WEBVTT
Kind: captions
Language: en-US

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Hi. Today I’m going to share
some of my work on active faults

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in northeastern California.
Before I begin, I want to acknowledge

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that this talk is just part of
a larger project with collaborators

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at a number of different
science centers at the USGS

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who have helped to study this
region on different time scales.

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So let’s start by taking a step back and
thinking about the fault network and

00:00:25.280 --> 00:00:29.440
seismic hazard in northeast California.
In current seismic hazard models,

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like UCERF3 shown here on the left,
there are relatively few faults

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and few geologic studies on those
faults in northeast California.

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So, in this image on the left-hand side,
those red lines represent faults included

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in the UCERF3 model, and the green
dots represent those geologic study sites.

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So let’s zoom in a bit more on
northeastern California and

00:00:50.720 --> 00:00:53.520
take a look at the Quaternary
Fault and Fold Database.

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This image in the center now shows
the faults in the region colored

00:00:56.560 --> 00:01:00.800
by the recency of fault activity.
And already we can see a more dense

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fault network than what
was included in UCERF3.

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And then, just for completeness,
let’s take a quick look at the

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2014 National Seismic Hazard
Model source faults, which were

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drawn directly from UCERF3.
So they also represent simplification

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of the faults systems and do not include
many of the fault systems that are in the

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Quaternary Fault and Fold Databases.
So, from this, we can clearly see

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that the fault network in the region
is incompletely mapped and

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incompletely characterized
in seismic hazard assessments.

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One of the reasons the fault network is
incompletely mapped and understood

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in this region is because northeastern
California lies at the intersection

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of multiple tectonic domains.
In far northeastern California,

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we have the Walker Lane transtension,
marked by this green shaded area,

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and westernmost extent of
east-west-directed Basin and Range

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extension marked by
this pink shaded area.

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From the west, there’s an influence
of eastward-directed Cascadia

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convergence, marked
by this blue shaded area.

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And all of this is overprinted
by Cascade volcanism.

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So these competing tectonic and
volcanic influences on the landscape

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make it challenging to decipher the fault
patterns, kinematics, and general causes,

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tectonic or volcanic. So now let’s zoom
in a little bit more on this red box here.

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So this is the region of northeastern
California that we focused on.

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The map on the right-hand side
now shows the documented

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Quaternary and Holocene faults
in the region, again with those faults

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colored by the age of
most recent fault activity.

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So we can see there is generally
a north-south fault pattern representing

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that westernmost extent of Basin
and Range extension and

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several northwest-trending faults
that represent the northernmost

00:02:41.440 --> 00:02:43.736
transtensional
Walker Lane.

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In addition, the region has some
seismicity, noted by these numerous

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blue dots, although admittedly
seismicity in the eastern and

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northeastern-most part of the –
of the region is a little bit sparse.

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Again, we have those three major
volcanoes of the southern Cascades

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that complicate our understanding
of the tectonics in the region.

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So we have Medicine Lake,
Mount Shasta, and Lassen Peak,

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marked by these
yellow circles here.

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So now let’s focus on the area within
this red box, which shows a prominent

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disruption in the overall
north-south fault pattern.

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So now we’re looking at a slopeshade
map with the same Quaternary faults,

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again, shown on the slide colored
by most recent fault activity.

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In addition, seismicity and focal
mechanisms are shown that reveal

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both normal faulting and dextral
transtension in the region.

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So, again, we see this overall
north-south fault pattern.

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But, even at this scale, I want to
point out that we can see faults

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that are incompletely mapped.
They’re numerous north-south

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faults and west-northwest faults that are
including in Quaternary fault databases.

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So now let’s zoom in on this yellow
polygon here where we focused on

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mapping the faults in this region.
So, for the rest of the talk,

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I’ll share some of our approaches
and key results as we work to identify

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and characterize the
fault systems here.

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So, as I mentioned at the beginning
of the talk, we interrogated the

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landscape at multiple temporal scales,
which included bedrock mapping,

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which is shown in the right-hand side
of the slide and will serve as a base map

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as we talk through some of
our observations and interpretations

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of the region. The key takeaway
from this figure is that the pink colors

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represent Miocene-to-Quaternary
volcanics that are offset by these faults,

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with the darker pinks representing
older volcanic units and the lighter

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pinks representing the
youngest volcanic units.

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But, for this talk, I’m just going to
focus on our work on how we mapped

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the faults, and then will only use these
dated volcanic deposits to constrain

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the most recent age of faulting.
So we used two main approaches.

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We had neotectonic remote mapping,
which relied on four high-resolution

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Lidar data sets, and three
structure-from-motion outcrop

00:04:57.760 --> 00:05:01.760
models of key but inaccessible areas.
We then followed up the remote

00:05:01.760 --> 00:05:04.720
mapping with field verification
and mapping of some of the faults

00:05:04.720 --> 00:05:08.560
in the area. And so those Lidar
data sets are marked by these

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red polygons now, so it covers a
significant part of the study area.

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From the Lidar data sets, we mapped
and characterized more than

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700 lineaments, most of which
we interpret to be faults.

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We observed primarily vertical offsets
of deposits that ranged in age from

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Miocene to latest Pleistocene,
potentially even some younger

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geomorphic surfaces
as young as the Holocene.

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From this mapping, we defined what
we’re calling the Pondosa Fault Zone.

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So that’s roughly shown
here by this yellow box,

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which is defined as a set of
west-northwest-oriented faults

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that disrupts the general overall
north-south fault pattern.

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We used the SfM outcrop models to
help us better characterize some of these

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faults in the Pondosa Fault zone because
there were some pretty nice,

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steep outcrops that allowed us
to actually view the faults.

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So these models were created
from UAV and helicopter photos

00:06:04.080 --> 00:06:07.520
in these inaccessible areas.
So let’s take a quick look at this

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northernmost model marked here
by this yellow box and shown

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in this image on the right-hand side.
At a first glance, we can clearly see

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several lineaments running across this
orthophoto, and some are vegetation

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lineaments, whereas others are
just these kind of tonal lineaments.

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In addition, we also
see regions of different soil

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or bedrock color
and textures.

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So, from these images,
combined with our field mapping,

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we interpreted four stratigraphic
packages and at least four faults

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that offset these
stratigraphic packages.

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In addition, we correlated these
stratigraphic packages with units

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that we mapped throughout the study
area with our bedrock mapping.

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Importantly, at least one of these
faults that we were able to map

00:06:50.320 --> 00:06:54.000
in the structure-from-motion model
clearly correlates to a fault mapped

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on the Lidar data, which we’ll look
at in more detail on the next slide.

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So now we’re going to be
looking to the east-southeast

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from this viewpoint shown
here by this blue symbol.

00:07:06.400 --> 00:07:09.440
So now we’re looking east-southeast
at the outcrop model overlain

00:07:09.440 --> 00:07:12.880
on the Lidar topography.
We can clearly see this prominent

00:07:12.880 --> 00:07:16.160
east-west-trending ridge coming
toward us in the Lidar data.

00:07:16.160 --> 00:07:19.256
That was the lineament that
we mapped on the Lidar data.

00:07:19.280 --> 00:07:23.120
We can also see these different textures
and colors in the structure-from-motion

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model, which represent these
different stratigraphic units.

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So we can throw on our interpretation,
where we can clearly see at least four

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faults that offset the stratigraphy.
So now these different numbers here

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represent these different stratigraphic
packages, and the red lines

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represent these different faults.
So really just want to draw

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your attention to this Fault B,
with this fault zone that clearly aligns

00:07:44.720 --> 00:07:48.056
with the fault mapped
in the Lidar data.

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We can also see from this angle
that the stratigraphic packages

00:07:51.520 --> 00:07:55.600
that are offset by these faults appear
to have different thicknesses and

00:07:55.600 --> 00:07:59.520
orientations across the faults.
And so we interpret these changes in

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thickness and orientation to represent
oblique motion of these faults.

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We also field-verified and
mapped several dozen lineaments

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in the Pondosa Fault Zone.
So here’s an example of one of them

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from the central part of the fault zone
noted by this red box above here.

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In this area, the faults generally trend
west-northwest and offset this dark pink

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Miocene-Pliocene Bartle Gap
unit and the 1 million-year-old

00:08:28.560 --> 00:08:32.320
lighter pink basalt at Pole Creek,
in addition to some Quaternary alluvium

00:08:32.320 --> 00:08:35.016
and younger
geomorphic surfaces.

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So, in the field, we observed scarp
across Quaternary alluvium.

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So now we’re at this blue symbol
right here looking to the southwest

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at this scarp in the
Quaternary alluvium.

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So, if we draw in yellow lines to mark
the top and the base of the scarp,

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also marked by the feet of the people
in the photo, we can see that the vertical

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separation is on the order of 2 meters,
which matches with what we observe

00:09:01.040 --> 00:09:04.776
on the topographic profile
extracted from the Lidar data,

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shown here on the
lower right-hand side.

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Then, if we move even farther southeast
along this fault, we’re looking at another

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profile, again going from southwest
to northeast across the fault,

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this time across the basalt of Pole Creek.
We can see there’s 30 meters

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of vertical separation on that older unit.
So the increasing offset on older units

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suggest to us that perhaps the
fault has hosted multiple events.

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So just showing you a flavor of
some of the results that we’ve had,

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but let’s pull this all together.
So first let’s remind ourselves of

00:09:37.760 --> 00:09:40.960
what is already known in the
Quaternary Fault and Fold Databases

00:09:40.960 --> 00:09:44.000
in this area, shown here
on the right-hand side.

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So, again, we see we have this general
north-south fault pattern to the north

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and south on this image with a zone of
relatively few mapped faults in between,

00:09:55.280 --> 00:09:58.936
specifically between this P and
the Pit River to the south,

00:09:58.960 --> 00:10:02.216
which is where we have
that Pondosa Fault Zone.

00:10:02.240 --> 00:10:04.960
So now let’s overlay the
newly mapped fault network,

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and we see so many more faults.
Some of these faults we could see

00:10:08.800 --> 00:10:13.360
at the scale of the 10-meter DEM,
particularly in this region to the north of

00:10:13.360 --> 00:10:18.720
the Pondosa Fault Zone, but the Lidar
was really instrumental in identifying

00:10:18.720 --> 00:10:23.040
a lot of them in higher terrain.
We see that the zone of relatively few

00:10:23.040 --> 00:10:26.640
mapped faults between Pondosa,
this P here, and the Pit River,

00:10:26.640 --> 00:10:30.000
actually does have a lot of faults.
So, shown here on the right,

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we now have the faults colored
by the most recent fault activity,

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which, as a reminder, was determined
by the known or estimated ages of the

00:10:36.960 --> 00:10:41.982
deposits that they offset that we
derived from bedrock mapping.

00:10:44.720 --> 00:10:48.240
And then, because part of our interest in
this region was driven by the disruption

00:10:48.240 --> 00:10:52.400
in the north-south fault pattern, let’s
take a quick look at fault orientation.

00:10:52.400 --> 00:10:55.920
So this region between the north –
the north and south faults

00:10:55.920 --> 00:10:59.840
contains a lot of these west-northwest-,
east-southeast-trending faults,

00:10:59.840 --> 00:11:02.880
which is part of our definition
for the Pondosa Fault Zone.

00:11:02.880 --> 00:11:05.600
And, as shown by the structure-from-
motion models, these faults have

00:11:05.600 --> 00:11:10.216
evidence for lateral motion,
suggesting that they’re likely oblique.

00:11:10.240 --> 00:11:13.760
So now you might ask, well, okay,
that’s great, but what about slip rates?

00:11:13.760 --> 00:11:17.280
How fast are these faults moving?
So coming up with a slip rate can

00:11:17.280 --> 00:11:20.320
be pretty challenging here.
First, this is a highly distributed

00:11:20.320 --> 00:11:23.336
fault system with numerous
individual strands.

00:11:23.360 --> 00:11:27.040
Second, we were really only able
to measure vertical separations.

00:11:27.040 --> 00:11:30.000
We couldn’t identify good
piercing points for lateral offsets,

00:11:30.000 --> 00:11:33.816
so any slip rate may be an
underestimate of the total slip rate.

00:11:33.840 --> 00:11:38.800
Third, there’s uneven original volcanic
topography and perhaps more recent

00:11:38.800 --> 00:11:42.240
deposition in the hanging wall of some
of the faults, which obscures the total

00:11:42.240 --> 00:11:46.560
vertical separation that we can calculate.
And fourth, we don’t know any of

00:11:46.560 --> 00:11:51.200
the fault dips, so it’s hard to
calculate a true slip rate on the fault,

00:11:51.200 --> 00:11:53.976
and so we’re stuck with
vertical separations.

00:11:54.000 --> 00:11:57.680
But despite all these assumptions,
let’s take a look at a transect across

00:11:57.680 --> 00:12:01.496
the Pondosa Fault Zone just to
get a ballpark estimate of rates.

00:12:01.520 --> 00:12:05.256
So here we’re going from
southwest to northeast,

00:12:05.280 --> 00:12:11.096
across the Pondosa Fault Zone, so southwest
to northeast on the right-hand side here.

00:12:11.120 --> 00:12:15.440
Starting in the older Miocene-Pliocene
Bartle Gap unit on the left with this

00:12:15.440 --> 00:12:20.400
dark gray, going into these lighter
grays for the youngest Late Pleistocene

00:12:20.400 --> 00:12:25.176
to Holocene volcanic flows
like the Giant Crater flow.

00:12:25.200 --> 00:12:28.880
And what we see is that the apparent
vertical separation rates on individual

00:12:28.880 --> 00:12:34.216
fault strands and the net rates across
different units are generally very low.

00:12:34.240 --> 00:12:38.160
So, in the oldest unit shown here,
the Bartle Gap unit, we have

00:12:38.160 --> 00:12:42.160
vertical separation rates less than
0.1 millimeters per year based upon

00:12:42.160 --> 00:12:47.816
an estimated 280 meters
minimum vertical separation.

00:12:47.840 --> 00:12:51.920
And then, even on the 1 million-year-
old basalt at Pole Creek, the rates are

00:12:51.920 --> 00:12:55.176
still only on the order of
0.1 millimeters per year

00:12:55.200 --> 00:13:00.616
using an estimate of about
130 meters of net vertical separation.

00:13:00.640 --> 00:13:04.480
So we have a very distributed fault
system and a very low-rate fault system

00:13:04.480 --> 00:13:10.156
with rates generally on the order
of 0.1 millimeters per year or less.

00:13:11.120 --> 00:13:15.120
Okay, so now let’s revisit the seismic
hazard in northeastern California.

00:13:15.120 --> 00:13:18.320
We already know the fault network
is incompletely mapped in the region,

00:13:18.320 --> 00:13:22.480
but the growing high-resolution
topographic coverage will help us fill in

00:13:22.480 --> 00:13:26.080
some of these gaps, like we were able to
do with the Pondosa Fault Zone, to

00:13:26.080 --> 00:13:30.776
identify and characterize many more of
these distributed low-rate fault systems.

00:13:30.800 --> 00:13:33.680
And so, shown on the right-hand
side here, again we have that

00:13:33.680 --> 00:13:37.280
Quaternary Fault and Fold
Database shown with

00:13:37.280 --> 00:13:40.320
the Pondosa Fault Zone
now overlain on that.

00:13:40.320 --> 00:13:45.256
So we filled in one of those gaps with
a distributed low-rate fault system.

00:13:45.280 --> 00:13:48.000
But now this begs the question of,
how do we treat these zones

00:13:48.000 --> 00:13:51.416
of distributed low-rate faulting
in seismic hazard models?

00:13:51.440 --> 00:13:55.440
Some of the challenges this region
faces include incomplete mapping,

00:13:55.440 --> 00:13:59.440
which we’ve touched on a lot in this
talk, in addition to unknown slip rates

00:13:59.440 --> 00:14:03.680
or recurrence intervals on these faults.
And we also don’t really understand

00:14:03.680 --> 00:14:07.520
or know the fault connectivity.
So ideally, we’d be able to have

00:14:07.520 --> 00:14:11.440
a lot of this information to know
which fault strands may link up

00:14:11.440 --> 00:14:14.880
during certain ruptures or
better understand slip rates

00:14:14.880 --> 00:14:19.040
across these systems.
So, without some of that information,

00:14:19.040 --> 00:14:23.423
what is the best way to incorporate
these distributed systems?

00:14:24.480 --> 00:14:27.816
The answer is certainly not clear
and still an open question.

00:14:27.840 --> 00:14:31.120
One potential pathway may be some
sort of fault zone polygon that

00:14:31.120 --> 00:14:34.296
encompasses all known
or suspected fault traces.

00:14:34.320 --> 00:14:37.440
But how something like this
is incorporated into seismic hazard

00:14:37.440 --> 00:14:39.736
models remains
under development.

00:14:39.760 --> 00:14:42.960
Another option, one that has been
implemented so far in the

00:14:42.960 --> 00:14:46.880
2023 National Seismic Hazard
Model update, is a proxy fault,

00:14:46.880 --> 00:14:50.720
shown here by this black line,
for the Pondosa Fault Zone.

00:14:50.720 --> 00:14:54.640
So a proxy fault is designed for geodetic
modelers to collapse deformation

00:14:54.640 --> 00:14:58.456
where a single connected fault
trace is challenging to define.

00:14:58.480 --> 00:15:02.000
However, a proxy fault may not be
completely suitable for linking fault

00:15:02.000 --> 00:15:06.320
ruptures in the broader fault network,
nor may it be suitable depending on

00:15:06.320 --> 00:15:09.416
the scale of the seismic hazard
assessment being conducted.

00:15:09.440 --> 00:15:12.800
So it’s certainly still an open question
on how we want to incorporate

00:15:12.800 --> 00:15:16.936
these distributed fault systems
into seismic hazard models.

00:15:16.960 --> 00:15:20.856
So, to summarize, here are
the key points from this talk.

00:15:20.880 --> 00:15:24.800
Northeastern California has distributed,
sometimes poorly mapped,

00:15:24.800 --> 00:15:28.960
low-rate fault systems.
We were able to identify and

00:15:28.960 --> 00:15:33.416
characterize one of these fault systems,
the Pondosa Fault Zone, in our work.

00:15:33.440 --> 00:15:36.960
This system generally trends
west-northwest and disrupts an

00:15:36.960 --> 00:15:41.040
overall north-south fault pattern,
which I didn’t have time to touch on

00:15:41.040 --> 00:15:44.880
today, but in a broader tectonic
context, we think may represent

00:15:44.880 --> 00:15:48.960
a left step in overall east-west-directed
Basin and Range extension

00:15:48.960 --> 00:15:51.576
or be part of a
microplate boundary.

00:15:51.600 --> 00:15:54.160
And finally, as we
talked about the end,

00:15:54.160 --> 00:15:57.840
characterizing and modeling these
distributed low-rate fault systems

00:15:57.840 --> 00:16:00.936
remains a challenge in
seismic hazard assessments.

00:16:00.960 --> 00:16:04.240
And with that, thank you for your time,
and I’d like to acknowledge funding,

00:16:04.240 --> 00:16:10.360
assistance, and discussion with the
folks listed on the slide. Thank you.