10.5061/DRYAD.GHX3FFBQB
Geertsema, Marten
0000-0002-4650-8251
Government of British Columbia
Menounos, Brian
0000-0002-3370-4392
University of Northern British Columbia
Bullard, Gemma
BGC Engineering (Canada)
Carrivick, Jonathan
University of Leeds
Clague, John
Simon Fraser University
Dai, Chunli
Louisiana State University
Donati, Davide
University of Bologna
Ekstrom, Goran
Columbia University
Jackson, Jennifer
Hakai Institute
Lynett, Patrick
University of Southern California
Pichierri, Manuele
3v Geomatics (Canada)
Pon, Andy
3v Geomatics (Canada)
Shugar, Dan
University of Calgary
Stead, Doug
Simon Fraser University
Del Bel Belluz, Justin
Hakai Institute
Friele, Pierre
Geological Association of Canada
Giesbrecht, Ian
Hakai Institute
Heathfield, Derek
Hakai Institute
Millard, Tom
Government of British Columbia
Nasonova, Sasha
Government of British Columbia
Schaeffer, Andrew
Natural Resources Canada
Ward, Brent
Simon Fraser University
Blaney, Darren
Homalco First Nation
Blaney, Erik
Homalco First Nation
Brillon, Camille
Natural Resources Canada
Bunn, Chris
Fisheries and Oceans Canada
Floyd, William
Government of British Columbia
Higman, Bretwood
Ground Truth Alaska
Hughes, Katie
Government of British Columbia
McInnes, Will
Hakai Institute
Mukherjee, Kriti
University of Northern British Columbia
Sharp, Meghan
University of Calgary
A deglacial hazard cascade exemplified by the landslide, tsunami and
outburst flood at Elliot Creek, Southern Coast Mountains, British
Columbia, Canada
Dryad
dataset
2021
FOS: Earth and related environmental sciences
NASA Shared Services Center*
80NSSC20K0491
2022-02-14T00:00:00Z
2022-02-14T00:00:00Z
en
https://doi.org/10.5194/egusphere-egu21-9148
222379248 bytes
12
CC0 1.0 Universal (CC0 1.0) Public Domain Dedication
We describe and model the evolution of a recent landslide and outburst
flood in the southern Coast Mountains, British Columbia, Canada. About 18
Mm3 of rock descended 1000 m from a steep valley wall and traveled across
the toe of a glacier before entering a 0.6 km2 glacier lake and producing
a >100-m high wave. Water overtopped the lake outlet and scoured a
10-km long channel before depositing debris on a 2 km2 fan below the lake
outlet. Floodwater, organic detritus, and fine sediment entered a fjord
where it produced a 70-km long turbidity current and altered turbidity,
water temperature, and water chemistry for weeks. The outburst flood
destroyed forest and culturally significant salmon spawning and rearing
habitat. Physically based models of the landslide, the displacement wave,
and the flood provide real-time simulations of the event and can improve
understanding of similar hazard cascades and the risk they pose.
Airborne laser altimetry We performed three airborne laser altimeter
surveys over the study area using a Riegl Q780 full waveform scanner (1064
nm). As part of a larger forest inventory survey, a commercial party
acquired lidar data on 28 August 2014 for the lower reaches of Elliot
Creek (up to about 2 km upvalley from the mouth of the creek). These data
were combined with pre-event lidar data obtained during a survey of the
Homathko Icefield on 11 October 2019. Finally, post-event lidar data were
acquired on 23 December 2020 with the Riegl Q780 scanner mounted on a
helicopter. Average point density for the three surveys are 15, 2.2, and
25 laser shots points/m−2, respectively. We classified the lidar point
data into ground and non-ground laser returns and gridded the latter into
1 m bare earth Geotiffs. We co-registered the two pre-event lidar
grids and subsequently co-registered the pre-event data against the
post-event lidar product. Due in part to dense vegetation cover and the
low point density of the October 2019 lidar survey, we ascribe an
uncertainty within vegetated terrain of ± 0.69 m (1σ). In contrast,
vertical and horizontal uncertainty over sparsely vegetated and bare
surfaces is closer to ± 0.25 m. Although our true positional errors are
likely lower given the large sample size, our surveyed area is too small
to correct our sample size for spatial autocorrelation. We thus
conservatively use ± 0.69 m to quantify the vertical and horizontal
uncertainty of these surveys. Landslide and tsunami modeling We used a
hydrodynamic model (FLOW-3D HYDRO) to simulate the whole process of
landslide generation and resulting tsunami propagation in Elliot Lake.
FLOW-3D HYDRO is a CFD software that solves the hydrostatic
Reynolds-averaged Navier-Stokes equations to obtain transient,
three-dimensional solutions to multi-scale, multi-physics flow problems. A
key feature of this numerical model is the implementation of the Volume of
Fluid (VOF) method for simulating free surfaces . The VOF method is a
numerical technique used to track the locations and movement of complex
free surfaces and to apply proper dynamic boundary conditions to those
surfaces. The model uses a structured computational mesh that is composed
of rectangular elements defined by a set of planes perpendicular to each
of the coordinate axes. Critical inputs to FLOW-3D are topographic data
and the modelling approach to simulate the rock slide. We imported the
topographic lidar data from 11 October 2019 (pre-slide event) into the
program as a raster (Figure S11). Given the modelling area and computer
capacity, we used a 10 m x 10 m grid size for the model. The water surface
elevation of Elliot Lake was set to 727.5 m asl, which corresponds to an
approximate lake surface area of 59 ha. We used a 2D radial basis function
interpolant to estimate the lake bathymetry using the adjacent side
moraines and slopes to guide the interpolation. The rock slide was
simulated as a clear-water flow with a total volume of 13.3 Mm3, which is
equal to the estimate of the deposit in the lake. The model outflow
boundary is approximately 300 m south of Elliot Lake and was set to an
outflow-type boundary in FLOW-3D. We used the renormalized group (RNG)
model to describe the turbulent flow and set a surface roughness height to
0.01 m for the entire domain. The time series data for the resulting
tsunami as it propagates away from the impact zone indicates there are
multiple reflected waves that continue to oscillate within the lake after
the leading wave has overtopped the dam. These reflected waves have a much
smaller maximum amplitude and a significantly longer wave period, which
translates to a slower moving wave. The time series data also indicates
that the maximum amplitude of the leading wave decreases with time until
P5 (x = 1965 m). Outburst flood modeling There were no direct
measurements or observations of the outburst flood, and so our estimates
of its properties came from a reconstruction approach, sometimes referred
to as palaeoflood analysis. We employed Delft3D model software (version
4.02.03) in this study because it can accommodate a wetting front (i.e.
propagation of a wave over an initially dry bed) and hydraulic jumps
(rapid transitions between sub- and super-critical flow regimes). It also
can simultaneously consider both hydraulic variables and interactions
between the flow and the bed, enabling both sediment transport and
iterative bed elevation updating (i.e. erosion and deposition at each
model time step). Specifically, the physically based, fully non-linear,
Navier-Stokes equations were solved based on shallow water assumptions and
computed on nodes of a curvilinear computational mesh that was created
based on high-resolution (2 m), pre-flood topographic data acquired during
an airborne lidar survey. Design of the model domain (i.e. the extent and
coverage of this curvilinear mesh) was guided by the mapped wash limits.
In this study, numerical simulations were used to calculate hydraulic
parameters including depth-averaged velocity, flow depth, Froude number
(Fr), and bed shear stress (ꞇ) for every node of the computational mesh
and for every model time step, which in order to conserve mass and
momentum, was necessarily small (0.0001 mins). The outburst flood model
was parameterised assuming a spatially uniform or ‘global’ roughness of
Manning’s n of 0.05, which in lieu of spatially distributed grain-size
information, we consider to be representative of glaciated mountain valley
gravel-bed rivers. Similarly, in lieu of any knowledge of distributed
sediment depth and grain size distributions, we assumed a spatially
uniform or ‘global’ sediment depth of 20 m, a specific density of 2650 k
gm-3, and a D50 grain size of 2000 µm, which we consider to be
representative of the alpine glacial valley sediment in this region of
western Canada. Although the model incorporates the effect of sediment in
the water column on water density, it is a Newtonian fluid model only, so
there is no consideration of sediment concentration effects on flow
behaviour. Additionally, only vertical exchanges of sediment with the bed
are considered; there is no formulation or representation of mass failures
such as bank collapses. We used two conditions to introduce water to our
outburst flood model. The first is the height of the mapped wash limits
above the valley floor at the moraine dam, which indicate peak flood stage
at our outburst flood model upstream boundary. The second is the output
hydrograph of the tsunami model, which indicates the rate of rise to peak
discharge, as well as the rate of the falling limb, at the moraine dam.
Our outburst flood model was therefore forced by a time-transgressive
water level, reaching peak stage just 30 seconds after the entry of the
landslide into the lake and then exponentially falling to valley floor
level after 3 minutes. The downstream boundary of our outburst flood model
was sea level and was parameterised as such; i.e. water level equal to 0 m
a.s.l. for the duration of the flood. A ‘spin-up’ model was used as input
to the full model runs. The spin up model was a 48-hour run using a base
flow of 10 m3 s-1 , which we regard as a realistic background discharge
for Elliott Creek at the time of the landslide, given scaling of
comparable discharges in the region based on catchment size. This model
served to ‘pre-condition’ or re-distribute the mobile sediment
realistically across the model domain. Fjord turbidity and water
temperature analysis Temperature, salinity, pressure (CTD), and oxygen
data have been collected at eight evenly spaced stations that span the
length of Bute Inlet since 1951 by the University of British Columbia,
Fisheries and Oceans Canada, and the Hakai Institute. Following Jackson et
al. (2021), we removed the seasonal cycle from temperature, salinity, and
oxygen data by using monthly averaged data from 1951 to 2010. Once the
seasonal cycle was removed, the time series could be examined in the
context of stochastic, annual, and decadal change. For the analysis
presented in Figure 4, data were collected 37 days before (22 October
2020), four days after (2 December 2020), and 16 days after (14 December
2020) the Elliott Creek landslide. Turbidity data and calibration
Beginning in 2018, Seapoint turbidity meters were attached to the CTD
systems to investigate particle dynamics within Bute Inlet. These sensors
have a light source in the near-infrared (880 nm), were factory calibrated
with Formazin (output in FTU), and were rated to have a linear response
(+/- 2%) to particle concentrations spanning 0 to 1250 FTU. Unfortunately,
a different sensor was utilized on the two surveys following the
landslide, and this sensor showed an approximately 2 FTU greater offset
than the sensor utilized prior to the landslide. A sensor-specific offset,
rather than increases in particle concentrations between surveys, was
proven by comparing data from the two sensors in Bute Inlet with data
collected at stations outside Bute Inlet, both of which showed a
comparable offset over a wide range of conditions. As a result,
corrections were performed for this offset to make the data from both
sensors comparable. First, we selected a station that consistently showed
the lowest profile turbidity magnitudes over the time series as a
reference station (BU2, 658 m deep and 54 km from the head of the fjord).
Second, for each survey, we averaged the 10 minimum turbidity values from
the profile collected at this reference station to represent a
“particle-free” instrument blank value. Data were averaged over the 10
minimum values to limit the influence of instrument noise, and the
standard deviations of these averages were low (0.002–0.006 FTU). Third,
this derived instrument blank value was then subtracted from data for each
station collected during the survey. At times, this method resulted in
slight negative values; these were set to zero. Care should be taken when
interpreting these data, as it is unlikely that true “particle-free” blank
offset values could be determined in dynamic coastal waters with high and
variable particle concentrations. However, the calculated offset values
were consistent over time in comparison to stations outside Bute Inlet,
suggesting a lack of environmental influence and adding confidence to the
method.
The 6 animations of various aspects of the landslide, flood, and tsunami
(impulse wave) are in .avi or .mp4 format. These are meant to be
visualizations to help understand the dynamics of the cascading hazards.
The lidar difference data is in .asc format, readable by open source GIS
software. Fjord turbidity and CTD (temperature, salinity, and pressure)
data are available in .csv and.xlsx formats.