Hello. I’m Dan Gittins, and today I’ll be talking about characterizing the
along-strike rupture lengths of creep events along the San Andreas Fault.
I would like to thank the organizers for inviting me to speak with you today.
I’ll also thank my collaborator Jessica Hawthorne for her help with this work.
So the San Andreas Fault has been observed to be creeping at the surface
between San Juan Bautista and Cholame since the 1960s.
This creeping section is bound by two 100-kilometer-long locked sections.
The one north of San Juan Bautista last ruptured in the
1906 magnitude 7.9 San Francisco earthquake
and also the 1989 magnitude 6.9 Loma Prieta earthquake.
And the locked section south of Cholame last ruptured
in the 1857 magnitude 7.9 Fort Tejon earthquake.
So this creeping section itself has some smaller magnitude approximately 6
earthquakes that occur near the edge of the creeping section,
typically around Parkfield. But there’s been no major magnitude 7
or above earthquakes reported along this creeping section.
So, since creep was observed at the beginning of the 1960s, this section of
the San Andreas Fault has been heavily instrumented with creepmeters,
strainmeters, GPS, alignment arrays, etc. Lots of instruments were installed.
And the installation of these instruments revealed that creep wasn’t occurring
at a steady rate, rather than, it was a steady rate that was
repeatedly punctuated by bursts of slip, known as creep events.
So these creep events typically have a few millimeters of slip.
They typically last a few hours to days and recur every few weeks to months.
So a fairly regular kind of burst that occurs.
So, despite these creep events being pretty abundant, we’ve known about
them since about the mid- to late 1960s, we don’t know how spatially large these
creep events are – like, how far they extend along strike, how far they extend
along depth, or the kind of fault zone process behind these creep events.
So these events are kind of important to understand because they may be
playing a key role in the physics of this creeping section as well as
other creeping faults and may also have a wider implication for
understanding fault physics in general. If your fault is creeping as well as
slipping seismically, then you need to understand both parts of that
system to be able to assess the hazard for that fault fully.
So today I’m going to be looking at how long creep events are.
So there’s kind of three categories of previous scenarios for how
big creep events are. There’s these short, shallow ruptures,
we are only located at one creepmeter. That’s the only place you’d record it.
Anywhere else is just kind of a coincidence.
Or you have these long and shallow ruptures that rupture multiple
creepmeters but are quite shallow – only a kilometer or so deep.
Or you have these kilometer-long, kilometer-deep big creep events
like in Scenario C. And each one of these scenarios
will have a different implication for the slip of the creeping region.
So, in order to understand how big creep events are, you kind of
need to know when they occur. So you can look at different records
manually – visually inspect them to try and pick out all these
creep events, but this is exceedingly time-consuming.
So what we did was we did a bit of visual inspection first to get a feel of
what these creep events were like, identified template events for each
creepmeter, and then, using a cross-correlation approach,
we identified these creep events within the creepmeter record.
So we tried to identify times that had a similarity to the template,
therefore we kind of get it was a creep event, and also had a significant
slip, so it wasn’t just something to do with the instrument themselves.
Doing this, we were able to identify 2,120 creep events across the
18 creepmeters that have a variety of different statistics,
which I’m kind of displaying here. So we have – for example, XSJ,
we have few events, under 100 events,
however, these are events which are larger and much longer, typically.
And then we also have, so like XMM, Middle Mountain, which has lots of
small short events, but it has over 500 events between 1985 and 2020.
But the thing that they kind of all have in common, despite whether there are
lots of small events or large fewer events is that they typically
accommodate over 50% of the slip at the surface for most creepmeters.
There are some exceptions of this, where the creepmeter might have
left-lateral slip, so it slips the other way, so it’s kind of hard to determine what
the maximum actual overall percentage of slip is accommodated in the events.
So now we have identified when these events occur.
We need to know how long they are.
So here is an example of a creep event at Cienega Winery in May.
And then we look for the next creepmeter, which is the Harris Ranch.
It’s 4 kilometers away. And if you search within 24 hours
either side of this start time for the creep event at Cienega Winery,
you see this creep event at Harris Ranch.
If you go further – 11 kilometers even further north of the creepmeter
at San Juan Bautista, you do not see a creep event here.
So this is kind of implying that, at this moment in time, we have
a creep event that might be 4 kilometers long, but it’s probably not 15.
This isn’t a very systematic way of doing it, if you just want to go through
and manually look at every single creep event, so we kind of took this
and then made a more statistical framework to base this on.
So we identified times that were coincident between one creepmeter
and every other creepmeter that had a creep event within 24 hours
either side of that event. This led to a possible detection
of 306 possible larger multi-creepmeter events.
So the reason we look at 24 hours either side of the main creepmeter is because
it provides a balance between robust statistics and slowly propagating
creep events. If we go for a time less than 24 hours, we will exclude
any creep event that might be slowly propagating.
But if we go longer than 24 hours, especially in the few years after the
2004 Parkfield earthquake, where the recurrence time of creep events
is reduced, we end up with double correlations, and therefore we don’t
know whether the creep event is going from one creepmeter to the other and
back again, or whether it’s only one of them is actually correlating, or
whether neither of them are correlating. So this is why we went for 24 hours.
So, to get a better understanding of the statistics behind this, we first off
take one creepmeter record and bootstrap it and then compare that time
to every other – those bootstrapped times to other creepmeters to work out
a distribution of creep events that were observed at both within 24 hours.
So you get this distribution, but then it could be the case that these might
just be occurring by chance. It’s a coincidence that they’re similarly timed.
So then we took the creepmeter record and time-shift it by multiples of years
with looping back around to the start to cover the beginning to look at whether
these just kind of happened by chance. This time-shifting over multiples
of years allows for the consideration of annual weather
and long-term effects of rainfall. So this is kind of
a by-chance or a coincidence distribution that we end up with here.
And then, to understand how much is actually occurring, we need to
take these by-chance events out of the observed distributions,
which we do by randomly sampling both the by-chance distribution and the
observed distribution and taking the by-chance away from the observed.
So this leaves us with a real distribution here, which can be seen in Panel C,
which gives you an idea of whether these group events are actually
a coincidence or whether there’s something relating them.
So, in this bottom Panel C, for example, we have creep events between
CWN and XSJ, and this distribution centers around zero.
So these events are likely to be unrelated.
However, if you look at the CWN-XHR ones, they hover around 25,
meaning these events are probably related to each other.
So then, doing this for all the creepmeters,
we end up with these five different behaviors for creep events.
So we end up with these isolated events. These creepmeters that only have creep
events at that one creepmeter, and you don’t see them anywhere else.
So, for example, we have XMR, or Melendy Ranch, which we only
see creep events there within 24 hours with itself.
However, it’s quite isolated from other creepmeters,
so if there was any creep events getting there, they might be
propagating slower than the allotted 24 hours that we allowed for.
The interesting pair here is that, in Carr Ranch and Gold Hill,
we have two creepmeters that are only 2 kilometers away from each other,
but they don’t have any interaction between each other.
One seems to slip and the other one stops, or vice versa –
one slips and the other one stops.
So then we also have this next group of events, which are these short events,
which are less than 2 kilometers long. These happen around Middle Mountain
and Melendy Ridge, as well as the two creepmeters around Highway 46.
So then we have these medium-size events, which happen around –
there’s a section of five creepmeters around Parkfield between
Middle Mountain and Taylor Ranch, which sit in two sections.
So we have a Middle Mountain- Middle Ridge-Varian section,
and then a Varian-Parkfield- Taylor Ranch section.
So this is two 5-kilometer-long stretches that both slip
independently from each other. And we also have this pair of
creepmeters in the north, Cienega Winery and Harris Ranch,
which slip at – about 4 kilometers away from each other,
and they often slip together.
So next we have the larger slip events. We have these events that look to
be over 10 kilometers long. So these are typically around,
again, this Parkfield section. So there’s – September 2000,
there’s a creep event that occurs – that joins those two sections around
Parkfield, that Middle Mountain to Taylor Ranch section.
And also there’s some evidence for longer relations between events
between Slacks Canyon and Work Ranch,
however I will explain more about these events later.
And finally, there is, around Parkfield, the San Andreas has two strands.
We have the main strand and we have the southwest trace.
And there appears to be evidence of creep events propagating on this
southwest trace between the two creepmeters on that strand as well as
evidence of interaction between creepmeters on the main San Andreas
Fault and creepmeters on that southwest trace, predominantly a relation between
the Hearst Southwest creepmeter and the Work Ranch creepmeter.
So the elephant in the room when talking about these creep events is because
we’re looking at creepmeters, and creepmeters are buried quite
shallow, is also that these events could be driven by rainfall.
So here we look at the short-term effects of rainfall.
So we’re only looking at up to about two weeks’ time scale for rainfall.
So we repeat the previous analysis that we’ve done already,
but we remove events from the main creepmeter that have rainfall
in the 3, 7, or 14 days beforehand. These typical time scales are
kind of arbitrary. They don’t really mean anything physically,
however they are longer than the typical time scale for association
with rainfall because we’re also allowing for varying time scales of
rainfall infiltration, as this is not a very well-constrained quantity.
But this does allow us to have a broad overview of the effects
of rainfall without having a proper, thorough investigation into it.
It just kind of gives us the idea of how this rainfall is affecting these
creep events. So we come up with these three kind of behaviors.
The creep events are either affected by rainfall, unaffected by rainfall,
or the percentages kind of increase when you remove rainfall.
So the main events that are affected by rainfall is these longer creep events
between Work Ranch and Slacks Canyon, which typically, when you
remove events that have rainfall, you remove the relation between the two.
So this would suggest that the closely timed events occurring at these
creepmeters is a coincidence driven by rainfall rather than
a longer creep event that’s connecting both regions.
The second one, which is the most common, is that, when you remove
rainfall, the change in percentages between the related two
creepmeters doesn’t really change. It just stays pretty constant,
doesn’t move. Which kind of implies that
the effects of rainfall here are minimal.
Finally, we have this kind of uncommon sort of behavior whereby,
the pair of Cienega Winery and Harris Ranch, when you remove the rainfall
at longer periods – at 7 or 14 days – we have this increase in relation
between the two creepmeters. So it could be that we are removing
these rainy intervals, which are already having shallow single creepmeter
events, and then what’s left is these deeper, longer creepmeters that –
creep events that span both creepmeters.
So, to summarize the study that we have done is that we’ve identified
and correlated 2,120 creep events along USGS creepmeters along the
creeping section of the San Andreas Fault between 1985 and 2020.
We’ve identified 306 potential multi-creepmeter events, which spans
various along-strike lengths. And the vast majority of these are
not correlated with rainfall. So this lack of correlation with
rainfall would imply that something else is driving these creep events,
and it’s not just a perturbation of a rainfall kick.
So finally, what we’re working on currently is we’re working on
currently to determine the depth of these creep events in order to
better understand the driving process of these events.
So this work is now available for you to read at your leisure if you’d like to,
but also we have made public the creep event catalog,
which some of you may also find useful. If you have any questions,
please feel free to contact me on the above email address or on Twitter.
And thank you again for this opportunity to speak to you today.