Hello. I’m Gareth Funning, and I’m going to present my results
on the Maacama Fault from InSAR and repeating earthquakes
as a means of understanding creep on that structure.
So the questions I hope to answer today are a couple of things.
Firstly, what can InSAR tell us about surface creep?
InSAR is very good at measuring surface deformation, and so it can give
us a comprehensive picture of what’s going on in the shallowest crust.
And, number two, what can repeating earthquakes
tell us about creep at depth?
There are very useful supplementary information
that we can get from earthquakes that can tell us about the
creep behavior a little deeper beneath the surface.
Just as a – as a little reminder, InSAR is a method that makes use
of radar on satellites. The phase of the radar,
which we measure periodically as the satellite flies over,
is related to the distance between the satellite and the ground.
If the ground moves, we can detect a phase shift, which is related to the
distance that the ground has moved, and we measure that distance towards
or away from the satellite. So, in this particular case, the ground
has moved away, and there’s a positive phase shift in this case.
We can makes maps like this of velocity covering the entire regions –
the entire Bay Area and North Bay from an older data set.
And you can see all kinds of things in here.
Really, today, though, the only thing I really am interested
in showing you is creep. And if you zoom in on the Hayward
and Concord Faults, you can see these abrupt changes in surface
deformation and velocity localized on fault structures indicate that those
faults are moving at the surface. And, from the offset in the line-of-sight
direction, we can estimate what the fault-parallel creep rate is.
For this study, we’re going to use data from the Sentinel mission.
Sentinel is a – is a monitoring mission that’s planned for 20 years
of regular SAR acquisitions. In California, we get an acquisition
every 12 days as a result of this mission, which is way better
than any previous mission that we’ve had access to.
And we have formed lots and lots of interferograms.
Each green line on this chart, which spans the time – the timespan
of the study that I’m going to show you that was conducted by my graduate
student – my former graduate student Jerlyn Swiatlowski in collaboration
with David Bekaert at JPL. Each of these interferograms has
been combined into a time series, and we’ve solved for the best-fitting
velocity from all of this data. And it’s a fantastically rich data set.
And what does it look like? It looks like this.
So here we have two different data sets from two different geometries.
On the left, we have the so-called descending data set.
This is where the satellite is flying from north to south and looking to the west.
On the right is the ascending data set.
Satellite, in this case, is flying to the north and looking to the east.
There are all sorts of features in here that are of interest.
There are some obvious big blobs, which I should explain what they are.
This dark blue thing that you see in both data sets is the
Geysers geothermal field. That’s the – one of the most prominent
deformation signals I see in my data. It’s subsiding. That’s what blue colors
mean in this – in this data set, is moving away from the satellite.
And we can see, because it’s moving away from a satellite that’s pointing –
there are two different geometries that are pointing in different horizontal
directions, what they have in common is they’re both moving away
from the satellite. This means the ground is moving down.
But, ignoring that, there are features that are much more similar to
the Hayward Fault that you can pick out in the data.
So, for example, in the northwest, there’s a section of the Maacama Fault,
and you can see it here, where there is an abrupt transition
in velocity across the fault. In general, you have cooler colors
on the west side and warmer colors on the east side, either from green to –
or yellow to red, or blue to green.
This is consistent with creep.
There are a couple of other places where you might pick that out as well.
Another is around here.
This is Cloverdale – CL. It’s just southeast of there.
You can see there’s an abrupt transition in the velocity localized
on a fault structure there. And actually, you can see the
reverse sense of color offset in the ascending data,
which is consistent also with horizontal movement of that fault.
So there are some other things.
One feature that remains to be explained is the color offset
that you see here.
In some sense, having a warm color to a cooler color from west to east is
consistent with the viewing geometry and there being an amount of creep.
But it also suggests that there’s likely to be vertical motion
of the ground on the east – on the west side of this fault structure.
And we’re not sure that that would be tectonic.
That could – that could be aquifer-related.
That’s something we’re looking into.
Anyway, we analyzed these velocity offsets by taking profiles through
them and fitting lines to them. So this is a procedure that was
documented in an earlier paper where we explain how we
select windows of data on either side of the fault.
We blank out the data in the very near field of the fault zone.
And that’s because there’s usually some complexity there.
And we also simplify the fault trace somewhat.
So we don’t have an exact location of the – of the fault in our profiles.
Anyway, we take this window data, and we fit a single – a line with
a common gradient but different offsets on either side.
The offset is related to the line-of-sight velocity offset
of the fault at the surface. We actually use that gradient
to de-trend the profiles when we plot them, for neatness’ sake.
And what you should see, at least in the descending data,
is a flat profile on one side of the fault with a step in it.
That shows that we have estimated what that step is
and what that gradient is. So here is Jerlyn’s profiles.
We’re going to focus on a subset of them in and around Cloverdale
because these are the ones that showed the largest offsets.
In the descending, you can see, by and large, most of these profiles
show a step to the right – a step up to the right.
And you can see here a number of them do that.
And you can also see, actually, in the ascending data, which is
looking the other way, the horizontal sense of offset should be reversed
in that case, and you actually see steps down in the profiles on the right,
which is consistent with fault-parallel right-lateral motion.
We can convert these offset rates into line-of-sight – into fault-parallel rates
using the fault geometry and the acquisition geometry of the radar.
And what do we see? Well, plotted at the top here
are the creep rates – the fault-parallel surface offset rates.
Some portions of some of the fault systems – I’ve already talked about
the Rodgers Creek Fault, but that shows consistent but low creep rates
on the order of 1 to 2 millimeters a year.
Northern Maacama Fault around Ukiah and further north,
that shows rates in the range of 4 to 6 millimeters a year.
And the area southeast of Cloverdale, highlighted before, has slip –
creep rates of the order of 7 to 11 millimeters per year.
And one intriguing feature is that they – the highest creep rates –
the ones around 10 or a little bit higher – are very close in proximity
to the Geysers geothermal field, and it’s making me wonder,
and it’s something we’re looking into, whether there is a causal relationship
between the presence of the Geysers field and the high creep rates.
Just a little aside, then in the second part of the talk,
to talk about repeating earthquakes.
These are seismic evidence for creep.
A little – or, at least they’re taken to be so.
These are little asperities, we think, that have been dragged along
by aseismic slip and continually reloaded to failure. They periodically fail.
And they fail in the same places with the same mechanisms,
and they produce identical waveforms.
Here’s an example of a set of identical waveforms from
a repeating earthquake source. This is all part of Nader Shakibay
Senobari’s Ph.D. that he completed a couple of years ago at UCR.
And the process of identifying repeating earthquakes is the process
of taking earthquake waveforms and cross-correlating them and
finding out how similar they are. Repeating earthquakes that we –
that we show in our – in our publications generally
have cross-correlation coefficients of 0.95 or higher.
They are very, very similar.
This is a data-mining process. We look at lots of data.
There were 350 stations recording 75,000 earthquakes in the –
in the North Bay – the extended North Bay that we show here.
670,000 waveforms. We didn’t compare all of them
to all of them, but we did run a lot of cross-correlations.
And part of the issue is that the network density is heterogeneous.
There’s a lot of dense station coverage in the south.
There’s much less station coverage in the north.
Stations are up for different amounts of time.
And a strategy that is often used for sort of detecting repeating earthquakes
is just to look at a single station and look at all the events that are recorded on it.
And, when you have a network that’s so varied like this, it’s quite
difficult to do that. So we had to come up with something else.
Our strategy is actually to look at pair-wise comparisons of earthquakes.
For example, these three colored events here – the red number 1,
magenta number 2, and blue number 3 are,
we think, a repeating earthquake family.
But they were not all recorded on common stations.
A different sets of earthquakes recorded 1 and 2 as recorded 2 and 3.
But, since the cross-correlations in each case were very high, we were able to
assemble them into a single cluster – a single repeating earthquake family.
In fact, only – of all of the waveforms shown here – and you can see that the
red waveforms, the blue waveforms, and the – and the magenta waveforms
are all very similar to each other in pairs, there was only one station,
NMC, that recorded all three of these events.
But they’re very, very highly cross-correlated.
If you looked on a cross-correlation dendrogram, these three events
had a similarity of 0.95 or higher. And the next-nearest most similar
event has a cross-correlation of 0.65, which is much lower.
In the end, we found 59 repeating earthquake families.
These are actually confirmed by doing relative relocations.
We weren’t able to do that for all of our highly cross-correlated events
because of station azimuthal coverage. The ones that are very highly –
have very high cross-correlations but we were not able to confirm
are shown as triangles, and there’s quite a lot of those as well.
You’ll see that, along much of the Maacama Fault, there are repeating
earthquakes. For some of these, we’re able to estimate creep rates
based on comparisons to shallow InSAR offsets.
And you can see that creep rates are somewhere between 2 – which are
the green colors – and 5 millimeters a year on the Maacama Fault.
Looking at the fault surface, you can see that most of these
repeaters follow a streak in seismicity that starts off
deep in the north and shallows to the south.
It seems that that may be related to creep behavior because a lot of
repeaters are found within it. Looking in detail at some of the
features of the structures that we can identify from the repeaters around
Cloverdale – there are a couple of places where it looks like there
are dipping structures picked out in the repeaters.
We haven’t really dug deeply into what these might represent,
but it seems that there are parallel or sub-parallel dipping trends that
have some of these repeating sources on them, which might then,
therefore, be creeping. Something to look into.
Further north near Willits, where we – where there was the excitement in the
fall last year, we know that there’s surface creep evidence there,
and of course we see it in the InSAR. But also you can see dipping trends
in the repeaters in these places too. You can see, for example, in A2-B2,
this fault’s dipping steeply to the east, and then A3-B3, something similar.
Curiously, some of the repeaters seem to form some kind of vertical structure
which surfaces a few kilometers – 5 kilometers to the east of the
surface trace of the Maacama Fault.
Most intriguingly, there may be some kind of Quaternary fault scarp
5 kilometers to the east of the Maacama Fault near Willits.
I don’t have time to talk about that, but it’s an intriguing thought that
perhaps this has repeating earthquakes and might be creeping at depth.
I realize I’ve taken all of my time, so I’m just going to say you can pause
the video and read my conclusions. Thank you very much for listening.
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