[silence]
All right. Welcome, everybody. We’re happy to see everyone here
for the seminar this week. Before we get started, just wanted
to remind you that the USGS public lecture series is starting up again
on March 25th – that’s tomorrow evening – at 7:00 p.m.
A Jaguar’s Field of Dreams is the title of that seminar.
The link is also provided in the chat.
All right. Let’s see if I can stop sharing the screen. [chuckles]
Okay.
So [audio cuts out] …
[silence]
- Looks like we may have lost Tamara. So, Susan, did we have any other
announcements that Tamara was going to go over?
- She was going to announce the talk on Monday the 30th.
- [laughs]
In any case, there are a variety of events coming up that you’ll have
received emails for, including, as she pointed out, the public lecture
tomorrow and a series of other talks from the Innovation Center.
I’ll hand it over now – or, next week, our seminar is Ian Stone, who was
delayed from last week when we watched the all-hands meeting
from the Department of the Interior.
So please stick around and join us for that in a week.
But, for now, I’ll hand it over to Jeanne Hardebeck, who will introduce
today’s speaker, Ruth Harris. - Hi, thanks. It’s my pleasure
to introduce Ruth, who many of you probably know.
A brief summary of her career. She was an undergrad at MIT.
She got a master’s degree at Cornell and earned her Ph.D.
at UC-Santa Barbara. She’s been at the USGS ever since
then, and for probably about 10 or 15 years now, has been the leader of the
Earthquake Process, Probability, and Occurrence Megaproject.
Ruth has won a number of awards, including the Department of Interior
Meritorious Service Award, and in 2019, she was elected
a fellow at AGU.
Some of the highlights of her research – she was an early pioneer in the field
of earthquake stress triggering, particularly in showing how large
earthquakes, like the 1906 and other large earthquakes like that can cause
stress shadows of areas where stress has been decreased and the number of
earthquakes decreases because those earthquakes have been delayed.
She also wrote a very influential early review paper on earthquake
stress interactions that’s still frequently cited in that field.
Much of her work has also been in dynamic rupture modeling, including
some pioneer studies on fault geometries, and particularly what fault
geometries will allow fault-to-fault jumping during earthquakes.
She’s been the leader for a number of years now of the SCEC Dynamic
Earthquake Rupture Code Validation Project, which is a large project that,
even though it’s under the – under the auspices of SCEC,
includes a lot of even international participants,
where everybody validates their code.
And all the hard work that Ruth has put into this really ensures the accuracy
of all the results that come out of dynamic rupture simulations.
Today she’s going to be talking about some dynamic rupture scenarios
for the Hayward, Rodgers Creek, and Calaveras Fault systems.
Take it away, Ruth.
- Thank you very much, Jeanne, for the kind introduction.
And now I seamlessly switch over to my slides, and we’ll see how this goes.
[silence]
And can you see my slides? - Looks great.
- Okay. And then I will try to get my pointer to work – the laser pointer.
And that – yes. All right. Whoo. First time.
So, welcome, everybody. And I want to give a big thank you
to Tamara Jeppson, who hopefully won’t be big-blued forever –
will be able to come back in – Austin Elliott, and Susan Garcia,
who are doing all the hard work of the seminar, organizing,
coordinating, and then helping all of us with Teams.
And thank you, again, to Jeanne for the kind introduction.
So today I’m going to talk about a project that I started in an almost
embarrassingly long time ago – I think almost 20 years ago now.
And, at that time, we didn’t know as much about these faults as we do now.
So I started on this project, and I think it was actually originally
suggested by Art McGarr. So I started on this project,
and I finished the project and wrote a paper,
and it went through internal review and did fine.
But then I hesitated before sending it to the journal because I really wanted
the model to be bigger and better. So, in the time of our doing the
first half of it, the Hayward and – the Hayward and Calaveras Faults
connected up to each other. And then we also learned a lot
more about the Hayward and the Rodgers Creek Faults.
So that made me realize that the model I was doing wasn’t quite sufficient.
So then I put the work aside for a few years and then started it up again.
And then here is the culmination of it.
So, of course, those two faults didn’t, in life – real life connect to each other,
but we learned so much more about them.
So I wanted to give many thanks to my JGR paper co-authors.
And this new paper just came out last week.
It was finally printed in its fully, glossy form.
Co-authors Michael Barall, Dave Lockner, Diane Moore,
Dave Ponce, Russ Grayer, and Carolyn Morrow all work at the USGS.
Gareth Funning from UC-Riverside. Christos Kyriakopoulos, who is
at University of Memphis. And then Donna Eberhart-Phillips, who
is at GNS Science New Zealand and also has an affiliation with UC-Davis.
Next – internal review. All right. A lot of people mutter and
mumble about USGS internal reviews, and that it slows down our work,
but it actually makes it so much better. So I want to acknowledge internal
reviewers for this manuscript, including really – got really helpful
comments from Evan Hirakawa and Jess Murray.
And then the previous iteration of this manuscript benefited a lot
from comments by Jim Lienkaemper and John Langbein.
So internal review works, and it helps us make our science even better and
helps us find subtle flaws that we then improve and make things look okay.
We received funding – or, I received funding from
the PG&E/USGS CRADA for this work, and then also for some related
work that I’m going to talk about – mention during this talk too.
And one of the great things about working at the USGS – one of the
many great things about working at the USGS is all the colleagues
that we have easy access to and can easily talk to about our work.
And then we also have, of course, our colleagues in academia.
So I want to just – this is a list of some of the many people who,
over the years, got to have me ask them questions and give –
and then they gave me thoughtful answers.
I want to most particularly point out Bob Simpson,
whose name is first on the list. He’s a – has been a long-time mentor
to so many of us at the USGS – a kind, wonderful, very smart,
and modest person who contributed a whole bunch to this work,
especially in the first – in the first year or so I was working on it.
All right. So here we are. San Francisco Bay area.
Pretty nice place. We’ve got the ocean.
We’ve got some mountains. We have the bay.
So that makes it kind of good. Sometimes we go on fire,
so that’s not so fun. But we also have a pretty high
probability of large earthquakes. This figure is from the Fact Sheet –
Aagaard et al. USGS Fact Sheet published in 2016.
And the results are based on work by Ned Field and colleagues that
were published in 2013 and 2014.
And that’s the California earthquake probability.
So this is just for the Bay Area – focusing on the Bay Area.
And here we have a 72% probability of one or more magnitude greater than
or equal to 6.7. And that number 6.7 is due to
a damaging earthquake in southern California – the Northridge earthquake
that occurred in ’94. So we know 6.7s and bigger are bad – bad for us.
And the 72% probability is for the 30-year period 2014 to 2043.
Now, we think a lot about the San Andreas Fault.
That’s really famous. Everyone knows about the
San Andreas Fault who knows about faults.
So we think about it as having a pretty high probability.
But we also have these other faults that even have higher probabilities
than the San Andreas. And these include the combined
Hayward and Rodgers Creek Faults with a 33% chance of one or more
magnitude greater than or equal to 6.7 earthquakes.
And then down here, we have the Calaveras Fault with a 26% probability –
Central Calaveras – that then moves over to the Northern Calaveras.
So we also have these other faults that have high chances of
having large earthquakes. We know that they’ve had them
in either historic or geologic times.
Rodgers Creek Fault had large earthquakes that is evidenced from the
geological studies by Suzanne Hecker, Dave Schwartz, and others have
worked a lot on the Rodgers Creek Faults.
The Hayward Fault – we know the best – the reason we have
the HayWired earthquake scenario is because we know that there was
a large earthquake in 1868 – about a magnitude 6.8 or so – on this fault.
We didn’t, of course, have a lot of seismic recordings of that,
but we do have some other information about its effects.
And the HayWired scenario has been worked on by – Ken Hudnut led that.
And then Anne Wein is also a collaborator on that –
one of the key leads on that. And they’ve looked at everything
from ground shaking to landslides, liquefaction, all the way to societal
effects, and that’s work that Anne Wein is particularly focused on.
Calaveras Fault – Calaveras Fault has also had large-ish earthquakes –
not quite as big, but the Northern Calaveras Fault, there’s geologic
evidence of maybe one or two events that Keith Kelson discovered.
And I think those are smaller than magnitude 6,
or maybe around magnitude 6.
And then, in our time, or some of our times, when we did have good
recordings of earthquakes, central Calaveras has produced events.
There was the Alum Rock event – I think that was in 2010.
But then, 1984 is the biggest one that we’ve had –
low magnitude 6, and that was well-recorded.
So these faults produce large earthquakes, but in addition to this,
they also creep. So we have to try to figure out,
what is the fact that they’re creeping all the time, or slowly slipping all the time,
what does that do to the large earthquakes?
Does it make them different or the same as our garden variety
larger earthquake on a locked fault,
such as the San Andreas Fault in this part of California?
So that’s – and that is part of the study, is to try to understand how the fact that
they are aseismic and slipping, what does that do to the ground motions
and extent of rupture that will be produced when we do
eventually have large earthquakes on these faults again.
Okay, and this is just showing two photos of the effects of
fault creep on the Hayward Fault. And these are – these two photos
are one of many in an Open-File report that was written by Phil Stoffer –
the late Phil Stoffer and published in a Open-File report in 2008.
The top is just showing what happens when you have fault creep –
creeping fault intersecting a school. That doesn’t go so well.
They had to close the school.
And then the bottom is kind of more just a fun thing to look at, but it’s
what happens when you have creeping fault go through a city park.
Your stone wall, which used to be pretty connected,
becomes disconnected. So sometimes you can have,
like, interesting and curiosity kind of features like this, but other times,
when you’re intersecting your infrastructure, then it doesn’t –
it doesn’t work so well with fault creep. So fault creep, overall, isn’t quite
as dangerous – isn’t as dangerous as large earthquakes.
But it still does cause some problems.
So creeping faults are rare, but, in the grand scheme of things, they’re
pretty abundant in northern California. And Diane Moore, Bob McLaughlin –
I think there are one or two other co-authors – have a paper in, I think,
Tectonics in 2018, where they go and explain why this is the case
for this part of the state – why we have so many creeping faults.
And these creeping faults include the Maacama Fault, Bartlett Springs Fault,
Rodgers Creek, which isn’t quite labeled here,
Greenville, Hayward, Calaveras.
And then, jumping down to central California, of course, we have the
famous San Andreas Fault creep, and that’s maybe even the one place
in the world where fault creep – on an active continental tectonic fault
where fault creep is almost, if not the whole, slip budget.
Then we have to head all the way down to southern California –
the southern part of southern California before we encounter
creeping faults again. And these are the Superstition Hills and Imperial Faults.
So this is a review article I wrote about large earthquakes,
creeping faults, published in 2017. Creeping faults also occur
in some places in the rest of the world.
They’re still quite rare. And this figure shows some of the
other locations where creeping faults have also been – also been noted.
Some faults do respond after an earthquake, and they will –
there will be, like, noticeable postseismic slip.
But, for here, the creeping faults that are being mentioned are
those where they’re slowly slipping all the time.
So it’s not just postseismic, but it’s always happening.
All right. So the question is, how are creeping-fault earthquakes
different or the same – different from or the same as locked-fault
earthquakes – your regular earthquakes?
So, for the – in the Reviews of Geophysics paper, did a comparison
looking at two things – looking at the rupture areas – fault surface
rupture areas and then also looking at the ground shaking effects.
So here’s looking at the fault surface at the rupture areas of earthquakes
that have occurred on creeping faults. So what I’ve done here is compared
the predicted rupture area based on empirical relation – an empirical
relation published in Tom Hanks’ and Bill Bakun’s BSSA 2008 paper.
So there – it’s a magnitude – a paper about magnitude-log area
for crustal earthquakes. So look at what the predicted rupture
area should be, and that’s based on primarily locked-fault earthquakes.
And then what the actual rupture area was.
Anywhere where it’s a red circle is a creeping-fault earthquake.
Any part of the plot where you see a blue – a blue square is a locked-fault
earthquake, so just mostly look to see where the red circles are.
And you’ll notice the red circles falling within the scatter of the blue squares.
So, at least in terms of rupture areas, it looks like the creeping-fault
earthquakes and the locked-fault earthquakes are behaving the same.
But the caveat is that the biggest creeping-fault earthquake here that we
looked at, that we had good data for – actually for the ground motion –
was a magnitude less than 6.7 earthquake.
So we don’t have information for magnitude greater than 6.7
creeping-fault earthquakes.
Okay. We did – also looked at the ground shaking and first published
this is a paper with Norm Abrahamson
and published this one in 2014 – a GRL paper.
And then I noticed there was a glitch on one point on the plot, so anyway,
showed it again in the 2017 Reviews of Geophysics paper.
So this is just a quick synopsis of looking at peak ground acceleration
versus earthquake magnitude for creeping-fault earthquakes
and locked-fault earthquakes. The main takeaway from this figure –
creeping-fault earthquakes are the red diamonds.
Locked-fault earthquakes are the blue and greens.
So the main thing to notice is that the red diamonds are falling within
the scatter of the blue diamonds for peak ground acceleration,
falling within the scatter of the green diamonds for peak ground velocity.
In other words, you can’t tell the difference in the peak ground shaking
between the creeping-fault earthquakes and the locked-fault earthquakes.
One again, this is just for magnitude less than 6.7 earthquakes.
Because that’s all the information that we had for creeping faults.
So, in the first figure that I showed you that had earthquake probabilities
for magnitude greater than or equal or 6.7 in the Bay Area – so the stuff
I just talked about was for magnitude less than 6.7.
But what about if you want to know about how creeping-fault
earthquakes behave if they’re magnitude 6.7 or larger?
So we don’t – we do not have empirical evidence for this.
We just know that they have occurred,
but we don’t know what they look like or anything.
So this takes us over to computational modeling.
So two tools that we could use to solve this problem of how creeping fault
earthquakes behave and what they look like are these kinematic
earthquake rupture simulations or dynamic, or spontaneous,
earthquake rupture simulations. I want to use the words “spontaneous”
meaning dynamic – dynamic, spontaneous.
So the main thing about them is that the earthquake is not pre-decided.
Instead, it happens through a physical interaction of all the processes.
So here is a schematic – so other people’s talks, including, I think,
the talk next week by Mendenhall postdoc Ian Stone,
will use the kinematic earthquake rupture simulation method.
You’ve also maybe heard talks by Artie Rodgers, who’s showed
simulations of Hayward Fault earthquakes – high-frequency,
really nice simulations looking at high-frequency ground motions
from Hayward earthquakes.
Next week’s talk, and also Artie Rodgers’ talks, these are all using
this kinematic earthquake rupture simulation tool.
For these, it’s already pre-decided what the earthquake source is going to be.
It’s already pre-decided how far along strike the earthquake will be,
how far along dip it’ll reach, how much slip there will be, how fast it will slip –
everything has already been predetermined.
And then they’re trying to see what the ground shaking will look like
based on that predetermined earthquake source.
So that’s other people’s talks. My talk is about spontaneous
or dynamic earthquake rupture simulation.
We are trying to figure out what the earthquakes are going to look like,
so we have that as an output of all the assumptions that we make.
So we have to assume the fault geometry, as these guys do – and gals,
the rock properties, as these people do.
But they do not have to assume the initial stresses are friction because
they’ve already – they already have pre-decided the earthquake source.
So we’re going to put all these pieces together.
And it’ll have interaction among them, but physically self-consistent results.
But beforehand, we don’t know what the result’s going to be.
Instead, it is an outcome of our simulations.
And also these models predict ground motions,
and our models also predict ground motions.
All right. So step number 1. Well, if you have all the stuff,
but you don’t have a code, you’re not going to go anywhere.
So how about, first of all, let’s go find a well-tested code.
This brings us to the SCEC-USGS Dynamic Rupture – Earthquake
Rupture Code Comparison Group, and this is a congenial group of people.
These are showing photos of everyone whose photos I could find,
and I think I’m still missing some people here.
But these are our collaborators over the years.
Some people have moved into other subjects.
A few people went over to induced seismicity.
Some people went into the oil industry. Some people went into the banking
industry or re-insurance. But many of these people are
still dynamic rupture modelers. And people often start as students.
Sometimes that’s their thesis project, where they have to write a code
or use someone else’s code. And then some people have made it
all the way up to be senior researchers, senior faculty, etc.
But it’s a evolving group. There are always new people
joining, and it’s very exciting. And the main point of our group
has been to check and make sure our codes are working okay
and then also to talk about dynamic rupture science.
So we’ve been around – I think we started in late 2003, early 2004.
We’ve now been around for about 17 years, and it’s just a really
good collaboration. And we’ve had people from –
by now, at least nine countries or 10 countries participating.
So these are the exercises that we did. These types of codes do not have
any analytic solutions with which to test them.
So really, I could just do anything and chose some pretty movie,
and you would have no idea if I did it right or just made up something.
You wouldn’t know unless you could also go and check – use the code –
your code or my code and go re-run all those – use all the same assumptions
and then see if we get the same results. So, when we’re doing this,
we wandered a little bit, maybe for a few months, and then we finally
settled on one benchmark where we could get it all together.
And that was a very simple model of a vertical strike-slip fault
in homogeneous fullspace. So we didn’t even have the
Earth’s surface. Then we tacked on the Earth’s surface.
So we went through all these different exercises, and for every one of them,
we had everyone use the same assumptions – so same fault geometry,
initial stresses, friction, rock properties. And then we’d see if we’d both get
the same – if we’d all get the same ground shaking at the Earth’s surface –
predicted the same ground shaking at the Earth’s surface, and actually
throughout the whole 3D model.
And then also if we would get the same rupture progress.
So we went through all these exercises, slowly making changes.
Because, as soon as you make a drastic change, guarantee it’s all going to fall
apart, and no one’s going to match. So we did it gradually.
We did the bimaterial problem. Some of these things we did because
they were – they were studies that individual scientists had done in our
group, and then we just wanted to see if our codes worked okay with them.
Others, we had kind of more funding motivations or other
reasons for doing them. So, in the middle part, we are stepping
slowly towards the bottom two cases, which was doing simulations
of extreme ground motion. And the reason we were doing these
is there had been a model that Joe Andrews, who was then a member
of our group before he retired, he had done some simulations
for extreme ground shaking at Yucca Mountain, the site of our
nation’s formerly proposed high-level nuclear waste repository.
So we wanted to check and make sure that his code and our codes were all
working the same and producing the same results. And that did work well.
And we also published a paper on that in 2011
in Seismological Research Letters.
Next, we wandered into the theme of friction.
So we looked at different forms of rate-state friction.
And then the bottom two we did also included thermal pressurization –
modeling thermal pressurization. And this last benchmark over here
is one that we just finished in October and was presented in October at
our most recent SCEC workshop.
Next, we also looked a bunch at fault geometry.
So the upper left example here was fault branches.
And fault branches are related to our specific Rodgers Creek-Hayward-
Calaveras-Northern Calaveras simulations because there, too,
we have a branch that’s a lot fancier than this branch.
But we did branches, and the reason that we did branches for the code
comparison exercise had to do with Jeanne Hardebeck discovering a branch
fault very close to Diablo Canyon Nuclear Power Plant in central
California. So suddenly, the owner of that power plant was very interested
in knowing whether or not a rupture could go from the main fault there
and go onto a fault branch, and thereby, get closer to the power plant.
That also was very helpful and led us to some extra funding, so that
was pretty nice. We looked at heterogeneous initial stresses.
These are often used in simulations and have been since the 1980s,
sometimes to represent other things, such as fault surface roughness.
We looked at the fault step-over problem.
That’s one of my favorites just because it’s the first one I ever did
for my own research – the first-ever multi-fault rupture study.
We looked at elastic and viscoplastic yield and what happens when the
off-fault material, or the off-fault rocks, don’t behave elastically.
This one was motivated by a study that two of our group members
had done for southern California, where they’re simulating large
San Andreas Fault ruptures and their effects on the L.A. Basin.
But the simulated ground shaking that they were getting was way too high.
It was much higher than seemed reasonable.
So they wanted to know if their code was implementing –
could implement viscoplasticity to try to tamp down those
ground motions, and that did, indeed, work.
Then we ventured over to rough faults. Rough faults are really popular.
People have thought about fault roughness for years, but it’s only
in more recent times that they’ve been able to put it into their codes.
So we did that. And then we looked at a range of velocity structures –
1D vertical, 1D horizontal, and then 3D – sort of like the
SCEC Community Velocity Model – the Harvard version of it.
Then we looked at one specific earthquake.
We modeled the 2004 magnitude 6 Parkfield earthquake and did synthetic
ground motions at each of the seismic – at the stations that actually recorded
ground shaking during the earthquake. Although didn’t do that great at
matching the data, but we did a really good job of matching
each other, so partly encouraging.
All right. So, so far, we’ve tested the codes for a variety of
generic ingredients. And these include mostly generic fault geometries,
generic rock properties – and, when I say rock properties,
I mean Vp, Vs, density. And then also elastic versus
viscoplastic or other forms of inelastic yielding.
A variety of initial stress conditions and a variety of friction formulations.
We wrote – our most recent – we had a group paper in 2009.
And then our most recent one that summarizes the whole group effort
was published in Seismological Research Letters in 2018.
And we have a group website that Michael Barall has put together.
And he’s also played a really important role in this whole group.
And it’s now called – the SCEC website has now
been renamed to – by SCEC – strike.scec.org/cvws.
And, if you have any questions about any of this stuff,
definitely feel encouraged to send me an email, and I’ll be happy
to communicate, or we could talk some other way too.
All right. So we started this because we were trying to find a code to use.
That was the goal a bunch of slides ago. So here is a list – this is Table 1 of
our SRL 2018 paper, and this shows a bunch of the different codes that
have participated in our code comparison exercises.
So we have – about 10 codes are still active.
Sometimes people would have a code – they came into the group – maybe it
was their code they used as a student, and maybe it was their adviser’s
code or someone else’s code. And then they might say,
oh, this is too hard to use. I want to go use someone else’s.
Maybe they had their own code, and then they made it a little bit better,
and then renamed it. But most of them, I guess, have been
staying maybe with the same name and sometimes with the same main authors.
A few of them are available online and have really good documentation.
Some of them are available on GitHub or the Computational
Infrastructure for Geophysics. And then I think one or two
are available on Bitbucket too.
Others are – you need to contact the authors, but all authors are very excited,
unless they’ve had already to move over to industry for their employment –
are very excited to have you use their code.
So definitely go see our paper. And if you have problems getting
access to it, just send me an email, and I’ll give you – give you a copy.
Okay. So now we need to choose the code for our own work.
And we used Michael Barall’s finite element code.
And he wrote about it in a GJI paper in 2009.
I know there’s also documentation about it on our SCEC website.
And it’s been used to run all the benchmark exercises that we’ve done.
And I really like to collaborate with Michael Barall,
so that is the code that we use for our work.
Okay, so we used FaultMod.
Step 1, we’ve chosen our code.
Step 2 – now we need to target this to our specific case
that we’re trying to model.
We need to figure out the correct ingredients for our Rodgers Creek-
Hayward-Calaveras-Northern Calaveras dynamic rupture simulations.
So we need to figure out our fault geometry, rock properties,
initial stresses, and friction behavior.
And so far, we’ve done Step 1, which is the code.
Now we got to figure out all the rest of it.
We got to figure out all these guys.
Okay. So let’s take us back to our setting.
This is a really nice figure that Luke Blair put together for me
for our JGR paper. I annotated it a little bit,
so anything that looks a little sketchy is because I annotated it.
But Luke gave me a great figure to start with.
All right. So we have our San Andreas Fault that we’re all familiar with.
Then we have our Rodgers Creek, Hayward, Calaveras,
and Northern Calaveras. These are – this is the fault model
that we’re going to use, and you’ll see a side view of it in the next slide.
Important features of it are – I should say, first of all,
the Rodgers Creek Fault actually does go a little farther north,
but for computational reasons, we had to truncate there.
Our model got too big for our memory – computer memory.
So we ended up truncating it near the city of Santa Rosa.
We had this thing here called Cf, and that’s the connector fault.
This is a fault that was discovered by Janet Watt, Dave Ponce,
and colleagues, and it was imaged using shallow geophysical studies
and imaged beneath San Pablo Bay. And this is a very important link in
our modeling between the Rodgers Creek Fault and the Hayward Fault
so that they’re actually a seamless fault structure.
Without this connector fault, earthquakes starting on the Rodgers
Creek Fault in our model are unable to jump across to the Hayward Fault,
and vice versa. So we include this – we include this connector fault because
we know at least it exists in the upper 100 meters or
few hundred meters of the Earth’s crust.
We have Point Pinole, which is point zero on our plots.
The Hayward Fault. And, right next to the Hayward Fault, of course,
goes through the city of Oakland. This is the right star.
Isn’t super far away from the city of San Francisco, the left star.
Traveling down the Hayward Fault, the Hayward Fault – when I first
started this work many years ago, we didn’t know yet that the Hayward
and Calaveras were connected. They’re not obviously connected
at their surface, but at depth, they are connected.
And that’s been seen by work by Bob Simpson, work by Dave Manaker
and Andy Michael, and work by Dave Ponce and [audio garbled],
so a bunch of people have seen this, that they actually connect.
Then we have the San Jose – city of a million people.
Calaveras Fault, and we truncate it at – just opposite the city of Gilroy.
It does go also a little farther and merge into the San Andreas Fault,
but for computational reasons, we needed to end there.
Then we have the Northern Calaveras Fault over here,
which is a branch off of the main fault surface.
So what we’re going to do is we’re going to be nucleating
earthquakes on the Rodgers Creek Fault, the Hayward Fault,
Calaveras Fault, and the Northern Calaveras Fault.
We’re going to start them there and then see what happens.
Okay, so here’s a side view of our fault geometry.
It’s a 3D fault geometry, and it’s set in a 3D mesh.
This is our schematic of our – not quite a schematic, but a coarse view
of our 3D finite element mesh. The top view, just showing
the fault surface itself. And it’s dark blue around it because
we’re using smaller elements closer to the fault, bigger elements
farther away from the faults. And then here’s a side view
going from southeast to north-35-west.
Central Calaveras, Hayward, connector faults imaged by
Janet Watt and colleagues.
And then the Rodgers Creek Fault, and then we have this kind of
fancy branch off the Northern Calaveras Fault there.
We’re going to nucleate earthquakes on each of these –
on the Rodgers Creek Fault here, Hayward there, Central Calaveras
there, and Northern Calaveras there. And, of these, three of them are
a little bit arbitrary locations for nucleation.
The Hayward Fault is the one that seems to have a physical basis for
starting there, and that’s based on work by Dave Ponce and colleagues,
who noted that the San Leandro Gabbro geologic unit that you’ll see
in the next slide – the next two slides appears to concentrate
the stress in that region. So they propose that this could be
a likely nucleation site for large Hayward Fault earthquakes.
Oops. Go back. All right. Now let’s go to our rock properties.
We’ve got our fault geometry. Now we have our rock properties.
So here are our rock units.
And they – this is a really nice model. I don’t think we have this in
too many other places, even in the world – the 3D geologic model.
And it starts with the Big Bay Model. So this is – and I should say these are
mapped – these are horizontal slices through the 3D model at
140 meters’ depth. And, at 7 kilometers’ depth,
we have a whole 3D model, but these are horizontal slices through it.
And the Big Bay Model is, I think, probably still in publication too –
even though it’s got a ton of work in it, is by Bob Jachens and co-authors.
So that’s the bigger view – bigger view. And then the smaller view, which is
in this little light gray rectangle that’s a little hard to see on this – on this figure,
is the finer-scale geologic unit structure published in – presented in
Russ Graymer’s paper – and co-authors paper in 2005 and Jeff Phelps and
co-authors papers in 2008. And I should also note that there’s
a lot of overlap among the authors. So this is a really impressive geological
study that has a nice 3D geologic model.
And we used this geologic model to then convert that information
into physical properties. So what are the P wave, S wave –
S wave velocities of the rocks, and then what are their densities?
Okay, so now let’s take a side view of this.
This is looking along the fault surfaces. Remember, before we had our central –
this is going from southeast to northwest, looking along strike.
And then this is depth. The vertical axis is depth in kilometers.
So we’re going Central Calaveras, Hayward, connector fault,
Rodgers Creek Fault, and now we’re blowing apart the two sides
of the fault – not literally blowing them up, but just separating them out.
So we have the east face of that fault surface, the west face of that
fault surface, and now we’re seeing which rock types – which rock units
touch each side of the fault. And we do the same thing for
the Northern Calaveras Fault. The east face of the Northern Calaveras
Fault surface and the west face of the Northern Calaveras Fault surface.
The main thing to notice here is that San Leandro Gabbro, which
I mentioned briefly a little bit ago, and that’s this orange rectangle here.
So it is a strong, dense rock that’s – the fact that it’s strong will come up
later when I talk about friction, but it’s also a dense rock –
has higher velocities – wave propagation velocities.
And then, right next to it, we have the serpentinite, and that’s
a weaker kind of slower rock. That’s on the east face.
And when you go to the west face, you also see the San Leandro Gabbro
again touching the west face of the fault, but it only goes down this far.
It only goes down a few kilometers on the west face.
It doesn’t extend as deep as it does on the other face.
So we’ll need to deal with that later on when we’re doing friction –
the fact that you have San Leandro Gabbro on one side at depth,
but something else on the other side at the same depth.
But, for right now, we’re looking at the velocities – especially the shear
wave velocities, and the densities. Okay, so we have our geologic model,
and we’re going to see this again just a little bit smaller.
Here, that same figure I just showed you – east face and west face of
the main fault surface – Central Calaveras, Hayward,
connector, Rodgers Creek, and then Northern Calaveras.
And now we’re going to turn that into a shear wave velocity.
So, for our 3D simulations, we need to know what the shear
wave velocities are throughout our whole big, giant structure.
We need to know what the densities are so we can do our wave propagation,
and the shear modulus tells us how much slip we’ll get.
We need all that stuff.
So we convert from the geologic model – 3D geologic model
to a 3D model of shear wave velocity and density.
And the way we do that is using the equations of Tom Brocher.
So he put together equations – I think it’s published in 2005 –
relating the rock units to Vs, Vp/Vs, and density.
All right. So we have our rock properties.
Now we need to know about friction. How does friction work?
So some people like to use very fancy friction when they do their simulations.
And this is a good idea of you’re doing, say, earthquake cycle models.
You do need to do that so you’re not only doing the earthquake itself,
but you’re also doing what happens during the postseismic time.
Then you need to do the interseismic time.
So that – you need to do that. You need to do fancier friction.
But we are just doing the earthquake itself.
We’re just doing the coseismic rupture. And, for that, as far as I understand
from talking to people who do the lab experiments, that that is fine to do that.
Slip-weakening is the same as rate-state friction if you have –
if the parameters are similar. And this – and Kenny Ryan and
David Oglesby showed this a while ago – maybe seven years ago
in a paper they published. And others have also shown this to be true.
So I’m going to use slip-weakening. And the thing I like about
slip-weakening is it doesn’t require as many parameters to be assumed.
So, for slip-weakening, behaves kind of like Coulomb.
It’s kind of like a Coulomb friction with some extra features.
So you start out – the strength of the two sides of the faults that –
what lets them slip past each other or not starts out as a static coefficient
of friction times your normal stress, which is time-dependent.
And then, as the fault gradually slips up to this critical slip-weakening distance,
the strength linearly decreases down to a dynamic coefficient of friction times
the time-dependent normal stress. So you don’t instantly drop as soon as –
as soon as the fault starts slipping. Instead, there’s a gradual drop.
And this actually uses up some energy in the process.
Slip-weakening critical distance has been inferred from inversions
of seismological source data to be anywhere from, like, 0.1 meters –
or I should – or even less than that, all the way up to 5 meters.
So, for our study, we used 30 centimeters – 0.3 meters –
as our slip-weakening critical distance. Some people do a fancier model, and
they might say, oh, it should vary over the fault with depth or along strike.
There’s very little, maybe no, direct evidence of how we should vary that
parameter. So, for ours, we just keep it constant at 0.3 meters.
Then we need to figure out our static and dynamic coefficients of friction.
So what we do is go back to our geology and our lab studies to look at
sliding coefficients of friction that have been measured in the lab.
So we look at the geology for this in lab experiments.
And then the static coefficient of friction has been related to dynamic
coefficient of friction as being about 20% bigger, and that’s work
by Teng‐Fong Wong that he published a wile ago.
All right. So let’s go back. For our geology, our main rocks that
are pretty different along our fault surfaces – we’re back looking at
our fault surfaces again – east face and west face.
So we noted that San Leandro Gabbro earlier.
It’s a strong rock – much stronger than everything else.
We have our San Leandro Gabbro. Right next to it, we have our
serpentinite, which is a much weaker rock.
And there were field samples collected on the Hayward Fault, and they were
studied carefully, and the results were published in a California Geological
Survey report by Carolyn Morrow and colleagues.
In addition, there’s been a bunch of work, of course, for the San Andreas
Fault at depth – San Andreas Fault Observatory at Depth.
They had a lot of lab work done on those samples from there.
And those are discussed a lot in many papers, including one by Diane Moore
and colleagues that’s published in Journal of Structural Geology in 2016.
So the San Leandro Gabbro from the Morrow et al. results has
a dynamic sliding coefficient of friction of about 0.8,
but due to the – that’s at the surface. But, as you go to depth, it makes sense
for it to be a little lower, so we choose a dynamic sliding coefficient
of friction of 0.65. Then work on serpentinite –
lab experiments on serpentinite show a dynamic sliding coefficient
of friction of 0.3 to be appropriate.
The rest of the rocks don’t behave that differently from each other
in lab experiments. So we assign most of the rest of
the rocks, many of which are Franciscan mélange,
a dynamic sliding coefficient of friction of 0.5.
All right. So now we are back to the situation where we have the
San Leandro Gabbro – that really strong rock on one side at depth,
but not on the other side. Also have the serpentinite on one side.
It doesn’t match up with the serpentinite on the other side.
So what do we do when we have two different strengths of rocks
on each side of the fault? So what we do is we end up using
the weaker value between the two. And this is work that Collettini et al.
published in 2009 that we should do that approach, and then also work by
Dave Lockner and Diane Moore and co-authors.
So this is what we end up for our final dynamic sliding coefficient
of friction along this fault surface for Central Calaveras, Hayward,
connector, and Rodgers Creek. Now, the Northern Calaveras,
it has lots of cool rocks abutting it, but they’re – we don’t have – at least,
from the views that we have, or the information that we have,
there’s no serpentinite or San Leandro Gabbro abutting it, so we just give it
a coefficient of friction – sliding coefficient of friction of 0.5.
All right. We’ve got our friction – our fault geometry, got our friction,
and now we’ve got to figure out our initial shear stresses.
So this is when we get kind of creative.
We don’t know what they actually are, but we can assume them.
And the technique I did is to say that, when you have a creeping fault,
it’s actually relieving some of the accumulating tectonic strain that
might be building up on a locked fault. So first we had to go and construct
a model for the creep rate on this – on these fault surfaces that we have here.
So Estelle Chaussard had already presented a creep rate figure –
or, picture for Central Calaveras and part of the Hayward Fault.
And then Gareth Funning, in his work, had a model for
the Hayward Fault, which he will hopefully publish really soon.
So we have the Hayward Fault, but we don’t have one big model
for the whole thing. So we merged those two.
And then, for the Rodgers Creek Fault, we used the wisdom of Gareth.
The Rodgers Creek Fault does creep farther north.
But it does not have much of a creep rate, if any creep rate,
as you go into the section that we are looking at.
So we put together this great big model. Northern Calaveras, we used –
Estelle Chaussard’s model does cover our entire Northern Calaveras Fault.
So we use her model, and that’s published in her
co-author paper in JGR 2015.
So now what we do is we look at where the creep rate is
1 millimeter per year or faster or 3 millimeters per year or faster.
So that’s the interseismic creep rate.
And anywhere where it’s either one or the other – and we look at them
individually, so then we have two different images of what the creeping
pattern looks like on the fault. So, say our 3 millimeters per year
slip rate, we use that or faster. Then, anywhere where it’s slipping
faster than that, we assign it a lower initial sheer stress.
Okay, so let’s go [inaudible] with that.
So we have our fault geometry, our rock properties, our initial –
our friction, and our initial stresses. We have our code.
And let’s go see some results.
Scenario large earthquakes.
Okay, so remind us again, we’re going to start scenarios
that start on the Rodgers Creek Fault, scenario earthquakes that start on the
Hayward Fault, scenarios that start on the Central Calaveras, and then
scenarios that start on the Northern Calaveras.
We start an earthquake. We don’t know if it’s going to go anywhere.
We don’t know how big it’s going to get. That’s the part of the
spontaneous rupture propagation. We find out what happens.
All right. So let’s start here. Pretend the right side
of the slide is not there. Just look at the left side.
So we’re going to do a locked scenario.
So, in this case, we pretend that the faults do not know
that they’re creeping. They just behave like regular
garden-variety faults. We’re going to do a nucleation
on the Rodgers Creek Fault, and then the contours that you see –
so, sorry, I should say, this is depth. This is distance along strike.
So we’re looking at the fault surface. We’re nucleating here on the
Rodgers Creek Fault, and then the contours that you see are the
progress of the rupture at half-second intervals as it’s propagating outward.
So it’s going out, out, out, out. See it all the way – and it gets all the
way to the southern end of the fault. All the way down the Central
Calaveras, all the way to the end, and then all the way to its northern end.
We do the same thing. We start a nucleation –
nucleate a rupture on the Hayward Fault.
Propagates, propagates, gets all the way to that end.
Propagates outwards. Gets all the way to the other end.
Calaveras nucleation – same thing. Sometimes they get slowed up a bit,
and that’s where you see these bunched-up contours,
but still makes it all the way. And the Calaveras nucleation
actually triggers a bit on the Northern Calaveras Fault.
Northern Calaveras nucleation propagates all over its whole fault,
and it always seems to do this in all our simulations.
This one actually manages to jump across, trigger Calaveras-Hayward and
then propagate the main surface too. Then, on the right side of the slide,
we see the final slip patterns for each of these situations.
And this is final slip and – contoured up to a little more than 6 meters.
So it’s hearty slip. A lot of slip.
And these are the locked fault cases.
All right. And then snapshots of the ground shaking at
15 seconds after nucleation, 30 seconds after nucleation –
this is the ground shaking at the Earth’s surface. So this is a map view.
And, for all these different things. And the main purpose of this figure
is just to show you that, yes, indeed, we are calculating
ground motion in these models.
All right. Now let’s go say that we do care about the fact that that faults
are creeping, that does make a difference to these earthquakes.
And now we’re going to look at where the creeping rate – the creep rate
was 3 millimeters per year or higher. So these parts.
And then assign those lower initial sheer stresses with the idea that
some of the accumulating tectonic strain has already been relieved
through the interseismic creep. Oops, sorry.
Okay, nope. Went too far. All right. So let’s look at creeping
patches – left side of the slide. Creeping patches are highlighted
by the shading here. So these have lower initial sheer stresses.
Rodgers Creek nucleation propagates to the north, propagates to the south,
slows down a bit, slows down a bit, slows down a bit, and then stops –
almost makes it all the way to the end of the Calaveras, but not quite.
Hayward nucleation – slows down but makes it through going to the south.
Gets slowed down and then stops early.
Northern Calaveras nucleation always goes. Has no problem
ever in our model. Makes it all the way through
and then jumps a little bit but then stops.
And then just samples of what the ground shaking looks like.
All right. Now let’s use the 1 millimeter per year contour to find where the
fault is creeping significantly and thereby has lower initial sheer stress.
So this is our biggest creeping section. So this whole part is,
with a few exceptions. And then Northern Calaveras,
it’s a bigger patch also.
So, for here – oh, and I should say, for the last one, the Central Calaveras
one nucleated but didn’t go anywhere.
Here, we have – for the 1 millimeter per year contour, so this whole
shaded area is all creeping. We have Rodgers Creek nucleation
propagates down, gets slower, and then stops.
So it makes it a little ways down the Hayward Fault and then stops.
Hayward nucleation starts, goes nowhere.
Central Calaveras nucleation starts, goes nowhere.
Northern Calaveras nucleation ruptures the entire Northern Calaveras Fault.
And snapshots of ground shaking.
All right. So, to summarize, we’ve used the spontaneous,
or dynamic, rupture method to simulate large earthquakes on the Rodgers
Creek, Hayward, Calaveras, and Northern Calaveras Fault system.
We produced large simulated earthquakes, some of which are
stopped by the creeping sections, and some of which aren’t stopped.
The most important factors were the nucleation site, the fault geometry,
and the pattern of fault creep.
And, in the future, we have a bunch more things that we want to do,
and included in this list is modeling a lengthier fault system.
I think we have more computer memory, so we could make the faults
a little bit longer, as they should be.
And then also looking at things such as the effects of inelastic yielding
and using different distributions of the initial stresses.
We have our new published paper.
And there’s just another advertisement for it.
Okay, so now we’re going to look at movies from a case that’s a little
variation on what you just saw. And, for this one, we’re going to
use the 3 millimeters per year with 3 kilometers of cohesion.
We’re going to look at a Hayward nucleation, so it’s this case here –
this second-line case. Hayward nucleation.
And the previous ones didn’t have cohesion at all, so we have our
creeping patch here, but then we also add a little factor of cohesion
in the upper parts of the fault surface of the faults, and that’s to make it
so that you don’t have quite as strong ground shaking.
And, in simulations, sometimes interactions with the free surface
causes a huge amount of ground shaking that probably doesn’t happen
in nature, and there’s probably damage and stuff that prevents that in reality.
So we do that – we accommodate that by including cohesion.
So let’s go look at a simulation.
And this is the one time the laser pointer does not work.
All right.
Huh.
I wonder if I could do that.
All right. Give me 10 seconds, and if this doesn’t work …
- Ruth, we’re seeing the laser pointer. - Yeah. But it doesn’t start the movie.
The laser pointer and the movie seem incompatible.
Oh, I was so close.
All right. Anyway, so there’s a fancy movie that you might
or might not be able to see – that you probably can’t see.
So there are movies also in the supplement of our paper.
And now I’m going to have to figure out how to do that in the future –
how to get out – I don’t want to escape the whole slide show
because that’ll mess it up.
- [inaudible] - My spouse is giving me a clue,
but it is not working. Okay, anyway, so there’s a cool movie.
And maybe I’ll be able to show it in the Q-and-A. Maybe I’ll figure it out.
But, in the meantime, I want to say thank you very much for listening,
and I welcome all questions.
- All right. Thanks, Ruth. I didn’t catch it all because I got
booted out a couple times. [laughs] But I’m sure it was great for
those who were able to hear it all.
And we’re going to open up to questions now.
We’ve had a few in the chat, so we’ll get started there.
And, of course, feel free to type your questions in the chat or raise your hand,
and we’ll help you turn on your videos and ask your question yourself.
So the first question was from Joan, and she asks, does your compilation
of creeping crustal faults include those that exhibit transient creep,
short-load aseismic slip events, and what is the fraction of these faults
for which their aseismic and slow-slip behavior is simply unknown due to
insufficient observations? So a couple questions there.
- Okay, so this is a question about the Reviews of Geophysics article –
the compilation? - Yeah.
- That I did there? So, for those, the creeping faults
that were included in that list were ones where we have modern geodetic
observations that the fault creep is occurring.
And I would say that the list in that paper – there was a big table
that I put together in that paper – 2017 paper is a subset.
So I went and did a literature search and looked for everywhere that I could
find things, but I didn’t include – so, yeah, subduction zones.
And then, lots of times, there were – there was evidence of postseismic slip,
but I only included cases where there was a good observation of interseismic
slip and generally not just at the Earth’s surface but a little bit deeper.
In that table, too, it also says what the depth extent was.
- Okay. And then a question from Brad about your models.
It says, what are you using for the initial normal tractions on the fault?
- Yeah, so the normal stress is constant.
I think it’s – going back – it’s 75 MPa, is that right? I have to look again.
But anyway, it’s a constant value. Yeah, I don’t – I don’t use
a depth-dependent value. We don’t use a depth-dependent value for
the normal stress, so we just – we just use a constant value for it.
And that’s something that – to look at in the future when we look to vary the
initial stress conditions a little bit more. So, for these dynamic rupture models –
well, Brad, of course, knows this, but in case other people that don’t
know, everything is time-dependent. So you’re starting with your initial
sheer and normal stresses, but then they vary with time as you have
all the interactions of all the effects, especially the propagating waves
and the stress waves. So, for this, we have constant
normal stress at depth because I didn’t know from observations –
it didn’t seem to indicate how we should vary it with depth.
But some people instead do – might do a depth-dependent normal stress.
And I know, Brad, that you have done this for your work.
- Okay. And then Brad also asked if you’ve compared your
ground motions to empirical ground motion models.
- So, I’m a little scared to do that right now. [laughs]
Our finite element mesh is 250 meters, so we don’t really have great resolution
for the ground – for the ground shaking.
It’s kind of more of a qualitative – a qualitative look at the ground motion –
at the ground motions. We have a really long –
I guess, maybe we’d be okay in our long periods.
Another thing we had to do is we had to truncate the shear wave velocities.
And I wrote down what we truncated it to – down to 1,950 meters per second.
So we not only have kind of big-ish elements, but we also had to
truncate the ground motions. So we’re kind of hesitant to
do that comparison, but I definitely did think about it.
It would be better to do if we had smaller element sizes and could
do more of the low velocities. But it’s a good – it’s a good –
definitely a good thought and something we should do.
- Okay. Thank you.
And a question from Janet. Might there be a greater degree of
cohesion need fault asperities – step-overs, bends, or intersections?
- So that’s a good question. So we could put the initial stresses
into – we could either put them into the normal stress or we
could put them into cohesion. So, yeah. Yeah, that’s a good idea
to just say that they’re – there fault’s more stuck where you have these
other – so we have the geometry pinning some parts of the fault.
And if you could put in – if we had model fault roughness,
that would also take into account – this into account, where we might
not need to put into cohesion, but instead, we might end up
in the normal stress. But that’s a really good idea.
- Okay, another question from Joan. What does the paleoseismic evidence
tell us about the persistence of creep on crustal – sorry, on crustal faults
over time scales of hundreds to thousands of years?
So that is a big topic, especially for the creeping section of the
San Andreas Fault. And we want to know.
And that’s the part of the fault that has – appears to have the fastest
creep rate relative to, say, deep slip rate of any fault, I think, in the world.
Although maybe there – maybe there were one or two others in that
compilation that were also inferred to be creeping really fast or to be
relieving everything aseismically. So, so far, paleoseismic studies by
Nate Toké and Ramon Arrowsmith and others have not been able to find
evidence of large events – really large events in the creeping sections.
I think this is still a topic of discussion and maybe work that Josie Nevitt
is doing now for Mee Ranch, maybe that will be able to help
find some more evidence. But that’s a big question.
Like, how long – when you have fault creep, how long does that
last over geologic time? I don’t think that we know that.
- Yeah, you’re right there. That’s still something
we are working on figuring out.
Okay.
From Jeff. As you go towards more complex models, how does –
how uncertain is the energy sink aspect of the creeping segment’s rheology
that you were trying to implement? - Yeah. So, right now, the energy
sink we – while we used a lower initial sheer stress –
that’s probably my fault we did that.
My co-authors went along with it, probably hesitantly.
So that’s, like, an energy sink – a lower initial sheer stress.
But there are probably other ways of doing it.
You could also model it with rate strength and friction,
but then you need to assume even more parameters.
We also have our slip-weakening critical distance, although that
applies for – that’s, like, an energy sink, although that applies for both
the creeping and the locked sections. So probably the transform fault setting
is the best way – the best place to look at – look at these sorts of things,
playing around with the models.
Because you have so many events and, you know, of course, Jeff, because
you’ve worked a lot on the oceanic transform faults, but trying to figure out
what limits – what limits the rupture extent in those settings
and then just playing around with the models for that.
- Okay. And another question from Ian.
In the plots showing slip contours for your various scenarios, it looks like
the slip consistently slows down shortly before initiating
before speeding up again. Is this an actual effect?
And, if so, do you have any idea what may cause it?
- Yeah, so sometimes that’s slowing down just due to the
change in fault geometry. Sometimes it’s slowing down
because they’re encountering other shear wave velocities of the rocks.
So we have our 3D geologic model, and each of those rocks have
different shear wave speeds. So there’s a whole combination of stuff.
We have the initial stresses. And they’re evolving with time.
The stresses are evolving with time, particularly the sheer stress,
but also the normal stress, because we don’t have a planar fault.
We have the fault – the rocks – the different shear wave velocities
for the rocks. And then we have our geometry.
So we have all these different things. So we did – we do have a figure
in our paper – Figure 12 of our paper, where we looked at the relative effects
of the fault friction and the velocity structure.
And we did 1D models and our usual 3D models to try to
see if we could pinpoint stuff. But it’s kind of hard because you
also have the effects of the free surface coming in there too.
But, yeah, so it’s a real effect that you really are slowing down
and then kicking up again and then starting up again.
But why it does that in some locations is easily understandable, but then,
in others, is a little more complicated just because you have the interactions
of all these different factors going on. So that’s a good question.
- Great. Thanks, everybody. A lot of gratitude for your talk and
compliments on a great talk, Ruth. We have reached the end of our time,
but we do invite everyone to stick around a little bit to continue
on the conversation a little bit more informally.
Feel free to turn on your videos and chat a little bit.
That would be great. And thanks, everyone, for coming.
We’ll see you next week for Ian’s talk.
- Thank you.