WEBVTT
Kind: captions
Language:  en

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[rustling sounds]

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[background conversations]

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Hello.
Welcome.

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Welcome to the U.S. Geological
Survey in another installation –

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or another installment – excuse me –
of our monthly public lecture series.

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My name is Leslie Gordon, and it’s
always my pleasure to introduce –

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not always – mostly my pleasure to
introduce the speaker for this evening.

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So please welcome – but before
I do introduce the speaker,

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I would like to entice you
to come back next month.

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On April 26th, Curt Storlazzi,
who is one of our geologists

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in our Santa Cruz office –
an oceanographer, geologist –

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coastal and ocean – is going to
be speaking about the role of

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U.S. coral reefs in coastal –
or, coastal protection.

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How the presence of coral reefs
actually helps mitigate any

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hazards of flooding and
wave inundation – storm waves.

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So please do join us next
month to listen to Curt Storlazzi.

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I have to slow down.

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[laughter]

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Thank you.

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So tonight’s speaker
is Erich Peitzsch.

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Erich’s a physical scientist in our –
the USGS Northern Rocky Mountain

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Science Center in
West Glacier, Montana.

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So I hope you’re enjoying our
sunny California weather.

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[laughter]

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At least it’s not snowy.

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He’s been studying snow and
avalanches, and occasionally some ice,

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with the USGS since 2007.
Erich began his snow and avalanche

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career first as a professional ski patroller
alongside the great avalanche hunters

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just up the road at Alpine Meadows
at Lake Tahoe, California.

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Erich bounced around between research
and the operational world of avalanche

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forecasting in Montana for a few years.
He earned his master’s degree in

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2009 and is currently working
on his Ph.D., both in snow science

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at Montana State University
in Bozeman.

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When not working, you might find Erich
chasing his two young energetic sons

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around the mountains and
wondering where all his time goes.

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So Erich will be speaking about
snow and avalanche science,

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highlights of applied avalanche
research and forecasting.

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So please join me in
welcoming Erich Peitzsch.

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[Applause]

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- Thanks.

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[Applause]

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Thanks, Leslie.
And thanks, everyone, for being

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here tonight, taking time out of your
evening – this beautiful sunny evening.

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They told me when I moved from
California to Montana that the quality

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of the snow would make up
for the darkness. [laughter]

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I’m on the fence still.
[laughter]

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So again, thanks for being here.
And I also want to acknowledge

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my colleagues in the Northern
Rocky Mountain Science Center,

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particularly Dan Fagre, who is my
supervisor and leads our research group.

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And then everyone there in our research
group. And as well as my colleagues

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and co-authors on the work that
I’m going to present today – tonight.

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So let’s do a little overview first.
And what is a snow avalanche?

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Has anyone here ever actually
seen a snow avalanche before

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in real – in real life?
[inaudible comments]

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Sure. Pictures, videos.
All right. Well here’s another video.

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And you can see the plume right there.
This in southwest Colorado

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near Ophir, if you’re familiar.
And they – you can see the

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avalanche fracture across the slope.
And it sort of looks like it’s really

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slow-moving, but avalanches
can travel up to 100 miles an hour.

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So what we’re looking at here is
the powder cloud of this avalanche.

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And you can see it’s moving into that
forest off to our looker’s left side there.

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Likely taking out
a few trees, maybe.

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We don’t really know about this
avalanche, but we’re going to talk about

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how avalanches can have an effect
on the landscape in this talk tonight.

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And they delivered the –
or, they delivered explosives

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via helicopter on this one, so no one
is actually in the starting zone.

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And they do this because,
below this avalanche path is a

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county road and utility infrastructure.
So they’re trying to protect the

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county road as well as the
infrastructure at the bottom of this road.

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I’m going to talk a bit about some
transportation corridors where

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avalanches have an effect as well,
but in northwest Montana.

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So, again, let’s talk a little bit
about the fundamentals here.

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So we need four ingredients
for an avalanche to occur.

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We need a sufficiently steep slope.
We need a weak layer, a slab

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above that weak layer, and a trigger.
So in terms of slope, you know,

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you can see on the snow on
this building that, at the top of

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the building, it’s not steep enough.
It’s below 30 degrees.

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Below the building,
it’s too steep.

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You know, greater than 50 degrees.
But just in the middle is where

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avalanches like to occur – pretty much
between 30 and 45 degrees.

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When it’s too steep, avalanches
sort of just – the snow sloughs off.

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And so we don’t necessarily
form a slab when it’s too steep.

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If it’s not steep enough –
and we’ve seen avalanches

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below 30 degrees on some slopes,
but if it’s not steep enough,

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it’s just not enough for the slab
to actually move downhill.

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And so what happens is,
we form a weak layer.

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In this case, this is a layer called surface
hoar, and it forms on the surface.

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It’s sort of the
winter equivalent of dew.

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Via storm and transport of wind,
we have a slab on top,

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and our skier comes along
and is able to trigger an avalanche.

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And you can see that, when that skier
comes along and hits just the right spot,

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perhaps it’s a convexity,
or a rollover on the slope,

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where the stress is
actually concentrated.

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The added addition of that stress
from that skier is too much

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for that weak layer to hold.
So that weak layer collapses.

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That fracture on that weak layer then
moves, or propagates, across the slope.

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And so a trigger
can be a skier,

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snowmobiler, snowshoer,
or it can be more snow.

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So a weak layer can sustain
a slab to a certain point, perhaps.

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And the weak layer either strengthens,
or we get an additional load.

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So let’s say
it snows again.

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Or let’s say we get a bunch of wind,
and the wind moves that snow

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onto that slope and effectively
increases the stress on that weak layer.

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At some point, our weak layer,
if it doesn’t strengthen, may not

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be strong enough to hold up that slab,
and that’s when we get that collapse.

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So why do we study avalanches?
Aside from, it’s a good excuse to

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go out into the field and ski around?
We study because it is, indeed, a hazard.

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Every year, the – or, the average
number of fatalities in the

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United States each year is 27.
And, on an annual basis, that’s actually

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more than earthquakes and any
other land slope failure combined.

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Of course, earthquakes
are much more devastating,

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as many of you know living here.
But every year, about 27 fatalities.

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And it also has an effect on
transportation corridors.

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So northwest Montana, on the
southern edge of Glacier National Park,

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we have a canyon called
John F. Stevens Canyon,

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named after the railroader
who put the railway in.

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And you can see the
red arrow pointing to the railroad

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just below these avalanche paths.
So if my cursor works, and it does,

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we’ll – this is our avalanche path
right here – oops – right through

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the middle between these trees,
and it comes right down here.

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And you can see that they
actually built a snow shed

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a number of years ago to
help protect against avalanches.

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And we’ll talk about
why snow sheds can be effective,

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and sometimes
they can’t be.

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And you also see that the other arrow
is pointing to U.S. Highway 2.

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So it’s a major transportation corridor –
shipping a variety of products

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from the Midwest to
the coast and Seattle.

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And we also have, again, the major
highway running through it as well.

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And in the past, they’ve closed
the road due to avalanches

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and avalanche activity.
And the alternatives are hundreds

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of miles south or going into Canada
and going hundreds of miles north.

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And so you can imagine
that it has economic ramifications

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when they close
this section of road.

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Even though it’s a relatively small
section, there are pretty big impacts.

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So we also study avalanches because,
not only are they a hazard,

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but they’re also a driver of
ecological and landscape change.

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So this is a picture of bulldozers
and another machine moving avalanche

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debris – not only snow, but a bunch
of big trees that were basically

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destroyed and taken out by a
large-magnitude avalanche in 2009.

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This is in Glacier National Park
along the Going-to-the-Sun Road.

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So if anyone has been there,
likely you traveled it in the summer,

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and there wasn’t a
whole lot of snow.

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Certainly not avalanche debris in the
middle of the road – hopefully not.

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And so we’ll talk about
some of the impacts that

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avalanches have on
the landscape as well.

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So first we’re going to dive
into avalanche forecasting.

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So we’re with the USGS Northern
Rocky Mountain Science Center,

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and we’re in a field station in West
Glacier, Montana, in northwest Montana.

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We partner with the National Park
Service in Glacier National Park.

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And we have an avalanche forecasting
program for the spring opening of the

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Going-to-the-Sun Road in the spring.
So it’s almost time – around April –

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the first week in April, April 1st,
where they start getting ready and

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they start moving snow off the road.
And it’s – as I go to here –

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it’s an 80-kilometer road, and
56 kilometers is closed every winter.

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So the forecasting program,
we use a variety of weather stations –

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automated weather stations.
We actually go into the field,

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we dig pits in the snow to look at
the snow structure, and we help

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forecast avalanches for the
road crew and other park personnel

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to safely get
the road open.

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So 11 kilometers of the road is
actually impacted by avalanches.

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And there are 37 total avalanche paths,
as you can see on the map here.

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Those green polygons indicate –
or, represent avalanche paths

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that cross the road.
So on the image on the right,

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you can actually see the road
as it crosses through right here.

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It crosses through the middle of
some of these avalanche paths.

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So in this case, the road isn’t
necessarily just at the bottom.

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So we’re not just forecasting for
big avalanches that have, you know,

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a probability of reaching the road.
We’re actually forecasting for

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avalanche – even small avalanches
that might cross the road when the

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road crosses through in the upper
part of the avalanche path.

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So, again, it’s a vital artery of
visitation, particularly in the summer.

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And that also, in and of itself,
has economic ramifications when it’s

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not open for the local surrounding
community, but region-wide as well.

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So the avalanche path starting zone
is along the Going-to-the-Sun Road.

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The starting zones are where
the avalanche starts, right?

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And that’s about 500 to 3,000
feet above the road level.

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So you can imagine that,
3,000 feet above the road,

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often conditions can
be very different.

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So it may feel like spring down
on the road at, say, 4,500 feet.

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But at 7,500 feet, or 8,000, above the –
well above the road right up here in

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this zone can be very different,
particularly the snowpack itself.

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So, while down here, it might
resemble more of a spring snowpack,

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up here it can still be a wintery
snowpack with quite a lot of variability.

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So a little historical look at
some of the avalanches

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along the Going-to-the-Sun Road.
In 1953, two machine operators

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were actually killed. Three were 
caught, and two were killed,

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in a wet snow avalanche that released
in an area called Alps 1 avalanche path.

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And you can see the debris here and
folks actually trying to dig through.

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And that was a pretty
destructive avalanche, of course.

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In 1964, a bulldozer was knocked off
the road in an area called the Big Drift.

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And this is pretty much right at the –
at Logan Pass, which is

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right on the continental divide.
So this is actually just on the east side.

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But you can see over here,
this is the crown of the avalanche

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where we’re looking at about 12 to
15 feet of snow that had released.

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So, as this bulldozer was moving
through, it actually triggered the

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avalanche itself and then
was knocked off the road.

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And the most recent was in 2005,
which was a close call.

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Fortunately, no one was injured, but a
similar situation where the bulldozer was

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moving snow, pushing snow off
the road, triggered an avalanche.

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It broke right next to,
or right at the bulldozer,

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and the bulldozer
went over the road.

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Fortunately it was a
very skilled operator.

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He was able to put the blade down,
and it didn’t roll the machine or

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didn’t go that far, and they were able
to pull it back up in a couple days.

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So, as I mentioned earlier, we have
the partnership with the Park Service.

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And we, as USGS researchers,
we try to figure out, how can we

00:13:08.760 --> 00:13:11.980
make forecasting better so
that we’re keeping people safe?

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And the biggest problem that the
road crew faces and that

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people traveling along the road
in the spring face is wet snow.

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Right? We’re moving into the spring,
so we’re not dealing so much

00:13:21.649 --> 00:13:24.690
with dry snow avalanches,
though we do when it does storm.

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We’re really focused on the
wet snow avalanche research.

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So let’s talk a little bit about
what wet snow actually is.

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And there’s three main types
of wet snow avalanches.

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We have wet, loose avalanches,
wet slab, and glide avalanches.

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So wet, loose avalanche –
as you can see from the image here,

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these avalanches involve
really just the surface snow.

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So anywhere from the top few
inches to maybe a foot at most.

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But what happens is, they start
at a point, and then they tend to fan out,

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as you can see, like in
an upside-down V pattern.

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And, in this case, sun is shining
on these – this is a southerly –

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or southwest-facing aspect,
so we have a lot of sun hitting this slope.

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It’s warming up the rocks.
And you can see that all of

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these avalanches in this
image started near these rocks.

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So we have a lot of short-wave
radiation being absorbed by the rocks,

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heating up the snow adjacent to it,
and that’s where we’re going to

00:14:16.160 --> 00:14:19.459
get these wet, loose avalanches.
So what happens is, as the sun and

00:14:19.459 --> 00:14:23.009
warm temperatures heat up the snow
on the surface, it reduces the strength,

00:14:23.009 --> 00:14:26.009
or reduces the bonds,
in between each little snow grain.

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And then it reduces its strength,
and it releases and goes downhill.

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Because that’s what
snow ultimately wants to do.

00:14:35.120 --> 00:14:37.899
And before I go to this one,
the wet, loose avalanche – you know,

00:14:37.899 --> 00:14:40.519
they’re relatively predictable.
We can say that it’s going to be

00:14:40.519 --> 00:14:44.639
warm and sunny, and we’re probably
going to see wet, loose avalanches.

00:14:44.640 --> 00:14:49.460
But slab avalanche, like in this image,
is definitely harder to predict.

00:14:49.460 --> 00:14:53.149
And this is a really large avalanche.
As you can see, it’s sort of – this is the

00:14:53.149 --> 00:14:58.639
crown right over here, starts up here and
comes all the way down and around.

00:14:58.639 --> 00:15:02.460
And what happens here is,
as I mentioned before in a

00:15:02.460 --> 00:15:05.309
dry slab avalanche, we have
avalanches occurring because the

00:15:05.309 --> 00:15:09.460
weak layer can’t hold the slab above.
Well, that’s the same in a wet slab

00:15:09.460 --> 00:15:14.120
avalanche, but instead of adding
more stress or a load to the slab,

00:15:14.129 --> 00:15:19.430
we’re actually decreasing the strength of
the weak layer in a wet slab scenario.

00:15:19.430 --> 00:15:23.410
So in the schematic here on the right,
as water moves through the snowpack,

00:15:23.410 --> 00:15:27.649
whether it’s melting or whether it’s
rain on snow, it moves through

00:15:27.649 --> 00:15:30.249
the snowpack via flow fingers.
It’ll – or, water will move through

00:15:30.249 --> 00:15:33.619
the snow pack any way it can –
the least-resistant path.

00:15:33.619 --> 00:15:37.480
And it’ll eventually hit, potentially,
an interface between the slab and,

00:15:37.480 --> 00:15:39.790
if we have a weak layer,
in the snowpack.

00:15:39.790 --> 00:15:41.970
And with fine grains
over coarse grains,

00:15:41.970 --> 00:15:45.660
what it tends to do is
pool along that interface.

00:15:45.660 --> 00:15:48.959
When it does that, it decreases
the strength of that weak layer,

00:15:48.959 --> 00:15:52.079
and it’s not able to
support the slab above.

00:15:52.079 --> 00:15:53.350
So that’s a
wet slab avalanche.

00:15:53.350 --> 00:15:56.560
And a glide avalanche – we sort of
call these the circus oddity

00:15:56.560 --> 00:16:00.800
of the avalanche world because
they’re really hard to forecast.

00:16:00.800 --> 00:16:06.000
So as I mentioned, snow likes to move
downhill. Gravity likes to do its thing.

00:16:06.000 --> 00:16:11.059
And it moves downhill at variable rates.
And we call that glide.

00:16:11.059 --> 00:16:13.870
So, as the snowpack moves
downhill at variable rates,

00:16:13.870 --> 00:16:17.500
we tend to get a
tensile crack that forms.

00:16:17.500 --> 00:16:20.999
And so here we have what we call
a glide crack, or a tensile crack.

00:16:20.999 --> 00:16:24.309
And you can see, sort of in this area,
and all the way around,

00:16:24.309 --> 00:16:27.879
the snow actually buckling.
And what can happen here is,

00:16:27.879 --> 00:16:32.610
when we get a glide crack, often we’ll
get a glide avalanche, but not always.

00:16:32.610 --> 00:16:36.709
But what we need is free water
at that ground-snow interface.

00:16:36.709 --> 00:16:41.879
So as water moves through the
snowpack, it then pools at the bottom of

00:16:41.879 --> 00:16:45.749
the snowpack and the ground interface.
And it basically lubricates that interface

00:16:45.749 --> 00:16:50.500
right there, so the snowpack will then
start to glide downhill even more.

00:16:50.500 --> 00:16:53.980
And it also requires relatively
minimal surface roughness.

00:16:53.990 --> 00:16:57.680
So if we look at this image,
and you can see these are glide cracks –

00:16:57.680 --> 00:17:01.860
one’s right here, over here,
another one here, up here.

00:17:01.860 --> 00:17:04.880
You can see that they’re all in rock slabs.
So you can imagine that, as the

00:17:04.880 --> 00:17:09.040
water moves through that – or, that slab,
when it hits the rock slab and the

00:17:09.050 --> 00:17:12.660
snow interface, it’s not like soil
where it can actually move into the soil.

00:17:12.660 --> 00:17:15.320
It actually hits the rock.
It’s got nowhere to go.

00:17:15.320 --> 00:17:17.390
So it’s going to move
along that interface.

00:17:17.390 --> 00:17:21.110
So we tend to see glide avalanches
occurring on smooth rock slabs.

00:17:21.110 --> 00:17:23.140
And in the same
location every year,

00:17:23.140 --> 00:17:25.960
which we’ll get into in
just a little bit here.

00:17:27.870 --> 00:17:31.120
So we wanted to start at the beginning.
You know, what’s actually causing

00:17:31.120 --> 00:17:32.990
these wet snow
avalanches to occur?

00:17:32.990 --> 00:17:35.900
So we looked at wet slab and glide
avalanches because we – again, we have

00:17:35.900 --> 00:17:40.640
a pretty good handle on what
happens with wet, loose avalanches.

00:17:40.640 --> 00:17:44.830
And so we looked at –
on the right is a – the results of a –

00:17:44.830 --> 00:17:46.740
what we call
a classification tree.

00:17:46.740 --> 00:17:49.640
And we looked at avalanche
days versus non-avalanche days.

00:17:49.640 --> 00:17:53.710
And we looked at the 60 variables
of weather and snowpack to

00:17:53.710 --> 00:17:56.500
basically determine, what are
the most important variables?

00:17:56.500 --> 00:17:59.800
Or what are the discriminatory
variables between an avalanche day

00:17:59.800 --> 00:18:02.510
and a non-avalanche day?
And so what we found out is the

00:18:02.510 --> 00:18:06.840
first node here – avalanche days
and non-avalanche days will split,

00:18:06.840 --> 00:18:09.900
and avalanche days we get
with maximum air temperature.

00:18:09.900 --> 00:18:13.820
And, as we move down, again,
non-avalanche and avalanche days,

00:18:13.820 --> 00:18:17.740
the non-avalanche days that were left
are split again on mean air temperature.

00:18:17.740 --> 00:18:21.310
And then the final node right here
splits on a change in snow depth

00:18:21.310 --> 00:18:24.620
over a period of five days.
So what this tells us is that,

00:18:24.620 --> 00:18:28.400
one, air temperature is important.
And two, the settlement in the

00:18:28.410 --> 00:18:31.550
snowpack seems to be
an important variable as well.

00:18:31.550 --> 00:18:34.940
And so this is really important because,
as we see increasing air temperatures,

00:18:34.940 --> 00:18:39.090
particularly, you know, creeping into
late winter, we may see – we may

00:18:39.090 --> 00:18:42.440
begin to see more wet snow avalanches,
so it becomes even more important

00:18:42.440 --> 00:18:45.760
to try and understand
these wet snow phenomena.

00:18:47.260 --> 00:18:51.540
So, as I mentioned, these glide
avalanches tend to occur in the same

00:18:51.540 --> 00:18:56.660
location every year in areas that affect
the road – transportation corridors.

00:18:56.660 --> 00:19:00.411
We call these repeat offenders.
And these repeat offenders, we wanted

00:19:00.411 --> 00:19:03.740
to figure out, well, why are they
occurring in the same spot each time?

00:19:03.740 --> 00:19:07.640
So we looked at, again, a number of
variables, but this time terrain variables.

00:19:07.640 --> 00:19:12.620
So slope, curvature of the slope,
substrate underneath – we were looking

00:19:12.620 --> 00:19:16.620
at smooth rock slabs versus, say, areas
with a lot of vegetation underneath.

00:19:16.620 --> 00:19:20.620
And what we were able to find is that,
of course, as we – as I just pointed out,

00:19:20.620 --> 00:19:23.580
the areas with smooth rock slab
are areas where we tend to see

00:19:23.580 --> 00:19:28.780
a lot of glide avalanches. So we modeled
this across Glacier National Park.

00:19:28.780 --> 00:19:32.590
The red polygons indicate areas of
known glide avalanche activity.

00:19:32.590 --> 00:19:36.310
And the blue indicate modeled areas.
And so we can see that there’s a

00:19:36.310 --> 00:19:42.420
fair amount of area that has the
potential to harbor glide avalanches.

00:19:44.810 --> 00:19:47.660
And we also use time-lapse
photography to get a handle on

00:19:47.660 --> 00:19:50.340
when these things are actually occurring.
Because we’re not out there 24 hours

00:19:50.340 --> 00:19:54.590
a day, and of course we can’t capture
it at night because the – it’s dark.

00:19:54.590 --> 00:19:58.740
But we can see here, just as an example,
where the red box highlights,

00:19:58.740 --> 00:20:02.250
you can see, two days later, we have
what appears to be a small avalanche.

00:20:02.250 --> 00:20:06.980
It’s actually about 200 to 300 feet
in width, but we’re pretty far away –

00:20:06.980 --> 00:20:08.930
or, the camera is
relatively far away.

00:20:08.930 --> 00:20:12.320
It’s actually about
7 to 8 kilometers away.

00:20:13.340 --> 00:20:19.580
And then, even two days later, we have
another small glide avalanche right here.

00:20:19.580 --> 00:20:22.230
And you can see the glide
crack begin to form right back here.

00:20:22.230 --> 00:20:25.601
And then, in just one hour, we have
a really massive glide avalanche

00:20:25.601 --> 00:20:27.480
that occurred in
this basin right here.

00:20:27.480 --> 00:20:30.730
So it’s – again, time-lapse photography
provides us a nice way to be able to

00:20:30.730 --> 00:20:35.840
capture these events when we’re not out
there and we can’t see them in person.

00:20:38.180 --> 00:20:40.951
So let’s shift a little bit from
avalanche forecasting, and we’re

00:20:40.951 --> 00:20:44.170
going to talk more about tree rings
and avalanche ecology and how we

00:20:44.170 --> 00:20:48.520
can use tree rings to actually
develop an avalanche chronology.

00:20:49.440 --> 00:20:53.160
So dendrochronology,
if anyone here or online is familiar,

00:20:53.160 --> 00:20:57.240
it’s the study of tree rings.
And so we can actually use tree rings –

00:20:57.240 --> 00:21:01.610
you know, people use tree rings to
sort of study how – perhaps how big

00:21:01.610 --> 00:21:04.670
of a snow year it was, right?
We get big tree rings sometimes.

00:21:04.670 --> 00:21:08.060
Or if we’re in a drought, you know,
we’ll have often really thin tree rings.

00:21:08.060 --> 00:21:11.900
So we can use these tree rings and
count them by actually looking at –

00:21:11.900 --> 00:21:14.440
avalanches, when they hit a tree,
will leave a signal.

00:21:14.440 --> 00:21:17.430
And I’ll get into that signal in just a
second, but first, let’s talk a little bit

00:21:17.430 --> 00:21:21.250
about the avalanche path morphology
because this is important.

00:21:21.250 --> 00:21:24.860
As I mentioned before, the starting zone
is where avalanches tend to occur.

00:21:24.860 --> 00:21:28.810
Avalanche will release in the starting
zone and move down this track.

00:21:28.810 --> 00:21:31.590
And then it’ll eventually
deposit debris in the runout,

00:21:31.590 --> 00:21:34.930
or the deposition, zone all
the way down here at the bottom.

00:21:34.930 --> 00:21:39.890
And so this is an image of the avalanche
path that I showed earlier where the

00:21:39.890 --> 00:21:43.570
bulldozers were moving a lot of debris.
This is in Glacier Park.

00:21:43.570 --> 00:21:47.170
And this was – this is the image –
this is an actual image taken

00:21:47.170 --> 00:21:51.400
after that large-magnitude event.
So all this brown color you see here

00:21:51.400 --> 00:21:56.560
is actually vegetation and debris –
trees knocked over and transported

00:21:56.560 --> 00:21:59.450
in this large-magnitude event.
A lot of these trees were actually

00:21:59.450 --> 00:22:04.060
carried from way up here.
So right here by this little nick point,

00:22:04.060 --> 00:22:07.340
this was actually forested.
And it increased the avalanche path.

00:22:07.340 --> 00:22:11.480
This large-magnitude event increased the
avalanche path by about 30% in width.

00:22:12.540 --> 00:22:17.060
So you can see here that this track is,
in this particular avalanche path,

00:22:17.060 --> 00:22:20.420
is relatively low-angled.
It’s about 15 to 20 degrees.

00:22:20.420 --> 00:22:24.700
And most avalanches, if they’re small, or
maybe even medium, in size will begin in

00:22:24.700 --> 00:22:29.680
the starting zone and probably end up –
and typically end up right around here.

00:22:29.680 --> 00:22:32.210
So from this starting zone,
to give you a sense of scale,

00:22:32.210 --> 00:22:35.670
all the way to the runout zone,
is about 4,000 vertical feet.

00:22:35.670 --> 00:22:39.890
And so, to begin – an avalanche
beginning way up here, to cross a track

00:22:39.890 --> 00:22:43.400
that’s relatively low-angled,
and then to take out a lot of trees

00:22:43.400 --> 00:22:46.930
and end up all the way
4,000 feet below in the riparian zone,

00:22:46.930 --> 00:22:50.620
or the valley bottom,
is a really big avalanche.

00:22:50.620 --> 00:22:53.520
And so we’ll talk a little bit
more about that one in just a sec.

00:22:53.520 --> 00:22:56.250
But getting back to tree rings.

00:22:57.100 --> 00:22:59.440
They’re kind of the fingerprint
of avalanche activity.

00:22:59.440 --> 00:23:04.740
You can see here that this sort of shape
right here and this shape of the tree,

00:23:04.740 --> 00:23:07.580
this would be the uphill side of the
tree before it was knocked over.

00:23:07.580 --> 00:23:11.590
So when an avalanche comes down,
hits a tree, it’ll impact that tree.

00:23:11.590 --> 00:23:16.310
And it’ll actually – not always,
but often leave a scar on the tree ring.

00:23:16.310 --> 00:23:21.010
So here – and this blue arrow
is pointing to a scar from 1993.

00:23:21.010 --> 00:23:25.940
This one is a little scar but more
of what we call reaction wood.

00:23:25.940 --> 00:23:29.360
And this one over here is, again,
a little bit more of reaction wood.

00:23:29.370 --> 00:23:32.130
And so there is a signal that it leaves,
and sometimes it’s a

00:23:32.130 --> 00:23:38.000
really good signal, like a big scar.
And oftentimes, it’s a little more subtle.

00:23:39.390 --> 00:23:43.020
So for this project, we actually
are in Glacier National Park,

00:23:43.020 --> 00:23:46.010
but also in the surrounding
adjacent mountain ranges.

00:23:46.010 --> 00:23:48.140
So we’re looking at
four mountain ranges here.

00:23:48.140 --> 00:23:51.470
The red dots
indicate our sample sites.

00:23:51.470 --> 00:23:55.710
So we collected over 600 samples –
these cross-sections from trees

00:23:55.710 --> 00:24:00.320
so that we can actually look at the –
look at the tree rings.

00:24:00.320 --> 00:24:02.350
And a quick little overview –
two of our sites, again,

00:24:02.350 --> 00:24:06.220
are in John F. Stevens Canyon.
The blue polygons are the avalanche

00:24:06.220 --> 00:24:09.650
paths, and then, again, the map that I
showed earlier, just in a different color,

00:24:09.650 --> 00:24:13.100
of the avalanche paths that affect
the Going-to-the-Sun Road.

00:24:14.880 --> 00:24:19.660
So here’s a little video about
what we actually do in the field.

00:24:20.700 --> 00:24:24.740
Oop. And let me – let me see
if I can plug in [chuckles] –

00:24:24.740 --> 00:24:28.620
I forgot to plug in the audio here.
But we’ll continue on.

00:24:28.620 --> 00:24:31.570
Basically, what’s happening –
and I’ll let it run –

00:24:31.570 --> 00:24:34.600
is we’re looking for
scars on the tree.

00:24:34.600 --> 00:24:38.411
And so, in this case right here,
we suspect that that’s a scar –

00:24:38.411 --> 00:24:43.480
or, that hit the tree, and what
we’ll then do is cut into the tree.

00:24:43.480 --> 00:24:46.100
We want to get a cross-section
from this tree, and so we take out

00:24:46.100 --> 00:24:49.500
this cross-section.
We could core these trees, but they’re

00:24:49.500 --> 00:24:53.780
dead and down, so it’s okay to take
a cross-section from these trees.

00:24:53.780 --> 00:24:57.460
But often what happens,
if we just get a core from this tree,

00:24:57.460 --> 00:25:01.220
we’re not able to –
we might miss the signal.

00:25:01.220 --> 00:25:03.700
And so, you know, depending on
where we core – even if we core

00:25:03.700 --> 00:25:06.990
in all four, or more, directions,
one, that’s a lot of cores.

00:25:06.990 --> 00:25:10.460
But some of these scars are really small.
And so we might actually miss it.

00:25:10.460 --> 00:25:14.310
Even if we go in where the scar is,
on the outside – the exterior of the tree.

00:25:14.310 --> 00:25:19.360
But again, not all trees are
going to show a scar on the exterior.

00:25:19.360 --> 00:25:23.710
So maybe an avalanche –
a really big avalanche hit in, say, 1950.

00:25:23.710 --> 00:25:26.720
And for instance,
let’s look here.

00:25:26.720 --> 00:25:32.250
We have avalanche scars from ’72, ’85,
and ’93 on this 83- or 82-year-old tree.

00:25:32.250 --> 00:25:35.060
So an avalanche came in
and hit this side.

00:25:35.060 --> 00:25:37.080
And then it looks like it
also came in and hit this side.

00:25:37.080 --> 00:25:40.920
So we sort of have the tree rings
growing around that scar –

00:25:40.920 --> 00:25:42.290
around that disturbance.

00:25:42.290 --> 00:25:45.460
But imagine that maybe this wasn’t here,

00:25:45.460 --> 00:25:48.010
and we didn’t know where the scar
was on the exterior, and we might

00:25:48.010 --> 00:25:50.000
have missed – by coring,
we might have missed

00:25:50.000 --> 00:25:53.740
a smaller scar that exists further in.
So having these cross-sections,

00:25:53.740 --> 00:25:55.590
while it is a lot of work,
because we actually have to

00:25:55.590 --> 00:25:57.710
sand them down and
make them really smooth.

00:25:57.710 --> 00:26:00.160
Because often you can’t see
these scars until that tree –

00:26:00.160 --> 00:26:03.400
that cross-section is quite smooth,
and then they pop out.

00:26:03.400 --> 00:26:08.330
And so for instance, here’s one where,
in 2003, we had an impact scar.

00:26:08.330 --> 00:26:14.200
And, as I mentioned before, there are a
variety of – or, there’s a degree of signal.

00:26:14.200 --> 00:26:17.170
And in 1959, we have something –
what we call reaction wood.

00:26:17.170 --> 00:26:19.840
So we might not necessarily
have a really obvious scar.

00:26:19.840 --> 00:26:24.200
But when it gets hit by a tree on
the uphill side, the tree – it counteracts

00:26:24.200 --> 00:26:28.010
that and buffers that by growing
more wood on the downhill side.

00:26:28.010 --> 00:26:32.140
They call that compression wood.
Or, if the rings are really small,

00:26:32.140 --> 00:26:35.990
we call that reaction wood.
So we don’t necessarily get a scar.

00:26:35.990 --> 00:26:38.840
We have other things
to sort of fall back on.

00:26:40.860 --> 00:26:44.140
So not only are we able to build
a chronology over time looking at

00:26:44.140 --> 00:26:48.480
sort of the large – or, the magnitude of
avalanches over time, but we’re able to –

00:26:48.480 --> 00:26:51.800
when we collect trees in place,
we’re able to develop a

00:26:51.810 --> 00:26:57.580
return period frequency map.
So this is near the railway in the –

00:26:57.580 --> 00:27:00.880
or, this is the railway in the
U.S. Highway 2 corridor.

00:27:00.880 --> 00:27:05.390
This black rectangle here is a snow shed.
And what we’re able to do then –

00:27:05.390 --> 00:27:09.020
again, with our in-place samples,
is we’re actually able to look and

00:27:09.020 --> 00:27:12.740
develop a return period frequency.
So you can see down here, obviously

00:27:12.740 --> 00:27:17.480
avalanches will reach the railway
grade or the road much less frequently

00:27:17.490 --> 00:27:20.850
as they do further up in the path.
You know, up here, it’s anywhere on

00:27:20.850 --> 00:27:25.760
a scale from about 2-1/2 to 4 years.
Whereas, closer to the snow shed,

00:27:25.760 --> 00:27:30.460
you know, we’re looking at about
a 6- to 10-year return frequency there.

00:27:32.620 --> 00:27:35.010
So these are just three avalanche paths
along the Going-to-the-Sun Road,

00:27:35.010 --> 00:27:38.380
which gives you a bit of a sense of, you
know, how old our avalanche paths are.

00:27:38.380 --> 00:27:42.411
The problem with studying trees
in an avalanche path is the avalanche

00:27:42.411 --> 00:27:46.100
likes to take out the trees.
And they’re not always there, sitting

00:27:46.100 --> 00:27:50.150
there nice at the bottom of the avalanche
path, or in place, for us to just sample.

00:27:50.150 --> 00:27:52.700
And so we have, you know,
regeneration of these –

00:27:52.700 --> 00:27:54.990
of these forests,
and a lot of these trees are young.

00:27:54.990 --> 00:27:59.520
So sometimes it’s hard to get a
chronology that goes back very far.

00:27:59.520 --> 00:28:03.580
Fortunately, so far,
we have a decent chronology.

00:28:03.580 --> 00:28:07.270
And, in this case, you can see,
this is the number of responses, actually.

00:28:07.270 --> 00:28:08.460
So this isn’t the
number of samples.

00:28:08.460 --> 00:28:11.720
We’re looking at avalanche
responses in these samples.

00:28:11.720 --> 00:28:15.560
And we actually have responses
that go back to the late 1700s, which,

00:28:15.560 --> 00:28:18.810
in an avalanche chronology,
is pretty far back.

00:28:18.810 --> 00:28:23.280
You know, folks who study
other proxies may not think so,

00:28:23.280 --> 00:28:26.280
but for an avalanche path,
that’s actually pretty far back.

00:28:26.280 --> 00:28:28.130
So what we’ve done here –
as you can see,

00:28:28.130 --> 00:28:31.750
there are more
responses in recent years.

00:28:31.750 --> 00:28:33.750
And that makes sense.
There are more trees.

00:28:33.750 --> 00:28:36.980
So in order to normalize it or to
scale for it, we actually take the

00:28:36.980 --> 00:28:41.860
number of responses per the number
of trees actually alive in that year.

00:28:41.860 --> 00:28:44.220
And so we then have a
threshold percentage that

00:28:44.220 --> 00:28:49.210
we use to say, well, this is,
you know, likely an avalanche here.

00:28:51.440 --> 00:28:55.440
So aside from developing a chronology
and a return period frequency,

00:28:55.440 --> 00:28:58.220
avalanches also have
an impact on the landscape.

00:28:58.230 --> 00:29:02.660
So you can see from these repeat photos
in 1997 to 2004, the number of trees,

00:29:02.660 --> 00:29:06.820
of course, is markedly different.
But one thing to notice over here

00:29:06.820 --> 00:29:09.390
is that there are – there are
a fair number of trees, but then,

00:29:09.390 --> 00:29:11.900
over on this image
in 2004, there aren’t.

00:29:11.900 --> 00:29:15.790
And you can see that in a large event,
we could potentially have an avalanche

00:29:15.790 --> 00:29:19.110
that comes down, and if it’s the whole
width from what we call the trim line

00:29:19.110 --> 00:29:22.790
over here to the trim line over here –
if it’s the whole width of this avalanche

00:29:22.790 --> 00:29:26.230
path, it’s going to come down
and potentially reach the rail grade

00:29:26.230 --> 00:29:28.180
on the side of
the snow shed.

00:29:28.180 --> 00:29:32.410
So, as I mentioned earlier,
snow sheds can be very effective.

00:29:32.410 --> 00:29:35.800
But when we have a changing
landscape like this, they’re

00:29:35.800 --> 00:29:39.560
not necessarily 100% effective
from guarding against avalanches.

00:29:39.560 --> 00:29:44.400
So, in this case, we also have
a interaction with wildfires

00:29:44.400 --> 00:29:47.050
where wildfires – you know,
if they burn the forest,

00:29:47.050 --> 00:29:50.770
they open up, potentially,
more avalanche terrain.

00:29:50.770 --> 00:29:53.590
Trees act as not only
an anchor in the snowpack,

00:29:53.590 --> 00:29:55.740
but they can also act
as surface roughness.

00:29:55.740 --> 00:30:00.140
When an avalanche comes down the
slope, and it hits a bunch of trees, it can

00:30:00.140 --> 00:30:05.700
actually – you know, the trees help slow
the velocity of that – of the avalanche.

00:30:05.700 --> 00:30:07.530
But when there aren’t any,
because they’ve been taken out

00:30:07.530 --> 00:30:11.120
by an already large avalanche,
it makes the probability of an avalanche

00:30:11.120 --> 00:30:14.660
reaching further down even greater.
So you can see that the difference

00:30:14.660 --> 00:30:20.280
in landscape change and how that
might affect the avalanche regime.

00:30:20.280 --> 00:30:24.050
And, again, you know, looking at
return period frequencies, this is just

00:30:24.050 --> 00:30:26.390
another illustration where,
when we – these are all

00:30:26.390 --> 00:30:29.860
downed trees from an avalanche.
So when we take out these downed trees

00:30:29.860 --> 00:30:34.340
from a large avalanche, perhaps
what was maybe a 2-1/2- to 5-year

00:30:34.340 --> 00:30:38.410
return period frequency up here
is now perhaps down here.

00:30:38.410 --> 00:30:42.220
And perhaps the 10-year now
becomes even further down.

00:30:44.580 --> 00:30:47.380
So by developing an avalanche
chronology, one of our goals in this

00:30:47.380 --> 00:30:51.820
study – and we’re in the process of this
work right now – is to actually associate

00:30:51.820 --> 00:30:55.910
some of these large-magnitude event
years with weather and climate drivers.

00:30:55.910 --> 00:31:00.170
So looking at things like, you know,
storminess or, you know, upper-level

00:31:00.170 --> 00:31:05.200
air pressure indices. And potentially
other teleconnection indices as well.

00:31:05.200 --> 00:31:09.500
And what’s sort of noteworthy
about this cycle – and this was the cycle

00:31:09.510 --> 00:31:14.000
in 2009 that I previously mentioned –
is, in early January, we had,

00:31:14.000 --> 00:31:17.440
you know, relatively cold
temperatures – minus 15 degrees C.

00:31:17.440 --> 00:31:21.530
And we had a pretty sharp increase
in air temperature to near-freezing.

00:31:21.530 --> 00:31:26.020
And this is at about 7,500 feet.
7,500 feet in northwest Montana

00:31:26.020 --> 00:31:29.490
is pretty much the alpine.
So it’s, you know, right at the

00:31:29.490 --> 00:31:32.890
upper level of sub-alpine and
right getting into the alpine terrain.

00:31:32.890 --> 00:31:36.540
And so that, for us,
is a pretty high snow level.

00:31:36.540 --> 00:31:39.020
You know, it’s pretty similar
to here in the Sierra as well.

00:31:39.020 --> 00:31:41.140
Where if you get
snow levels at, like, 8,000 feet,

00:31:41.140 --> 00:31:43.400
that would be
fairly comparable.

00:31:43.400 --> 00:31:46.670
Or at least in the Tahoe region in the
high Sierra, it’s a bit different, of course.

00:31:46.670 --> 00:31:50.270
But you can also see the –
during the cycle, we had

00:31:50.270 --> 00:31:53.820
a sharp increase in precipitation as well.
And so it rained at the low and

00:31:53.820 --> 00:31:57.200
mid elevations, and even
a little bit into the upper elevations.

00:31:57.200 --> 00:32:00.950
So what we had is a lot of rain on
snow and a potential wet slab scenario.

00:32:00.950 --> 00:32:04.260
But then we also had really
heavy wet snow up high,

00:32:04.260 --> 00:32:07.560
sort of acting as a dry slab scenario.
So we have sort of the combination

00:32:07.560 --> 00:32:11.990
of both wet slab and
dry slab in this same avalanche.

00:32:11.990 --> 00:32:15.030
And the image on the left is –
it’s actually from a different avalanche,

00:32:15.030 --> 00:32:16.920
but it’s from a
wet slab avalanche.

00:32:16.920 --> 00:32:21.820
And you can see that the debris that
it can deposit is pretty substantial.

00:32:23.060 --> 00:32:27.440
So in that 2009 avalanche,
the image on the left shows the

00:32:27.450 --> 00:32:31.300
debris pile left along the lower part
of the Going-to-the-Sun Road.

00:32:31.300 --> 00:32:35.740
Again, about 4,000 feet below.
And the image is foreshortened there,

00:32:35.740 --> 00:32:40.100
but that debris pile is about 30 feet deep.
And that person is definitely not 10 feet,

00:32:40.100 --> 00:32:43.890
so it’s a little foreshortened.
But then, on the upper part of the road,

00:32:43.890 --> 00:32:45.240
it actually damaged
part of the road.

00:32:45.240 --> 00:32:49.220
So it took them a while
to repair that that summer.

00:32:51.840 --> 00:32:56.640
All right. So another project we’re
working on is snow depth mapping.

00:32:56.640 --> 00:33:01.771
And we want to know the,
not only variability of snow depth

00:33:01.771 --> 00:33:06.080
across an avalanche path starting zone,
but we also want to get a sense of,

00:33:06.080 --> 00:33:08.320
you know, how much
it’s changing over time.

00:33:08.320 --> 00:33:10.880
So when we get a storm, you know,
we have automated weather stations

00:33:10.880 --> 00:33:13.560
that sort of give us an
idea of how much it snowed.

00:33:13.560 --> 00:33:18.150
But then, when we have wind events
that tend to load snow from perhaps

00:33:18.150 --> 00:33:22.210
the leeward or the windward –
or, the windward side of the ridge,

00:33:22.210 --> 00:33:25.100
loading the leeward side, some –
you know, what we do is basically

00:33:25.100 --> 00:33:29.060
make a good educated guess about how
much new snow has been transported.

00:33:29.060 --> 00:33:32.910
So we might say, well, we had
winds for, you know, six hours

00:33:32.910 --> 00:33:35.870
in the 30-mile-per-hour range,
and now we have a slab that’s

00:33:35.870 --> 00:33:39.660
about maybe a foot in addition
to what we already had.

00:33:39.660 --> 00:33:42.710
So what we’re trying to do is
get a better sense of how much

00:33:42.710 --> 00:33:45.890
things are actually changing.
So we’re using drones, or unmanned

00:33:45.890 --> 00:33:50.250
aerial systems, and a photogrammetry
technique called structure from motion.

00:33:50.250 --> 00:33:53.310
And we’re basically flying over these
starting zones and mapping them.

00:33:53.310 --> 00:33:55.360
And I’ll explain
how we can do that.

00:33:56.040 --> 00:33:59.620
But first, structure from motion
is a photogrammetry technique

00:33:59.630 --> 00:34:03.580
where you take our – in the middle here,
our scene that we want to –

00:34:03.580 --> 00:34:06.300
we want to
image and map.

00:34:06.300 --> 00:34:08.990
And in our case, you know, we don’t
need to map the back of the avalanche

00:34:08.990 --> 00:34:12.649
path or the back of the mountain,
so we just do about a 180 around it.

00:34:12.649 --> 00:34:15.569
And what that allows us
to do is get overlapping images

00:34:15.569 --> 00:34:17.690
of our scene of interest.

00:34:17.690 --> 00:34:21.570
And the objective is to detect change
in snow depth through time so that

00:34:21.570 --> 00:34:24.230
we can create these high-resolution
products where we can actually

00:34:24.230 --> 00:34:27.370
look at a change in snow depth from,
say, one week to another week.

00:34:27.370 --> 00:34:31.280
Or even just a few days if we
have a storm or a big wind event.

00:34:32.349 --> 00:34:37.700
So we take – we take our drone out,
and we just have a small quadcopter.

00:34:37.710 --> 00:34:41.190
And we’re able to attach our
camera to the bottom of this.

00:34:41.190 --> 00:34:46.340
And it’s a 15- to 20-megapixel camera,
depending on which one we’re using.

00:34:46.340 --> 00:34:48.720
And we’re actually able –
in this case, we were mapping

00:34:48.720 --> 00:34:52.200
the open area to the –
to the right over there.

00:34:52.200 --> 00:34:55.220
And while it doesn’t look like
your classic avalanche path,

00:34:55.220 --> 00:34:57.440
it is avalanche terrain.
It’s sufficiently steep,

00:34:57.440 --> 00:34:59.789
but it’s a little more forested.
So we wanted to get a sense –

00:34:59.789 --> 00:35:02.900
can we – you know, we have a
pretty good sense that we can capture it

00:35:02.900 --> 00:35:06.400
in this open terrain, the snow depth
change, but we wanted to look at,

00:35:06.400 --> 00:35:10.839
are we able to capture it in
more forested or sub-alpine terrain.

00:35:10.839 --> 00:35:15.180
So here you can see, in the bottom right
where those two green markers are is

00:35:15.180 --> 00:35:18.950
where we launch and land. And the
other lines indicate our flight paths.

00:35:18.950 --> 00:35:22.650
And so this is just a small screen shot
of when we plan our missions in the

00:35:22.650 --> 00:35:26.589
office before we go out and actually fly.
We want to be sure that, one, we’re,

00:35:26.589 --> 00:35:28.819
you know, well above the –
above the ground.

00:35:28.819 --> 00:35:31.290
So we use a digital elevation model,
but we also have to account for

00:35:31.290 --> 00:35:33.750
trees that are
out there as well.

00:35:33.750 --> 00:35:37.490
So we – you know, we have to –
we have to plan it pretty carefully.

00:35:37.490 --> 00:35:40.690
And we take, you know,
a cross-section – or, a upslope

00:35:40.690 --> 00:35:45.359
and downslope and then
a cross-slope transect as well.

00:35:45.360 --> 00:35:49.620
And we’re limited by battery
power on this particular drone.

00:35:49.620 --> 00:35:53.470
And, you know, it’s a quadcopter,
so our battery life is about 12 minutes.

00:35:53.470 --> 00:35:57.569
So we’ll typically fly in upslope and
downslope transects, bring it back,

00:35:57.569 --> 00:36:01.000
and then send it back out again
after we swap our batteries.

00:36:02.230 --> 00:36:06.660
So if we go out and we
just try and map this, that’s great.

00:36:06.660 --> 00:36:09.660
We have an idea of what think –
you know, or what shows how much

00:36:09.660 --> 00:36:12.841
snow depth is and the variability.
But we actually need to go out and

00:36:12.841 --> 00:36:16.249
make sure and verify that
that’s the case, particularly now.

00:36:16.249 --> 00:36:19.630
So we go out and we do snow
depth manual measurements.

00:36:19.630 --> 00:36:23.190
Again, we don’t want to necessarily
put ourselves in the starting zones here.

00:36:23.190 --> 00:36:27.869
So what we tend to do is walk around
on the safe ridges around our avalanche

00:36:27.869 --> 00:36:30.840
path, and that’s still within our
scene that we’re interested in.

00:36:30.840 --> 00:36:33.700
And so we’re able to verify
these snow depths by probing

00:36:33.700 --> 00:36:36.230
and taking
manual measurements.

00:36:36.230 --> 00:36:39.320
We also have to place ground control
points out there so that, when we take

00:36:39.320 --> 00:36:44.400
our images, that they need to be visible
in a number of our photographs.

00:36:44.400 --> 00:36:49.890
And so we put these – we spray
paint these X’s on the snow.

00:36:49.890 --> 00:36:53.119
And we take manual measurements
there too, but we get high-resolution

00:36:53.119 --> 00:36:59.069
GPS and GNSS points so that we’re
able to actually georeference our images

00:36:59.069 --> 00:37:02.380
and our maps, of course, once we
bring it back into the office and

00:37:02.380 --> 00:37:06.140
do all of our processing
so that it’s even more accurate.

00:37:08.380 --> 00:37:11.180
So going out in the field is really fun.
You know, that’s the fun part.

00:37:11.180 --> 00:37:13.540
That’s why we do the work.
[laughter]

00:37:13.540 --> 00:37:16.260
But the processing, of course,
is what takes the longest.

00:37:16.260 --> 00:37:20.820
And the nice thing, though, is that we
put all the time in by processing and,

00:37:20.830 --> 00:37:23.609
you know, let our – let our –
let our computers do a bunch of

00:37:23.609 --> 00:37:25.140
the work and
let it run overnight.

00:37:25.140 --> 00:37:29.320
And we’re able to create these really
cool and high-resolution products.

00:37:29.320 --> 00:37:33.260
This is a dense point cloud.
So if anybody is familiar with Lidar,

00:37:33.260 --> 00:37:36.100
you know, you fly over an area,
and Lidar basically shoots a –

00:37:36.109 --> 00:37:42.000
the sensor shoots a laser down,
and it gives you a return pulse,

00:37:42.000 --> 00:37:44.410
and you can basically –
it gives you a bunch of points.

00:37:44.410 --> 00:37:49.480
And you can then get a bare earth
digital elevation model with Lidar.

00:37:49.480 --> 00:37:51.400
Structure from motion
works similarly.

00:37:51.400 --> 00:37:53.930
As I mentioned, we take
these overlapping images.

00:37:53.930 --> 00:37:57.070
And so what it does is, it takes
the common or top points in

00:37:57.070 --> 00:37:59.480
those overlapping images,
and you can imagine that that sort of

00:37:59.480 --> 00:38:02.480
propagates through every image as
you have these common points.

00:38:02.480 --> 00:38:06.500
So, in this dense point cloud,
we have about 50 million points.

00:38:06.500 --> 00:38:09.400
And it’s a relatively small slope,
even though it is, you know,

00:38:09.400 --> 00:38:11.999
an avalanche terrain.
The vertical relief here is

00:38:11.999 --> 00:38:14.460
about 500 feet,
so it’s not quite that large,

00:38:14.460 --> 00:38:19.589
but 50 million points is, you know,
when processing is – can be fairly large.

00:38:19.589 --> 00:38:25.059
And so the difference with structure
from motion is that, when Lidar

00:38:25.059 --> 00:38:27.589
moves through, it can actually –
moves through gaps, you know,

00:38:27.589 --> 00:38:30.769
in trees, and it’ll create
a bare earth model for you.

00:38:30.769 --> 00:38:33.150
Structure from motion isn’t
able to actually move through.

00:38:33.150 --> 00:38:35.410
You know, it’s not
sending a pulse down.

00:38:35.410 --> 00:38:38.700
It’s using these tie points.
So we can’t create a bare earth

00:38:38.700 --> 00:38:42.019
elevation model, but we can
create a digital surface model.

00:38:42.019 --> 00:38:48.400
And so here we’ve created a 3D model.
And it’s really low-resolution.

00:38:48.400 --> 00:38:50.230
The high-resolution one
that we created would have

00:38:50.230 --> 00:38:53.720
crashed the presentation,
so I didn’t want to put it in here.

00:38:53.720 --> 00:38:56.190
But 3D models are nice.
You know, they’re pretty to look at.

00:38:56.190 --> 00:38:58.940
They’re good for outreach
and presentations, but really,

00:38:58.940 --> 00:39:03.049
it’s the digital surface
model that we’re interested in.

00:39:03.049 --> 00:39:06.231
And you can see – this is a
digital surface model

00:39:06.231 --> 00:39:09.369
with an accuracy of
about 4.9 centimeters.

00:39:09.369 --> 00:39:12.099
And so it’s good enough
that you can actually see –

00:39:12.099 --> 00:39:14.490
right here, you can
see our ski tracks.

00:39:14.490 --> 00:39:17.829
And we made nice, pretty figure 8s
coming down. [laughter]

00:39:17.829 --> 00:39:20.019
And over here, you can see
sort of our up-track

00:39:20.019 --> 00:39:23.210
where we skimmed up to
take our manual measurements.

00:39:23.210 --> 00:39:26.150
And down here on the far right,
you can actually see our vehicle.

00:39:26.150 --> 00:39:29.280
So this is important because,
with a 5-centimeter accuracy

00:39:29.280 --> 00:39:33.020
in both the X and Y and even
the vertical realm, we can actually

00:39:33.020 --> 00:39:36.910
detect change on a really small scale.
So, yeah, we’re going to be able to

00:39:36.910 --> 00:39:41.040
detect change when it snows 2 to 3 feet,
but we can hopefully also detect

00:39:41.040 --> 00:39:43.510
this change when we have,
you know, storms or wind events

00:39:43.510 --> 00:39:47.320
that are around a foot,
or maybe even a little less than that.

00:39:48.109 --> 00:39:51.260
So what we then do is take our digital
surface models or our point clouds

00:39:51.270 --> 00:39:56.759
that I showed earlier, and we basically
take the difference between the two.

00:39:56.759 --> 00:40:01.700
It’s simple subtraction of those points
in the point cloud or the pixels

00:40:01.700 --> 00:40:05.510
in your digital surface model.
And that allows us to get our change.

00:40:06.780 --> 00:40:11.940
And, again, this is a great tool.
Because now we’re able to, you know,

00:40:11.940 --> 00:40:15.061
launch from all the way down here,
not necessarily put ourselves in a

00:40:15.061 --> 00:40:19.500
hazardous position, but we’re able to
map a really big area and look at the

00:40:19.500 --> 00:40:23.440
variability across that area as well.
And that helps with, you know,

00:40:23.440 --> 00:40:25.880
forecasting for, okay,
we got a wind event,

00:40:25.890 --> 00:40:28.019
so how much more of a slab
did we put on top of

00:40:28.019 --> 00:40:32.360
that weak layer, if there is one?
Or how much new snow did we get?

00:40:34.580 --> 00:40:38.480
Another nice product that we’re able –
or, another byproduct is we’re able to

00:40:38.480 --> 00:40:40.490
map these
avalanche crowns.

00:40:40.490 --> 00:40:45.580
And so this is a digital surface
model that was created last spring.

00:40:45.580 --> 00:40:48.680
And you can see here this arrow points
to an avalanche crown right here.

00:40:48.690 --> 00:40:52.839
And the accuracy of this digital surface
model is about 13 centimeters.

00:40:52.839 --> 00:40:55.269
And it captured a small one
over here as well.

00:40:55.269 --> 00:40:59.420
So in real life, this is what it looks like.
This is the avalanche crown that we

00:40:59.420 --> 00:41:02.660
were able to capture, and then
this is the small one over there.

00:41:02.660 --> 00:41:07.560
So any guesses as to the height of the
crown of this avalanche right here?

00:41:08.360 --> 00:41:10.180
No guesses?

00:41:10.180 --> 00:41:12.520
- Thirty feet.
- [inaudible] the trees. It’s [inaudible].

00:41:12.520 --> 00:41:14.340
- Thirty feet?
- Little higher.

00:41:14.340 --> 00:41:16.660
- That was a guess. Higher?
- Higher. Much higher.

00:41:16.660 --> 00:41:18.200
- Much higher?

00:41:18.200 --> 00:41:22.480
In the last talk, anyone – we got
a range from 2 meters to 200 meters.

00:41:22.480 --> 00:41:25.680
[laughter]
So it’s somewhere in between there.

00:41:25.680 --> 00:41:28.900
So, yeah, around here,
it’s about 15 to 20 feet.

00:41:28.910 --> 00:41:33.029
And then over here, at its farthest
edge where this crown is, it’s upwards

00:41:33.029 --> 00:41:36.109
of 60 feet. So that’s a big –
you know, that’s the whole snowpack.

00:41:36.109 --> 00:41:38.109
We’re looking at a
glide avalanche right here.

00:41:38.109 --> 00:41:42.220
And, you know, this is an incredibly
deep snowpack because what’s

00:41:42.220 --> 00:41:44.450
happening is, over the course of
the winter – and this is in the spring,

00:41:44.450 --> 00:41:47.359
but over the course of the winter,
we have, of course, storms falling,

00:41:47.359 --> 00:41:50.039
but then we have wind
loading from sort of the

00:41:50.039 --> 00:41:53.660
back of this image,
as wind transports snow.

00:41:53.660 --> 00:41:57.280
And it just basically deposits
all that snow right down here.

00:41:57.280 --> 00:41:59.759
And we also have
avalanches that occur up here

00:41:59.759 --> 00:42:02.279
and put all their
debris down here as well.

00:42:02.279 --> 00:42:04.859
And so it’s an incredibly
deep snowpack over here.

00:42:04.859 --> 00:42:08.010
But this tool allows us –
because this is quite far away,

00:42:08.010 --> 00:42:12.180
this tool allows us to actually capture
how large these avalanche crowns are.

00:42:12.180 --> 00:42:14.849
And when it goes to the ground,
you know, that’s obvious.

00:42:14.849 --> 00:42:19.410
But when we’re working with crowns
that aren’t necessarily at the ground,

00:42:19.410 --> 00:42:22.760
it gives us an idea of what
layer they actually released on.

00:42:26.580 --> 00:42:30.720
All right. So to finish up here, you know,
our next steps is our research is going to

00:42:30.720 --> 00:42:34.680
continue to be driven by operational or
decision – management decision-making.

00:42:34.680 --> 00:42:38.049
So we’re there to basically help –
you know, in this case,

00:42:38.049 --> 00:42:42.360
on the transportation corridors,
we’re there to help keep people safe.

00:42:42.960 --> 00:42:45.320
We’re going to continue
to refine our wet snow models.

00:42:45.329 --> 00:42:48.420
So, you know, we used a
number of variables as inputs.

00:42:48.420 --> 00:42:52.279
But we also want to continue down
that road and make sure that, you know,

00:42:52.279 --> 00:42:55.210
the variables we put in and what’s
coming out still works and it –

00:42:55.210 --> 00:43:00.109
and we’re using that operationally
to some extent as guidance as well.

00:43:00.109 --> 00:43:03.720
And then, this spring, as we –
if it ever melts in Montana –

00:43:03.720 --> 00:43:07.589
it’s been a big year – a big snow year.
But when it does melt, we’re going to

00:43:07.589 --> 00:43:11.380
continue to explore and map our
snow depths across these starting zones,

00:43:11.380 --> 00:43:14.140
not only in periods of
accumulation, but also melt.

00:43:14.140 --> 00:43:16.770
So look at how rapidly
the snowpack is settling.

00:43:16.770 --> 00:43:19.619
Because, as we learned before,
that was one of our important

00:43:19.619 --> 00:43:22.849
variables for our
wet slab avalanches.

00:43:22.849 --> 00:43:25.480
So thanks for attending.

00:43:25.480 --> 00:43:27.260
And any questions?

00:43:27.880 --> 00:43:34.040
[Applause]

00:43:34.040 --> 00:43:38.200
- Thank you, Erich. And I’m sure
many of you have questions.

00:43:38.200 --> 00:43:41.630
And many of you have been here
every time, so you know the routine.

00:43:41.630 --> 00:43:46.080
You’re first in line. We have two
microphones set up in the two aisles.

00:43:46.080 --> 00:43:50.320
Please, if you are able, get up and use the
microphone so that we can all hear you.

00:43:50.320 --> 00:43:52.000
If, for some reason,
you’re not able to get up

00:43:52.000 --> 00:43:54.820
to the microphone, wave at me,
and I’ll come and bring you one.

00:43:54.829 --> 00:43:57.829
So why don’t you go ahead, sir,
with the first question?

00:43:57.829 --> 00:44:04.329
- Thank you for the presentation.
I had a question about pre-empting

00:44:04.329 --> 00:44:07.910
these avalanches through blasts.
- Yeah.

00:44:07.910 --> 00:44:11.789
- The way they do on ski slopes.
So if you knew that, say,

00:44:11.789 --> 00:44:19.160
the BNSF railroad was in the –
in the path, could you potentially

00:44:19.160 --> 00:44:21.980
pre-empt that or trigger
that avalanche before?

00:44:21.980 --> 00:44:24.840
And if so – if not, why not?
- Yeah.

00:44:24.840 --> 00:44:26.740
- Thank you.
- That’s a great question,

00:44:26.740 --> 00:44:29.020
and I should have
elaborated on that one.

00:44:29.029 --> 00:44:32.049
But – so, yes, obviously,
you know, using explosives

00:44:32.049 --> 00:44:35.619
is a great mitigation tool.
So there’s a couple of things there,

00:44:35.620 --> 00:44:38.940
is, one, yeah, you can close the road
and the railway for a short period of time

00:44:38.940 --> 00:44:42.180
and, you know, deliver the
explosives in a variety of techniques.

00:44:42.180 --> 00:44:45.720
And, again, you know,
create the avalanche on your terms,

00:44:45.720 --> 00:44:48.440
when you want it
to go down.

00:44:48.440 --> 00:44:51.210
One of the issues –
and they do that along the railway

00:44:51.210 --> 00:44:54.579
in emergency purposes – so if it’s a really
big storm, and avalanches are imminent,

00:44:54.579 --> 00:44:56.749
and they’ve already seen
smaller avalanche activity.

00:44:56.749 --> 00:45:00.529
But one of the issues is that the starting
zones are in Glacier National Park,

00:45:00.529 --> 00:45:03.049
which is a wilderness area.
And so they did an entire

00:45:03.049 --> 00:45:09.019
environmental impact – or, EA –
environmental assessment, and they –

00:45:09.019 --> 00:45:12.440
it was deemed that they weren’t
going to allow avalanche mitigation

00:45:12.440 --> 00:45:17.440
via explosives on a regular basis
and only in emergency conditions.

00:45:17.440 --> 00:45:21.740
So that’s the reason now that the –
that they don’t do it regularly.

00:45:21.740 --> 00:45:24.160
Because you’re right.
You know, if you – if you –

00:45:24.160 --> 00:45:26.830
basically, at every storm,
even if it’s a small storm,

00:45:26.830 --> 00:45:31.650
you’d basically mitigate it through
explosive mitigation then, you know,

00:45:31.650 --> 00:45:34.470
you could – you could knock down
smaller avalanches and potentially

00:45:34.470 --> 00:45:37.180
have less – you know,
less of an effect.

00:45:37.180 --> 00:45:42.600
But because the starting zones are in
the park, that’s what they decided.

00:45:48.300 --> 00:45:53.200
- Hi. I’d be interested to hear anything
more you might say about how global

00:45:53.200 --> 00:45:57.059
warming is affecting your work.
- Yeah.

00:45:57.059 --> 00:46:01.519
So that’s a – that’s a great question
that I actually get quite often.

00:46:01.519 --> 00:46:03.380
And it’s one of the questions
that we’re working on.

00:46:03.380 --> 00:46:06.880
So obviously, you know, global
air temperatures are increasing.

00:46:06.880 --> 00:46:10.859
And as I – as I sort of alluded to,
we might – we might see more

00:46:10.860 --> 00:46:13.980
wet snow avalanches
creep into late spring.

00:46:13.980 --> 00:46:17.740
And perhaps even more
rain-on-snow events mid-winter.

00:46:17.740 --> 00:46:19.820
You know,
especially here in the Sierra.

00:46:19.820 --> 00:46:23.320
I mean, you know,
we’re used to rain-on-snow events.

00:46:23.329 --> 00:46:25.230
And in the Cascades –
but those coastal regions.

00:46:25.230 --> 00:46:28.119
But now, you know, we may begin
to see – and I say “may” because,

00:46:28.119 --> 00:46:30.769
at least in the U.S., there hasn’t
been any definitive work.

00:46:30.769 --> 00:46:35.539
So that’s part of what we want to try
and look at with the tree ring work is to

00:46:35.539 --> 00:46:40.089
see – we can’t necessarily tease out, you
know, rain-on-snow events mid-winter.

00:46:40.089 --> 00:46:46.230
But we can sort of determine, at least on
a shorter scale, where we have weather

00:46:46.230 --> 00:46:52.039
records that – you know, automated
weather stations that sort of show that.

00:46:52.039 --> 00:46:56.599
Just north in British Columbia, north of
us, near Rogers Pass they looked at,

00:46:56.599 --> 00:46:58.529
you know, some of this,
and they found that there is

00:46:58.529 --> 00:47:01.420
a slight increase in
mid-winter rain-on-snow events.

00:47:01.420 --> 00:47:08.829
And their observational record goes back
a lot further to the, like, 1940s or ’50s.

00:47:08.829 --> 00:47:10.710
And then, in the Alps,
you know, they’ve shown that

00:47:10.710 --> 00:47:13.900
there has been no change.
But, again, you know, observational

00:47:13.900 --> 00:47:19.240
records can be pretty scarce and hard to
come by as we go further back in time.

00:47:19.240 --> 00:47:22.900
So that’s why we’re trying to use
tree rings as a – as a proxy there.

00:47:24.220 --> 00:47:26.380
- I had a question.
So I was wondering if drones

00:47:26.390 --> 00:47:31.779
would have any role in delivering
explosives for – and how does

00:47:31.779 --> 00:47:34.980
your work compare with
what’s going on in Europe?

00:47:34.980 --> 00:47:40.070
They’ve built things in the path of –
we’ve got a head start as we haven’t

00:47:40.070 --> 00:47:42.450
built in front of these things as much.
- Yeah, exactly.

00:47:42.450 --> 00:47:45.040
- But I was wondering how this work
compares to what’s going on over there.

00:47:45.040 --> 00:47:50.839
- Yeah. So the first question of
delivering explosives via drones,

00:47:50.839 --> 00:47:55.410
I actually read something a few
months ago about a company that was –

00:47:55.410 --> 00:47:57.589
that proposed to do that,
or they were trying to do it,

00:47:57.589 --> 00:48:01.349
outside of Telluride in Colorado.
I haven’t heard anything since.

00:48:01.349 --> 00:48:04.400
And it’s doable.
As long as the payload, of course,

00:48:04.400 --> 00:48:07.779
on the – on the drone is –
or as long as the drone has a,

00:48:07.779 --> 00:48:12.420
you know, pretty high payload, and
depending on what sort of explosive.

00:48:12.420 --> 00:48:16.269
You know, if it’s a 2-pound charge
that a lot of skiers use – you know,

00:48:16.269 --> 00:48:21.200
just a stick of explosive,
then that’s certainly doable.

00:48:21.200 --> 00:48:26.489
But other than that, I haven’t heard.
And, yeah, it might be – and in terms of

00:48:26.489 --> 00:48:31.340
the work that we’re doing, you know,
comparable to Europe, in that – I mean,

00:48:31.340 --> 00:48:35.819
they have – you know, yeah, they’ve
been living and working and dealing

00:48:35.819 --> 00:48:39.849
with avalanches and avalanche terrain
all the time – or, for a long time.

00:48:39.849 --> 00:48:43.250
And they have a variety of techniques
that they use to mitigate avalanches,

00:48:43.250 --> 00:48:46.819
from explosives to – you know,
they basically will build structures

00:48:46.819 --> 00:48:50.099
in the starting zones to disrupt the
snowpack so that that weak layer

00:48:50.099 --> 00:48:54.269
can’t form – you know, or can’t
form widespread across the slope.

00:48:54.269 --> 00:48:57.489
So they’ll use snow fencing.
They also have avalanche dams.

00:48:57.489 --> 00:49:01.150
Like, for instance, in Innsbruck
in Austria, they have avalanche paths

00:49:01.150 --> 00:49:04.380
that come all the way down into town.
But they have these really big diversion

00:49:04.380 --> 00:49:08.170
dams sort of higher up, of course,
so that, when an avalanche

00:49:08.170 --> 00:49:11.299
comes down, it’s diverted.
And so you don’t have the

00:49:11.299 --> 00:49:15.359
concentration of impact,
and it sort of disburses that impact.

00:49:15.359 --> 00:49:20.349
So they – and, you know – and in
Colorado too, there’s a lot of work

00:49:20.349 --> 00:49:26.229
being done there in terms of, you know,
building structures that help mitigate

00:49:26.229 --> 00:49:29.599
and also explosive delivery –
remote explosive delivery too.

00:49:29.599 --> 00:49:33.940
Not just throwing charges.
- That was kind of the basis of the

00:49:33.940 --> 00:49:40.480
question is that you could get access – 
well, quickly and to areas that people

00:49:40.489 --> 00:49:44.549
wouldn’t want to – well, you just
wouldn’t get into normally.

00:49:44.549 --> 00:49:46.800
- Yeah.
- Or wild areas.

00:49:46.800 --> 00:49:48.740
- Yeah, exactly.

00:49:50.500 --> 00:49:55.280
- It seems to me this is similar
to fracture in brittle materials.

00:49:55.280 --> 00:49:56.970
- Yeah.
- And I wonder if you’re using

00:49:56.970 --> 00:50:01.190
the methodology of fracture mechanics
to look at stress intensity and critical

00:50:01.190 --> 00:50:04.460
flaw size and all that sort of thing?
- Yeah. Yes. [laughter]

00:50:04.640 --> 00:50:05.660
- Yeah.

00:50:05.660 --> 00:50:08.880
- I’ll explain more than that.
So I – let me caveat that with,

00:50:08.880 --> 00:50:13.440
I am not an engineer.
But, yeah, a lot of – a lot of folks,

00:50:13.440 --> 00:50:19.569
particularly, again, in Switzerland and
folks out of Bozeman have looked at –

00:50:19.569 --> 00:50:25.240
have used fracture mechanics to look
at fracture within the weak layer.

00:50:25.240 --> 00:50:29.460
So, you know, one of the things – and it
was actually a really cool test we use –

00:50:29.460 --> 00:50:32.720
when we dig snow pits, we do
something called a stability test.

00:50:32.720 --> 00:50:37.880
So you can basically isolate a column.
And previously, we would just isolate a

00:50:37.880 --> 00:50:41.529
30-centimeter-by-30-centimeter column.
So 1 foot by 1 foot.

00:50:41.529 --> 00:50:44.470
And we’d take our shovel – our
avalanche shovel and set it on the top.

00:50:44.470 --> 00:50:47.130
And you sort of tap on it
to apply stress, right?

00:50:47.130 --> 00:50:50.670
And so you’re looking to
see if that weak layer, or any layer,

00:50:50.670 --> 00:50:55.670
in the snowpack breaks.
So about 10 or 12 years ago,

00:50:55.670 --> 00:51:00.140
sort of using mixed-mode propagation, 
where we’re not just looking at –

00:51:00.140 --> 00:51:04.140
we’re not looking at shear.
We’re also looking at collapse.

00:51:04.140 --> 00:51:08.559
And so what they found is, if you
take a block, now 30 centimeters back,

00:51:08.559 --> 00:51:13.599
but 90 centimeters wide, we can actually
look at not just the fracture part of

00:51:13.599 --> 00:51:17.109
that equation, but also propagation.
And that’s really what we want to

00:51:17.109 --> 00:51:21.500
know is, yeah, it might break, but is it
actually going to propagate across?

00:51:21.500 --> 00:51:25.029
So, again, we’re using a small block
that may or may not be representative.

00:51:25.029 --> 00:51:28.520
It’s just a small point.
Especially with spatial variability.

00:51:28.520 --> 00:51:32.519
But it gives us a better idea
of how likely is that weak layer

00:51:32.520 --> 00:51:35.380
to not just fracture
but also propagate?

00:51:35.380 --> 00:51:40.040
So, yeah, those guys have been doing a
lot of work with fracture mechanics.

00:51:40.040 --> 00:51:41.799
- Thank you.

00:51:41.800 --> 00:51:46.440
I was curious why you
chose the photography over Lidar?

00:51:47.720 --> 00:51:52.819
- Yeah. So the – right now –
we actually have Lidar – or have

00:51:52.819 --> 00:51:59.009
flown Lidar along the entire canyon.
That was in the summer.

00:51:59.009 --> 00:52:04.410
So we have a reference –
digital model that we can use.

00:52:04.410 --> 00:52:07.900
Problem with – we want to – we want to
sample on a relatively short time scale.

00:52:07.900 --> 00:52:10.990
So we’re talking, you know, maybe
every week or every couple weeks,

00:52:10.990 --> 00:52:16.000
or even more frequent than that.
To be able to – you know, typically,

00:52:16.000 --> 00:52:20.640
Lidar is flown from
a fixed-wing aircraft.

00:52:20.640 --> 00:52:25.020
And so, as it’s flying – or, just to get
it in the air is incredibly expensive.

00:52:25.020 --> 00:52:28.819
And then to process all of those
data are really expensive as well.

00:52:28.820 --> 00:52:32.680
So the bottom line there is
that it is cost-prohibitive.

00:52:32.680 --> 00:52:36.020
If you’re sampling a large area,
it’s well worth it, but the frequency

00:52:36.020 --> 00:52:40.579
that we want to sample, it’s just not
economically or fiscally responsible.

00:52:40.579 --> 00:52:43.099
- Not until the instruments are,
like, pint-sized, right?

00:52:43.099 --> 00:52:45.700
- Exactly. Yeah, so and I –
you know, we’ve looked into,

00:52:45.700 --> 00:52:50.700
are there small Lidar units
available to put on these drones?

00:52:50.700 --> 00:52:53.700
And I think folks are in the process
of trying to develop them.

00:52:53.700 --> 00:52:57.180
And actually, there are small Lidar units,
but they’re just – they’re just not that

00:52:57.180 --> 00:52:59.979
great right now in terms of
the accuracy that we want.

00:52:59.979 --> 00:53:03.900
So right now we’re – yeah, we’re just
plunking down a camera and using that.

00:53:03.900 --> 00:53:06.340
And it works really well. So far.
[chuckles]

00:53:06.340 --> 00:53:07.960
- Thank you.
- Yeah, thanks.

00:53:12.400 --> 00:53:14.120
One more?
[chuckles]

00:53:14.120 --> 00:53:15.760
- Here’s a fun question.
- Uh-oh.

00:53:15.760 --> 00:53:19.900
- Have you ever [static sounds]
been in an avalanche or [inaudible]

00:53:19.900 --> 00:53:23.440
actually surf out of
an avalanche? [laughs]

00:53:23.440 --> 00:53:26.680
- Yeah, so the first part of that
question is, unfortunately, I have been.

00:53:26.690 --> 00:53:30.940
And it was, thankfully – well, maybe
I shouldn’t say – it has been twice.

00:53:30.940 --> 00:53:36.340
And they were small avalanches.
It was early in my career. [laughter]

00:53:36.340 --> 00:53:40.519
So they were relatively small,
and I wasn’t buried, which is good.

00:53:40.519 --> 00:53:46.309
And they were – you know, I like to
think that I chose these sort of small,

00:53:46.309 --> 00:53:50.509
low-consequence slopes, and
that’s where I was testing things.

00:53:50.509 --> 00:53:54.720
And it was actually during –
when I was conducting a stability test,

00:53:54.720 --> 00:54:00.950
and it was just right after that.
But, again, they were really small slopes.

00:54:00.950 --> 00:54:05.470
So can you surf out of an avalanche?
You know, it really depends.

00:54:05.470 --> 00:54:08.600
Sometimes – a lot of it
depends on the debris flow.

00:54:08.600 --> 00:54:13.540
And within, again, the past
10 to 15 years, there has been a

00:54:13.549 --> 00:54:17.349
development in technology called
a balloon pack, or an airbag pack.

00:54:17.349 --> 00:54:20.920
And so you basically have a
backpack on, and it has a little ripcord.

00:54:20.920 --> 00:54:24.749
And it’s powered by
either a fan or a gas cylinder.

00:54:24.749 --> 00:54:27.410
And you can pull this ripcord,
and you basically have a big balloon

00:54:27.410 --> 00:54:32.509
that – a big airbag, basically,
that blows up right around your head.

00:54:32.509 --> 00:54:34.490
So you have this big
balloon around your head.

00:54:34.490 --> 00:54:37.172
And the theory there being is that
these – sort of like the Brazil nut effect,

00:54:37.172 --> 00:54:39.819
that you have these – you know,
the Brazil nuts always end up on the

00:54:39.820 --> 00:54:42.080
top in your mixed nuts canister.
[laughter]

00:54:42.080 --> 00:54:46.859
And so the – you basically get to –
you get basically pushed to the surface

00:54:46.859 --> 00:54:50.609
as you get mangled through
the avalanche debris.

00:54:50.609 --> 00:54:55.620
So, you know, if you’re not –
if you’re not injured, or if you don’t die

00:54:55.620 --> 00:55:01.780
by trauma, then, you know, they do
help with, you know, survival rates.

00:55:01.780 --> 00:55:03.569
And they’re not the
silver bullet, by any means.

00:55:03.569 --> 00:55:06.020
You know, people have been
fully buried while still wearing

00:55:06.020 --> 00:55:09.109
an avalanche balloon pack,
or an airbag pack.

00:55:09.109 --> 00:55:12.880
And so they’re not a silver bullet,
but they do help.

00:55:12.880 --> 00:55:18.349
If you don’t have one, you know,
the advice from sort of age-old

00:55:18.349 --> 00:55:22.100
avalanche hunters is that, you know,
you just got to – if you’re caught in one,

00:55:22.100 --> 00:55:26.880
you fight, and you just try
and fight to stay near the surface.

00:55:26.880 --> 00:55:30.280
And again, that’s much
easier said than done.

00:55:30.280 --> 00:55:36.260
And, yeah, they’re really powerful –
really powerful things.

00:55:39.580 --> 00:55:44.600
- Any other questions tonight for
Erich about snow avalanches?

00:55:46.880 --> 00:55:49.100
Well, I want to thank you
all for coming and joining us.

00:55:49.100 --> 00:55:50.720
[Applause]

00:55:50.720 --> 00:55:54.460
And especially I want to thank Erich
Peitzsch for such an enlightening talk.

00:55:54.460 --> 00:55:55.880
[Applause]

00:55:55.880 --> 00:55:58.440
Thank you.
- Thanks, everyone. I appreciate it.

00:55:59.720 --> 00:56:06.420
[Silence]