Thank you very much to the organizers for inviting me to give this talk.
Today I’m going to be speaking about ground shaking and hazards from
Cascadia subduction zone earthquakes with a focus on northern California.
And I just want to acknowledge my collaborators Alex Grant,
Art Frankel, and Nasser Marafi.
Subduction zones are hosts to the world’s largest earthquakes,
and in addition to ground shaking, they also produce devastating
tsunamis and ground failures.
This is a map of recorded and well-constrained historical earthquakes
with magnitudes greater then 8.5, and the colors indicate the tsunami
maximum water height, which you can see, in some cases, exceeds 30 meters.
Now, in Cascadia, where the Juan de Fuca Plate is subducting beneath North
America, we haven’t experienced a large megathrust earthquake in recent history.
We know from a variety of paleoseismic evidence
that the subduction zone is capable of generating
magnitude 8 to 9 earthquakes.
So this is a figure from Walton and Staisch and others highlighting the
multitude of paleoseismic evidence at sites, both onshore and offshore,
for Cascadia megathrust earthquakes. It’s a bit hard to see, but these horizontal
bars represent turbidite age ranges, and the downward arrows and waves
are dated estimates of coastal subsidence and tsunami inundation
at corresponding sites. And thus, these vertical gray bars
here are interpreted as ages of previous Cascadia earthquakes.
So, for margin-wide magnitude 9 ruptures, such as shown in this figure,
the paleoseismic record suggests a recurrence interval of roughly
every 500 to 530 years.
Now, for shorter partial-margin ruptures on the order of magnitude 8,
paleoseismic evidence suggests that the ruptures may be more frequent
and closer to about 300 years or so in southern Cascadia.
So I’m sure many of you have heard me talk about the M9 Project, and the work
I’m going to show you today is an extension of those simulations.
So, just as a reminder, as part of the M9 Project, we ran 3D kinematic
simulations of 50 M9 Cascadia earthquake scenarios using a compound
rupture model where low-frequency energy comes from the steep
background slip, and high-frequency energy is radiated from distinct
sub-events on the deeper portions of the fault.
So these 3D simulations are run up to 1 hertz.
And, for higher frequencies, we used a stochastic approach and assumed that
the high frequencies are coming from these high-stress drop sub-events.
Now, 30 of those earthquake scenarios were derived from a logic tree that
varied multiple parameters. So we varied the down-dip rupture
extent, so whether it was completely offshore, kind of brushing the coastline,
or if the down-dip rupture limit extended eastward beneath the
coastline. We varied the hypocenter location, the slip distribution was
randomly generated, and we also varied the locations
of those high-stress drop sub-events.
So last year, we expanded upon the M9 Project simulations and
used them to develop what we refer to as ensemble ShakeMaps.
So, for each of the 30 M9 Cascadia earthquake scenarios that were derived
from that logic tree, we developed a single-scenario ShakeMap,
and then we combined those to make a median ensemble ShakeMap,
as well as plus or minus 1 or 2 sigma ensemble ShakeMaps.
So these ensemble ShakeMaps have a few important differences from
traditional scenario ShakeMaps. They include additional epistemic
uncertainty, such as considering different down-dip rupture limits,
while in a traditional single ShakeMap, you’d assume a single fault plane.
In addition, because our ensemble ShakeMaps are based on a 3D –
on 3D numerical simulations, that means that, for periods greater than
1 second, we should be able to better capture regionally specific
3D wave propagation effects that might not be well-represented
in ground motion models. So a good example of this is in the
Seattle Basin where we know that simulated ground motions do a better
job of matching observational data compared to ground motion models.
Since I know everyone here is interested in California, I do want to point out
something important about the extent of these ShakeMaps.
So the M9 Project 3D earthquake simulations only covered the extent
that is shown in this green box here. Our original intent was not to expand
the ShakeMaps to a larger geographical extent.
But, towards the end of our project, the state agencies and FEMA partners
that we were working with requested this larger extent shown in the blue box
here in order to facilitate state- and margin-wide risk analyses.
[dog barking briefly]
So, to do this, we extended the simulated ground motions at the
edges of our model box – again, shown in green, using a fall-off rate
that was – a fall-off rate with distance that was derived from the subduction
zone ground motion models used in the 2018 National Seismic Hazard Maps.
So we know that areas outside of this green box don’t have any
local 3D wave propagation effects included, and that is
an obvious place for future improvement.
So, to make these ensemble ShakeMaps, we had to apply some site corrections.
So the original M9 Cascadia simulations did not include site effects.
So Vs30 in the Puget Lowland was about 600 meters per second.
Vs30 elsewhere was about 800 meters per second.
So, to model site response, my collaborator, Alex Grant,
took 580 Pacific Northwest shear wave velocity profiles that were collected
by Sean Ahdi and others for the NGA subduction project.
We did remove the profiles from the Fraser Delta, which were very deep
and didn’t capture the shallow velocity gradients that we were interested in
for the broader Pacific Northwest. So, using the Ahdi et al. data set,
Alex then solved for shear wave velocity as a function of depth
and Vs30 for all of the shallow profiles across the Pacific Northwest.
Some examples of this are shown in this figure.
So, for example, for Vs30s between 120 and 160 meters per second,
the Ahdi et al. profiles are shown in gray.
The median of those profiles are shown in black.
And our Pacific Northwest model, based on this equation, is shown in blue.
So you can see that our model, the blue line, is doing a good job
of tracking the median across a range of Vs30s.
An equivalent model that was developed by Shi and Asimaki
using data from central and southern California is shown in red.
And you can see that there’s a clear regional difference.
And this is what motivated us to do this analysis ourselves through the Pacific
Northwest instead of just borrowing from the existing work in California.
So, to estimate site response, we computed amplification factors
using equivalent linear analysis and PI SRA and running 30 examples
for every input PGA-Vs30 pair in our sample space.
So the resulting amplification or de-amplification for all combinations
is shown here. So, for example, you can see that, for a site with Vs30
around 400 meters per second, the ground motions are typically
amplified over the original M9 Project ground motions.
And sites with very low Vs30, so less than 200 meters per second,
often de-amplify due to nonlinear site behavior.
So, once we’ve extended the model region and applied the site corrections,
this is the resulting median ensemble ShakeMap based on our 30 M9
Cascadia earthquake scenarios. So, in general, we note shaking
intensity levels around MMI 8, so severe shaking for coastal areas,
including in northern coastal California. This decreases to MMI 6 or 7 –
so strong or very strong shaking around the inland I-5 corridor, and to MMI 4
or 5 in eastern California, and around MMI 4 in the Bay Area.
As I mentioned earlier, we also developed ensemble ShakeMaps
for the plus or minus 1 or 2 sigma shaking intensity levels.
So there’s quite a bit of variability, but just to focus on California,
at minus 1 sigma, we see MMI 6 or 7 in coastal northern California,
MMI 3 in the Bay Area. For the plus 1 sigma, we see MMI 8 or 9
around coastal northern California and MMI 4 or 5 in the Bay Area.
So how does our median ensemble ShakeMap compare to the previous
Cascadia ShakeMap that was based exclusively on empirical
ground motion models? So these maps show the difference
in MMI, PGA, and PGV. So red means our ensemble
ShakeMaps are higher than the previous GMM-based ShakeMap.
And blue means our ensemble ShakeMaps are lower.
And these plots show the GMMs that are used to develop the legacy Cascadia
ShakeMap in orange, the GMMs used in the 2018 National Seismic Hazard Maps
in blue, and the gray dots are data from our ensemble ShakeMap.
So, for the purpose of this talk, I’ll just speak about California.
So, in general, we see higher MMI, PGA, and PGV in northern coastal
California with our new ensemble ShakeMaps and slightly lower shaking
intensity as we move closer to the Bay Area, so further south.
These higher ground motions along the coast, which occur throughout
the margin, are due to two things. So one is the high-stress drop
sub-events in our rupture model that place the high-frequency ground
motions in distinct patches near the coastline.
So that contributes to this increase around the coast.
But also the coastal ground motions are also being influenced by our
consideration of multiple M9 Cascadia earthquake scenarios, 30% of which had
a down-dip rupture limit that is deeper than that used for the legacy ShakeMap.
And this was following the weighting of the national maps.
The lower shaking intensities as you move further south in California,
we think that’s because the GMMs are based on the closest distance
to the fault. So they might be underestimating ground motions
towards the middle of the fault where sites are likely to see incoming waves
from a larger portion of the rupture. Conversely, the GMMs might be
overestimating ground motions towards the end of the fault where sites are
impacted by a smaller portion of the rupture.
And our 3D simulations would have captured that.
So I think there’s still a lot of open questions related to this work and to
ground shaking in California from Cascadia subduction zone earthquakes.
So one open question is, how does 3D wave propagation in the Central Valley
impact ground shaking from Cascadia subduction zone earthquakes?
So recall that the 3D earthquake simulations didn’t extend south
of the Mendocino Triple Junction.
So any local 3D wave propagation effects in California were not included.
Another open question is, how do differences in near-surface
geology along the Cascadia margin impact site effects?
So here we used all the Pacific Northwest velocity profiles
in aggregate. But in some work we’re doing now, we’re instead
breaking those profiles up into geologic regions such as those profiles in the
Seattle Basin, in the Puget Lowland, those on hard rock, and you can
imagine that there might be along-strike differences in Vs profiles as well.
Another important question is, what is the range of ground shaking
from partial margin ruptures? So here I only talked about M9
Cascadia subduction zone earthquakes, but this is a question that we’re about
to start working on as part of a new NSF-funded project,
which I’ll talk about in a moment. And then also, as part of that project,
we’re going to be looking at, how does ground shaking, tsunami inundation,
and ground failure from Cascadia subduction zone earthquakes
interact in space and time? So, for my last slide, I just want to
briefly mention this newly funded project by the National Science
Foundation called the Cascadia Coastlines and Peoples Hub.
So the CoPe Hub is a five-year, $19 million project to improve coastal
resilience to hazards in the Pacific Northwest through targeted scientific
advances and modeling, which are co-produced in collaboration with
impacted coastal communities. And you can see all the range
of institutions that are involved in this project down here.
So a big part of this project includes modeling of tectonic geohazards,
both regionally and with a specific focus on a few specific
coastal communities that are shown in this map,
so including Humboldt County in northern California.
So some of the modeling that’s going to be coming out of this project
includes coupled Cascadia subduction zone earthquake-tsunami simulations.
These will be kinematic, but they will be using the same
earthquake sources for both the earthquake and
tsunami simulations, which we haven’t done previously.
We’re also going to be looking at a wider range of magnitudes based on
the logic trees that are in the National Seismic Hazard Maps.
And other researchers will be looking at multi-hazard impact,
so shaking and inundation on coastal infrastructure, as well as
tsunami debris forecasting and vulnerability assessments.
And so we look forward to sharing some of these results
with you as they come out over the next few years.
So that’s all I have. Thanks for your time.