. Therefore, the results reported here appear
representative of the typical sediment transfer conditions in these streams for
that period. However, longer records of seasonal sediment transfer processes
are still needed to evaluate interannual sediment hysteresis and further elaborate
the likely responses of arctic watersheds to projected climate change. Finally,
these results demonstrate the need to evaluate long-term sediment delivery
43
processes and to carefully consider watershed processes prior to the
interpretation of downstream sedimentary records.
44
Chapter 3 Inflow and lake controls on short-term mass accumulation and particle size in a High Arctic lake: implications for interpreting
varved lacustrine sedimentary records
In Press, Journal of Paleolimnology
Authors:
Jaclyn M.H. Cockburn
Scott F. Lamoureux
Keywords: Suspended sediment discharge; deposition; turbidity; grain size;
paleoclimate; laminae
3.1 Abstract:
Sedimentary processes monitored in a lake with varved sediments in the
Canadian High Arctic through three melt seasons revealed that seasonal
sediment deposition rates were highly dependent on short-lived inflow events
driven by high suspended sediment concentrations that varied with runoff
intensity. Our results illustrate that in accordance with suspended sediment
discharge into the lake, the rate of sediment accumulation changed over short
distances down-lake, in a given year. This result indicates that there is a rate
and accumulation dependence on short-lived, intense inflow conditions. In
addition, there was strong evidence for substantial decoupling between
deposition rate and mean grain size of sedimentary deposits. These results have
45
important implications for paleoclimatic interpretation of annually laminated
sedimentary records from dynamic lake environments and suggest that grain size
measures may not be representative proxies of inflow competence. Grain size
indices based on a measure of the coarser fraction, rather than the bulk
sediment, may be more appropriate to use as a link between contemporary
runoff processes and sedimentary characteristics.
3.2 Introduction
Several multi-year studies have examined the relationship between
hydroclimatologic behaviour and sediment delivery to arctic lakes (e.g. Retelle
and Child 1996; Braun et al. 2000; Lewis et al. 2002) in an effort to quantitatively
understand the factors that control the formation of the lacustrine sedimentary
record. In addition to these studies, physical limnologic studies elsewhere have
focused on contemporary processes that control seasonal and/or annual
sediment deposition in lakes and have assisted in the paleolimnologic
interpretation of sedimentary records (e.g. Gilbert 1975; Ross and Gilbert 1999;
Gilbert and Butler 2004). In cases where sedimentary deposits are annually
laminated, other studies have described spatial variability in sediment deposition
through time and through multiple sediment core studies in the High Arctic
(Lamoureux 1999; 2000; 2002) and in other alpine regions (Smith 1978; Leonard
1997; Menounos et al. 2006; Schiefer 2006a, b). Although these studies have
emphasized seasonal mass accumulation, recent work has suggested grain size
may be a potentially useful sedimentary parameter to evaluate past hydroclimatic
46
conditions from the sedimentary record (Francus et al. 2002). However, to date,
few field studies have demonstrated that sedimentary grain size relates to inflow
characteristics (e.g., Sundborg and Calles 2001).
Several recent studies (e.g. Lamoureux 1999; Hodder et al. 2007) have
identified the need to examine the direct and indirect links between sedimentary
proxy records of past hydrometeorologic behaviour. In this paper, we report
results from a study that investigated the detailed sediment delivery
characteristics and deposition patterns in a High Arctic lake located at Cape
Bounty, Melville Island, Nunavut, Canada, for three melt seasons (2003, 2004
and 2005). In addition to the documented seasonal relationship between
hydroclimatological processes and physical sedimentation in West Lake, the
character (texture) of the seasonal deposits was evaluated to determine if
particle size could be used as a representative hydroclimatic proxy indicator. In
an effort to understand the contemporary hydroclimatic processes that influence
sediment deposition, we hope to further elucidate the environmental signal
preserved in varved and other sedimentary sequences.
3.3 Study Site
Melville Island is located in the western Canadian Arctic Archipelago (Figure 3.1).
At Cape Bounty (74º55’N, 109º35’W, Figure 3.1), there are several, freshwater
coastal lakes fed by small rivers draining non-glaciated watersheds without
47
Figure 3.1: (a) Cape Bounty, Melville Island, Nunavut, and locations of meteorological and hydrological stations. Inset shows location of Melville Island in the Canadian Arctic Archipelago. (b) West Lake bathymetry and limnological monitoring sites.
48
present-day glaciers. The landscape is characterized by gentle hills and incised
plateaux mantled with Late Wisconsinan glacial and Holocene marine sediments
(Hodgson and Vincent 1984). Vegetation cover in this continuous permafrost
region is classified as graminoid tundra, which is dominated by patchy sedges
and other prostrate dwarf-shrub and ford tundra species (Walker et al. 2005).
West Lake (unofficial name) is located ~5 m above sea level and has a maximum
depth of 34 m (Figure 3.1).
Nearby weather stations at Mould Bay, Northwest Territories (250 km
west) and Rea Point, Nunavut (100 km northeast) have relatively long summer
temperature records that extend to 1948 and 1969, respectively. Mean June and
July temperatures from these stations are similar and demonstrate that initial
melt generally begins in June and lasts until mid- to late August. Mean June and
July temperatures were 0.0ºC and 3.8ºC at Mould Bay (1948-2006) and were -
0.1ºC and 4.0ºC, respectively, at Rea Point (1969-2006). The West Lake
watershed has a maximum elevation of 126 m, which is substantially higher than
the low elevation stations at Mould Bay and Rea Point, but previous work
suggests that these stations and Cape Bounty experience broadly similar
meteorological conditions (Cockburn and Lamoureux, 2008a).
Runoff is dominated by snow melt which typically reaches peak discharge
during a one-week period between mid to late June. Maximum suspended
sediment in the river typically occurs early in the runoff season and is associated
with peak discharge (McDonald 2007). Snowpack was found to be the dominant
49
control on seasonal river runoff and suspended sediment discharge in the West
River and the adjacent watershed (Cockburn and Lamoureux 2008a). The short
period of intense runoff is the main control over seasonal suspended sediment
transfer (Cockburn and Lamoureux, 2008a) and is consistent with similar studies
of nival Arctic watersheds (e.g. Lewkowicz and Wolfe 1994; Braun et al. 2000;
Forbes and Lamoureux 2005). Infrequent, low-intensity (less than 12 mm/d)
rainfall occurred through the summer months in 2003 and 2004 and generated
limited runoff responses, while no events were observed in the 2005 melt
season.
3.4 Methods
3.4.1 Hydrometeorology
Hydrometric monitoring at Cape Bounty began in early June 2003 and continued
each melt season thereafter. Snow surveys were completed prior to runoff each
spring in order to estimate snow water equivalence (SWE) and potential runoff
for each season. The snow survey network designed in 2003 was expanded in
2004 and again in 2005 as familiarity with the area increased (Cockburn and
Lamoureux, 2008a). Transects were established across the watershed in
different landscape units. Each 100 m-long transect was comprised of 11 depth
measurements and at least one density measurement. Transect SWE estimates
were averaged for each terrain unit and catchment SWE was determined from a
terrain-weighted mean (Yang and Woo, 1999). Weather stations were
50
established in two locations in the watershed (Figure 3.1a). Precipitation was
recorded with Davis Industrial gauges (0.2 mm resolution, 4% accuracy)
recorded with an Onset Hobo event logger or Unidata Prologger. Air
temperature was recorded at 10-minute intervals with a shielded Onset Hobo H8
(0.4ºC accuracy, West Met) or Onset HoboPro loggers (0.2ºC accuracy, Main
Met Station) at 1.5 m above the ground. Systematic wind, incoming solar and
net radiation, and relative humidity measurements were also recorded, but these
data were not used for this study.
The river gauging station, established upstream of West Lake, recorded
water stage with a Sensym SCX vented differential pressure transducer recorded
at 10-minute intervals with an Onset Hobo H8 (±2 mm) in 2003, and Omega CP-
Level101 (±0.2%, 0.5 mm) pressure transducer logger with an Omega CP-
PRTEMP101 (±0.4% atmospheric pressure) logger for barometric compensation
in 2004 and 2005. Water temperature was measured with a Campbell Scientific
107-L water temperature sensor (±0.2ºC) logged with a CR10 logger in 2003 and
with the Omega pressure logger (±0.2% water temperature) in 2004 and 2005.
Stream rating was carried out at the gauging station using either a Columbia
current meter (±4%) or General Oceanics Flowmeter (±1%) at regular intervals
during the runoff period. Point suspended sediment samples were collected with
a DH48 integrated water sampler three times daily in 2003, and hourly through
the peak runoff and bi-hourly during the recession period in 2004 and 2005.
Volumetric suspended sediment samples were filtered in the field on tared 0.45
51
µm Whatman cellulose acetate filters (2003) and Osmotics 1.0 µm glass fibre
filters (2004, 2005) and returned to the laboratory to be dried at 50ºC and
weighed to calculate suspended sediment concentrations through the season.
The change in filters after 2003 was required to increase sample processing
capacity and comparative tests revealed minimal impacts on resultant suspended
sediment concentrations.
3.4.2 Limnology
Perennial lake ice was present during all seasons and provided a platform for
limnological deployments. Bathymetry was mapped using a Garmin GPS and
Humminbird depth sounder (± 1 m) through ice holes and through the ice pan in
2003 and 2004 (Figure 3.1b). Based on the bathymetry, traps were deployed in
the deepest known location in West Lake prior to runoff in 2003 (“Mid” site). After
initial results from 2003, a second site (“Proximal” site) was established for 2004
and 2005. At each site, sediment that settled out of the water column was
trapped to measure suspended sediment deposition (SSD) at frequent time
intervals. The sediment traps were constructed of a replaceable receptacle
mounted with a funnel with vertical walls to reduce turbulence along the upper
edge of the funnel and minimize the potential for sediment to settle along the
sides of the funnel (Figure 3.2). In 2003, the traps were changed daily during the
peak period and then as infrequently as once a week afterwards. In 2004 and
2005 the traps were collected and redeployed daily during the peak discharge
period and reduced to bi-daily intervals afterwards. The traps were moored at
52
0.5 m (lower trap) and 15 m (upper trap) from the lake bottom at each location in
order to evaluate how sediment was distributed through the water column (Figure
3.2).
2 l polyethylene bottle with the bottom cut off
50 mL centrifuge tube
Hole through
ice
Water Column
Weight
Lake Bottom
0.5 m frombottom
2 small holes in the plastic with a leader fed through to secure the line
Line
15 m frombottom
Anchor across the hole to secure line
Figure 3.2: Schematic of the suspended sediment trap system deployed at Cape Bounty.
The trap receptacles were retrieved and separated from the funnels,
sealed with headspace water and returned to the laboratory where they were
filtered through pre-weighed 0.4 µm Isopore polycarbonate filters, oven dried
(50ºC) and re-weighed to determine dry mass accumulation. Particle size
analysis of the trapped sediment was carried out with the filtered sediment
53
samples after pretreatment with 30% hydrogen peroxide to digest organic
material. Removal of the sediment from the filters was facilitated by the smooth
surface provided by the laser-drilled polycarbonate filter material. After
pretreatment, the samples were rinsed with distilled water into a Beckman
Coulter LS200 laser particle size analyzer equipped with a fluid module. Each
sample was analysed for 60 seconds with sonication, three times successively
and the unaveraged third run was retained. Individual trap samples from the
peak runoff period provided sufficient material for the particle size analyzer to
calculate the grain size distribution for the lower trap at each site on a daily basis
(>30 mg). However, reduced available sediment mass precluded daily particle
size characterization of the 2004 upper traps and in both trap sets from 2005. In
these cases, successive daily samples were combined until sufficient material
was present to obtain reliable results with the particle size analyser.
In addition to sediment trapping, water temperature (resolution 0.01ºC, ±
0.1ºC) was recorded at 20-minute intervals deployed 0.5 m above the sediment
water interface at the Mid site with a Sequoia LISST-100 CTD. Progressive lens
obscuration precluded use of the in-situ particle size information from the CTD.
In 2005, two Hobo Water Temp Pro loggers (resolution 0.02ºC, ± 0.2ºC) were
also deployed to monitor temperature in the water column at 1 m (not shown)
and 15 m (mid-column) above the sediment water interface at the Mid site. To
isolate short-lived fluctuations in lake bottom temperature from the seasonal
54
background warming trend, temperature departures (Td) were calculated as
follows:
Td = Tn -Tn-1 (1)
where Td was the calculated temperature departure, and Tn and Tn-1 were
the sequential measured temperature values (ºC).
3.5 Results
The results reported in this study were collected as part of a comprehensive
watershed monitoring program established at Cape Bounty in 2003. Field
observations were carried out to obtain relevant data to support investigations of
the linkages between meteorological, hydrological, and limnological processes
that contribute to the sedimentary record. Detailed analysis of sediment delivery
characteristics and hysteresis in the West River are described in McDonald
(2007) and climatic controls over seasonal sediment yield in the West and
adjacent East catchments (unofficial names) are assessed by Cockburn and
Lamoureux 2008a.
3.5.1 Hydrometeorology
Snowcover and snow-water equivalence varied substantially between the three
seasons. 2004 had the largest SWE estimates and a relatively continuous
snowcover in early June (Table 3.1). Snowcover was patchy and SWE was
lower in 2003 and 2005 (Table 3.1). In 2003 and 2004, initial snowpack melt
ponded in portions of the river channel prior to flow channelization due to
55
temporary snowpack dams. The ponded meltwater built up substantial runoff
potential and subsequent runoff was intense (Lamoureux et al. 2006; Cockburn
and Lamoureux, 2008a). The meltwater progressively incised into the snowpack
and reached the channel bottom during or after the peak spring discharge. Initial
melt and flow channelization was substantially different in 2005, due to warmer
spring temperatures. Channelization occurred within a 24-hour period and
temporary ponds did not form. Thermal conditions in 2005 were more favourable
for rapid and continuous melt, as opposed to the cooler conditions in the previous
years (Table 3.1) which led to episodic melt water generation and significant
meltwater storage in temporary ponds. As a result, runoff intensity was
substantially less intense in 2005 and flow remained on a snow-lined channel
through the initial runoff period and isolated from potential sediment sources on
the channel bed during peak runoff (Lamoureux et al. 2006). In addition to the
warmer conditions (Table 3.1), the thin 2005 snowpack melted and fragmented
rapidly, which further contributed to the moderate runoff intensity and reduced
total runoff volume (McDonald 2007; Cockburn and Lamoureux 2008a).
Table 3.1 Mean June temperature at Cape Bounty, snow-water equivalence (SWE), total discharge and suspended sediment yield for the West River during 2003-2005 at Cape Bounty.
Year Mean June
Temperature (ºC)
Estimate SWE (mm)
Total Runoff (mm)
Total Suspended Sediment Yield (Mg)
2003 -0.9 43 69 134 2004 -0.1 82 120 413 2005 2.0 55 81 63
56
Runoff and sediment delivery to West Lake began in mid June in 2003
and 2004 and early June 2005. In 2003 and 2004, peak suspended sediment
concentrations generally coincided with peak discharge and occurred 2-4 days
afterwards (Figures 3.3, 3.4). In 2005 suspended sediment concentrations were
comparatively low (Figure 3.5). The larger lag between peak runoff and
suspended sediment concentrations observed in 2005 was due to flow that was
isolated from the channel bed and potential sediment supplies for the majority of
the runoff period (McDonald 2007; Cockburn and Lamoureux 2008a). This
contrasts the observations from 2003 and 2004, where flow reached the channel
bed and sediment supplies relatively quickly (McDonald 2007). Additionally, the
magnitude of peak discharge and suspended sediment yield in 2005 was
considerably less than in 2003 and 2004. This is attributed to the decreased
runoff intensity due to continuous melt without ponding and a reduced and
fragmented snowpack (Table 3.1; Cockburn and Lamoureux 2008a).
57
Lower Lake Trap
DateJun 20 Jun 24 Jun 28 Jul 02 Jul 06 Jul 10 Jul 14 Jul 18 Jul 22 Jul 26 Jul 30
Cum
ulat
ive
Dep
ositi
on (m
g. cm-2)
0
1
2
3
4
Mid
Upper Lake Trap
Cum
ulat
ive
Dep
ositi
on (m
g. cm-2)
0.0
0.1
0.2
0.3
0.4
0.5
Mid
Tem
pera
ture
(o C)
-0.08
-0.04
0.00
0.04
0.08
Dis
char
ge (m
3.s-2
)
0.0
0.5
1.0
1.5
Hou
rly R
iver
Te
mpe
ratu
re (o C
)
-2024681012
Sus
pend
ed S
edim
ent
Con
cent
ratio
n (m
g. L-1)
0
500
1000
1500
2000
Susp
ende
d Se
dim
ent
Dis
char
ge (M
g)
0
50
100
150
200
Sus
pend
ed S
edim
ent
Dis
char
ge (M
g)0
50
100
150
200
(a)
(b)
(c)
(d)
(e)
(f)
Lake
Bot
tom
Te
mpe
ratu
re (o C
)
0.300.350.400.450.500.550.60
Hou
rly A
ir Te
mpe
ratu
re (o C
)
-10-505
1015
Rai
nfal
l (m
m)
051015
(g)
(h)
Instruments removed July 1, 2003
Instruments removed July 1, 2003
Figure 3.3, see caption below, next page.
58
Figure 3.3: West Lake seasonal inflow and depositional summaries for 2003. (a) Hourly air temperature and daily rain fall, (b) hourly river temperature, (c) hourly river discharge, (d) hourly suspended sediment concentration in the river, (e) lake bottom temperature (f) lake bottom temperature departures, (g) cumulative suspended sediment deposition in the upper water column trap (20 m depth; bar graph), cumulative suspended sediment discharge from the river (solid line) and (h) cumulative suspended sediment deposition in the lower water column trap (33.5 m depth; bar graph) and cumulative suspended sediment discharge from the river (solid line).
59
Lower Lake Traps
DateJun 20 Jun 24 Jun 28 Jul 02 Jul 06 Jul 10 Jul 14 Jul 18 Jul 22 Jul 26 Jul 30 Aug 03 Aug 07
Cum
ulat
ive
Dep
ositi
on (m
g. cm-2)
0
2
4
6
8
10
12
14
ProximalMid
Sus
pend
ed S
edim
ent
Con
cent
ratio
n (m
g. L-2)
010002000300040005000D
isch
arge
(m3.s-1
)
0.0
0.4
0.8
1.2
1.6
Hou
lry R
iver
Te
mpe
ratu
re (o C
)
-2024681012
Upper Lake Traps
Cum
ulat
ive
Dep
ositi
on (m
g. cm-2)
0.0
0.2
0.4
0.6
0.8
1.0
1.2
ProximalMid
Tem
pera
ture
(oC
)
-0.15-0.10-0.050.000.050.100.15
Cum
ulat
ive
Sus
pend
ed
Sed
imen
t Dis
char
ge (M
g)
0
100
200
300
400
500
Cum
ulat
ive
Sus
pend
ed
Sed
imen
t Dis
char
ge (M
g)
0
100
200
300
400
500
Hou
lry A
ir Te
mpe
ratu
re (o C
)-4
0
4
8
12
Rai
nfal
l (m
m)
051015
Lake
Bot
tom
Tem
pera
ture
(o C)
0.00.20.40.60.81.01.2
(a)
(b)
(c)
(d)
(e)
(f)
(g)
(h)
Figure 3.4, see caption next page.
60
Figure 3.4: West Lake seasonal inflow and depositional summaries for 2004. (a) Hourly air temperature and daily rain fall, (b) hourly river temperature, (c) hourly river discharge, (d) hourly suspended sediment concentration in the river, (e) lake bottom temperature (f) lake bottom temperature departures, (g) cumulative suspended sediment deposition in the upper water column trap (20 m depth; Proximal site dark gray bars, Mid site light gray bars) and cumulative suspended sediment discharge from the river (solid line) and (h) cumulative suspended sediment deposition in the lower water column trap (33.5 m depth; Proximal site dark bars, Mid site light bars) and cumulative suspended sediment discharge from the river (solid line).
61
Lower Lake Trap
Date
Jun 05 Jun 07 Jun 09 Jun 11 Jun 13 Jun 15 Jun 17 Jun 19 Jun 21 Jun 23 Jun 25 Jun 27
Cum
ulat
ive
Dep
ositi
on (m
g. cm-2)
0.0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
ProximalMid
Dis
char
ge (m
3 )
0.00.20.40.60.81.0
Hou
rly R
iver
Tem
pera
ture
(o C)
0
1
2
3
4
Tem
pera
ture
(o C)
-0.06-0.04-0.020.000.020.040.06
Cum
ulat
ive
Dep
ositi
on (m
g. cm-2)
0.0
0.1
0.2
0.3
0.4
ProximalMid
Upper Lake Trap
Cum
ulat
ive
Sus
pend
ed
Sed
imen
t Dis
char
ge (M
g)
0
20
40
60
80
Cum
ulat
ive
Sus
pend
ed
Sed
imen
t Dis
char
ge (M
g)
0
20
40
60
80
Hou
rly A
irTe
mpe
ratu
re (o C
)
-202468
No precipitation
Sus
pend
ed S
edim
ent
Con
cent
ratio
n (m
g/L)
0100200300400500
Lake
Col
umn
Tem
pera
ture
(o C)
0.40.50.60.70.80.9
Bottom tempMid-column temp
(a)
(b)
(c)
(d)
(e)
(f)
(g)
(h)
Figure 3.5, see caption next page.
62
Figure 3.5: West Lake seasonal inflow and depositional summaries for 2005. (a) Hourly air temperature and daily rain fall, (b) hourly river temperature, (c) hourly river discharge, (d) hourly suspended sediment concentration in the river, (e) lake bottom temperature (f) lake bottom temperature departures, (g) cumulative suspended sediment deposition in the upper water column trap (20 m depth; Proximal site dark gray bars, Mid site light gray bars) and cumulative suspended sediment discharge from the river (solid line) and (h) cumulative suspended sediment deposition in the lower water column trap (33.5 m depth; Proximal site dark bars, Mid site light bars) and cumulative suspended sediment discharge from the river (solid line).
63
3.5.2 Sediment deposition rates and patterns
When channelized runoff initially reached the lake, the ice within 100 m of the
delta flooded temporarily (1-2 days). The lake ice at the delta rapidly melted and
the remainder of the lake-ice pan lifted from the shore, which allowed river flow to
enter the lake unimpeded by the lake ice thereafter. The ice pan persisted
through to at least mid-August (based on field observations and satellite imagery)
each year.
Suspended sediment deposition (SSD) from traps generally corresponded
with suspended sediment concentrations (SSC) in the river and the resultant
cumulative river suspended sediment discharge curve mirrored the cumulative
SSD profile in all three years (Figures 3.3-3.5). The periods of highest SSD were
associated with periods of the highest SSC in the river. In 2003 and 2004, these
periods of high sediment inflow were associated with temperature perturbations
up to 0.12ºC in the lake bottom (Figures 3.3, 3.4). By comparison, the bottom
temperature departures were less frequent in 2005 and were substantially lower
magnitude with a maximum absolute value 0.05ºC. Temperature in 2005 was
stable to the resolution of the instrument (0.01ºC) for several periods of 24 hours
or more.
The multi-level trap deployment generated daily and near-daily records of
suspended sediment deposition in the upper and lower water columns (Figures
3.3-3.5 bottom two panels (g, h)). In general, deposition was greatest in the
64
lower trap compared to the upper water column trap as to be expected based on
the relative depths of the overlying water columns, with the lower traps exposed
to sedimentation from approximately two times the potential suspension
deposition. The lower Proximal monitoring site received the most sediment each
year and the upper Mid monitoring site received the least sediment each year
(Figures 3.3-3.5; Table 3.2). However, total deposition in the lower trap was not
twice the deposition in the upper trap for a given season, which indicated that
sediment was not distributed uniformly through the water column. Furthermore,
the ratio of lower to upper deposition varied substantially, and included instances
where deposition patterns were inverted (ratio <1, Figure 3.6; Table 3.2). After
peak discharge and concurrent river suspended sediment concentrations,
differences between sedimentation rates in the lower traps and upper traps
declined and approached the idealized ratio of two (Figure 3.6). The ratios from
2005 did not follow a similar pattern and may be due to the shorter monitoring
period or the relatively small differences observed between the upper and lower
traps.
Table 3.2 Total suspended sediment deposition in the upper and lower traps in the Proximal and Mid stations in West Lake. Year Upper Trap Lower Trap Lower:Upper Ratio Proximal:Mid Ratio
Proximal
(mg·cm-2)
Mid
(mg·cm-2)
Proximal
(mg·cm-2)
Mid
(mg·cm-2) Proximal Mid Upper Traps
Lower
Traps
2003 - 0.40 - 3.45 - 8.62 - -
2004 1.02 0.82 13.26 8.03 13.0 9.79 1.24 1.65
2005 0.29 0.19 1.20 0.47 4.14 2.47 1.53 2.55
65
(b) Mid Site Lower:Upper
DateJun 05 Jun 13 Jun 21 Jun 29 Jul 07 Jul 15 Jul 23 Jul 31 Aug 08
Low
er:U
pper
Tra
p D
epos
ition
Rat
io
0.1
1
10
100 200320042005
120
2
(a) Proximal Site Lower:Upper
DateJun 05 Jun 13 Jun 21 Jun 29 Jul 07 Jul 15 Jul 23 Jul 31 Aug 08
Low
er:U
pper
Tra
p D
epos
ition
Rat
io
0.1
1
10
100
2
20042005
Figure 3.6: Ratios of lower trap sedimentation rates to upper trap sedimentation rates for each year at the (a) Proximal and (b) Mid site mooring locations. The lines for ratios of 1 and 2 are shown on each graph.
66
Expanded trap deployment in 2004 and 2005 yielded data to evaluate the
proximal-distal relationship in the near-delta environment. The Proximal site
recorded the most sediment deposition each year and on June 29-30, 2004, the
lower trap received a large portion of sediment that was not observed at the Mid
site (Figure 3.4). With this one exception, the two sites otherwise mirror
seasonal sediment delivery to the lake closely, with lower sedimentation rates at
the Mid site. The ratio of Proximal to Mid site deposition for each season was
similar over the two year comparison (Table 3.2). However, daily Proximal:Mid
site ratios were largest for the lower traps, up to 300 on June 29, 2004, when
increased sedimentation at the Proximal site was not observed at the Mid site
(Figure 3.7). The high ratios were primarily associated with high sediment inflow
to the lake during the early season. After peak runoff and sediment delivery in
2004, the ratio stabilized ~1-3, and in some cases, sedimentation rates were
slightly greater in the lower Mid site trap relative to the lower Proximal site trap
(ratio <1, Figure 3.7b).
Sediment delivery to the lake was closely linked to suspended sediment
concentration and river discharge. Periods of turbid discharge corresponded to
the largest daily suspended sediment deposition events (Figure 3.3, 3.4). In
2004, over a period of 12 days, 97% of the total seasonal suspended sediment
discharge was delivered to the lake and coincided with 90% of the total
deposition in the lower Proximal trap site and 57% of the total deposition in the
67
(b) Proximal:Mid Lower Trap Ratios
DateJun 05 Jun 13 Jun 21 Jun 29 Jul 07 Jul 15 Jul 23 Jul 31 Aug 08
Pro
xim
al:M
id S
ite T
rap
Dep
ositi
on R
atio
s
0.01
0.1
1
10
100 20042005
(a) Proximal:Mid Upper Trap Ratios
DateJun 05 Jun 13 Jun 21 Jun 29 Jul 07 Jul 15 Jul 23 Jul 31 Aug 08
Prox
imal
:Mid
Site
Tra
p D
epos
ition
Rat
ios
0.1
1
1020042005
20
300
Figure 3.7: The ratio of Proximal to Mid site sedimentation rates for each year in the (a) upper and (b) lower traps. The line for a ratio of 1 is shown on each figure.
68
lower Mid trap site (Figure 3.8). As was noted above, between June 28 and June
30, more than 50% of the total sediment in the lower Proximal trap was
deposited, while very little sediment accumulated in the lower Mid trap (Figure
3.8, event 1). This deposition episode (1) in the Proximal site corresponded to
peak river discharge and high suspended sediment concentrations. At the Mid
site, minimal temperature changes occurred at this time (Figure 3.8). However,
in two later events (July 3 and 4, events 2 and 3 respectively), bottom
temperature underwent short-lived, rapid perturbations up to 0.1ºC that were
coincident with both high discharge and suspended sediment concentrations in
the river. These large temperature fluctuations coincided with the two highest
sediment deposition episodes in the lower Mid trap site for the season, and
relatively high deposition in the lower Proximal trap as well (Figure 3.8). By
comparison, the upper traps at both locations did not collect substantial amounts
of sediment (Figure 3.4).
Warm temperatures on July 21, 2004 increased discharge and lake
bottom temperatures following a slight time lag. There was also a small, short-
lived increase in suspended sediment concentrations during the higher discharge
period (increased from ~18 mg•l-1 to a maximum 114 mg•l-1). For approximately
eight hours, SSC exceeded 100 mg•l-1, and coincided with positive temperature
anomalies recorded at Mid site. There was also a noticeable increase in
sediment deposition at both trap sites for this period of time.
69
Date
Jun 28 Jun 29 Jun 30 Jul 01 Jul 02 Jul 03 Jul 04 Jul 05 Jul 06 Jul 07 Jul 08 Jul 09 Jul 10
Cum
ulat
ive
Dep
ositi
on (m
g. cm-2)
0
2
4
6
8
10
12
14
ProximalMid
Susp
ende
d Se
dim
ent
Con
cent
ratio
n (m
g. L-2)
010002000300040005000 D
isch
arge
(m3.s-1
)
0.0
0.4
0.8
1.2
1.6H
oulry
Riv
er
Tem
pera
ture
(o C)
012345
Tem
pera
ture
(oC
)
-0.16-0.12-0.08-0.040.000.040.080.120.16
Cum
ulat
ive
Sus
pend
ed
Sedi
men
t Dis
char
ge (M
g)
0
100
200
300
400
500
Lake
Bot
tom
Tem
pera
ture
(o C)
0.4
0.6
0.8
1.0
(a)
(b)
(c)
(d)
(e)
(f)
2
3
1
1
2
2
3
Figure 3.8: West Lake inflow and deposition between June 28 and July 10, 2004. (a) Hourly river temperature, (b) hourly river discharge, (c) hourly suspended sediment concentration in the river, (d) lake bottom temperature (e) lake bottom temperature departures, (f) cumulative suspended sediment deposition in the lower water column trap (33.5 m depth; Proximal site dark gray bars, Mid site light gray bars with diagonal hatching) and cumulative suspended sediment discharge from the river (solid line). Three notable events are labelled 1-3, and the lag between peak SSC and maximum temperature departures for events 2 and 3 is shown with a dashed line.
In 2005, nearly 50% of the deposition in the lower Proximal trap occurred
between June 11 and 12 (Figure 3.5). However, this rapid deposition was only
70
observed at the Proximal site in 2005 and it was nearly an order of magnitude
less than the maximum daily deposition rate during peak runoff in 2004 (Figure
3.4, 3.5). The substantial difference in accumulation observed between 2004
and 2005 was less than the difference in total SSQ for the two years and cannot
be easily explained by these differences. The most likely cause was that
deposition in 2005 was much less energetic (Table 3.3). As well, the
temperature record from the bottom of the lake at Mid site in 2005 did not
indicate major temperature perturbations through this high accumulation period
at the Proximal site. This was further evidence for passive suspension settling
type deposition in 2005.
Table 3.3 Specific suspended sediment delivery and deposition (Mid lower trap) in West River and Lake 2003-2005. Sediment delivery was determined from the seasonal sediment yield unweighted across the entire catchment (from Cockburn and Lamoureux, 2008a). Deposition rates were determined from traps.
2003 2004 2005
Total suspended sediment discharge
(g·m-2) from inlet 16.8 51.3 7.6
Total suspended sediment deposition
(g·m-2) in lake 34.5 80.3 4.7
Deposition to Delivery Ratio 2.1 1.6 0.6
3.5.3 Sedimentary grain size characteristics
Overall mean grain size of trapped sediment was substantially finer in 2005 than
in 2004 at both sites (Figure 3.9). Mean grain size was coarsest early in the
71
2004 season at both sites and coincident with high deposition rates. With few
exceptions, mean grain size fined to less than 10 µm by the end of the season
(Figure 3.9). Due to limited material in the sediment traps in 2005, daily trap
samples were combined in order to achieve sufficient amounts of material for
grain size determination. Despite the reduced number of 2005 analyses, the
season was characterized by finer material than 2004, and a trend towards finer
grain size through the season was observed (Figure 3.9). An abrupt increase in
air temperature on July 22, 2004 resulted in a minor increase in river discharge,
SSC and trap deposition at both sites, but the trapped sediment was only
substantially coarser (20 µm) in the proximal trap.
In 2004, the prominent sedimentation event recorded in the lower
Proximal trap and absent from the Mid trap between June 28-30 was not as
coarse (224 µm Proximal compared to 40 µm at Mid) as the event that followed
and recorded at both trap sites (Figure 3.9). Overall, the Proximal site exhibited
counter-clockwise grain size hysteresis which was weaker or absent at the Mid
site in 2004 (Figure 3.10). With limited material for particle size analyses in
2005, hysteresis interpretations were not possible (Figure 3.10). Overall, there
was a general divergence of grain size and deposition rates through both
seasons and both locations. Thus, higher deposition rates did not necessarily
correspond with coarser particles and may reflect sediment grain size hysteresis
observed within the fluvial system (McDonald 2007).
72
(a) Proximal Lower Trap 2004
Jun 20 Jun 24 Jun 28 Jul 02 Jul 06 Jul 10 Jul 14 Jul 18 Jul 22 Jul 26 Jul 30 Aug 03 Aug 07
Cum
ulat
ive
Dep
ostio
n (m
g. cm-2
)
0
2
4
6
8
10
12
14
Mea
n G
rain
Siz
e (u
m)
0
10
20
30
40
50Cumulative depositionMean grain size
224 um
*Insufficient material for grain size determination
*Insufficient material for grain size determination
(c) Proximal Lower Trap 2005
Jun 05 Jun 07 Jun 09 Jun 11 Jun 13 Jun 15 Jun 17 Jun 19 Jun 21 Jun 23 Jun 25 Jun 27
Cum
ulat
ive
Dep
ostio
n (m
g. cm-2
)
0.00.20.40.60.81.01.21.4
Mea
n G
rain
Siz
e (u
m)
0
10
20
30
40
50Cumulative depositionMean grain size
(d) Mid Lower Trap 2005
DayJun 05 Jun 07 Jun 09 Jun 11 Jun 13 Jun 15 Jun 17 Jun 19 Jun 21 Jun 23 Jun 25 Jun 27
Cum
ulat
ive
Dep
ostio
n (m
g. cm-2
)
0.0
0.1
0.2
0.3
0.4
0.5
0.6M
ean
Gra
in S
ize
(um
)
0
10
20
30
40
50Cumulative deposition Mean grain size
(b) Mid Lower Trap 2004
Jun 20 Jun 24 Jun 28 Jul 02 Jul 06 Jul 10 Jul 14 Jul 18 Jul 22 Jul 26 Jul 30 Aug 03 Aug 07
Cum
ulat
ive
Dep
ostio
n (m
g. cm-2
)
02468
101214
Mea
n G
rain
Siz
e (u
m)
0
10
20
30
40
50Cumulative depositionMean grain size
* * * * * * * * * *
* * * * * * *
Figure 3.9: Mean grain size and deposition rates in the lower traps at (a) the
Proximal (b) the Mid sites in 2004 and (c) Proximal and (d) Mid sites in 2005. Light gray bars are mean grain size and wider bars represent the traps that were combined to determine particle size. The white bars represent the cumulative suspended sediment deposition.
73
(a) Lower Proximal Trap 2004 and 2005
2004 Deposition (mg.cm-2)0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0
2004
Mea
n G
rain
Siz
e (u
m)
0
50
100
150
200
250
2005 Deposition (mg.cm-2)0.0 0.2 0.4 0.6 0.8 1.0
2005
Mea
n G
rain
Siz
e (u
m)
0.0
2.0
4.0
6.0
8.0
10.0
12.0
14.0
16.0
18.0
20042005
(b) Lower Mid Trap 2004 and 2005
2004 Deposition (mg.cm-2)0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5
2004
Mea
n G
rain
Siz
e (u
m)
0.0
10.0
20.0
30.0
40.0
50.0
2005 Deposition (mg.cm-2)0.0 0.2 0.4 0.6 0.8 1.0
2005
Mea
n G
rain
Siz
e (u
m)
0.0
1.0
2.0
3.0
4.0
5.0
6.0
7.0
8.0
9.0
20042005
JN 29
JL 1
JL 3JL 4
JL 6
JL 1
JL 2JL 3
JL 4
JN 5-11JN 12-14
JN 15-21
JN 22-26
Figure 3.10: Deposition rates versus mean grain size in traps from the (a) Proximal site in 2004 (solid line) and 2005 (dashed line) and the (b) Mid site in 2004 (solid line) and 2005 (dashed line). Arrows in both figures point to the next trap in the chronological order and dates represent the day the trap was deployed.
74
3.6 Discussion
Seasonal suspended sediment delivery to West Lake generated by snowmelt
runoff resulted in highly seasonal sediment deposition in the lake. Over the three
year study, total sediment deposited in West Lake at the two sites monitored was
broadly proportionate to the total suspended sediment discharged by West River
(Table 3.3). However, the inter-annual differences in total sediment
accumulation did not proportionately reflect the differences in total suspended
sediment yield in each season (Table 3.3) and suggests that within-lake
processes modified location-specific sediment deposition (e.g. Lewis et al. 2002).
This disproportionate deposition highlights the important role in which lake
processes modify the sediment inflow signal through distribution and ultimate
deposition at the bottom of West Lake. Trap observations at two stations and
depths through multiple seasons indicated that the areal and vertical distribution
of sediment in West Lake was strongly dependent on the interaction between
river inflow and lake water, controlled primarily by the density imposed by
variable suspended sediment concentrations. Furthermore, primary particle size
measurements of trap sediments suggest that maximum particle size occurrence
was relatively independent of maximum suspended sediment deposition rates.
3.6.1 Short-lived deposition patterns in mass accumulation and vertical distribution
The majority of sediment delivered to West Lake occurred over several days
(2003 and 2004) and up to two weeks (2005). Sediment delivery after that period
75
was not as significant and as a result, mass accumulation patterns, both in areal
and vertical distributions were characteristic of the earlier short-lived deposition
events (e.g. Retelle and Child, 1996). These short-lived events were what
collectively formed the majority of the annual sediment deposit in West Lake,
subject to deposition of fine-grained sediments after the active runoff period.
Watershed conditions and seasonal meteorology were comparatively
similar in 2003 and 2004, and resulted in high magnitude nival discharge peaks
and suspended sediment concentrations. Reduced SWE in 2005 and rapid
ablation and fragmentation of catchment snowpack resulted in a comparatively
low nival peak and SSC in the river (Cockburn and Lamoureux 2008a). Sediment
deposition at the lower Mid and Proximal sites reflected the relative intensity of
the river conditions. In 2003 and 2004, nearly 50% of the total accumulation
occurred in the first week of runoff (Figures 3.3, 3.4). By contrast, in 2005,
nearly two weeks of runoff was necessary before 50% of the seasonal sediment
was deposited. Furthermore accumulation in the lower traps in 2005 was
gradual and similar to the cumulative suspended sediment discharge curve
(Figure 3.5).
Sedimentation rates were higher in the lower traps at both sites at the
beginning of 2003 and 2004 and the highest rates were coincident with
temperature perturbations at the lake bottom. Temperature perturbations lagged
short-lived periods of high suspended sediment concentrations in the river and
daily discharge maxima (e.g. 2004; Figure 3.8). In proglacial Bear Lake, Devon
76
Island, Nunavut, bottom temperature perturbations were also coincident with
diurnal peaks in discharge and likely indicated underflow activity (Lewis et al.
2002). Lambert and Giovanoli (1988) also recorded temperature anomalies in
Lake Geneva as large as 3ºC that were associated with pulses of warm
sediment-laden river water and even larger bottom temperature departures (>5
ºC) were recorded in Lillooet Lake, British Columbia, and associated with turbid
inflow (Gilbert 1975). Although the temperature departures in West Lake were
much smaller (<0.10ºC), the only plausible cause of these short-lived
temperature changes would be by external processes to the lake. Temperature
measurements from 15 m depth did not reveal similar perturbations (Figure
3.5e), and indicated that the short-lived thermal variations were limited to the
lower part of the water column. Given the coincident occurrence of the
perturbations with high suspended sediment concentrations in the river, it is likely
that dense river inflows descended the delta foreslope and traveled along the
bottom of the lake as turbid underflows, which was similarly observed in other
studies (e.g. Gilbert 1975; Lambert and Giovanoli 1988; Lewis et al. 2002).
During the early melt season when river temperatures were cooler than the lake
water, underflows caused negative anomalies. However, as the river water
temperature warmed, turbid underflows resulted in step-wise increases in bottom
temperature. Thus, a positive or negative perturbation in the bottom temperature
record reflected the difference between inflow temperature and ambient lake
water temperature.
77
Differences between the upper and lower traps in both stations further
reveal the control of lake processes on sediment deposition. Initially, sediment
deposition rates were disproportionately higher in the lower traps compared to
the upper traps as indicated by deposition ratios substantially greater than two
(Figure 6). Alternatively, if suspended sediment was distributed in an overflow
plume in the upper part of the water column (no deeper than half the water
column), the expected ratio of lower trap to upper trap deposition would be close
to one. Daily lower:upper trap deposition ratios indicated that periods of high
deposition rates in both trap sites were characterized by large (> 2) ratios
indicative of sediment delivery primarily to the lower portion of the water column
coincident with intense and turbid inflow (Figure 3.6). The trap ratios likely
represented minimum estimates of sedimentation during times of underflows, as
the traps were designed to capture sediment that settled vertically through the
water column and likely under-trapped sediment that was advected during the
more active periods.
The absence of rapid early-season sediment deposition in 2005 reflects
the reduced intensity of suspended sediment discharge in the river during this
season due, in part, to lower discharge produced by a small and fragmented
snowpack (Cockburn and Lamoureux, 2008a). The overall lower sedimentation
rates, combined with the near absence of bottom temperature perturbations
strongly suggest that underflow activity was infrequent compared to the previous
two years. Unlike the highly focused underflow deposition associated with peak
78
river sediment inflow in 2003 and 2004 that produced a clear proximal-distal
trend in sediment accumulation at the Proximal and Mid sites, decreased
discharge and sediment transport intensity in 2005 disproportionately reduced
early season deposition rates in the Mid location (Table 3.2). These differences
indicate that the spatial patterns of sediment delivery processes were affected by
the different inflow conditions in each season.
Intraseasonal differences in sedimentation between stations were also
observed. The temperature perturbation record at Mid site likely represents a
minimum estimate of the number of turbid underflows in a given season, as
evidenced by the missed early event in 2004 when more than half the total
seasonal sediment accumulation at the Proximal site in 2004 occurred before
significant accumulation in the Mid site (Figure 3.8, denoted 1). Despite the
importance of this sediment inflow and deposition event, there was little thermal
or depositional evidence that the underflow reached the Mid station. Particle size
determination from the Proximal trap recovered after the early pulse indicated
that the mean particle size was fine sand (224 µm), relatively coarse material
compared to the rest of the dataset (Figure 3.9). Potentially, this initial pulse in
2004 was a primarily coarse deposit and underflow competence was not
maintained substantially beyond the Proximal station, and hence, material was
not transported to the Mid site.
After the initial pulse in June 2004, two more notable deposition events
were measured at both trap sites (Figure 3.8, denoted 2 and 3). Unlike the event
79
on June 28, these events were characterized as positive temperature departures
as river water temperature had increased by this time and were associated with
high suspended sediment discharge. The first of these two events generated a
large increase in accumulation in the lower Mid trap. The second event was
associated with peak suspended sediment concentration, had a minor response
in the Mid trap, but a relatively large response in the Proximal trap (Figure 3.8).
After event 3, the Mid site recorded little accumulation, although there were large
temperature departures. This apparent lack of sediment deposition for these
events might be explained by the same processes that account for the lack of
deposition in Mid site in the first event of the season (event 1). Furthermore, it is
possible that a portion of the turbid underflow traveled below the trap and was
under-trapped.
In 2005, the temperature anomalies were much smaller and less frequent
(Figure 3.5f). The lack of temperature departures in 2005 was likely due to the
absence of dense, sediment-laden river water, hence the slow accumulation in
the lower traps in 2005 compared to the upper traps in the same location. Rather
than a disproportionate increase in sediment accumulation in the lower trap, as
observed in 2004 associated with peak runoff and suspended sediment yield,
accumulation in the lower and upper traps in 2005 mirrored each other (Figure
3.5). These similarities were further reflected in the low 2005 lower:upper trap
deposition ratios (Figure 3.6) and are consistent with reduced inflow intensity in
2005 which resulted in a lack of energetic or active deposition events.
80
These two distinctly different seasonal deposition patterns observed in
2004 and 2005 suggest that sediment delivered to the lake bottom depended on
inflow conditions. In 2004, sediment was rapidly delivered as turbid underflow
pulses, whereas in 2005 sediment delivery was less energetic and more closely
resembled a homopycnal plume in the water column (Smith and Ashley 1985;
Lemmen et al. 1988). This energetic difference in these two regimes was
reflected in the deposited sediment grain size characteristics, with substantially
coarser sediment deposited in 2004 (Figure 3.6). Furthermore, sediment texture
was coarsest in the Proximal trap in 2004 after maximum deposition rates; this
corresponds to similar trends demonstrated in the grain size and river suspended
sediment concentrations (McDonald 2007).
Based on these observations, two sediment delivery and deposition
regimes in West Lake are inferred (Figure 3.11). The first is a low-energy
delivery regime and the second, a more episodic and energetic delivery regime.
These regimes are conceptually similar to other detailed sedimentary studies in
dynamic lake settings. Schiefer (2006b) mapped the spatial variability of
sediment yield (based on event thickness) for a small alpine lake in southwestern
British Columbia and was able to classify the sediment regimes within the lake
based on the dominant delivery processes through the last century. As well,
Lamoureux and Gilbert (2004) noted that varve presence and absence in a more
distal location of arctic proglacial Bear Lake was dependent on underflow
intensity inferred from the thickness of varves in the proximal basin sedimentary
81
record. These two core-based sedimentary studies are examples of the different
regimes observed in lacustrine sedimentary environments operating over
timescales of years to at least decades.
20052004-II
2004-I
vfSiC
lay
fSi
mS
icS
ivfSfS
vfSiC
lay
fSi
mS
icS
i
20052004-II
2004-I
Suspension Settling
Inflow
Underflow
Figure 3.11: Schematic representation of the two types of delivery and hypothesized deposition in West Lake based on the 2004 and 2005 deposition observations. The dotted lines represent passive suspension settling that occurs each year and the solid line represents underflow and more energetic sediment delivery events that occurred in 2004. Two such events were recorded in the Proximal trap (2004-I and 2004-II), only the second event was recorded in the Mid trap (2004-II). Sedimentary sequences for each trap site are based on the grain size data from the trap samples. Along the bottom of the sequences the letters represent grain size fractions: clay, (vfSi) very fine silt, (fSi) fine silt, (mSi) medium silt, (cSi) coarse silt, (vfS) very fine sand and (cS) coarse sand (after Evans and Benn, 2004).
The deposition regimes documented in this study operate on subseasonal
timescales and contribute to substantial differences in sediment deposition in
time and space in response to varying inflow conditions. The active delivery
regime at Cape Bounty is highly dependent on runoff intensity and results in high
sediment accumulation and coarser particle size at both the Proximal and Mid
sites. In order to initiate the active delivery regime in West Lake and deliver
82
relatively coarse sediment to both sites, inflow must be intense, as is generated
by greater runoff due to snowpack melt (Cockburn and Lamoureux, 2008a) and
contact between meltwater and the channel sediment sources (MacDonald
2007). By contrast, conditions similar to those observed in 2005 and associated
with low-energy sedimentary processes, result in low accumulation rates, and
finer sediment deposition. Results indicate that the low-energy depositional
regime will likely occur to some degree each year (presuming runoff occurs).
The presence of coarser grains at the Proximal site, and especially the Mid site,
can serve as primary indicators of high intensity runoff and delivery of sediment
to the bottom of the lake through turbid underflows. This may suggest that the
coarser fraction of the sedimentary record at the Mid site in West Lake is a
reasonable proxy for melt and runoff intensity dependent on snowpack and melt
conditions processes that impose primary control over sediment transport to the
lake. However, these results suggest that the sedimentary record from the
Proximal site in West Lake may be more sensitive to inflow processes and
contain more subannual sedimentary events in the record compared to the Mid
site (e.g. Smith 1978; Lamoureux 1999; Lamoureux and Gilbert 2004; Schiefer
2006b).
3.6.2 Implications for sedimentary grain size interpretations
Sedimentological studies often report bulk grain size measurements, as
necessitated by sample size limitations for physical analysis. As observed in the
Proximal setting in West Lake, short-lived sediment pulses can deliver coarse
83
material and reveal important information about the inflow and delivery
mechanisms at that setting. However, maximum grain size was not proportional
to total deposition (Figure 3.9) and in several cases, maximum grain size
preceded maximum deposition rates (Figure 3.10). This relationship was
clearest in the Proximal site as counter-clockwise hysteresis between mean grain
size and deposition rates in 2004. These results are consistent with observed
hysteresis in fluvial systems (e.g. MacDonald 2007) and have important
implications for linking sedimentary grain size measures to hydrological inflow
intensity.
For example, Francus et al. (2002) inferred seasonal snowmelt intensity
from the particle size measurements made with varves from Sawtooth Lake,
Ellesmere Island, Nunavut. The snowmelt intensity index developed by Francus
et al. (2002) correlated to the particle size measurement from each varve and
was poorly correlated to varve thickness, which suggests that a similar
decoupling between accumulation and hydrological processes may also exist at
Sawtooth Lake. Results from this study suggest that grain size characteristics
reflect complex inflow characteristics and direct estimates of paleohydrological
estimates are biased due to the decoupled response between sediment
accumulation rates and deposition of the coarsest grains. Additionally, integrated
grain size estimates reflect both early and late season contributions, and it may
be necessary to focus grain size analysis to the coarsest fraction to avoid
possible dilution caused by finer grains deposited through much of the season.
84
Overall, these results suggest that sedimentary grain size proxies may represent
complex paleoenvironmental signals where fluvial and lake processes alter the
primary association between stream power and grain size (cf. Sundborg and
Calles 2001). Further analysis of different lake systems is necessary to
determine the extent to which these complexities occur in other settings.
3.6.3 Interpreting the sedimentary record from West Lake and similar settings
Contemporary process studies provide important information to link delivery and
deposition with the sedimentary records produced by these processes. A
number of studies suggest a strong hydroclimatological relationship between
sediment delivery and deposition (Retelle and Child 1996; Lewis et al. 2002;
Schiefer 2006a, b; Schiefer et al. 2006). The strong seasonal delivery and
deposition of sediment in deep lakes can often lead to annually laminated
sediments (varves) which can be used to reconstruct past variability in the
processes that dominate depositional conditions (e.g. Hardy et al. 1996). This
study, along with others, demonstrates that hydroclimatic conditions can
determine the amount and type of sediment deposited in lakes. However,
limnological processes can modulate these conditions and should be taken into
consideration when sedimentary records from such lakes are interpreted (Gilbert
1975; Sturm 1979).
In a case that is remarkably similar to the results presented in this study,
Lamoureux and Gilbert (2004) inferred that the presence and absence of varves
85
in a distal location of Bear Lake was dependent on the intensity of underflow
activity. They noted that coarse sediment was necessary for the formation of
visible varves in the more distal location and that coarse sediment was absent
from the site in years where the varves from the more proximal site were
relatively thin. Hence, they suggested years with reduced delivery of coarse
sediment in the proximal location were indicative of weak underflow activity and
the absence of coarse sediment in the distal site. A similar analogy existed in
West Lake during 2004 on a sub-seasonal scale. An early pulse of sediment
was deposited at the Proximal site while negligible accumulation occurred at the
more distal Mid site. Implications are that the sedimentary records from such
lakes could be episodic and that the strongest hydroclimatic link in these cases is
based on the processes that generate underflow conditions. In the case of West
Lake, these conditions were observed during high sediment delivery to the lake
associated with intense snowmelt generation. The magnitude and duration of the
snowmelt event was broadly associated with catchment snow-water equivalence
(Cockburn and Lamoureux, 2008a). However, additional controls in the fluvial
system (McDonald 2007) and in the lake (this study) alter the delivery and
deposition of sediment. Accurate interpretation of the sedimentary record
requires systems where these factors remain stationary for long time periods, or
detailed characterization of the processes and associated sedimentary deposits
is possible.
86
3.7 Conclusions
Contemporary process studies aid sedimentary record interpretations and help
explain patterns in sedimentary reconstructions. As seen from this study, total
deposition rates over short distances in West Lake were strongly dependent on
the presence and the strength of turbid underflows generated by intense river
inflow. These results suggest that it may be important to evaluate the
hydrological factors that drive sediment transfer, delivery and distribution to the
lake. Inflow conditions established the deposition regime type that dominated
sedimentation in a given season. When sediment inflow was highly turbid,
pulses of sediment were rapidly delivered to the bottom of West Lake. When
discharge and suspended sediment concentration were persistently lower, as
was the case during all of 2005 and late stages of the melt season of 2003 and
2004, sediment-laden water moved through the water column as a homopycnal
plume rather than a discrete underflow. Sedimentary grain size was a function of
the character of the inflow, the sediment load and the deposition regime, and was
substantially decoupled from the mass accumulation.
87
Chapter 4 Snowfall variability and post-19th century arctic landscape disturbance revealed by paired varved sedimentary records
In Prep. Geology
Authors:
Jaclyn M.H. Cockburn
Scott F. Lamoureux
Keywords: Varved sediments, permafrost, sediment supply, climate change
4.1 Abstract
Two 600-year varved lake records from the Canadian High Arctic (Cape Bounty,
Melville Island, 74º55’N, 109º35’W) were compared to evaluate signal
reproducibility and to identify the dominant signal. Previous process studies at
Cape Bounty demonstrated that annual sediment delivery to these lakes was
strongly dependent on snowmelt runoff intensity and available sediment supply
and therefore the sedimentary records likely reflect variability in those two
factors. The two records were highly correlated (r=0.599, n=602, p<0.000) over
the last six centuries and the weakest time-dependent correlations occurred
during the 20th century. The reduced correlation is likely due landscape
disturbance due to dissimilar ground-ice melt generated by subtle differences in
watershed geomorphic conditions. The recent varve thickness record in the
West Lake exhibited a significant correlation (r=0.698, n=18, p=0.002) with
88
autumn snowfall in the previous year at the nearest long-term meteorological
station (Rea Point, Nunavut). However, the East Lake record showed reduced
and insignificant correlations. This correlation decline is attributed to differing
sediment supply in the two catchments driven by differential permafrost
degradation and landscape instability between the two catchments through the
last 200 years.
4.2 Introduction
Varved lacustrine records provide a means to reconstruct past environments at
an annual resolution, although one key challenge is to understand the
relationship between sediment deposition and environmental conditions.
Numerous studies have correlated varve thickness records with weather records
to generate proxies of temperature, precipitation or discharge (Leeman and
Niessen, 1994; Hardy et al., 1996; Ohlendorf et al., 1997; Hughen et al., 2000;
Sander et al., 2002; Tomkins and Lamoureux, 2005). Despite these results, the
relationship between varve formation and environmental conditions (e.g.,
hydroclimate behaviour) is not simple (e.g., Desloges, 1994; Cockburn and
Lamoureux, 2007; Hodder et al., 2007). Generally speaking, simulations of proxy
data and climate records have shown that variability in a proxy data set is not
necessarily entirely explained by the associated environmental factors and in
several cases, the hydroclimatic or environmental correlations were not as strong
as might be expected (von Storch et al., 2004; Moberg et al., 2005), largely due
to internal or local proxy noise (von Storch et al., 2004). The challenge lies in
89
quantifying this variability and determining whether or not it is satisfactory to
remain as unexplained noise. For example, geomorphic factors such as
sediment supply and landscape stability can also complicate the hydroclimatic
signal contained in varve records (Lamoureux, 2002; Hodder et al., 2007). In
polar environments, permafrost degradation has been widely documented
(Lawrence and Slater, 2005; Smith et al., 2005) and can potentially alter fluvial
sediment supplies (Syvitski, 2002) and thus, downstream sedimentary
deposition. Records from permafrost regions may exhibit recent changes due to
the observed disruptions in landscape stability due to permafrost degradation
caused by observed warming (Serreze et al., 2002; ACIA, 2005).
We examine this long-term landscape stability through varve records from
two similar lakes from adjacent catchments in the continuous permafrost zone of
the Canadian High Arctic. We limited our study to the last six centuries in order
to utilize published records of past environment and climate conditions in the
Arctic, in an effort to identify known periods of climate or environmental variability
(e.g., Overpeck et al., 1997; Mann et al., 1999; Crowley, 2000; Hughen et al.,
2000; Smol et al., 2005). Given the close proximity of the two lakes and
demonstrated similarity of seasonal sediment yields (Cockburn and Lamoureux,
2008a), it was expected that the varve records would be similar and highly
correlated. Our hypothesis was that destabilization of the permafrost would alter
sediment supplies and total yield in the two watersheds. Hence, while the two
records were expected to be highly correlated, episodes of weaker correlations
90
would reflect local changes to sediment supply in either watershed. This study
marks the first occasion where varve records from adjacent and similar lakes
were used to evaluate differential sediment deposition to elucidate geomorphic
impacts on long-term sediment yield.
4.3 Study Site and Methods
Paired lakes at Cape Bounty, south-central Melville Island, Nunavut, Canada
(75º55’N, 109º35’W; Figure 4.1) were investigated. The freshwater lakes are 34
and 32 m deep (maximum known depth, West and East Lakes, respectively).
Both watersheds are composed of extensive plateaus and rolling hills mantled by
glacial till and transgressive Holocene marine deposits, underlain by continuous
permafrost (Hodgson and Vincent, 1984). Vegetation cover is limited to dwarf-
shrub and herb tundra (Walker et al., 2005) and the active-layer typically reaches
a maximum depth of 0.5 m. Cape Bounty has been the location of a major multi-
year, multidisciplinary cold region watershed study since 2003. Several studies
have detailed the hydroclimate, fluvial, sediment yield and deposition processes
in the watersheds (Lamoureux et al., 2006; McDonald, 2007; Cockburn and
Lamoureux, 2008a, b).
91
Figure 4.1: Coring locations in West and East Lakes at Cape Bounty, Melville Island, in the Canadian High Arctic. The locations of the Meteorological Services Canada stations at Mould Bay, NWT (MB) and Rea Point, NU (RP) are indicated in the High Arctic Regional map. .
Long sediment cores were obtained from West Lake at 34 m depth using
a vibra-coring system in 2003 (Smith, 1998). An Aquatic Research Instruments
percussion coring system was used to obtain long cores from 32 m depth in East
Lake in 2005. In both lakes, short surface cores were retrieved with gravity
coring systems (Boyle, 1995) to recover undisturbed surface sediments that
bridged potential gaps between the longer cores and the sediment-water-
interface. The surface cores were dewatered, kept upright and unfrozen during
storage and transport to the laboratory. Cores were split lengthwise and
92
sampled for 137Cs activity. Freeze-dried samples were measured on an EG&G
ORTEC high-purity germanium coaxial well photon detector (80000 s count time)
to develop an independent age-depth model.
Overlapping monoliths of sediment were removed from the core for thin
section preparation, wrapped in paper towel, dehydrated with acetone and
embedded in Spurr’s epoxy resin (Lamoureux, 2001). The embedded slabs were
mounted to glass slides and prepared as thin sections following standard
methods. Thin sections were scanned with an HP S20 slide scanner at 2400 dpi
resolution and the files arranged in stratigraphic order in CorelDraw© to identify,
count and measure laminae. Once an initial sediment chronology from each lake
was independently established, the images and chronologies were compared on
a laminae-specific basis. Distinct marker beds and other visual structures were
found in both records and used to verify the chronologies.
Meteorological records from Mould Bay (MB 1948-2007) and the shorter
record from Rea Point (RP continuous 1969-1986) were compared with the
chronologies to determine correlations between annual deposition and the
climate data. Process work completed at this site demonstrated significant
correlations between melt season weather at Cape Bounty and the
Meteorological Services Canada (MSC) weather stations (Cockburn and
Lamoureux, 2008a, b). Comparison of the overlapping periods between the two
meteorological stations indicated that for each month, mean temperatures were
strongly and significantly correlated (Table 4.1, Appendix A).
93
Table 4.1: Pearson correlation coefficients between the varve thickness measurements from West and East Lakes and mean monthly temperature and monthly total snow fall recorded at Meteorological Service of Canada station at Rea Point, NU. Bolded values represent the strongest correlation between West Lake varve thickness and climate parameters (n=18).
Parameter West Lake East Lake Parameter West Lake East Lake
Mean Temperature r p r p Total Snowfall r p r p
Jan -0.214 0.410 -0.170 0.514 Jan 0.218 0.401 0.268 0.298 Feb -0.342 0.179 -0.325 0.203 Feb -0.186 0.475 -0.132 0.614 Mar -0.261 0.312 -0.070 0.790 Mar -0.059 0.822 -0.042 0.873 April -0.532 0.028 -0.291 0.258 April -0.230 0.375 -0.211 0.416 May -0.498 0.042 -0.526 0.030 May 0.242 0.349 0.357 0.160 June -0.671 0.003 -0.278 0.280 June 0.397 0.115 0.163 0.532 July 0.099 0.705 0.056 0.831 July -0.136 0.603 -0.157 0.547 Aug, lagged 0.069 0.792 -0.317 0.215 Aug, lagged 0.129 0.622 0.110 0.674 Sept, lagged 0.085 0.746 -0.059 0.822 Sept, lagged 0.548 0.023 0.345 0.175 Oct, lagged 0.352 0.166 0.014 0.958 Oct, lagged 0.619 0.008 0.247 0.339 Nov, lagged 0.264 0.306 -0.390 0.122 Nov, lagged 0.360 0.156 -0.213 0.412 Dec, lagged 0.110 0.674 -0.380 0.132 Dec, lagged 0.245 0.343 -0.074 0.778 ASON, lagged 0.312 0.223 -0.097 0.711 ASON, lagged 0.698 0.002 0.235 0.364 AMJJ -0.454 0.067 -0.317 0.215 SON, lagged 0.680 0.003 0.298 0.245 MJJ -0.640 0.006 -0.453 0.068 Previous Winter 0.645 0.005 0.272 0.291 With East VT 0.593 0.012
4.4 Results
Sediment delivery to the two lakes at Cape Bounty is driven by seasonal
snowmelt generated runoff (Cockburn and Lamoureux, 2008a). Runoff intensity
and sediment transported by the rivers is highly dependent on snowmelt
processes early in the season. The seasonal sediment delivery to the lakes,
which is dependent on total spring snowmelt and relatively infrequent intense rain
storms, results in seasonal sediment deposition in the deep basins primarily via
short-lived underflows (Cockburn and Lamoureux, 2008b). In addition, slow
deposition of clay occurs throughout the season but becomes the dominant
94
sedimentary material after the active hydrological season wanes. This
combination of depositional processes produces a visually distinct couplet of
coarser material overlain by finer material.
In both lakes, peak 137Cs activity coincided with the sample depth for the
AD 1963 layer (Figure 4.2). The consistent pattern in sediment structure, highly
seasonal sediment delivery to the lake and 137Cs age-depth models confirmed
that the laminated deposits found in West and East Lakes were varves. Couplet
thicknesses were measured and counted to AD 1400 (Figure 4.2) with the mean
couplet thicknesses measured as 0.92 and 0.93 mm in West and East Lakes,
respectively. The chronologies were not extended beyond AD 1400 because the
scope of this research was to investigate periods of known climate variability and
the impact on sediment supply and delivery at a local scale.
Overall, the two varve records were significantly correlated over six
centuries (r=0.599, n=602, p<0.000) and time-dependent Pearson correlation
coefficients of the two series indicated that correlation strength declined after ca.
AD 1800 (Table 4.2; Figure 4.3). Although the two records correlate well,
variability in the later half of each record is significantly different (Table 4.3;
Figure 4.4). In general the magnitudes of high-yield years in the West record
were much greater than high-yield events in East (Figure 4.4).
95
a) West
Year AD1400 1450 1500 1550 1600 1650 1700 1750 1800 1850 1900 1950 2000
Var
ve T
hick
ness
(mm
)
0
5
10
15
20
Cum
ulat
ive
Dep
artu
res
-30
-20
-10
0
10
20
30
40
50
VTCD
b) East
Year AD1400 1450 1500 1550 1600 1650 1700 1750 1800 1850 1900 1950 2000
Var
ve T
hick
ness
(mm
)
0
5
10
15
20
Cum
ulat
ive
Dep
artu
res
-30
-20
-10
0
10
20
30
40
50
VTCD
Core Depth (cm)0 1 2 3 4 5 6 7
137C
s Ac
tivity
(dpm
. g-1)
012345
Lam
ina
Age
(yea
rs b
efor
e 20
02)
0102030405060
Core Depth (cm)0 1 2 3 4 5 6 7
137C
s Ac
tivity
(dpm
. g-1)
01234567
Lam
ina
Age
(yea
rs b
efor
e 20
02)
0102030405060 *
*
*
Figure 4.2: West (a) and East (b) varve thickness (VT) records (solid line) and cumulative departures (CD, grey dashed line). Cumulative departures reveal periods of persistent above and below average accumulation. The inset graph illustrates the 137Cs profile (grey bars) and the number of laminae (line) from the top of the core with depth. Astrices represent samples with less than 0.02 dpm·g-1 measured, the arrow indicates the lamina for 1963 AD.
96
Table 4.2: Pearson correlation coefficient between the annual West and East Lake varve records
Time Period r n p
Entire Series, 1400AD-2001AD 0.599 602 <0.0000
20th Century 1900AD-1999AD 0.424 100 <0.0000
19th Century 1800AD-1899AD 0.689 100 <0.0000
18th Century 1700AD-1799AD 0.881 100 <0.0000
17th Century 1600AD-1699AD 0.666 100 <0.0000
16th Century 1500AD-1599AD 0.787 100 <0.0000
15th Century 1400AD-1499AD 0.871 100 <0.0000
Post Industrial 1850AD-2001AD* 0.424 152 <0.0000
Pre Industrial 1400AD-1849AD* 0.828 449 <0.0000
*Coincides with correlation periods used by Hughen et al, 2000, Table 1
Year AD
1400 1450 1500 1550 1600 1650 1700 1750 1800 1850 1900 1950 2000
50-y
ear
Cor
rela
tion
Coe
ffici
ent
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
Figure 4.3: Time-dependent Pearson correlation coefficients. Correlation was calculated for a 50-year period.
97
Table 4.3: F-test statistic for selected time periods testing significance of variance differences between the Cape Bounty varve records, a significant F-value indicates that the variance in the two records are significantly different
Time Period F - value P-value
1400-2001 2.089 <0.0000
1400-1700 0.968 0.60784
1700-2001 3.350 <0.0000
1900-2001 12.15 <0.0000
a) West
Year AD1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000
Varv
e Th
ickn
ess
(mm
)
0.1
1
10VTVT Mean
b) East
Year AD1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000
Varv
e Th
ickn
ess
(mm
)
0.1
1
10VTVT Mean
Figure 4.4: West (a) and East (b) varve thickness (VT) records for the 20th century indicate that thicker events were more common in West than East at this time. The mean varve thickness (VT Mean) is shown in dark gray on all plots.
98
Correlation between varve thickness (VT) and mean monthly temperature
and total snowfall recorded at RP was assessed (Table 4.1). Similar correlation
patterns were found with MB, but were not as strong or significant. There was a
stronger relationship with data from closer RP and thus, this data set was used in
the analyses presented. Previous autumn snowfall (August – November) was
the strongest weather signal correlated with West Lake VT. A strong, positive
correlation with previous autumn, snowfall was expected, as the majority of snow
falls during the autumn in the High Arctic (Maxwell, 1981). June temperature
(peak melting period) of the same year was negatively correlated with West Lake
VT and represents the strongest and most significant relationship with thermal
conditions.
Correlations with East Lake VT and similar climate parameters from RP
were similar but not as strong (Table 4.1). Lagged September-November total
snowfall exhibited the strongest correlation with East VT, but was not significant
and less than the correlation between West VT and previous autumn snowfall
(lagged ASON). Mean snow-melt season temperatures (May, June, July and
combined MJJ) were negatively correlated with East Lake VT as well, which
suggests the pattern observed with West Lake was robust (Table 4.1).
Previous ASON snowfall and June temperature at RP had the strongest
and most significant correlations with West Lake VT (Table 4.1). Combination of
these parameters in multiple regression analysis explained 65% of the variability
in the VT record from West Lake (r2 = 0.65, n=15, p<0.040). However, both
99
parameters co-varied (r=-0.558, n=15, p=0.015) and each accounted for 73 and
41% of VT variability.
4.5 Discussion
4.5.1 Divergent varve records
The two varve records at Cape Bounty show remarkable similarity in episodes
with higher sediment accumulation (varve thickness) and long-term cumulative
departures (Figure 4.2). The largest discrepancy between the two records arises
from the occurrence and magnitude of individual years with high yield (Figure
4.2). Given the close proximity of the two lakes and general seasonal similarities
demonstrated in recent process studies (Cockburn and Lamoureux, 2008a), it
was expected that the two records would exhibit similar long and short-term
variability. The high degree of correlation between these series is
unprecedented for records of this length. For example, work that compared
recent portions of varved records in northern Sweden reported significant
correlations (r=0.46, n=34 and r=0.43, n=45) between adjusted varve thickness
records from Nylandssjön and nearby Koltjärnen (Gälman et al., 2006). Less
directly, Menounos et al. (2005) determined that the first principal component
based on a network of five varved lake records from the British Columbia Coast
Mountains explained 46% of the variance. Correlation between individual
records varied in strength but was mostly attributed to spatial and scale
differences (Menounos et al., 2005). Hence, the strong correlation between the
100
sedimentary records from Cape Bounty represents a unique opportunity to
compare both the internal and external mechanisms that contribute to varve
formation in this High Arctic, non-glacierized (nival) setting.
During the post-industrial period identified by Hughen et al. (2000) (i.e.,
1850 – present) the correlation between the Cape Bounty series substantially
decreased, and was lowest in the 20th century. The Cape Bounty records reveal
divergence during a time when other sedimentary records begin to exhibit
stronger correlations (Hughen et al., 2000). Subsequent divergence in the
records cannot be readily explained by chronological differences as the records
get older (Overpeck et al., 1997; Hughen et al., 2000; Menounos et al., 2005).
Hence, it is likely that the divergence was driven by increased frequency of large-
magnitude sediment-yield years in West Lake after AD 1800. Hence, the
divergence represents a change in what were otherwise similar long-term
physiographic and limnic conditions in the lakes and respective watersheds.
Record temperatures during the summer of 2007 at Cape Bounty saw
massive ground-ice melt-out and sediment transport in the West Catchment and
effectively none in the East Catchment (Lamoureux and Lafrenière, 2007).
These discrepancies were likely caused by slightly different slope gradients and
vegetation covers in the two catchments (Lamoureux and Lafrenière, 2007).
Hence, subtle geomorphic and vegetation cover differences can generate
substantial differences in landscape disturbances with potential impacts on
downstream sedimentary records.
101
Longer-term studies of permafrost dominated landscapes have also
demonstrated differential ground-ice disturbance across the Arctic (e.g.,
McNamara et al., 1998; Smith et al., 2005; Lawrence and Slater, 2005).
Jorgenson et al. (2006) used image analysis of photographs from AD 1945, AD
1982 and AD 2001 to quantify the magnitude of permafrost degradation on the
Alaskan Arctic Coastal plain. Their results indicated an increase in ice-wedge
degradation and changes to thermokarst topography. In a similar study from the
Central Range in Alaska, permafrost degradation was estimated to have begun
in the mid-1700s (Jorgenson et al., 2001) which is similar to the timing of
divergence between the two varve records from Cape Bounty.
Correlations with recent meteorological records at Rea Point were poor
when compared to the East varve record (Table 4.1). Landscape stability or
sediment availability plays an important role in overall sediment accumulation in
both lakes. However, seasonal meteorological conditions have imparted
significant control on accumulation in at least West Lake during the 1970s and
1980s. The long-term sedimentary records from Cape Bounty show remarkable
similarity over the last six centuries and appear to diverge only during the recent
record when differential permafrost degradation and landscape instability likely
increased in the West Lake catchment. Moreover, given the similar
hydroclimatic conditions for both lakes, the divergence at Cape Bounty cannot be
directly explained by climate change or increased summer temperatures.
102
4.5.2 Hydroclimatic record
Comparison between varve thickness (VT) and the nearby meteorological
records (MB and RP) indicated that VT was correlated to the previous year’s
autumn (ASON, lagged) snowfall and the current year snow-melt season (spring)
air temperature (Table 4.1). Process work conducted at Cape Bounty monitored
discharge and sediment delivery to the lakes during peak runoff and indicated
that snow-water equivalence (SWE) was the primary factor in seasonal sediment
delivery to the lakes (Cockburn and Lamoureux, 2008a).
Correlations were strongest and most significant with the shorter RP
record and West Lake VT, while correlations were similar, but with reduced
strength and significance between RP and East Lake VT. The observed
difference in correlations between West and East Lakes was consistent with the
general decline in correlation between the two records apparent throughout the
20th century (Table 4.3; Figure 4.3).
June temperature was strongly negatively correlated with VT in both lake
records. Process work suggested that milder spring temperatures delayed
snowmelt processes, which led to a build-up of meltwater within the snowpack
and eventually produced an intense runoff (Cockburn and Lamoureux, 2008a).
In general, June is the most important month in Arctic river systems with respect
to snowmelt. In most glacial or biogenic/clastic varve systems, correlations with
spring/early summer temperatures are typically positive; (e.g., Hardy et al., 1996;
Hughen et al., 2000; Tomkins and Lamoureux, 2005; Chutko and Lamoureux,
103
2007) thus, the negative correlations with temperature at Cape Bounty are
unique but consistent with the findings from the on-site process studies
(Cockburn and Lamoureux, 2008a, b).
These results agree with other studies that indicate that SWE or total
discharge represented the primary control over annual sediment yield
(Lewkowicz and Wolfe, 1994; Braun et al., 2001; Forbes and Lamoureux, 2005).
Lamoureux and Gilbert (2004) reported the strongest climatic influence on varve
thickness at Bear Lake was temperature during the last half of September and
the first half of October, which was interpreted to indicate the amount of snowfall
generated by relatively warm autumn storms. In that study, as well as the case
of Cape Bounty, conventional snowpack data are sparse both spatially and
temporally because meteorological stations are located in potentially problematic
locations (i.e., windswept airports; Yang and Woo, 1999). Hence, proxy
indicators of snowfall appear necessary to assess catchment SWE in an
environment like the Canadian Arctic where detailed measurements are not
available (e.g., Cockburn and Lamoureux, 2008a). Furthermore, seasons that
exhibit, or may be most sensitive to climatic changes may have an increased
impact on surficial processes in these regions (e.g., longer melt seasons,
decreased sea ice conditions).
104
4.6 Conclusion
Two clastic varve records from adjacent watersheds were strongly correlated
through most of the six centuries evaluated. Weakened correlations between the
Cape Bounty lakes after AD 1800 were unlike results from earlier studies that
demonstrated stronger correlations during the recent period of the records
(Hughen et al., 2000). The divergence in the correlation between the two records
was likely caused by differential permafrost degradation due to warming.
Sediment supply to the Cape Bounty lakes was relatively consistent between the
two catchments prior to ca. AD 1800, when the landscape was inferred to be
stable and deposition was subject to similar hydroclimatic forcings. Observed
differences between permafrost disturbances in the watersheds in 2007, indicate
that the West Lake catchment was likely influenced by increased permafrost
degradation and active layer disturbance after ca. AD 1800.
The West Lake varve thickness (VT) record was highly correlated with the
nearby Rea Point meteorological station. Correlation with previous autumn
snowfall and cool spring conditions (negative correlation with temperature) was
consistent with observations during three years of process work conducted at
Cape Bounty (Cockburn and Lamoureux, 2008a). Correlations with the East
Lake VT record were neither as strong nor significant as those for the West.
The paired lake approach facilitated long-term analysis of intra-watershed
variability in sediment supply and provides important cautions for related
sedimentary studies. The record divergence at Cape Bounty likely indicates
105
subtle landscape sensitivity to climate warming and reaffirms the benefit of
multidisciplinary process monitoring paired with sedimentary records to better
quantify the impact of climate change on these systems.
106
Chapter 5 Conclusions and Future Work
High Arctic system science is important and, given the current changes in global
climate, changes in the Arctic are likely going to be unlike any changes seen
before. In this study, paired, arctic watersheds were monitored through three
melt seasons in an effort to quantify the mechanisms of sediment transport and
the sedimentary records from the two lakes were then used to further elucidate
patterns in the physical processes for the last 600 years.
5.1 Summary
The major conclusions based on three years of snowmelt runoff and sediment
delivery monitoring and analyses of the sedimentary records from two High Arctic
watersheds at Cape Bounty, Melville Island, Nunavut are summarized below.
Seasonal snowfall and its subsequent melt intensity drive the magnitude
of seasonal sediment yield in the two catchments at Cape Bounty. Cooler
springs delayed meltwater runoff, which lead to meltwater ponding and increased
water storage within the snowpack. Once meltwater channelized, discharge was
intense and came into contact with the river channel floor (sediment supply)
within days of channelized runoff. In warmer springs, rapid reduction of the
snowpack leads to patchy and discontinuous snowcover. The patchy snowcover
left large amounts of snow hydrologically disconnected from the rest of the
107
system. Furthermore, river channels remained snowlined and potentially frozen
up to eight days longer than that observed in cooler springs.
There was a disproportionate response between runoff and sediment yield
in both watersheds. Sediment yield discharge from year to year was potentially
dependent on the previous years sediment yield. Although three years of data
were insufficient to assess this fully, it seems likely that the East watershed was
less sensitive to this effect than the West watershed.
Detailed physical limnologic observations at West Lake concluded that
deposition was driven by short-lived turbid underflows generated by intense
sediment-laden runoff. A two-depth trap system deployed and recovered daily
through the intense runoff period and every two days at the end of the recession
period indicated that suspended sediment was rapidly delivered to the bottom
half of the lake in event pulses that coincided with turbid inflow. Grain-size
analysis of trapped sediment indicated that maximum grain-size and
accumulation rates were decoupled. The implications of these findings are
significant when considering the association between grain size and
paleoenvironmental conditions inferred from lake sedimentary sequences.
Potential grain-size hysteresis may lead to misinterpretation of the
paleohydrological flow competence.
Paired varved sedimentary records from West and East Lakes at Cape
Bounty through the last 600 years revealed that until recently (post-18th century)
108
the two records were remarkably similar. Through 600 years, the two varve
records were positively correlated (r=0.599, n=602, p<0.000). However, time-
dependent correlation analysis revealed that correlations declined through the
last 200 years. The recent divergence may indicate a change in local processes
in the two catchments and is likely directly geomorphic in nature rather than
climatic.
A comparison of the recent varve thickness records with nearby
meteorological records indicated a strong positive correlation with previous
autumn snowfall. Correlations were strongest and most significant with the West
Lake (total snowfall in ASON, 0.698, n=18, p=0.002) record; the East Lake
record correlations were similar, but not significant (total snowfall in SON,
r=0.298, n=18, p=0.245). Spring melt-season temperatures and varve thickness
correlations were strongly negative. Mean June temperature was the strongest
thermal correlation with West Lake (r=-0.671, n=18, p=0.003). East Lake varve
thickness was most strongly correlated with mean May temperature, but was not
as significant (r=-0.526, n=18, p=0.030).
Due to the divergence in the records, reconstruction of climate parameters
beyond the instrumentation period should be done with caution. The recent
divergence suggests that for a long period of time the dominant signal that
controlled sediment accumulation in both lakes was similar and therefore
apparently largely independent of inter-watershed processes. However, during
the last 200 years, intra-watershed processes have altered hydrological and
109
sedimentological pathways such that West Lake appears to have more frequent
and larger sedimentary events, likely due to landscape disturbance possibly
caused by permafrost alteration such as active layer detachments.
5.2 Future Work
As one of the first studies to compare the sedimentary processes and deposition
patterns in two adjacent watersheds there are many ways in which to continue
and further the work initiated in this study. Most importantly, process work
should be continued and where possible expanded to further quantify underflow
events in both lakes, and the distribution of sediment and nutrients through the
water column.
Future process work in the lakes could focus on areal distribution of
sediment. It is understood that sediment accumulation is variable along both the
long axis and the short lake axes. A comprehensive network of sediment cores
and sediment traps throughout the lakes would expand our knowledge of spatial
sedimentary patterns and processes within the lake and could help elucidate
geomorphic versus hydroclimatic sedimentary events.
A comprehensive survey of ground ice and active layer distribution is
necessary in order to understand the complicated relationship between
permafrost degradation, potential ground ice melt-out and its impact on sediment
supplies. Within the catchments at Cape Bounty, different potential clay sources
exist (lacustrine and marine) and it is possible through X-ray diffraction to
110
differentiate which source is contributing clay particles to the total sediment yield.
The sources may contribute at different times depending on active layer
detachments and ground ice melt-out frequency.
At the beginning of most seasons, large amphipods were present in the
deepest basin of West Lake. The presence of these amphipods was unique to
West Lake and they disappeared when underflow activity increased. In 2005,
when few underflows occurred, the amphipods were present through the entire
season. Further work to understand the impact of these amphipods on the
aquatic ecosystem and sedimentary record would be significant, as few studies
have documented these fauna in the Arctic. As well, few cases have the multi-
year, observational and quantitative process analyses to support an
investigation.
5.3 Conclusion
The combination of multi-year process work and detailed sedimentological
analyses from two varve records in adjacent lakes represents one of the most
comprehensive studies of its kind to date. These results are the culmination of
in-situ field observations, laboratory preparation, analyses and data interpretation
through three years of arctic field science that have continued for several years
since the work in this thesis was completed. The implications of this work for
paleoenvironmental interpretations from arctic systems are becoming
increasingly important and complicated. The conclusions presented in this study
111
are potential starting points for future work and understanding of climate change
in the Arctic. Observations at Cape Bounty are on-going and at this point the
Cape Bounty Watershed Observatory project is the longest continuous multi-
disciplinary and integrated study of several watersheds in the High Arctic.
112
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Appendix A Correlation between Mould Bay and Rea Point weather stations
Mould Bay/ Rea Point R n p Mould Bay/ Rea Point R n p
T1 0.860 15 0.000 S1 0.184 15 0.511
T2 0.938 17 0.000 S2 0.822 17 0.000
T3 0.786 17 0.000 S3 0.046 16 0.867
T4 0.710 16 0.002 S4 0.452 16 0.079
T5 0.632 16 0.009 S5 0.125 14 0.669
T6 0.877 17 0.000 S6 -0.107 17 0.682
T7 0.827 17 0.000 S7 -0.101 16 0.708
T8, lagged 0.696 17 0.002 S8, lagged 0.410 17 0.102
T9, lagged 0.786 16 0.000 S9, lagged 0.025 16 0.927
T10, lagged 0.931 17 0.000 S10, lagged 0.319 17 0.212
T11, lagged 0.866 16 0.000 S11, lagged 0.153 16 0.572
T12, lagged 0.871 16 0.000 S12, lagged 0.370 16 0.158
T8-10, lagged 0.904 17 0.000 S8-11, lagged 0.107 16 0.693
T4-6 0.512 17 0.036 Winter 0.663 17 0.004
T5-7 0.481 17 0.051
Tn is monthly mean temperature (ºC) Sn is monthly total snowfall (cm) n is the numeric number for the month of the year
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Appendix B
Suspended sediment trapping in limnological process studies
Sediment traps are used in a variety of ways in an effort to quantify sediment flux
and characterize the quality of the sediment deposited in a number of
environments. This overview considers the major factors of freshwater sediment
studies: trap efficiency and disturbance due to trap deployment (causing
resuspension) and trap design.
Sediment traps used in suspended sediment settling studies are designed
to minimize errors due to resuspension of particles and maximize trap efficiency.
Bloesch and Burns (1980) review sediment trap techniques through previously
published work and several experiments and have identified four critical issues to
be considered in trap design: 1 - The effect of turbulence on particle settling
velocity as it pertains to resuspension and distribution of particles in the water
column; 2 –vessel shape on collection efficiencies; 3 – interaction of vessel
shape and turbulence on the mean concentration of particles suspended within
the trap; and, 4 – the effect of particle concentration within the trap in the
sediment collection efficiency of the trap itself.
The turbulence effect on particle settling can lead to resuspension of
particles from the bottom of a lake or from a layer within the water column where
particle concentration may be greater such as the thermocline (Bloesch and
Burns, 1980). In general, turbulence affects the distribution of particles in a water
column which may lead to more particles in a zone where the concentration is
131
usually reduced. For example, the bottom of the water column usually has
greater concentrations of particles, and turbulence may lead to resuspension and
then transport of particles upwards, to a zone with relatively lower concentrations
(Bloesch and Burns, 1980).
Resuspension of sediment in lakes can have a significant effect on
sedimentary budget analyses and influence lake metabolism and other biological
processes (Bloesch, 1994; 1995). There is some disagreement as to the
significance of resuspension on overall budget analyses because its effect is
variable. Davis (1973) demonstrated that the effect of resuspension was
insignificant in lake depth greater than 10 m and suggested earlier (Davis, 1968)
that thermostratification also reduced the potential for resuspension. However,
Bloesch and Burns (1980) indicate that the potential impact of resuspension was
greatest along gradients such as the thermocline or chemocline.
In several studies, radiometric dating was used to verify that sediment
accumulation rates in sediment traps was equal to accumulation rates measured
from sediment core samples (Pennington, 1974; Yamada and Aono, 2006). In
most cases, it was found that traps tended to over-estimate accumulation and
this was likely caused by some resuspension (Pennington, 1974; Yamada and
Aono, 2006). In effort to detect resuspension researchers have experimented by
adding dyes (Kirchner 1975) and/or density solutions (Rigler et al., 1974) to the
traps. A sodium chloride solution added during deployment would establish a
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density gradient to limit disturbance of the material collected and minimize
potential resuspension during recovery (Rigler et al., 1974).
Verifying accumulation and minimizing resuspension or disturbance are
the primary issues with respect to sediment trap studies. In general these issues
are possible to minimize with care and proper trap design and deployment. As
well, the environment in which the studies are conducted poses potential issues
due to turbulence. Sediment trap studies have not been standardized and pose
potential problems and conflicts when attempting to compare between studies
using different methods. However, given the complexity of the processes it is not
plausible that a single design or standard protocol could be introduced that
address every issues sufficiently in every environment. It is recommended that
future studies consider issues such as turbulence and resuspension in trap
design and deployment, and introduce measures of verification either by
redundancy in trap deployment or through the use of dyes or marker solutions.
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References for Appendix B:
Bloesch J. 1994. A review of methods used to measure sediment resuspension.
Hydrobiologia 284: 13-18.
Bloesch J. 1995. Mechanisms, measurements and importance of sediment
resuspension in lakes. Marine and Freshwater Research 46: 295-304.
Bloesch J, Burns NM. 1980. A critical review of sedimentation trap technique.
Schweizerische Zeitschrift fuer Hydrologie 42: 15-55.
Davis MB. 1968. Pollen grains in lakes sediments: redeposition caused by
seasonal water circulation. Science 162: 796-799.
Davis MB. 1973. Redeposition of pollen grains in lake sediments. Limnology
and Oceanography 18: 44-52.
Kirchner WB. 1975. An evaluation of sediment trap methodology. Limnology
and Oceanography 20: 657-660.
134
Pennington W. 1974. Seston and sediment formation in five Lake District lakes.
Journal of Ecology 62: 215-251.
Rigler FH, MacCallum ME, Roff JC. 1974. Production of zooplankton in Char
Lake. Journal of the Fisheries Research Board of Canada 31: 637-646.
Yamada M, Aono T. 2006. 238U, Th isotopes, 210Pb and 239+240Pu in settling
particles on the continental margin of the East China Sea: Fluxes and particle
transport processes. Marine Geology 227: 1-12.