NHESSNatural Hazards and Earth System ScienceNHESSNat. Hazards Earth Syst. Sci.1684-9981Copernicus GmbHGöttingen, Germany10.5194/nhess-15-1265-2015Dynamics of the Oso-Steelhead landslide from broadband seismic analysisHibertC.hibert@ldeo.columbia.eduStarkC. P.EkströmG.Lamont-Doherty Earth Observatory, Columbia University, Palisades, NY, USAC. Hibert (hibert@ldeo.columbia.edu)17June20151561265127312November20145December201414May201521May2015This work is licensed under a Creative Commons Attribution 3.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by/3.0/This article is available from https://nhess.copernicus.org/articles/15/1265/2015/nhess-15-1265-2015.htmlThe full text article is available as a PDF file from https://nhess.copernicus.org/articles/15/1265/2015/nhess-15-1265-2015.pdf
We carry out a combined analysis of the short- and long-period seismic
signals generated by the devastating Oso-Steelhead landslide that occurred on
22 March 2014. The seismic records show that the Oso-Steelhead landslide was
not a single slope failure, but a succession of multiple failures
distinguished by two major collapses that occurred approximately 3 min apart. The first generated long-period surface waves that were
recorded at several proximal stations. We invert these long-period signals
for the forces acting at the source, and obtain estimates of the first
failure runout and kinematics, as well as its mass after calibration against
the mass-centre displacement estimated from remote-sensing imagery.
Short-period analysis of both events suggests that the source dynamics of the
second event is more complex than the first. No distinct long-period surface waves
were recorded for the second failure, which prevents inversion for its source
parameters. However, by comparing the seismic energy of the short-period
waves generated by both events we are able to estimate the volume of the
second. Our analysis suggests that the volume of the second failure is about
15–30 % of the total landslide volume, giving a total volume mobilized by
the two events between 7 × 106 and
10 × 106 m3, in agreement with estimates from ground
observations and lidar mapping.
Introduction
On 22 March 2014, a catastrophic landslide occurred 6.4 km east of
Oso (Washington, USA), in the North Fork Stillaguamish River valley,
destroying the neighbourhood known as “Steelhead Haven” and causing 43 fatalities
. The failure occurred on a slope
which had already been affected by at least six episodes of collapse since
1955. It was preceded by several days of heavy rainfall. The lithology of the
North Fork Stillaguamish River valley consists of a surface unit formed by
glacial-fluvial sediments, underneath which lies a sequence of
glacial-lacustrine silts and clays .
The block field constituting the bulk of the landslide travelled approximately
1.1 km and separated into two segments. The majority of the
mobilized material accumulated in the western segment. The highly-liquefied
distal debris flow travelled a maximum distance of approximately
1.4 km in the western segment and 1.6 km in the eastern
segment . Deposits of the landslide formed a dam on the
north fork of the Stillaguamish river. Ground observations suggest a total
volume of the deposits comprised between 7.3 × 106 m3
and 9.2 × 106 m3.
Reconstructing the failure sequence of a landslide mass is a challenging
task, as direct observations of the mass movements are rare. In recent years,
seismology has proven useful in this regard by offering a way to infer the
dynamics of large mass movements e.g., and estimate important
properties such as the mobilized mass . Additional
analysis of the short-period waves provides an extra constraint on source
mechanisms and a more complete understanding of the dynamics of slope
failures e.g.,.
Map of seismic stations used in the investigation of the
Oso-Steelhead landslides. Blue squares show stations with good short-period
signals (1–10 Hz); red squares show stations with good long-period signals
(40–150 s). The stations belong to the Pacific Northwest Regional Seismic
Network (CMW, JCW, MBW and TWW), the USArray Transportable Array (A04D, B05D,
C06D, D03D and D04D) and the Cascade Chain Volcano Monitoring network
(PANH).
In this study we present a joint interpretation of the long-period force
history of the Oso-Steelhead landslide and the associated short-period
seismic signals. Our study builds on and extends the ground observations and
results presented in the Geotechnical Extreme Events Reconnaissance report by
. Our work also benefits from some of the results presented
in the recent study of the landslide by . We note that our
seismological analysis is different from that of , and that
our results differ in important ways from those obtained in that study. We
discuss these differences and their likely explanation in some detail in the Appendix.
We first present the seismic observations made on short-period and broadband
stations, which indicate that two consecutive slope failures occurred. We
then present the results of the inversion of the landslide force history
(LFH) of the long-period signals generated by the first landslide, and
provide an estimate of its mass, peak velocity and acceleration. Finally we
compare the short-period seismic signals to the LFH, which leads to an
interpretation of the dynamics of the first landslide. We discuss, based on a
comparison of the seismic records and with reference to the ground
observations, possible source characteristics of the second event.
Seismic observations
The seismic waves generated by the Oso-Steelhead landslide were recorded by
several short-period and broadband stations (Fig. ).
Two high-amplitude short-period signals were recorded on stations at
distances ranging from 11.7 to 180 km. The first
seismic signal onset was recorded at 17:37:22 UTC on the closest
short-period station (JCW) from the Pacific Northwest Regional Seismic
Network (FDSN network code UW), at a distance of 11.7 km. The
short-period (1–10 Hz) seismic signal recorded at JCW has a duration of
approximately 100 s, and exhibits all the known features of
landslide-generated seismic signals: emergent onset, no distinct P and
S waves and no clear peak amplitude visible in the higher-frequency bands
(Fig. a and b) .
Spectral analysis of the seismic signal recorded
at JCW shows persistent high energy between 1 and 10 Hz (Fig. c),
remaining high for approximately 1 min before a gradual decay.
A second event was recorded at 17:41:53 at JCW. Its signal has a more
impulsive onset than that of the first event and a shorter duration of
60 s. It exhibits several consecutive amplitude peaks in the
1–3 Hz frequency band (Fig. a). The onset
of the seismic signal of the second event is marked by a high-amplitude burst
of energy in the 3–10 Hz band (Fig. b). A
second burst of energy in this frequency band is observed at the end of the
signal (Fig. b and c). The two peaks following the
onset and observed in the 1–3 Hz band do not appear in the
3–10 Hz frequency band (Fig. ). On the
closer station (JCW), several other weak but distinct short-period signals
were recorded (e.g., at 17:43:30 – Fig. b) that were
possibly generated by residual collapses in the hours following as a result
of local destabilization caused by the two main events.
Seismic signals recorded at the short-period station JCW, located
11.7 km from the Oso-Steelhead landslide, filtered between
(a) 1–3 Hz and (b) 3–10 Hz. (c) Spectrogram of
the seismic signal computed using fast-Fourier transform, with an 8 s moving
window and a 90 % overlap. (d) Long-period seismograms recorded at
the station B05D and filtered between 40 and 150 s (0.0067–0.025 Hz). The
black arrow indicates the onset time of the short-period seismic signal
generated by the second event.
Seismic signals in detail for (a) and (b) event 1,
and for (c) and (d) event 2 at station JCW, filtered between
1–3 Hz and 3–10 Hz, respectively.
The onset time for both signals is indicated by the green line. Labels p1
and p2 indicate the two amplitude peaks observed only in the seismic signal
of the second event filtered in the 1–3 Hz frequency
band.
Long-period surface waves (period ranging from T= 40 s to
T= 150 s, corresponding to a frequency range of 0.0250 to 0.0067 Hz) were also detected for the first event
(Fig. d) at five broadband stations (four from the
USArray Transportable Array), with distances from the landslide ranging from
18.3 to 140.8 km. No distinct long-period seismic
signal was observed for the second event (Fig. d).
Several differences between the seismic signals of the two events are
therefore identified: (1) the seismic signal of the second event has a more
impulsive onset than the first (Fig. a and b);
(2) several distinct amplitude peaks are observed in the signal of the second
event filtered in the 1–3 Hz frequency and not for the first
event (Fig. a); (3) the seismic signal of the second
event has less energy in the frequency band above 5 Hz compared to
the first (Fig. c); (4) a long-period signal was
generated by the first event, and absent for the second. These observations
suggest differences in the dominant source characteristics.
Force history of the first Oso-Steelhead landslide
The acceleration and deceleration of the bulk mass during the landslide cause
a loading and unloading of the slope that generates long-period seismic
waves. The forces acting on the slide mass that bring about this
loading–unloading cycle are gravity, basal friction, and centripetal forces,
and each of these has a reactive counterpart acting on the solid earth in the
opposite direction across the slide contact area
e.g.,. The
landslide therefore exerts a force F on the solid Earth that is
the vector opposite of the force FS, equivalent to the
bulk momentum change of the slide
F[x,t]=-FS=-d(mv)dt[x,t]
with m the mass of landslide, v the velocity of the
centre-of-mass at the position of the centre of mass x and at the
time t. The time-varying forces acting on the slope during the
loading–unloading cycle can be retrieved by inversion of long-period seismic
waves, and thereby provide a force history from which information on the
dynamics of the landslide can be inferred.
We use the inversion method developed by to determine
the landslide force history (LFH) of the Oso-Steelhead landslide from the
long-period waveforms recorded at five broadband stations. The method is
based on the approximation that, when considering the long-period signals,
the landslide seismic source can be described as a time-varying, 3D force
vector acting at a fixed point .
This assumption is justified to the extent
that the spatial scale of the slide is small compared to the wavelength of
the seismic waves and to the distances to the recording seismic stations.
Hence we restrict our analysis to signals with periods comprised
between 40 and 150 s.
The time history of each component (north, east, vertical) was parameterized
using a sequence of isosceles triangles overlapping by their half-duration.
We solved for the amplitudes of the triangles that define the time histories
of each component of the force by minimizing, in a least-squares sense, the
misfit between observed and corresponding synthetic seismograms
(Fig. a). Synthetic seismograms were calculated by summation
of Earth's elastic normal modes with corrections for laterally heterogeneous
crust and mantle . The time history of each force
component was constrained to integrate to zero to satisfy the condition that
the sliding mass must be at rest before and after the landslide. We tested a
wide range of different source models by adjusting the number of and width of
triangular subsources, as well as by the selection of seismograms to include
in the inversion. The preferred model was obtained using a parameterization
in terms of 8 triangles with a half duration of 10 s. The main
characteristics of the derived Landslide Force History are robust with
respect to data selection and source parameterization.
(a) Observed (black) and synthetic (red) long-period
seismograms filtered between 40 and 150 s for the first Oso-Steelhead
landslide. The station name, component and distance to the landslide are
given to the right of each trace. (b) Landslide force histories
inverted for the first Oso-Steelhead landslide. (c) Temporal
evolution of the acceleration and the velocity of the centre of mass inferred
from the integration of the inverted forces.
The maximum of the inverted forces is 1.3 × 1010 N and the
duration of sliding is approximately 90 s (Fig. b).
The time-varying displacement D[t] of the centre of mass is
estimated from double integration of the forces
D[t]=-1m∬0tF[τ]dτ.
The trajectory is scaled to fit ground observations by adjusting the mass m
in Eq. (), thus also providing an estimate of the mass.
The inverted trajectory that best fits the geometry of the source area and of
the deposits was obtained by using a mass of 1.5 × 1010 kg,
and it shows an initial centre-of-mass acceleration to the south-east and
then a propagation to the south (Fig. ). The
curvature of the trajectory follows the shape of the maximum
accumulation area well. We infer a run-out distance of 800 m. Assuming a
density of the deposits of 2000–2500 kg m-3, the
inferred volume ranges from 6.0 × 106 to 7.5 × 106 m3. This is similar to, but smaller than,
the value obtained by an analysis of the total landslide deposits .
We infer kinematic parameters from the integration of the inverted forces.
The maximum bulk speed reached by the centre of mass of the landslide was
19.4 m s-1 and the maximum acceleration was
1.0 m s-2 (Fig. c). The maximum speed,
and the associated momentum and kinetic energy, are reached after
35 s after a displacement of approximately 400 m
(Fig. ), which corresponds to the moment
when the centre of mass reached the break between the slope and the valley
(Fig. ). After this time the scalar product of the
opposing force F and the normalized momentum
p^ becomes negative (red curve on
Fig. a), which indicates that the centre of mass
starts to decelerate along the path. The total potential energy lost during
the slide computed from the drop in height inferred from the LFH is about
1.6 × 1013 J. It is almost 6 times the maximum kinetic
energy calculated from the centre-of-mass velocity, estimated at 2.8 × 1012 J
(Fig. a and b).
(a) Short-period seismogram at station JCW filtered between
3 and 10 Hz together with the modulus of the inverted forces (black curve),
the scalar product of the opposing force F and the normalized
momentum p^ (red curve), the modulus of the inverted
momentum (blue curve) and the smoothed envelope. Time t0 indicates the
origin start time of the LFH, before shifting it by the travel time of the
seismic waves. (b) Inferred centre-of-mass trajectory for the first
landslide. Coloured dots indicates the time at which the centre of mass
occupied the corresponding position along the inferred trajectory. The yellow
and orange-dashed contours labelled A and B indicate the extent of the first
and second landslides deposits respectively, identified by
. The red lines labelled 1 and 2 indicate two possible
locations for the source area of the second
landslide.
Total energy (black), potential energy (green) and kinetic energy
(red) as (a) a function of the time and (b) a function of
the travelled distance. Momentum of the centre-of-mass as (c) a
function of the time and (d) a function of travelled distance. Speed
of the centre-of-mass as (e) a function of the time and
(f) a function of the travelled
distance.
DiscussionDynamics of the first event from comparison of the LFH and short-period data
The combined analysis of short-period seismic data with the dynamics inferred
from long-period waves provides important information on large landslide
motion . While
the long-period waves and the force-history (LFH) inversion provide insight
into the temporal evolution of the bulk momentum of the whole landslide mass,
the short-period waves reflect spatially complex momentum exchanges across
the basal slide area at shorter length scales. Hence short-period signals are
sensitive to far more variables, including small-scale relief and topographic
obstacles along the runout path, variability in basal friction and mobility
of the granular material within the sliding mass. Strong impulsive bursts of
energy in the short-period signals can sometimes be tied to the fall of
individual blocks or to the impact of debris after a
free-falling phase .
In order to compare the LFH with the short-period seismic signals, we first
computed the travel time of the signal with respect to the origin time given
by the LFH inversion. An average propagation velocity can be estimated from
comparison of the arrival times recorded at stations JCW and CMW, for which
good quality time-picks of the signal onset were possible. We find an average
velocity of ∼ 1.1 km s-1. Using this velocity, a
shift of 10 s is applied to the LFH to align it with the
short-period seismic signal recorded at station JCW. The interpretation that
follows is not sensitive to small variations in this assumed propagation velocity.
As Fig. shows, the initial acceleration of the
landslide generated very weak short-period seismic waves. Once peak
acceleration of the centre of mass was reached, a low-amplitude short-period
signal emerged from the noise. This delay suggests fragmentation of the
initially intact mass while it was already accelerating on the slope
. At that point, the magnitude of
acceleration along the trajectory started to decrease. The highest amplitudes
of the short-period seismic signal occurred at the moment deceleration began.
During the whole deceleration phase (inferred from the LFH), the short-period
seismic signal amplitude decreased monotonically and passed below the noise
level at roughly the same time that the centre of mass came to a halt.
Estimating the dynamics and size of the second event from short-period signals
The seismic signals of the second event are more difficult to interpret. The
two amplitude peaks observed (following band-pass filtering at
1–3 Hz; indicated by p1 and p2 on Fig. ) at
approximately 15 and 25 s after the signal onset of the
second event are possibly related to the impacts of large chunks of debris
with the terrain or with the earlier landslide surface after a free-fall or a
very short-lived motion. A composite slope failure process is another
possible explanation. These two amplitude peaks are not visible in the
3–10 Hz band. In a previous study , we
observed that seismic signals produced by the two major landslides during the
Bingham Canyon open-pit mine collapse exhibited amplitude peaks that
originated in the flowing mass hitting topographical barriers and that were
stronger in the 1–3 Hz frequency band than in the
3–10 Hz band. This observation points to a potential higher
sensitivity of the 1–3 Hz frequency band to topographical
effects, and prompts the interpretation that the two peaks observed for the
second Oso-Steelhead event might have been generated as sliding and flowing
debris encountered topographic obstacles. A succession of multiple intricate
breakaways and short phases of motion may also explain why no strong
long-period waves were generated by the second event.
In the absence of significant long-period seismic waves records for the
second event, we are not able to determine its mass and volume using the
inversion method presented above. However, the lack of a long-period signal
constrains the bulk momentum change of the second event to be much smaller
than that of the first. The amplitude of the long-period signal of the first
event recorded at the closest station (B05D) is approximately 3 times
higher than the noise amplitude. The amplitude of the long-period signal is
roughly proportional to the force exerted by the landslide on the earth, and
hence to the mass and the acceleration of the centre-of-mass of the
landslide. If we assume the same peak acceleration for the centre-of-mass of
both events , the fact that the amplitude of the
long-period seismic signal of the second event is lower than the noise level
implies that the mass of the second landslide is at least 3 times lower
than the mass of the first. Consequently, the upper bound for the second
landslide mass is roughly 25 % of the total mass mobilized. Note that this
upper bound would increase if the centre-of-mass peak acceleration of the
second landslide were smaller than the first.
Earlier studies have shown that a rough
estimate of landslide volume can be deduced from analysis of the seismic
energy of the short-period waves, thought to be related to the potential
energy released by vertical displacement of the landslide mass. It is
important to note that the direct relationship between the seismic energy and
the volume of granular flows established by is dependent on
the slope parameters. Therefore comparing the seismic energy of the
short-period waves generated by two different landslides is only relevant
when the geometry of the source is similar, and the dominant process at the
origin of the short-period seismic wave is the flow of a granular mass. With
the assumption that the two events of the Oso-Steelhead sequence roughly
share the same source geometry and behave principally as granular flows, we
computed and compared the energy of the seismic signal of the first and
second landslides in the 3–10 Hz frequency band. This frequency
band is close to that chosen for the events for which this seismic-energy
approach has been developed . Choosing to
compare the seismic energy generated in the 3–10 Hz frequency
band also has the advantage that it eliminates the two high-amplitude peaks
that could otherwise unduly influence the computation of the seismic energy,
as they are probably generated by other mechanisms than the simple flow of
the granular mass. We found a seismic energy ratio between the first and
second events of 6.5 at the JCW station. If the ratio of dissipated
potential energies is the same as their seismic energy ratio, and if we
assume (for the moment) the same run-out distances and the same average
sliding angle for both events, the second slope collapse would have a mass
approximately 13 % of the total mobilized Oso landslide mass. However,
ground observations and the measured duration of
short-period seismic signals suggest that the run-out distance of the second
event is shorter than the first, possibly by a factor of 2 or 3,
depending on where the source area of the second landslide is located.
Two possible locations for the source area of the second event can be assumed
(Fig. b): (a) at the head scarp, or (b) from the
collapsed structure resting at the top of the deposits of the first event. A
shorter run-out distance with the same amount of potential energy dissipated
would imply that the mass of the second event is bigger, assuming the same
angle of sliding. For scenario (a), with a run-out distance half that of the
first landslide, the second landslide would represent approximately 20 % of
the total collapsed mass. For scenario (b), with a run-out distance for the
second landslide a third of the first, the mass of the second collapse would
represent 30 % of the total landslide mass. Given the uncertainty over
which scenario is correct, we estimate the percentage of the debris mobilized
by the second event at between 15 and 30 % of the whole Oso landslide
mass. This is in agreement with the ground observations
and their volume estimate for the second major failure at around 15 to
50 % of the total.
Conclusions
Our analysis of the seismic signals generated by the Oso-Steelhead landslide
provides information on its failure sequence together with estimates of key
parameters of the landslide dynamics. Two separate events are identified from
the seismic data recorded at proximal stations, confirming ground
observations of two distinct and substantial slope failures
. Differences in the seismic features of each event point
to variation in their source characteristics and therefore differences in the
way runout took place in each case.
The seismic signal of the first event exhibits all the known features of
those generated by landslides, with emergent onset, no distinct P and S waves
and no clear high-amplitude peak in the higher frequency bands. The strong
long-period surface waves indicate the mobilization and acceleration of a
large landslide mass. Inversion of these long-period surface-waves generates
a “landslide-force history” or LFH. The bulk run-out trajectory inferred from
this LFH is consistent with ground and remote-sensing observations. Through
approximate scaling of the LFH trajectory against these observations, we
estimate that the mass of the first landslide is about
1.5 × 1010 kg, corresponding to a volume in the range
6.0 × 106 to 7.5 × 106 m3. The peak
centre-of-mass velocity and acceleration inferred from the LFH inversion are
19.4 m s-1 and 1.0 m s-2, respectively.
The seismic signal of the second event is more impulsive, shows several
amplitude peaks, and has little energy at long periods, which makes LFH
inversion impossible. While these observations are difficult to interpret in
geomorphic terms, recent studies of short-period seismic signals generated by
mass movements provide some guidance. They lead us to suspect that the
observed signal may have resulted from a complex breakaway sequence that
merged into one apparent failure event, with possibly free-fall episodes,
followed by a short runout that was abruptly stopped by topographic
obstacles. Analysis of the seismic energy of the signal filtered between
3–10 Hz recorded at the JCW station gives a rough estimate of
the volume of the second event, at around 15–30 % of the total mobilized
volume, in agreement with that estimated from other observations. Based on
this estimate and the volume inferred for the first landslide from
long-period seismic wave inversion, we deduce the total debris volume
mobilized by the Oso-Steelhead events to be between 7 × 106 and
10 × 106 m3, consistent with estimates from ground
observations and lidar mapping .
Comparison with the results of Iversion et al. (2015)
In a recent study, presented a comprehensive
investigation of the Oso landslide, including a seismological analysis of the
force history of the landslide. Their seismological analysis, which is based
on a methodology developed by , is different from the
analysis presented here, and leads to significantly different results for the
force history and inferred dynamics of the Oso landslide. In particular,
while our results indicate a simple overall slide history,
concluded that the Oso landslide occurred as a two-stage
failure, with the first stage (“interval 1” in their study) involving
acceleration and deceleration of a coherent mass at the low end of the slope,
which subsequently destabilized material above it, leading to a more
energetic second stage. A second notable difference is that
determine a maximum force that is approximately one fifth
of the maximum force obtained in our study.
Here we illustrate how the initial part of the force history determined by
is likely spurious and a consequence of the narrow
frequency band used in their seismological data analysis. Similarly, we show
that the small magnitude of the forces recovered in the
study is a second consequence of the details of their data analysis.
The method of for recovering the history of forces
acting on the Earth's surface is technically close to a time-domain
deconvolution. If we denote the forces exerted on the Earth by the landslide
motion by F(t), the effects of the propagation through the Earth (the Green
function) by G(t), and the resulting ground displacement at the seismometer
by S(t), these functions are related by
S(t)=F(t)*G(t),
where * signifies convolution. recovers the force
history from observed ground motion O(t) by solving an inverse problem for
the time series F(t) by minimization of the squared difference between
O(t) and the predicted S(t). Ideally, this procedure can recover F(t)
without assumptions about the origin time of the landslide, or its time
history. This is in contrast with the parameterized inversion method used in
our analysis , in which the force history is
prescribed to have a finite duration, and the origin time is solved for in an
iterative inversion.
Difficulties with a deconvolution approach arise when part of the landslide
signal is buried in the background seismic noise, and only a band-passed
version of O(t) is matched in the inversion. The recovered force will then
be a band-passed version of the true F(t).
We simulated the analysis performed by to investigate the
effect of the narrow period band (30–60 s) used in their inversion. We
first simulated the observed signal in the simplest way, by convolving our
LFH with a band-pass filter with the parameters used by ,
and by taking the derivative to capture the fundamental relationship between
forces acting on the Earth's surface, and the observed ground displacement at
a distance . We then fitted the filtered signal by
minimizing the difference between it and a similarly filtered prediction by
inverting for the time history F(t). Because the problem is poorly posed
after the signal has been band-pass filtered, we minimize the norm of F(t)
in the same way as to stabilize the inversion.
curve shows the N–S force history as determined in our analysis
(cf. Fig. 4). Second curve from the top shows the output from our simulation
of the effect of the method used by on the recovery of
the N–S force history. The third curve from the top shows the N–S force as
determined in . The top three curves are plotted with the
same vertical scale, and on the same time axis, with 0 corresponding to
17:37:10.5 (UT). The bottom trace shows the short period seismogram recorded
at the closest station JCW, shifted earlier by 6.4 s to account for the
propagation delay to the station.
Same as Fig. , but showing the E–W force
history.
Figure illustrates the result of this simulation experiment
for the N–S component of the force. The top trace shows the force history
determined in our study. The sinusoidal shape is typical of landslides,
corresponding to a centre-of-mass acceleration followed by deceleration, with
a duration of ∼ 80 s. The second trace shows the output from the
inversion that simulates the analysis of . The amplitude
of the force is only ∼ 20 % of the input force history, illustrating
the distortion caused by the narrow band-pass filter and damped inversion.
The second trace also shows significant signal before the onset of the input
force, reflecting that the deconvolution by inversion introduces acausal
precursory signals, or Gibbs effects. The third trace shows the force history
of , plotted on the same absolute time scale. The low
amplitude of the force and the precursory signal are characteristics that
closely resemble the acausal and attenuated output of our simulation. The
results for the E–W and U–D components of the force are analogous as shown
in Figs and .
The similarities of the force histories of and our
results after simulating their analysis steps and using our best estimate of
the true landslide force history are striking. We infer from this experiment
that one key element of the seismological results presented in
, the 40 s early sliding during “interval 1” is a
spurious result that is a consequence of the narrow band-pass filter used in
the filtering and inversion of the seismograms. This inference is
corroborated by examination of the short-period seismogram recorded at the
station JCW at 11.5 km distance from the landslide. We follow
and shift the trace earlier by 6.4 s to account for a
propagation delay before comparing the timing of the record with that of the
inferred landslide forces. We find that the emergent JCW signal agrees very
well with the onset of the landslide force as determined in this study. This
is consistent with results from other well-recorded landslides
e.g.. The absence of earlier short-period signal at
JCW further supports our inference that the forces during “interval 1”
discussed by are spurious.
Same as Fig. , but showing the U–D force
history.
The experiment provides an explanation for the difference in the force
magnitude. The forces determined by are small and not
consistent with the centre-of-mass movement observed. On the other hand, we
find good agreement between our combined mass estimate and trajectory,
obtained by integration of our force history, and the observed and simulated
mass transport reported by .
Acknowledgements
This work was supported by the US National Science Foundation Division of
Earth Sciences and the Geomorphology and Land-use Dynamics/Geophysics
programs under awards 1227083 and 1148176, and the US National Science
Foundation Division of Civil, Mechanical and Manufacturing Innovation and
the Hazards SEES program under award 1331499. We thank the operators of the
seismic networks for collecting the data used in this study, and the IRIS
Data Management System for providing easy access to the data.
Edited by: F. Guzzetti
Reviewed by: three anonymous referees
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