[Silence]
- So I’m going to get started? - Yeah.
- All right. Hello, everybody. Thanks for coming to seminar
Just a couple of announcements before getting started.
I guess we were asked to announce that tomorrow morning there’s going to be
an all-hands meeting with Mark Sogge. And also then let you know about our
semester for next week is going to be given by one of our new postdocs here,
Noha Farghal, discussing the work that she did at Stanford.
So I’m going to turn the mic over to Ruth Harris
to introduce today’s speaker.
- See if I can see with my reading glasses on.
I’m very happy that Hongfeng has come to visit us.
He flew from Hong Kong yesterday, and I’m very jealous because
he flew on Singapore Airlines. We always have to fly on those
American carriers, but he gets to fly in a comfortable carrier.
He received his bachelor’s and master’s from USTC – University of Science and
Technology in China, and then his Ph.D. from St. Louis University in 2010.
He then went to Woods Hole to be a postdoc from 2010 to 2012,
and then he was a research scientist at Georgia Tech from 2013 to ’14.
And since 2014, he’s been a professor at the Chinese University of Hong Kong.
He serves on the editorial boards of Earth and Planetary Physics and also
Seismological Research Letters. And he’s received some really cool
awards – the Editor’s Citation for Excellence in Refereeing from GRL,
and then also the Young Scientist Award from the Chinese Geophysical Society.
And this was in recognition of his contributions to integrating earthquake
rupture dynamics in observational seismology to advance
our understanding of earthquake physics in seismic hazard evaluation.
So I’m really happy to present to you Hongfeng.
- Should I turn it on? - Yep. Turn it on.
- Okay. And good morning.
It’s really my great pleasure to visit the USGS and present at seminar today.
Thanks for the introduction from Ruth. It was really nice.
So today, I’m going to share with you some recent research we are doing
on the earthquake magnitude estimation based on interseismic locking.
- [whispering]
- Here? All right. Okay.
So first, before I start – and then I want to thank my students and postdocs and
collaborators who all contribute to this study in different means.
And also, of course, I need to thank the sponsor as well.
And this map I’m showing – I’m showing you basically the purpose,
the focus, of this talk and also the main geographical region,
which is in Central – Central America subduction zone Nicoya Peninsula
and then where I’m going to derive, based on the – on the map is the
interseismic locking distribution and dynamic rupture scenario.
But the focus here is to test how this scenario is, you know,
reliable and then how can we validate such different
rupture scenarios based on the different locking distributions?
So I’m interested in this question, or this problem, partly because of the
question I was always being asked. You know, as a Chinese scientist, I was
asked often by my relatives or friends, can you predict the earthquake?
So initially, then, I would just answer, no, we can’t.
And just – as shown in this Perspective paper more than two decades ago,
published in Science, and that we think earthquake cannot be predicted.
And then some of – some of them, we respond rather, you know,
discouraging after hearing, oh, that we can’t.
And they would say, okay, you guys suck. [laughter]
And then some of them would even respond with a rebuttal.
Can’t earthquake be predicted?
With a coincidence being identical to this title
of the Technical Comments on that paper.
And I don’t think they have read these comments, however, they come up
with the rebuttal based on different lines of evidence,
like the animal and cloud patterns that we don’t believe.
However, this is basically – we, you know, sometimes got challenged.
And such a simple question seems to be, you know, tricky or difficult to answer.
And then later, I tried to respond with
my questions when I was asked again, can you predict the earthquake?
And then I would tell them, okay, there are three critical elements, which we
cannot do all of them simultaneously. However, if I ask you to
pick up your own priority, which one would you care the most?
Most of them will respond, okay, what about the city I live?
So they care about locations.
If I answer, okay, there might be earthquake in your city,
then they will immediately ask, you know, how big it will be.
So they care about the magnitude. If I answer, okay, your city is safe.
Only small earthquakes in magnitude 3, 4,
and then they don’t bother asking when.
So, of course, my – you know, limited sampling point,
and then very small group. But then that made me think,
okay, how should we put, you know, that critical question
up in the – in terms of location, magnitude, and time.
So, in my view, and then, I think our common understanding is that
we can do location with pretty good confidence as, you know, what we
can derive based on the historical large earthquake distributions with our –
all associated with major plate boundaries.
And then we can also come up with seismic hazard map,
which has been done as, you know, the leading expert
in USGS with the probability-based hazard map prediction.
So we have confidence in where we may face the serious seismic hazard threat.
However, if we just pick up one particular region, or a smaller scale –
for example, in the particular segments of the subduction zones
or in the inter-plate region, it is pretty difficult to say, okay,
how large the next earthquake will be.
So that will be something I want to discuss and to share what we want to
learn, or what we can learn, based on some physical-based models.
So my focus here will be on subduction zones.
Because subduction zones is where we may see frequent earthquakes.
And we all know subduction zones – then in certain subduction zones,
we may expect to observe the vertical uplift and the horizontal landward
motion, indicating that some portion on the megathrust is locked.
Although the locking degree can be calculated if we have
a very good measurement. For example, here I’m showing,
in South America subduction zone in Chile. And then all consistent landward
motion indicates that the megathrust is locked to different degrees.
And then, if we calculate and then – carefully, then we can derive such a
colorful map that’s commonly called a locking distribution or locking models.
And that have been used very effective to qualitatively assess potential –
earthquake potential in the particular segment.
And which have been proven true in a lot of places, or occasions,
when you see a recent megathrust rupture.
For example, in this map, we can see at least three recent major
megathrust earthquakes. In the north, 2014, Iquique, magnitude 8.2
And this part – smaller segment – is the 2015 Illapel, magnitude 8.3
And this large one is 2010 Maule earthquake.
So then we feel, okay, kind of a confidence in terms of inferring
the future earthquake potential based on locking maps.
Although we all understand earthquakes rupture propagation
are rather more complicated and not only depending on
the static imaging of a locking distribution.
However, if we look – take a closer look – for example,
if I just take the southern portion of this map, for example here, then we
see the locking, it seems – the dark color indicating strong locking seems to
be everywhere, nearly. And then why the rupture
cannot just rupture all of them once with a much larger event.
And so the central question is, if we just stare at a locking distribution,
can we infer the potential rupture segmentation
and thus the megathrust earthquake magnitude?
So, if so, then how?
And of course, after the occurrence of recent megathrust earthquakes,
then we can attribute all the rupture segmentations are caused by different
heterogeneities, either subducting, geometrical, heterogeneities,
or stress or material rheology, or different earthquake histories.
For the place like in southern Chile, then we know, you know, roughly well,
where historical rupture occurred. For example, in this case, that made
me think, okay, the central segment, seemingly locked, but then remain
unbroken, may be associated with the different rupture histories.
However, they post a challenge because we know some subduction zones are
locked, but then they don’t produce recent megathrust earthquakes.
Not even relative moderate size. That’s the case you guys probably
know very well, which is in Cascadia. Then here, Cascadia – we believe
Cascadia has been locked, but the locking degree has been a debate,
mostly because we are measuring – or, we are
inferring the offshore locking distribution using inland measurement.
But the question is, we don’t – you know, it is really challenging
for us to answer, if next Cascadia earthquake happens,
it’s going to be rupturing the entire Cascadia [inaudible], or it’s going to
be segmented, or to certain degrees. I think that question
is important and also the main focus of today.
However, I would not put all the examples, or most of the examples,
along Cascadia because, if we want to derive such,
you know, spontaneous rupture models, then we first need to validate
our models in some means. And this is why I chose the Nicoya.
And then, for Cascadia case, of course, I chose three typical locking models.
Another question on the locking model is that these models
may have the different uncertainties. And assuming a different locking degree
near trench, then we may come up with very different locking distribution,
even using the exactly same data set. Like, assuming the free variation
with the near-trench locking or the full locking near trench,
then we come up with very different locking distributions.
And the model also depending on the material rheology we are using.
If we use a viscoelastic upper mantle rheology, and then we may come up
with such a locking distribution which is
different than assuming pure elastic material.
So these all pose the questions, how we can better evaluate the future
earthquake potential in terms of rupture segmentation and from locking models.
I think the critical questions are, first, how we can infer rupture segmentations.
And then second question is that we have to validate
any models that we can derive. And based on these two critical
questions, I choose the geographical focus in Nicoya Peninsula.
And one of the reasons is that because of the peninsula is protruding to the trench,
so that we even use only the land measurement, we can construct
a relatively good locking models in the region.
And, on the map view shown here, in this color – the red color is
showing the locking model. And here is the coastline over here.
And then another important thing in Nicoya Peninsula is that
there is a megathrust earthquake being well-recorded
occurring in 2012 with a magnitude 7.6.
So here – although we may have the – kind of a unique geographical
environment for Nicoya, but different locking model exist.
And using the different data set. For example, on the right-hand side,
this model is mostly derived from trans-parallel GPS measurement.
And then later, they were – they update the locking model
using both trans-parallel and trench-normal GPS measurement
and plus some InSAR constraint. So then they slightly update this.
So we can see the difference between the two different locking models,
but the key feature is that they all constrain two major locked patches.
Which, if ruptured once, then will produce a magnitude 7.8 earthquake.
So the purpose here is to derive coseismic rupture models
from the locking model. For example, from the left,
which is the locking, then I can derive a spontaneous rupture simulation.
But the key is that I have to validate my model using kinematic model
in the Nicoya earthquake that occurred in 2012.
So that is the first step we need to do.
And how to derive the spontaneous rupture model, and then there are
some critical ingredients. So first, it’s the geometry.
And then some – we have to prescribe a friction law as well.
And the most important thing, we need to specify those parameters
in the friction law, and then we have to estimate the stress
on the megathrust from interseismic locking.
So I will spend some time to explain how we can set up
the different parameters. And here we use the linear
slip-weakening law, which is – I know it’s a very simplified version,
but then it’s commonly used in spontaneous rupture simulations.
And then, to some extent, it can present some
coseismic slip behavior in past earthquakes.
And here – the good thing for this linear slip-weakening law is that
there are only four parameters. So we need to get the estimate of
the initial stress. Then we need to also get the yield strength on the fault.
Then we need to have the critical slip distance, D slope of C, and then
we need to describe the dynamic stress during the rupture.
So here, I simplify the problem by looking at the rock-sliding
experiment with [inaudible] the seismic slip rate in
meters per second, then also, regardless of the different rock samples
and experimental conditions. And in the seismic rate,
nearly all samples are showing very low friction coefficient.
So that I make the assumption that we assume a constant dynamic stress.
Then the next question is, how can we get the initial stress?
And for the yield stress, we prescribe as a uniform yield strength on the
megathrust, assuming the near-lithostatic pore pressure.
And for the D slope of C,
then we can try the different distribution. Later, I will discuss
some additional constraint we may – we may have, based on observations.
And then I should say, all the calculation, including static calculation
and dynamic simulations, are all done using the software [inaudible].
So really thank the developer – one of the developers
sitting in the audience right over here.
So the key thing for us to think about first is how to convert the locking
into the estimation of the stress on the megathrust.
Here I use the strategy is to infer the potential slip deficit on the
megathrust from locking. So the slip deficit qualitatively can
be calculated by the locking and times the plate convergence rate in subduction
zones, and the plate convergence rates are mostly well-constrained.
And then the years since the last major rupture.
In Nicoya, the characteristic earthquake rupture history is rather simple.
And then some earthquake will be generated with magnitude 7.8
also in roughly 50 years. And with the most recent one, of course, in 2005.
And then the last most recent one was in 1950.
So that – I got the years since the last rupture, which is 62 years.
And then the key is that, by estimating slip deficit over here,
we implicitly made certain assumptions. For example, the slip deficit
accumulated since the last major rupture will not be released by other, you know,
thrust earthquakes on the megathrust. And then there was no other form of
slip deficit released by, for example, SSEs or any other means.
So, in Nicoya here – so first, these blue circles – and then they
indicate the locations of cumulative SSE distributions.
So they happen to be surrounding the locked patch, with the shallow one
overlapping with the locked patch. Over here – and then I want to remind
us that in both the offshore constraint on the SSE location and the locking are
not very well constrained, so that small overlap may not play a major role
in terms of releasing the slip deficit. Rather, if the SSEs really occur
in the surrounding regions, they may likely load the locked patch.
And second, what about the potential release by the interface earthquakes,
or smaller size? So, in this region, which I outline
with a yellow box over here, if we just look at the thrust earthquakes –
and I can – I took all the moment tensor solutions from GCMT catalog.
And then we found there were not so many thrust earthquakes
occurring on the interface. And then the magnitude are much
smaller comparing to the 7.6 magnitude. And over here, of course, now, after the
2012 earthquake, only got seven years. But then we don’t observe any
thrust earthquake larger than 5.5. So maybe in this Nicoya Peninsula,
this is sort of the characteristic earthquake cycle where you may –
you know, you may not have a lot of smaller-size thrust earthquake releasing
the slip deficit. So then here I will say, okay, that’s assumption.
With very little slip deficit released by other – by other forms may
hold true in the Nicoya Peninsula. So next part is that I assume the
entire slip deficit will be released by this single large rupture.
So here, then I just use that locking and then got the slip deficit.
If I assume the entire slip deficit will be released by one earthquake,
then I can basically calculate the static stress drop.
Then, if we recall that linear slip-weakening, then by knowing
the constant dynamic stress, and then using the static stress drop calculated
by the slip deficit, then we can estimate the initial stress distribution.
So this is how we got the initial stress, which is shown in this map.
So after we got the initial stress distribution, then we can nucleate
the rupture. For a spontaneous rupture simulation, we have to
artificially nucleate the rupture. Then I nucleate the rupture from
here because this is the hypocenter inferred by the kinematic model –
kinematic rupture model. Because I need to validate my dynamic
rupture model by the kinematic model, so I first force the rupture start
from here, which seems to be in a relatively low stress region.
So after we nucleate the rupture over here, because the stress
is heterogeneously distributed, so the stress will be dominant factor
for the rupture propagation. So the rupture started from
the hypocenter, and then first propagate up-dip and down-dip,
and then propagate along strike, and then eventually stops,
forming moment magnitude 7.6 earthquake in this scenario.
So at this point, at least the moment magnitude seems to
be consistent with observations. But then we also need to validate to
see whether our slip distribution will be consistent with the kinematic model.
And then, for earthquake, one important factor is the moment rate, which is a
[inaudible] function. So next thing is to compare, first the slip distribution.
On the left-hand side, I plot our dynamic model using the black color.
And the red showing one kinematic model, and blue is
showing another kinematic model. The blue one is mostly derived from
GPS, and the red is from a combination with GPS and seismic data.
So, by looking at the 1-meter slip contour and then this seems to
be spatially well-correlated. And, although the peak slip region
may not be identical, but then at least, you know,
the major slip patch are well-constrained.
In terms of moment rate, the red and blue are the two different moment rate
derived from different kinematic models, and the black is our dynamic
model, which falls in between the two different kinematic models.
So then I will say, okay, this dynamic rupture models, in terms of a final
slip distribution and moment rate, are both consistent with observations.
Then we will build up our confidence in our spontaneous rupture scenarios.
So here, then, we just basically demonstrate using the interseismic
locking distribution, we may be able to derive a rupture scenario.
And then, if we choose the – you know, careful parameters, then we may derive
some reliable rupture scenarios that are consistent with observations.
But one challenge is that, if we really want to do, you know,
the magnitude estimation, or future rupture scenarios, another thing is that
we don’t really know where the rupture may nucleate before the earthquake
occurred. And even after a megathrust earthquake occurred,
in subduction zones, it is typical, we always have the station from the land.
So we may not be able to constrain the epicenter very well.
And that’s the case for the Nicoya earthquake shown on the map on
the right and where we may see the different green stars over here.
And these are the different hypocenters suggested by different groups.
And of course, this yellow star, I think,
is a automatic network location – it’s a USGS location.
So over here, then, we have to consider this factor because,
in the heterogeneous stress distribution, different initiation point may
play different roles in terms of a final slip distribution
and even moment magnitude.
So I will firstly show you a few simple case.
Over here, the message is clear. If we start the rupture from different
nucleation point, then the rupture may end up in different moment
magnitude and slip distribution. For example, if I start with a rupture
from Point A, then that is the final slip distribution, and that moment
magnitude is 7.4. And if I start a rupture from this point, which is
bounded with nearly identical initial stress distribution, but the rupture will
only rupture one locked patch down-dip and forming a magnitude 7.2.
So, although the magnitude difference is only 0.2, but the moment is
actually different by – you know, doubled – twice.
And so you may think, okay, this is one up-dip or one down-dip.
And then now, if we try – really the two points just next to each other with
nearly identical – or, actually, just call it identical stress distribution.
But at the point from the blue star, then that rupture will only rupture
the up-dip locked patch, forming a magnitude 7.2.
And then the case next to it, starting from the red star,
then we’ll break the entire locked patch from magnitude 7.4. So, again,
the epicenter – different nucleation points really play critical roles over here.
So, if we conduct spontaneous rupture simulations at any potential point in the
locking map, and this is what we have done, and this is what we get.
So over here – and then I just tried different potential locations
in the locking. And then I prescribed the nucleation point, the size.
And then I observe the final moment magnitude.
So the color is showing here the final moment magnitude.
And with the black line showing here is the locking degree with
50% locking and the dashed line showing 75% of the locking.
So if we consider 75% is high locking, and then yes, in the Nicoya region,
most of the nucleation points in the high locking will run into
a magnitude 7.2 or 7.4 earthquake, which is – which is large in this region.
But, if we start the rupture from intermediate locking regions, then we
only observe with magnitude, you know, 5 or 6 – you know, that size earthquake.
And here is a very simple statistic to show the different percent
of the nucleation point running to different magnitude.
And, of course, this is – you know, based on how many points we have
tried. And over here is less than 40% of the rupturing
or nucleation point that will develop into a magnitude
earthquake that are – that will be larger than 7 in the Nicoya region.
So if we change this plot into another view, by evaluating the locking models,
and then I can plot the moment magnitude, which is showing in
the Y axis, versus the locking degree. So each point over here is indicating
the rupture starting from the point with the associated locking degree,
and then with the final moment magnitude marked over here.
So we tried a different nucleation size, but then, regardless of the nucleation
size, as we can see, most nucleation from relatively high locking
will run into large earthquakes. However, there are significant points
where the ruptures start from intermediate to moderate locking
degrees but then will end up being a relatively small earthquake.
And a interesting feature over here is that, based on the locking distribution,
then in our spontaneous rupture model predictions, we don’t see, you know,
magnitude 6 to 7 earthquakes over here. Either we will have larger than 7
or either we have a smaller – or, smaller than 6. So why there is a gap?
So, based on the – from the modeling point of view, we can understand it.
Because of the heterogeneous stress distribution, then the rupture will
be dominated by the heterogeneity – by the stress.
So that different locations, then you may have the different size.
But then why there is a gap? It seems – you know, the magnitude
seems not to be continuous. So first, we need to check whether
this is artificial from the locking model or it is somehow, to some extent, real,
representing something real in the Nicoya Peninsula.
So first, we test another locking model. And then the epicenter or
hypocenter-dependent moment magnitude feature seems to be true
regardless of the locking model. This is a earlier locking model.
Then also, based on this locking model, we also see that gap.
And then, of course, there will be a different locking model so that
the different initial stress distribution, but then we just don’t see that
magnitude 6 to 7 earthquakes in our model predictions.
And then we go back to see the observations.
And if we look in the other interface earthquakes again,
for the Nicoya Peninsula. And over here, here is showing,
in the yellow box, and where we extract all the moment tensor
from GCMT catalog, and indeed, I would call between – you know,
I draw these two lines kind of artificially.
I didn’t do – run any statistical means.
But then we don’t see many earthquakes having magnitude larger than 5.5
Before 2005, there were not many larger earthquakes anyway, but then there
are only two potential earthquakes, which this one has large uncertainties
in terms of locations. Even the fault within the locking region,
but still, there are only two earthquakes within that range.
So I think, over here, the locking models – although the
locking model may have a limited spatial resolution, but they somehow
probably reflect something, you know, to some extent,
the stress state occurring on the megathrust.
And so that – in our model predictions, we don’t see that particular magnitude
earthquakes which is also – seems to be true in the Nicoya Peninsula.
If we run the comparison by moving a little bit north, and then we see this
segment, regardless of the occurrence of the 2012 Nicoya earthquake,
and that earthquake’s magnitude seems to be more consistent with the different
magnitude distribution on the interface. So I think this is – in the Nicoya
Peninsula, that locking model, at least to some extent,
can reflect some earthquake potential.
And then, based on this hypocenter- dependent magnitude distribution,
although we may see, you know, some earthquake may end up being
the same magnitude with different nucleation points, but I think,
for the subduction zone environment,
another important thing is potential generation of a tsunami.
So here I will show you two cases. One case being the rupture –
the rupture nucleating from the shallow point with magnitude 7.4.
And then another case is the rupture nucleating
from the deeper portion with a magnitude 7.4 as well.
But the final slip distribution may be little bit different in details,
but the moment magnitude are pretty much the same.
However, the rupture directivity effect may play
critical roles in terms of a final ground displacement.
If we look at the ground displacement produced by the two different case
scenarios across the – as shown across this profile, the right one is showing
the rupture nucleating from the deeper portion which is this case.
And the blue one is showing this case. Actually, the peak – especially in the
shallow part, in the peak displacement on the ground, maybe twice, or even
larger, for a deeper-nucleating rupture than a shallower-nucleating rupture.
So I think, over here, if we incorporate, you know, our ground displacement
predicted by the different nucleating points, then we may incorporate with
tsunami models, providing potential constraints for the near-field tsunami
early warning if we can have, you know, very good locking
model constraint and then using the pre-computed cases.
And if we consider all the different nucleation points, and then for the –
all the deeper portion was – highlight – use the different red points over here.
And here I am showing you the slip distribution versus the depth
on the megathrust. And the red one are showing
all the ruptures nucleating from the deeper portion.
And then, at the shallow depths, they all tend to have a much larger slip,
which will, in turn, generate much larger ground displacement at the
shallower portion versus the rupture nucleating from the shallower depths.
So, over here then, I tried to demonstrate, we can, you know,
derive reliable rupture scenarios, and then we also found the
hypocenter-dependent rupture scenarios. Then you may question it,
so these are just models. And then I completely agree that
we got the quote, actually seen often at different occasions – all models
are wrong. But some are useful. So how would I convince myself and
then convince, hopefully, some of you to believe, oh, those models are useful.
I’m thinking, so for example, for the kinematic rupture models, we tend to
believe, because at least, you know, these models capture some features.
And then these models can produce synthetics being
consistent with the data. So can we produce, also from
our dynamic rupture model, and being consistent with the data?
So I think – I want to run a little bit quickly, and then, to be short –
to have a short statement, yes, we can, if we can have well-constrained
frictional properties on the seismogenic fault.
Which is not easy, of course. And I’m showing you here is the –
you know, the difficulty comes from, you know, different means. But one of
them is the strong tradeoff between the potential strength and critical slip
distance, even using a very simple friction law, like the linear slip
friction law. As demonstrated in this paper, if we observe the different
ground displacement, then even up to 1 hertz, we cannot really
distinguish whether it’s a high-strength smaller critical slip distance or a
much lower strength or a much larger critical slip distance.
If the two models are derived based on the same fracture energy.
And then that tradeoff is believed to be true, but then recently,
we come up with another approach, and then we found, yes, there are actually,
indeed, the strong tradeoff between the strength and the critical slip distance.
But based on only one single constrained parameter.
But if we look at the different constraints, for example, the final slip
or the rupture speed, or the ground velocity versus ground displacement,
and then the tradeoff trend are different. So for example, as shown here,
then we see the red line represents the theoretical – the best fit of the model.
But then this strong tradeoff between the strength and the slip-weakening
distance. And that is so as well, but the trend are different.
So if I combine two of them together, then hopefully I will see the intersection
between the two theoretically best fit curves so that I can come up with
a very good constraint with the strength and the critical slip distance.
So that approach was first derived based on the 2015 Nepal earthquake.
And here – I will ignore the details, but I would rather show you –
this is a kinematic model. And also showing that kinematic
model predictions with the static near-field ground displacement
and the ground velocity. And here is our best fit dynamic model,
also showing us the static displacement and then the ground velocity as well.
So that we can remove the tradeoff between the strength and the critical slip
distance – come up with a very good or robust ground velocity prediction.
For the Nicoya, we are conducting the same approach, but deriving the
best-constrained dynamic model. And here is all the model fits.
Black is the data observed in the 2005 earthquake.
And the purple ones are our dynamic model prediction.
In terms of direction and amplitude, I would call this a very good fit.
In terms of moment rate function. And the different observed ground
velocity as well – high-rate GPS record.
And then the black are data. The red are our models.
So we can derive some reliable, you know, ground velocity
prediction up to 1 hertz over here.
So now we have the location dependence, magnitude distribution.
We can also put further effort into the ground velocity prediction in Nicoya.
And then this slide, I wanted to show that such location-dependent
magnitude distribution, it’s not only limited to Nicoya.
And then this is a very preliminary model – actually,
but that was done very long ago. And the work was [inaudible].
But here is one of the locking model in Cascadia.
And then, if we just catch this segment in central Oregon, and then if I –
the rupture is starting from, you know, the northern part
in that segment and central and then south, and then we see very
different final slip distribution and moment magnitude as well.
So I was – I will – you know, basically, point out and then such feature is
probably true along every subduction zone given the different heterogeneous
distribution with the interseismic locking. But then I will highlight the, you know,
quantitative approach using, you know, spontaneous rupture models.
And here, for Cascadia again, and then, if we can derive the reliable rupture
scenarios as well as the ground velocities, and then
maybe we can think about, in terms of getting a hazard map
based on those physics-based rupture models.
And then I’m not sure how easy or reliable that will be for Cascadia
if we do not have any data to validate. But this is something actually I think
a lot of experts sitting in the audience who can help me out over here for
deriving the probability-based, but also physics-based, you know,
hazard map or potential ground velocities for other subduction zones
or seismic hazard potential in a seismogenic fault.
So in the end, I want to summarize that we can derive some rupture scenarios.
And in the case I demonstrating – the Nicoya case, we can derive a very good
or reliable rupture scenario that seems to be consistent with the observations.
And that potential earthquake magnitude actually dependent on
the locations of the initiation point, which underscore the necessity of
quantifying the interseismic lockings in terms of hazard distribution.
And in Nicoya, we also found a magnitude gap in both model
predictions and in the observations. So the locking models are, at least
to some extent, reflect potential stress distribution on the megathrust.
And then eventually, we hope to derive more, you know,
cases along different locking distributions for different subduction
zones and then to derive a physics-based hazard map.
Okay, I will stop there. And thank you very much.
[Applause]
- Thank you very much. That was a great talk.
Lots of – lots of things for us to think about.
Jess.
- Hi, thanks. That was a very interesting talk.
One of the assumptions you talked about that you made was that
the earthquake would release all the accumulated slip deficit.
And I’m wondering whether you’ve looked at models in which that isn’t
the case and what your thinking is on how important it is to consider the
possibility that any given earthquake is not releasing the full slip deficit.
- Right. This is a very good question. Here, we want to evaluate the
potentially extreme scenario, or the worst scenario, so that we assume
the entire slip deficit will be released by just one single earthquake.
If only a portion of that will be released, then of course, we may run into much
smaller magnitude earthquakes. And then, given, you know, that
locking distribution in Nicoya, then there will probably a magnitude
of 5 or 6. Yeah. But then we want to evaluate the worst scenario.
- Early in the talk, you suggested that these might be characteristic
earthquakes happening here, but how can you reconcile that
with such a strong sensitivity to nucleation point?
- Okay. Yeah. This is a question we have been thinking about for
a long time after we see that result. So, in Nicoya, based on observations,
and then we do see magnitude 7.7, 7.8, drop every 50 years.
But based on the locking distributions, and then after we checked the different
parameters, different input locking models, and then we think, if this is
somehow, you know, reflecting something real, then that may help us
to understand, for some earthquakes, or some sequences, that might occur
in close spatial locations. But some of them run into –
we call it the maybe smaller size or some foreshocks.
And then some of them are – you know, ending up being a large one,
then we call them main shock.
So, in the Nicoya case, I think it’s rather sensitive to the location –
where the earthquake may start. And then for these …
For these ones – actually, for those black ones, these are the earthquakes –
interface earthquake before the 2005 7.6 event.
So I think they just didn’t start in the right position.
And of course, based on the different time since the last major rupture,
even though they may start in that particular position,
they may not be magnitude 7.6. It should be smaller.
But then, the main reason over here is that likely they didn’t start
from the right position. That would be my interpretation.
- Following up on Justin’s question, it seems to me that it’s not necessary
that – I mean, the implication is that you assume that the previous earthquake
released all the stress. And so you can do a sort of a slip predictable model.
Whereas, if the previous one hadn’t released all the stress, then your
assumption that a slip predictable model only gives a 7.8 is a pretty
big assumption. And it wouldn’t be the worst case. So which is it?
Do you have to assume that every single earthquake is a maximum stress drop?
And this sort of gets at the point where you chose Nicoya for sort of specific
reasons in terms of the resolution, no slow slip earthquakes, and so
how well does this methodology work when you go to these sort of
more complex areas that tend to be sort of maybe more of our subduction
zones than what the Nicoya region has? - Right. This a very good question.
Yes. If we – based on this approach, certainly, we assume the last major
earthquake released most of the – or all the slip deficit
before that earthquake as well.
If, indeed, certain slip deficit was not completely released, then that will just
put into certain perturbations to our – for example, the slip deficit.
Then that will affect our initial stress distribution over here, to some extent.
So we may think, in this stress – you know, initial stress distribution,
then there will be some difference in quantities.
And then, that will, in turn, affect this distribution.
But then I don’t think it will play a critical role unless we perturb
this by a certain significant amount.
And then with such location-dependent feature.
So that is something I think, you know, how to consider an answer to these.
But, in terms of Nicoya, yes, I agree this is rather a unique
subduction environment. We choose here because we
want to validate the model. To – you know, we need to have
a large earthquake that can be used to validate the spontaneous rupture model,
and then we want to validate from a different perspective,
including that magnitude gap. And then, if we want to, you know,
apply this to other subduction zones, then we have to be more careful
in terms of getting this, you know, rupture history.
For example, in Chile, then we have to consider the different potential segment
released in different time, and then calculating the slip deficit
across the different segment. For Cascadia, then there is pretty much
no interface earthquakes, and then that is, I think, close to a Nicoya case.
And then, if we assume the slip deficit is building up and then released by
some degree, then we can probably use the similar approach.
[Silence]
- So, since you have this figure up, there’s a big locked patch, and I think
it’s the southern end, that doesn’t rupture in any of the scenarios.
What would you have to change about the mapping between the locking map
and the slip-weakening parameters to allow it to rupture through to that patch?
- Right. Here – if we want to rupture this patch, then, over here, then
we basically have to artificially increase either the stress –
initial stress or sort of decrease the fracture energy across that gap.
But here, this patch – we put it over here because
that is included in every locking model.
But in every locking model, this patch is not as well-constrained as this one.
Because this is really sitting on the peninsula, and this is rather
to the south offshore. So we didn’t really attempt to break,
you know, that central locking patch to the south.
But in models, yes, we can.
But we don’t know whether this is something real or not.
[Silence]
- Any more questions?
- Does anyone have any more questions?
All right. Well, that’s the end of our seminar for today.
We will taking Hongfeng to lunch here on campus if anyone wants to join us.
And let’s thank our speaker once again. - Okay. Thank you very much.
[Applause]