WEBVTT

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Drew Decker - Today's
discussion, as you can see here,

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is going to be Strategies for
Improving the Washington State

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hydrography dataset, or Wash-D.
I believe I'm saying that

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correctly.

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And today's presenter is of
course Joshua Greenberg with

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Washington Department of
Ecology.

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Joshua is the Washington
Hydrography steward and he had

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provided a nice bio background
earlier which we put into the

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meeting announcement, and I was
showing it earlier.

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I don't think I need to read
that. Most everyone here knows

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Joshua and we're very happy to
have him here.

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So, if there are any immediate
questions or announcements

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anybody needs to make, please
let us know.

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But we'll go ahead and get
started in just a second.

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Please be sure to mute your
phones and turn off your camera

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if you're not presenting or
asking a question.

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And I think we are ready to go.

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And Joshua, if you if you're
ready, I think you can go ahead

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and take it away.

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Joshua Greenberg - All right.

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Thanks, Drew and thank you so
much for having us to present

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today.

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I'm going to be covering some of
the work that we've been

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struggling through,

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although it's been a great
experience.

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I have been with Ecology almost
three years now.

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I came in right before the 3DHP
announcement and so it's been a

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fun and interesting ride going
through this transition.

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Just wanted to talk a little bit
today about our experiences and

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what we've been doing for the
last year and a half on some

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project work.

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And also, I plan to have about
45 minutes' worth of

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presentation and that hopefully
will allow time for questions,

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if there are, I'll try and keep
an eye on the chat as well in

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case there's something immediate
that comes up.

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So with that I just wanted to
dive right in and talk about

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that

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water is very important in
Washington State.

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We get a lot of it falling on
us, particularly in the western

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part of the state where annually
we get about 11 feet of

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precipitation.

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The eastern part of the state is
quite a bit drier, but this

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creates an amazing amount of
stream networks within the

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state.

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We have almost a quarter million
miles of NHD to begin with and

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so where the water location is,
is important.

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And back in 2009, Washington and
Oregon together created an MOU

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with USGS to be stewards for the
NHD program.

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And in 2011 we had an OCIO
policy, a statewide IT policy,

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that says that the NHD would be
the standard hydrography data

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set to be used by all state
agencies.

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In 2015, our Fish and Wildlife
and Northwest Indian Fisheries

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Commission started using the NHD
to link the fish distribution

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data and they are probably one
of the best examples that we

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have of how data can be
addressed to NHD, although there

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are quite a few other datasets.

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NHD has a history within
Washington and it has been a

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very important dataset.

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When I came on, one of our goals
was to start creating a program

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and go beyond just being a
steward that moves data to the

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USGS, but to create more of a
program.

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And we we thought that a good
starting point would be a

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strategic plan.

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This is still a draft strategic
plan, but I wanted to share with

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you the vision which is a single
hydrography data layer for

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Washington State.

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And even though we have that
OCIO policy that says all state

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agencies must use the NHD there,
we found that in reviews done by

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our Fish and Wildlife group that
very few of the cities and

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counties were using NHD. That
they all have their own

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variations of hydrography data
and that statewide, outside of

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the agencies, NHD was not always
being heavily used.

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So, one of the other things we
started doing, and I can't

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emphasize how important this is,
is reaching out to our

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stakeholders.

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And we currently have about 150
people signed up on our

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stakeholder meeting
announcements.

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40% of those are from local
government.

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That same group that I just said
have not historically been using

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NHD extensively.

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And so that's really reassuring.

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We also have state agencies,
tribal participation, as well as

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universities, consulting firms,
all in that stakeholder feedback

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group where we talk about what
people need and what is

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available.

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And it's been very helpful as we
go through this transition from

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NHD to 3DHP to have these
information meetings. In the

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feedback we got was resoundingly
that what people need from

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hydrography data is accurate
information, accurate location.

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And that was one of the things,
that for better for worse, was

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missing in our NHD.

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It was a great dataset.

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It still is a great dataset, but
the accuracy was not to the

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level that would be useful for
state and local government.

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I'm sorry - for local
government, for the cities and

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counties when they're trying to
do setbacks for planning and

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permitting and things like that.

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So, they also mentioned though,
connected attributes,

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accessibility, and
communication.

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And so we've been keeping this
feedback in our minds as we are

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going through and talking about
how do we structure our

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long-term plans and what do we
need to support moving forward.

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This is just a quick map showing
the distribution of our

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stakeholders and mostly just
want to show that we have a very

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strong participation rate in the
Puget Sound area, Seattle,

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Olympia, up the Bellingham and
that is where 60% of the

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population of Washington
resides.

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But we also are trying to make
sure that this is a statewide

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plan.

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We want to make sure that all
streams are being mapped,

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whether there are resources
within that community or not.

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This gets to some of our desires
of having equity in data

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creation and sharing.

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So many of you have seen this,
but like I mentioned, after I

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started, it wasn't too long that
USGS came out with the plan for

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the 3DHP which will supersede
NHD, WBD, and NHDPlus HR. And

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we'd actually already started
our project, but we were luckily

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this came out at a time when we
were able to pivot that project

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from just an elevation-derived
hydro to elevation-derived hydro

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to feed into the specifications
of 3DHP.

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And I'm probably not going to
spend too much time on this, but

e352f0ce-2547-4628-81ef-f6a9437c4b75-1
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that transition where the NHD
has now stopped, takes some load

e352f0ce-2547-4628-81ef-f6a9437c4b75-2
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off of myself because I'm not
supporting updating NHD anymore.

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NHD is now static. And so, what
we've been able to do is focus

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on the future which is the 3DHP.
Which we hope -

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I know there's already been a
service created for that and

8a237a98-80b8-4ab6-8e2a-6c69f1b3d7b8-1
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we've been looking at that, but
I think things will become a

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little bit more solid in 2024.

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And also, the decision to
include all NHD lines and

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polygons in the 3DHP was really
helpful.

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I know that was a change that
USGS made after some feedback,

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but that's really been helpful
for us as we try and talk about

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00:08:18.468 --> 00:08:20.520
the transition from NHD to 3DHP.

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So, I want to talk a little bit
about this project that was two

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years of funding that we got
from the state originally to

410a4edc-f4bc-4283-a7f1-15b8d434d4c5-2
00:08:30.425 --> 00:08:34.567
look at what are the techniques
and methods for updating

410a4edc-f4bc-4283-a7f1-15b8d434d4c5-3
00:08:34.567 --> 00:08:35.440
hydrography.

e51c5fe8-5013-4ecb-a784-e40e800521d1-0
00:08:35.440 --> 00:08:40.000
And like I said, 'accuracy' was
the resounding word.

b6f99e9e-a959-400f-af7f-b9cd421d6dfb-0
00:08:40.000 --> 00:08:42.928
So we are interested in
location, location, location.

b6f99e9e-a959-400f-af7f-b9cd421d6dfb-1
00:08:42.928 --> 00:08:46.291
And I wanted to talk a little
bit about what we have found in

b6f99e9e-a959-400f-af7f-b9cd421d6dfb-2
00:08:46.291 --> 00:08:49.600
that pilot project and a little
bit about the pilot project.

fab51a50-e12a-47a3-bae5-9a8a2c06d60b-0
00:08:49.960 --> 00:08:53.972
So, first off, I want to address
that elevation-derived

fab51a50-e12a-47a3-bae5-9a8a2c06d60b-1
00:08:53.972 --> 00:08:57.627
hydrography is a fundamental
change in how we have

fab51a50-e12a-47a3-bae5-9a8a2c06d60b-2
00:08:57.627 --> 00:08:59.920
historically mapped hydrography.

33cb1a7d-e003-4950-a428-0529ae061af1-0
00:09:00.160 --> 00:09:04.490
We used to use aerial
photography. We used to use on

33cb1a7d-e003-4950-a428-0529ae061af1-1
00:09:04.490 --> 00:09:07.840
the ground surveys, and visits,
and GPS.

9287c637-60a6-44f5-87e6-9d0b2e553afb-0
00:09:08.280 --> 00:09:16.123
But EDH is really a model. And
it models where we expect water

9287c637-60a6-44f5-87e6-9d0b2e553afb-1
00:09:16.123 --> 00:09:17.120
to flow.

6fb2655f-f4ea-4652-8abc-31e6573bc546-0
00:09:17.920 --> 00:09:20.040
And I I love this.

63527aa4-c833-4e7a-9ab4-d7b900cef4f4-0
00:09:22.680 --> 00:09:24.720
I'm a Monty Python fan.

c3a47b43-89cd-46d0-b834-e7ddc2923ffc-0
00:09:24.720 --> 00:09:27.040
And so this "EDH, EDH, EDH.

ed35efe6-1e56-4466-9ec8-a4feaa8b8a10-0
00:09:27.160 --> 00:09:29.960
It's only a model."

621d5c5d-6b72-49cd-8652-fa4b9e73cfc6-0
00:09:30.160 --> 00:09:36.960
And I want to be clear that you
know that this model is

dafb78eb-7e61-40b3-b51a-f1378fd379ba-0
00:09:36.960 --> 00:09:41.518
a prediction of where we expect
water to flow. And as the

dafb78eb-7e61-40b3-b51a-f1378fd379ba-1
00:09:41.518 --> 00:09:46.313
British statistician, George
Fox, once said, "all models are

dafb78eb-7e61-40b3-b51a-f1378fd379ba-2
00:09:46.313 --> 00:09:48.200
wrong, some are useful."

3536e7bf-e606-48b6-b5f7-f990037c37bc-0
00:09:48.800 --> 00:09:52.055
And his point is that we should
focus more on whether something

3536e7bf-e606-48b6-b5f7-f990037c37bc-1
00:09:52.055 --> 00:09:55.260
can be applied to everyday life
in a useful manner rather than

3536e7bf-e606-48b6-b5f7-f990037c37bc-2
00:09:55.260 --> 00:09:58.160
debating endlessly if an answer
is correct in all cases.

3b77925e-1afa-4f25-b99a-a7e1fd51d6e3-0
00:09:58.160 --> 00:10:02.633
And that is the approach we are
taking going into this

3b77925e-1afa-4f25-b99a-a7e1fd51d6e3-1
00:10:02.633 --> 00:10:07.026
evaluation of EDH and
particularly I will admit I had

3b77925e-1afa-4f25-b99a-a7e1fd51d6e3-2
00:10:07.026 --> 00:10:10.686
a lot of concerns about the
effectiveness of

3b77925e-1afa-4f25-b99a-a7e1fd51d6e3-3
00:10:10.686 --> 00:10:15.160
elevation-derived hydro in all
parts of the landscape.

6e321949-a772-4bcd-9c26-baa816e597c5-0
00:10:15.520 --> 00:10:20.081
So, in Washington we have our
mountainous areas, and I was

6e321949-a772-4bcd-9c26-baa816e597c5-1
00:10:20.081 --> 00:10:24.642
pretty sure that in steep
terrain the EDH approaches would

6e321949-a772-4bcd-9c26-baa816e597c5-2
00:10:24.642 --> 00:10:25.879
work quite well.

52adf602-e103-425b-b36b-2e0fb01e15ed-0
00:10:25.880 --> 00:10:30.059
Where I was very concerned is in
the low elevations,

52adf602-e103-425b-b36b-2e0fb01e15ed-1
00:10:30.059 --> 00:10:34.317
human-modified areas, dynamic
alluvial hydrology, and

52adf602-e103-425b-b36b-2e0fb01e15ed-2
00:10:34.317 --> 00:10:39.443
agricultural areas that we would
see things just completely fall

52adf602-e103-425b-b36b-2e0fb01e15ed-3
00:10:39.443 --> 00:10:42.440
apart and that it wouldn't be
useful.

90396efe-8697-4c47-b4ca-ddec85eeaf1e-0
00:10:42.440 --> 00:10:43.520
So, we did,

9aedbc90-6632-449f-ab3e-e883eb9c7510-0
00:10:43.520 --> 00:10:46.480
I will admit, went into this
with skepticism.

0d9cf6cb-ec5a-4278-9106-2ffef03744c9-0
00:10:51.640 --> 00:10:52.880
Sorry, I think I got muted.

f1107f4a-38eb-4cce-9555-869f28a2e222-0
00:10:53.440 --> 00:11:00.030
We wanted to create a process to
look at the 3DHP objectively

f1107f4a-38eb-4cce-9555-869f28a2e222-1
00:11:00.030 --> 00:11:06.939
and, to be quite honest, we did
not have in our plan that we had

f1107f4a-38eb-4cce-9555-869f28a2e222-2
00:11:06.939 --> 00:11:08.640
to move to 3DHP.

d4bff59f-6733-49da-8604-d18d53767512-0
00:11:08.920 --> 00:11:13.281
We were thinking if it doesn't
work for us, we may have to move

d4bff59f-6733-49da-8604-d18d53767512-1
00:11:13.281 --> 00:11:14.440
to another model.

535cb92a-c8a4-45f8-9d3c-9943a675982e-0
00:11:19.080 --> 00:11:23.440
So, we have a two-year project,
the "Stream Mapping Assessment."

da895d08-e06e-4294-9f7a-c0a935d39e87-0
00:11:23.440 --> 00:11:27.365
The first year was working with
a contractor. We selected NV5 to

da895d08-e06e-4294-9f7a-c0a935d39e87-1
00:11:27.365 --> 00:11:29.600
do our elevation-derived hydro
work.

a429bfb1-7209-4c93-a040-951208c3307f-0
00:11:29.880 --> 00:11:34.377
They are a GPSC contractor with
USGS and quite familiar with the

a429bfb1-7209-4c93-a040-951208c3307f-1
00:11:34.377 --> 00:11:37.560
specifications of what needs to
go into 3DHP.

c8795099-13d0-4402-baaf-1a9b6955cc7f-0
00:11:38.200 --> 00:11:42.308
And our charter was to identify
the best methods, data, and

c8795099-13d0-4402-baaf-1a9b6955cc7f-1
00:11:42.308 --> 00:11:46.690
resources - particularly cost -
needed to accurately update and

c8795099-13d0-4402-baaf-1a9b6955cc7f-2
00:11:46.690 --> 00:11:50.388
maintain the Washington
Hydrography dataset statewide

c8795099-13d0-4402-baaf-1a9b6955cc7f-3
00:11:50.388 --> 00:11:54.360
and to execute this pilot in the
Stillaguamish watershed.

2c51a472-71fa-4f16-82be-796f9ea9e6dd-0
00:11:54.360 --> 00:11:56.920
And I'll talk a little bit more
about that watershed.

1c22fb4d-f0f2-4b67-bbcd-38f94de435bd-0
00:11:57.400 --> 00:12:01.698
And we also are interested in
tools and processes needed for

1c22fb4d-f0f2-4b67-bbcd-38f94de435bd-1
00:12:01.698 --> 00:12:05.644
stakeholders to use the
hydrography dataset and that is

1c22fb4d-f0f2-4b67-bbcd-38f94de435bd-2
00:12:05.644 --> 00:12:08.040
that accessibility that we
heard.

4cc6d9ec-f164-4a14-b119-af2d1c45b5b9-0
00:12:08.320 --> 00:12:11.699
It's one thing if you have a
dataset, but if no one can use

4cc6d9ec-f164-4a14-b119-af2d1c45b5b9-1
00:12:11.699 --> 00:12:13.840
it, it's not achieving the main
goal.

b7418971-8e37-4e64-a057-b5b9e2bee0ae-0
00:12:13.840 --> 00:12:17.639
So we wanted to make sure that
this was both accurate and

b7418971-8e37-4e64-a057-b5b9e2bee0ae-1
00:12:17.639 --> 00:12:18.360
accessible.

99aa6a68-3205-4da8-b359-c123cbc2e2ec-0
00:12:18.640 --> 00:12:23.457
And as Steve Aichele has said,
the NHD became a bearcat of a

99aa6a68-3205-4da8-b359-c123cbc2e2ec-1
00:12:23.457 --> 00:12:28.116
database that has grown over
years and with related tables

99aa6a68-3205-4da8-b359-c123cbc2e2ec-2
00:12:28.116 --> 00:12:30.960
and lots of complicated
attributes.

5cafec58-0a26-4616-895c-8594d560c09b-0
00:12:31.120 --> 00:12:33.568
We wanted to make sure that we
didn't make something that was

5cafec58-0a26-4616-895c-8594d560c09b-1
00:12:33.568 --> 00:12:34.200
worse than that.

7dc46495-4b9e-483b-988a-0cc7d3afbcff-0
00:12:34.200 --> 00:12:36.931
We wanted to make sure that we
were on a path to making

7dc46495-4b9e-483b-988a-0cc7d3afbcff-1
00:12:36.931 --> 00:12:38.200
something more accessible.

33f666df-ee75-4765-9f19-b0db207891a1-0
00:12:39.080 --> 00:12:43.199
We picked the Stillaguamish
watershed, which is north of

33f666df-ee75-4765-9f19-b0db207891a1-1
00:12:43.199 --> 00:12:47.173
Seattle, south of Bellingham,
because it was a compact

33f666df-ee75-4765-9f19-b0db207891a1-2
00:12:47.173 --> 00:12:51.509
watershed, goes from the Cascade
ridges down to the Olympic

33f666df-ee75-4765-9f19-b0db207891a1-3
00:12:51.509 --> 00:12:54.400
Sound, the Puget Sound, the
Salish Sea.

9be11319-78ad-43d2-89f5-7b3137f65d50-0
00:12:54.720 --> 00:13:00.800
So, it has from Ridge to the
ocean, a complete watershed.

0810d5e2-6667-4348-9555-41ec64fed0fb-0
00:13:00.800 --> 00:13:06.196
We had QL1 lidar for the entire
watershed except for a couple

0810d5e2-6667-4348-9555-41ec64fed0fb-1
00:13:06.196 --> 00:13:10.200
small spots. And it has a
diverse land cover.

809d9145-f22f-448a-958c-9aa1dcf94641-0
00:13:10.200 --> 00:13:14.565
It has both forested lands,
agricultural lands, and some

809d9145-f22f-448a-958c-9aa1dcf94641-1
00:13:14.565 --> 00:13:16.480
suburban developed lands.

b16f95da-95b1-4f16-9e65-7cad79f07031-0
00:13:16.480 --> 00:13:18.280
So, it was a nice test

40a2d440-0259-44f4-91ad-fa7c522f7f7f-0
00:13:18.280 --> 00:13:21.994
watershed to at least
representing the Puget Sound. It

40a2d440-0259-44f4-91ad-fa7c522f7f7f-1
00:13:21.994 --> 00:13:25.777
does not represent eastern
Washington very well, but it

40a2d440-0259-44f4-91ad-fa7c522f7f7f-2
00:13:25.777 --> 00:13:30.100
does represent a lot of western
Washington. And our process was

40a2d440-0259-44f4-91ad-fa7c522f7f7f-3
00:13:30.100 --> 00:13:33.680
to take as much data as we could
find and review it.

4de1a62c-edcf-4230-81ce-a304baa371de-0
00:13:34.560 --> 00:13:38.666
The primary dataset that we were
looking at was the

4de1a62c-edcf-4230-81ce-a304baa371de-1
00:13:38.666 --> 00:13:43.720
elevation-derived hydro that NV5
created specifically for 3DHP.

ca71eee7-797e-4844-bc2d-b84ed7441133-0
00:13:43.960 --> 00:13:46.200
But we also wanted to compare
other methods.

e8f3eba8-ba66-4c33-a7e1-663540746fd1-0
00:13:46.200 --> 00:13:50.072
We worked with the University of
Maryland's Professor Matt Baker

e8f3eba8-ba66-4c33-a7e1-663540746fd1-1
00:13:50.072 --> 00:13:51.800
with his geomorphon approach.

2034dd26-5466-4b86-a1bf-cedd5859181a-0
00:13:52.360 --> 00:13:55.160
We worked with US Forest Service
and BLM.

8db09c37-3361-4406-9812-54e8c381d2a3-0
00:13:55.320 --> 00:13:59.811
We collected a lot of local data
from both Snohomish County,

8db09c37-3361-4406-9812-54e8c381d2a3-1
00:13:59.811 --> 00:14:04.376
which had done extensive work of
mapping hydro hydrography in

8db09c37-3361-4406-9812-54e8c381d2a3-2
00:14:04.376 --> 00:14:08.720
that area, as well as WDFW and
our tribal interest groups.

3e0d2b43-48dd-4f6d-a62e-251ce01ab120-0
00:14:09.120 --> 00:14:12.779
So we had a lot of different
data to compare as well as

3e0d2b43-48dd-4f6d-a62e-251ce01ab120-1
00:14:12.779 --> 00:14:13.760
aerial imagery.

50ef1e53-5b6f-4b1b-8147-1559f811a4ab-0
00:14:13.920 --> 00:14:17.339
We looked at hillshade. And we
took all of that and we reviewed

50ef1e53-5b6f-4b1b-8147-1559f811a4ab-1
00:14:17.339 --> 00:14:20.811
to compare against the standard,
which was the data that we were

50ef1e53-5b6f-4b1b-8147-1559f811a4ab-2
00:14:20.811 --> 00:14:21.720
getting from EDH.

baf39f29-83a2-4cb1-9743-420717a5cf60-0
00:14:22.640 --> 00:14:25.278
We also had a technical
committee that would help us

baf39f29-83a2-4cb1-9743-420717a5cf60-1
00:14:25.278 --> 00:14:28.065
with some of the technical
issues and we had a steering

baf39f29-83a2-4cb1-9743-420717a5cf60-2
00:14:28.065 --> 00:14:29.360
committee that would meet.

02ebe4bb-88ae-4539-9ac6-3d23ba5c0619-0
00:14:29.360 --> 00:14:31.160
Both of these groups would meet
monthly.

44754faa-6d29-42e9-910c-8c07a3e8d828-0
00:14:31.360 --> 00:14:35.320
They were representations of
state agencies and local

44754faa-6d29-42e9-910c-8c07a3e8d828-1
00:14:35.320 --> 00:14:38.400
government that could review the
process.

1e0905d5-5832-4dee-b1d6-fac27b8db9ce-0
00:14:38.560 --> 00:14:42.280
Steering committee looking at
the big picture and direction,

1e0905d5-5832-4dee-b1d6-fac27b8db9ce-1
00:14:42.280 --> 00:14:46.123
technical committee looking at
the more details. And I'm going

1e0905d5-5832-4dee-b1d6-fac27b8db9ce-2
00:14:46.123 --> 00:14:49.600
to just jump right into some of
the results that we got.

5165d5db-4860-4685-9f6a-2be0da4dc344-0
00:14:49.600 --> 00:14:54.920
So, we did the work for the
first year, The second year,

5165d5db-4860-4685-9f6a-2be0da4dc344-1
00:14:54.920 --> 00:14:57.440
from July 1st of this year,

b79bf516-cff6-416a-a187-fdbb22cbfefe-0
00:14:57.680 --> 00:15:01.125
we have been assessing the
results and putting together a

b79bf516-cff6-416a-a187-fdbb22cbfefe-1
00:15:01.125 --> 00:15:04.750
final report which is a draft
but it's getting close, and we

b79bf516-cff6-416a-a187-fdbb22cbfefe-2
00:15:04.750 --> 00:15:08.195
hope to make this report
something that will be available

b79bf516-cff6-416a-a187-fdbb22cbfefe-3
00:15:08.195 --> 00:15:09.800
to anyone who's interested.

0b7ab930-b49d-4079-8f92-604a3eb841fa-0
00:15:10.240 --> 00:15:13.623
It's quite long because we are
trying to cover a lot of what

0b7ab930-b49d-4079-8f92-604a3eb841fa-1
00:15:13.623 --> 00:15:17.172
I'm talking about today with the
background and it has a lot of

0b7ab930-b49d-4079-8f92-604a3eb841fa-2
00:15:17.172 --> 00:15:19.280
the graphics that I'll be
presenting.

c9859c94-2b96-4408-95ff-189b481d10fa-0
00:15:20.440 --> 00:15:24.608
So this is the result of the
comparing the elevation-derived

c9859c94-2b96-4408-95ff-189b481d10fa-1
00:15:24.608 --> 00:15:28.640
hydro that we got from NV5 to
all of those other datasets.

421e07ab-27cf-4968-86d3-a7206d3c41e7-0
00:15:28.640 --> 00:15:33.320
And we have a fantastic team,
and we went through and reviewed

421e07ab-27cf-4968-86d3-a7206d3c41e7-1
00:15:33.320 --> 00:15:34.880
every single segment.

f74b7dee-3e9c-4dc9-a36c-a96d7b18ab96-0
00:15:35.680 --> 00:15:40.487
There were 7,000 miles of
streams that were mapped, and we

f74b7dee-3e9c-4dc9-a36c-a96d7b18ab96-1
00:15:40.487 --> 00:15:44.480
were looking at all the
different data remotely.

fed6ef56-d1a5-43c3-94e3-f0f1aa09c9ce-0
00:15:44.480 --> 00:15:48.844
So, we did not do a lot of field
or on the ground research but

fed6ef56-d1a5-43c3-94e3-f0f1aa09c9ce-1
00:15:48.844 --> 00:15:52.863
remote using all the best
available information. We found

fed6ef56-d1a5-43c3-94e3-f0f1aa09c9ce-2
00:15:52.863 --> 00:15:56.742
that there was only 1.6% of
those segments that we felt

fed6ef56-d1a5-43c3-94e3-f0f1aa09c9ce-3
00:15:56.742 --> 00:15:58.960
could have an improved location.

d3b292b7-3241-43a2-b937-3f687d8fc0a4-0
00:15:59.160 --> 00:16:02.265
Not that the entire segment was
wrong, but that something was

d3b292b7-3241-43a2-b937-3f687d8fc0a4-1
00:16:02.265 --> 00:16:04.720
wrong with that - somewhere
within that segment.

a5434e69-7753-4d35-af1e-d139d00dcfbb-0
00:16:05.320 --> 00:16:09.786
And we've had another category
that was about 2 1/2% where we

a5434e69-7753-4d35-af1e-d139d00dcfbb-1
00:16:09.786 --> 00:16:14.325
couldn't really sense where a
better path for the stream would

a5434e69-7753-4d35-af1e-d139d00dcfbb-2
00:16:14.325 --> 00:16:17.640
be, but we felt like it needed a
field check.

8a753949-b036-4dcc-bf52-4fe05c4e3fa1-0
00:16:17.960 --> 00:16:21.620
A lot of times this was places
where streams went subsurface or

8a753949-b036-4dcc-bf52-4fe05c4e3fa1-1
00:16:21.620 --> 00:16:24.880
maybe through a pipe system and
it just was not obvious.

3d0df171-c88e-4a81-a9ff-d97dd6917228-0
00:16:25.160 --> 00:16:29.405
But it was a very small percent.
That left about 72,000 segments

3d0df171-c88e-4a81-a9ff-d97dd6917228-1
00:16:29.405 --> 00:16:33.520
that we felt were quite accurate
and we were pretty impressed.

c337307b-bf42-4280-b692-96b306bf5323-0
00:16:34.160 --> 00:16:38.055
And I'll say even I was
surprised at how accurate in

c337307b-bf42-4280-b692-96b306bf5323-1
00:16:38.055 --> 00:16:40.040
this data turned out to be.

a9692153-4f23-46f4-9eec-0a16be638c3f-0
00:16:41.240 --> 00:16:46.503
We did find that through this
process we essentially doubled

a9692153-4f23-46f4-9eec-0a16be638c3f-1
00:16:46.503 --> 00:16:51.680
the blue lines from NHD to the
elevation-derived 3DHP data.

3f9e378d-6da8-4b08-b7f8-420f4e15e221-0
00:16:51.680 --> 00:16:56.226
So a doubling in the length. In
this case we're showing miles

3f9e378d-6da8-4b08-b7f8-420f4e15e221-1
00:16:56.226 --> 00:17:00.846
doubling in that length of the
blue lines. And some of that is

3f9e378d-6da8-4b08-b7f8-420f4e15e221-2
00:17:00.846 --> 00:17:04.440
I think mapping streams that
were missed before.

667d3146-f2a3-4c60-b847-ee18fdd60f5d-0
00:17:04.600 --> 00:17:08.539
But I also think the
elevation-derived hydro process

667d3146-f2a3-4c60-b847-ee18fdd60f5d-1
00:17:08.539 --> 00:17:12.478
allows us to extend a stream
probably beyond what we

667d3146-f2a3-4c60-b847-ee18fdd60f5d-2
00:17:12.478 --> 00:17:15.600
initially would call an
initiation point.

dc8cdc42-9737-4bea-8b1c-e2bbccb6c441-0
00:17:16.440 --> 00:17:20.661
These might be places where the
water only flows certain times

dc8cdc42-9737-4bea-8b1c-e2bbccb6c441-1
00:17:20.661 --> 00:17:24.213
of the year, but I think the
some of those headwater

dc8cdc42-9737-4bea-8b1c-e2bbccb6c441-2
00:17:24.213 --> 00:17:26.760
extensions were part of this as
well.

7b1f3fce-4b1f-4003-8ac3-c1cd3540b5b6-0
00:17:27.400 --> 00:17:32.560
However, we did look at specific
streams for length changes.

020d0e1a-8d6b-4541-8f46-b8cc87537650-0
00:17:33.000 --> 00:17:37.173
What we found was just because
of the increased complexity.

020d0e1a-8d6b-4541-8f46-b8cc87537650-1
00:17:37.173 --> 00:17:41.278
That if you have a smaller
measuring tool, you're going to

020d0e1a-8d6b-4541-8f46-b8cc87537650-2
00:17:41.278 --> 00:17:42.599
have a longer line.

3b22ce8e-b564-4eff-8614-ed8d580db71b-0
00:17:42.600 --> 00:17:46.811
It's that the British coastline
example that we get in our GIS

3b22ce8e-b564-4eff-8614-ed8d580db71b-1
00:17:46.811 --> 00:17:47.480
101 class.

7055b429-9c56-480f-9afb-0a5ca0ad320b-0
00:17:48.040 --> 00:17:51.484
When you have a more detail,
you're going to have an increase

7055b429-9c56-480f-9afb-0a5ca0ad320b-1
00:17:51.484 --> 00:17:52.040
in length.

07846e98-b6de-49c9-b052-fe8a2108c6fa-0
00:17:52.360 --> 00:17:57.240
So when we looked, we saw an
increase in length of streams -

07846e98-b6de-49c9-b052-fe8a2108c6fa-1
00:17:57.240 --> 00:18:01.240
just because of complexity -
that were up to 18%.

a12f6bad-be18-456b-9d5d-c867eb2aaf18-0
00:18:01.320 --> 00:18:05.793
So, some of that increase in
length is because it's new blue

a12f6bad-be18-456b-9d5d-c867eb2aaf18-1
00:18:05.793 --> 00:18:09.240
lines and some of it is just
increased detail.

6857d7c7-3735-4a5a-8c19-2ffb097c6cf5-0
00:18:09.240 --> 00:18:14.061
When I saw someone mentioned
fractals and man I got so into

6857d7c7-3735-4a5a-8c19-2ffb097c6cf5-1
00:18:14.061 --> 00:18:18.320
fractals in grad school. It's
really exciting to see

06cf15c9-4b32-4eca-8f1e-2fe8628bf640-0
00:18:18.400 --> 00:18:21.520
here's a real-life example of
that

cbd86a96-0e9b-40e4-ba1c-27a467121b14-0
00:18:21.520 --> 00:18:26.138
in practice. We also were
curious about how different the

cbd86a96-0e9b-40e4-ba1c-27a467121b14-1
00:18:26.138 --> 00:18:30.200
elevation-derived hydro was from
the original NHD.

6eddbfbb-189b-4d42-acc9-355d0f287d55-0
00:18:30.640 --> 00:18:34.799
And the best approach that we
could come up to do this was to

6eddbfbb-189b-4d42-acc9-355d0f287d55-1
00:18:34.799 --> 00:18:37.080
compare segment stream by
stream.

c55eb4f4-2b79-411b-9b3a-fbb21ed0e365-0
00:18:37.080 --> 00:18:41.304
So we didn't want to make sure
that tribs coming in or if there

c55eb4f4-2b79-411b-9b3a-fbb21ed0e365-1
00:18:41.304 --> 00:18:45.000
was a new stream, that it didn't
impact our assessment.

5b8d9b63-2fe9-4ed6-a401-594673650929-0
00:18:45.000 --> 00:18:48.533
But we looked at the distance
that NHD was from

5b8d9b63-2fe9-4ed6-a401-594673650929-1
00:18:48.533 --> 00:18:53.172
elevation-derived hydro on the
same named stream and so we did

5b8d9b63-2fe9-4ed6-a401-594673650929-2
00:18:53.172 --> 00:18:57.884
some kind of buffer analysis and
what we found was for the most

5b8d9b63-2fe9-4ed6-a401-594673650929-3
00:18:57.884 --> 00:19:00.240
part the NHD was within 50 feet.

8f7f5f60-29a7-4522-ad45-ec94013d0d35-0
00:19:00.240 --> 00:19:03.771
Now there were definitely
examples where NHD was quite a

8f7f5f60-29a7-4522-ad45-ec94013d0d35-1
00:19:03.771 --> 00:19:06.560
bit further and we felt that was
reassuring.

8b259810-342d-44dc-b81a-1c0358dbde16-0
00:19:06.920 --> 00:19:10.517
But when we compared, we did
that same analysis on the

8b259810-342d-44dc-b81a-1c0358dbde16-1
00:19:10.517 --> 00:19:11.760
non-named streams. 

741ae018-274b-4fb5-862a-54545fc6e98f-0
00:19:11.760 --> 00:19:15.782
So, we went in and said, OK,
this stream in NHD matches this

741ae018-274b-4fb5-862a-54545fc6e98f-1
00:19:15.782 --> 00:19:20.002
stream in the elevation-derived
hydro and these are going to be

741ae018-274b-4fb5-862a-54545fc6e98f-2
00:19:20.002 --> 00:19:22.640
the smaller streams. They're not
named.

b0a115f9-abeb-45ce-a006-3c137de9b12c-0
00:19:23.040 --> 00:19:27.991
We did find that there was a lot
less, there was a bigger

b0a115f9-abeb-45ce-a006-3c137de9b12c-1
00:19:27.991 --> 00:19:28.760
distance.

c2b28d43-0ee4-42bf-af17-1f2dd246e731-0
00:19:28.760 --> 00:19:32.566
So essentially, we're assuming
that means NHD had a greater

c2b28d43-0ee4-42bf-af17-1f2dd246e731-1
00:19:32.566 --> 00:19:36.246
error in those smaller streams
and that's kind of what we

c2b28d43-0ee4-42bf-af17-1f2dd246e731-2
00:19:36.246 --> 00:19:39.989
expect to see because larger
streams are visible in aerial

c2b28d43-0ee4-42bf-af17-1f2dd246e731-3
00:19:39.989 --> 00:19:42.400
imagery. They have more
significance.

ab681d6c-25b0-4e78-b3df-87f9b29c8866-0
00:19:42.400 --> 00:19:44.553
They're probably the ones that
we were updating more

ab681d6c-25b0-4e78-b3df-87f9b29c8866-1
00:19:44.553 --> 00:19:45.000
frequently.

27332444-608a-4697-8d5c-cabc03f277ef-0
00:19:45.840 --> 00:19:48.710
But where we're seeing the big
improvement is in some of these

27332444-608a-4697-8d5c-cabc03f277ef-1
00:19:48.710 --> 00:19:49.440
smaller streams.

66ad4f62-0493-4583-8faf-6ddab1d9b084-0
00:19:51.040 --> 00:19:55.740
We were also interested in
comparing lower elevation with

66ad4f62-0493-4583-8faf-6ddab1d9b084-1
00:19:55.740 --> 00:20:01.008
upper elevation to see if there
were any divisions. Because like

66ad4f62-0493-4583-8faf-6ddab1d9b084-2
00:20:01.008 --> 00:20:05.871
I mentioned at the beginning, we
expected to see a lot more

66ad4f62-0493-4583-8faf-6ddab1d9b084-3
00:20:05.871 --> 00:20:10.814
errors in the lower elevations.
And we did not actually find

66ad4f62-0493-4583-8faf-6ddab1d9b084-4
00:20:10.814 --> 00:20:12.759
that it was significant.

d1e022d9-ad0b-42df-8fb1-843e483416f7-0
00:20:12.840 --> 00:20:14.640
It was not a big difference

8eef766b-46f5-45b5-bafa-a83594acbabf-0
00:20:15.080 --> 00:20:17.440
high elevation to low elevation
with the error rates.

1a6d6362-3772-4c66-a319-678a670d0bd4-0
00:20:17.840 --> 00:20:21.858
However, we did find that there
were a lot more new stream

1a6d6362-3772-4c66-a319-678a670d0bd4-1
00:20:21.858 --> 00:20:26.013
segments, a lot more blue lines
in the upper elevation areas

1a6d6362-3772-4c66-a319-678a670d0bd4-2
00:20:26.013 --> 00:20:27.240
than in the lower.

aa87eaa5-954b-4993-b361-34977e99b8c2-0
00:20:27.240 --> 00:20:31.926
So that suggests that those
tree-covered areas are where

aa87eaa5-954b-4993-b361-34977e99b8c2-1
00:20:31.926 --> 00:20:36.284
elevation-derived hydro is
modeling and mapping more

aa87eaa5-954b-4993-b361-34977e99b8c2-2
00:20:36.284 --> 00:20:39.080
hydrology than we had
previously.

e233c10e-8a8c-4524-a04c-fc1423020e85-0
00:20:39.200 --> 00:20:42.640
And I guess hindsight's always
2020.

4d709492-6814-4970-a45a-d866033fbe97-0
00:20:42.720 --> 00:20:44.680
Once I saw there's like, oh that
makes sense.

0ee8350d-b9fa-44ab-af80-5416fcc8ed3d-0
00:20:44.680 --> 00:20:47.674
Those are areas that were very
difficult to map. They're not

0ee8350d-b9fa-44ab-af80-5416fcc8ed3d-1
00:20:47.674 --> 00:20:47.920
open.

3264da4b-f269-44f4-9063-c2386bc27af6-0
00:20:48.200 --> 00:20:49.120
So it makes sense.

a33e6cd2-8306-4ab4-a9ca-aa03252abd4a-0
00:20:49.120 --> 00:20:54.040
But I was really surprised that
we did not see huge differences

a33e6cd2-8306-4ab4-a9ca-aa03252abd4a-1
00:20:54.040 --> 00:20:58.960
in the low elevation error rates
and the upper elevation rates.

4be150f1-115e-46c3-8c8c-e61adf195f9b-0
00:21:00.280 --> 00:21:05.963
But this does bring up some
issues that we'll kind of talk

4be150f1-115e-46c3-8c8c-e61adf195f9b-1
00:21:05.963 --> 00:21:07.120
about later.

d81b5b90-b93f-408f-b594-6d14660999ed-0
00:21:07.120 --> 00:21:11.580
How do you do conflation when,
in this example where we have

d81b5b90-b93f-408f-b594-6d14660999ed-1
00:21:11.580 --> 00:21:15.967
NHD in the green, and on the
part of the slide on the left,

d81b5b90-b93f-408f-b594-6d14660999ed-2
00:21:15.967 --> 00:21:20.061
you can see the green line and
the blue line very close

d81b5b90-b93f-408f-b594-6d14660999ed-3
00:21:20.061 --> 00:21:20.720
together.

d0bcc709-e77f-4d1d-95f9-0b804d150da1-0
00:21:20.720 --> 00:21:24.560
So that was the majority of what
we saw on the larger streams.

0d998438-5154-4858-9243-52a3e86e1f14-0
00:21:24.880 --> 00:21:27.913
But what do you do when things
are going sideways; when they're

0d998438-5154-4858-9243-52a3e86e1f14-1
00:21:27.913 --> 00:21:29.240
perpendicular to each other?

a9f181a6-4f85-48ff-a5ba-4dcd305a1001-0
00:21:29.240 --> 00:21:32.675
How do you take attributes from
that NHD line and try and put

a9f181a6-4f85-48ff-a5ba-4dcd305a1001-1
00:21:32.675 --> 00:21:35.779
those onto the new blue lines
And that is unfortunately

a9f181a6-4f85-48ff-a5ba-4dcd305a1001-2
00:21:35.779 --> 00:21:39.048
something we don't have a
solution for, but it's something

a9f181a6-4f85-48ff-a5ba-4dcd305a1001-3
00:21:39.048 --> 00:21:39.879
we're aware of.

534e2706-ef00-46e1-b033-98e92d96aa6f-0
00:21:39.880 --> 00:21:43.842
And so that's some things that
we are working on. And I think

534e2706-ef00-46e1-b033-98e92d96aa6f-1
00:21:43.842 --> 00:21:47.804
this is going to be some of our
challenges of moving from old

534e2706-ef00-46e1-b033-98e92d96aa6f-2
00:21:47.804 --> 00:21:51.000
NHD to this new improved
elevation-derived hydro.

c1f80157-7768-4b4d-977d-a0d3cb9ccb12-0
00:21:52.560 --> 00:21:56.786
Wanted to talk real quickly. We
did look at the polygon data as

c1f80157-7768-4b4d-977d-a0d3cb9ccb12-1
00:21:56.786 --> 00:22:00.815
well, the waterbodies. And we
did recognize that some of the

c1f80157-7768-4b4d-977d-a0d3cb9ccb12-2
00:22:00.815 --> 00:22:02.400
categories were removed.

5c3c6a95-48fd-4e87-9b38-04946e50a333-0
00:22:02.400 --> 00:22:06.720
So, swamp/marsh is a category
that's not in 3DHP.

f8404aae-9022-4ee4-add8-cf05dae23cc3-0
00:22:06.840 --> 00:22:10.327
So we did not want to make
apples to apples in our

f8404aae-9022-4ee4-add8-cf05dae23cc3-1
00:22:10.327 --> 00:22:11.080
comparison.

248bdf4e-0198-4217-9977-e175717b510f-0
00:22:11.280 --> 00:22:13.880
We removed swamp/marsh out of
the NHD as well.

09785816-9400-442a-a2a0-b407fa6e2991-0
00:22:14.080 --> 00:22:19.552
But even when doing that we did
see that there was a lot more

09785816-9400-442a-a2a0-b407fa6e2991-1
00:22:19.552 --> 00:22:22.200
polygon area from NHD to 3DHP.

a9695a17-436e-4e50-a68b-7f9c7a7bbdeb-0
00:22:23.040 --> 00:22:27.601
Some of that was increased ponds
that were identified, but we

a9695a17-436e-4e50-a68b-7f9c7a7bbdeb-1
00:22:27.601 --> 00:22:32.089
also found that there was an
extension of rivers so that the

a9695a17-436e-4e50-a68b-7f9c7a7bbdeb-2
00:22:32.089 --> 00:22:36.651
river - the polygon around the
river - extended significantly

a9695a17-436e-4e50-a68b-7f9c7a7bbdeb-3
00:22:36.651 --> 00:22:40.918
beyond where it was in the NHD
and honestly that's a good

a9695a17-436e-4e50-a68b-7f9c7a7bbdeb-4
00:22:40.918 --> 00:22:41.359
thing.

15cc5043-5e8f-4721-b87f-4752f103c11e-0
00:22:41.360 --> 00:22:45.050
So, we were very pleased with
the increase in polygon data

15cc5043-5e8f-4721-b87f-4752f103c11e-1
00:22:45.050 --> 00:22:48.240
that we were getting from
elevation-derived hydro.

8a096f59-2300-4997-8aac-e8f659168578-0
00:22:50.040 --> 00:22:55.807
We also in many cases saw that
there were updates, just over

8a096f59-2300-4997-8aac-e8f659168578-1
00:22:55.807 --> 00:22:56.280
time.

4ddc8f35-65a8-489f-9fb5-51dd10aaeedf-0
00:22:56.280 --> 00:23:00.960
Some of those changes were just
because the river actually had

4ddc8f35-65a8-489f-9fb5-51dd10aaeedf-1
00:23:00.960 --> 00:23:05.640
moved and we were capturing that
movement, in addition to some

4ddc8f35-65a8-489f-9fb5-51dd10aaeedf-2
00:23:05.640 --> 00:23:10.097
examples where there were lakes
and ponds that just weren't

4ddc8f35-65a8-489f-9fb5-51dd10aaeedf-3
00:23:10.097 --> 00:23:12.400
captured previously in the NHD.

338dceff-6e3e-4e69-a397-a2e58d7dd2a2-0
00:23:14.120 --> 00:23:19.536
And comparing those overall, we
found that there was about a 50%

338dceff-6e3e-4e69-a397-a2e58d7dd2a2-1
00:23:19.536 --> 00:23:23.870
overlap in polygons. But as much
as 33% of areas in

338dceff-6e3e-4e69-a397-a2e58d7dd2a2-2
00:23:23.870 --> 00:23:29.120
elevation-derived hydro were new
that were not covered by NHD.

9d499b8b-7905-4a23-831c-694854c3d8f9-0
00:23:29.400 --> 00:23:32.570
And like I said in this example,
you can see it's clearly because

9d499b8b-7905-4a23-831c-694854c3d8f9-1
00:23:32.570 --> 00:23:35.501
the river has moved, but there
were some cases where it just

9d499b8b-7905-4a23-831c-694854c3d8f9-2
00:23:35.501 --> 00:23:38.143
picked up water where we
previously did not have water

9d499b8b-7905-4a23-831c-694854c3d8f9-3
00:23:38.143 --> 00:23:38.480
mapped.

1a2de6b0-03be-4a35-ab09-e3168ed3a955-0
00:23:40.800 --> 00:23:44.720
And another cool benefit that I
know a lot of our local

1a2de6b0-03be-4a35-ab09-e3168ed3a955-1
00:23:44.720 --> 00:23:48.640
jurisdictions are very
interested in, is the catchment.

4bcbbd42-6a53-4087-b014-0dab9bb080e9-0
00:23:48.640 --> 00:23:54.163
And NV5 did a catchment for
every reach, and this was nested

4bcbbd42-6a53-4087-b014-0dab9bb080e9-1
00:23:54.163 --> 00:23:56.880
to work within the HUC system.

cced2187-3590-4eb5-ba23-f11d9dbb6cfa-0
00:23:56.880 --> 00:23:59.280
It's in the HU system.

a5001beb-90c9-4958-97b1-a27de80eae0a-0
00:23:59.280 --> 00:24:04.122
So these catchments are
subdivisions that then would

a5001beb-90c9-4958-97b1-a27de80eae0a-1
00:24:04.122 --> 00:24:07.320
modify up to a HUC12, -10, and
-8.

18000ee5-2026-41c1-a6b3-3aa79d0014f3-0
00:24:07.760 --> 00:24:11.800
I am a huge fan of the HUC
system.

b8bb0e63-a8eb-4ca6-8705-37624fb2cf98-0
00:24:11.800 --> 00:24:15.263
I love that it's a nested
watershed delineation, but a lot

b8bb0e63-a8eb-4ca6-8705-37624fb2cf98-1
00:24:15.263 --> 00:24:18.610
of our local jurisdictions
needed something smaller than

b8bb0e63-a8eb-4ca6-8705-37624fb2cf98-2
00:24:18.610 --> 00:24:22.426
the HU12 and these catchments, I
think, are going to work really

b8bb0e63-a8eb-4ca6-8705-37624fb2cf98-3
00:24:22.426 --> 00:24:22.720
well.

454a8f22-5569-4099-979c-5361e984fd03-0
00:24:23.080 --> 00:24:27.681
Having said that, there are a
lot of them, 55,000 within just

454a8f22-5569-4099-979c-5361e984fd03-1
00:24:27.681 --> 00:24:28.720
this one HUC8.

4e8c1a01-0cae-47e6-92be-5ead4d18de93-0
00:24:28.960 --> 00:24:33.261
I'm sorry if I didn't mention
that Stillaguamish is a HUC8

4e8c1a01-0cae-47e6-92be-5ead4d18de93-1
00:24:33.261 --> 00:24:38.001
basin. So that's a lot of data,
but I know that it's going to be

4e8c1a01-0cae-47e6-92be-5ead4d18de93-2
00:24:38.001 --> 00:24:42.521
really useful. And again, being
able to aggregate up to HU12s

4e8c1a01-0cae-47e6-92be-5ead4d18de93-3
00:24:42.521 --> 00:24:46.240
and -10s and -8s, is a going to
be a real benefit.

d59f3fb7-7c41-4097-ae8f-a67763fa5ef0-0
00:24:47.200 --> 00:24:51.412
The other thing that we found
which was a surprise was that

d59f3fb7-7c41-4097-ae8f-a67763fa5ef0-1
00:24:51.412 --> 00:24:55.976
the 3DHP specifications require
the contractor to show a terrain

d59f3fb7-7c41-4097-ae8f-a67763fa5ef0-2
00:24:55.976 --> 00:24:57.240
breach over roads.

cf40626d-1b81-4084-86e9-042eac9025ba-0
00:24:57.240 --> 00:25:01.179
So anywhere where a stream hits
that berm created by a road and

cf40626d-1b81-4084-86e9-042eac9025ba-1
00:25:01.179 --> 00:25:05.119
they have to have that water go
up and over, they classify that

cf40626d-1b81-4084-86e9-042eac9025ba-2
00:25:05.119 --> 00:25:05.920
as a culvert.

1749f716-6f1e-4c1c-a6c0-b104998da845-0
00:25:05.960 --> 00:25:10.360
Sometimes it's not, sometimes it
could be like a small bridge.

f944c552-d275-4d10-a843-117a58e28c70-0
00:25:10.720 --> 00:25:15.611
But in any case, there is some
constraint there for the water

f944c552-d275-4d10-a843-117a58e28c70-1
00:25:15.611 --> 00:25:20.108
and it was identified on the
line data and we are really

f944c552-d275-4d10-a843-117a58e28c70-2
00:25:20.108 --> 00:25:24.289
excited that this can be an
additional connection to

f944c552-d275-4d10-a843-117a58e28c70-3
00:25:24.289 --> 00:25:25.000
culverts.

671acb43-c81b-4d98-aa64-b3406a4760a5-0
00:25:25.000 --> 00:25:29.669
Culverts are really important in
Washington State because they

671acb43-c81b-4d98-aa64-b3406a4760a5-1
00:25:29.669 --> 00:25:32.560
can be impediments to anadromous
fish.

025be5e7-d85e-4c04-aabd-a79cde5015f3-0
00:25:32.880 --> 00:25:36.876
We actually have a state law
that says culverts cannot block

025be5e7-d85e-4c04-aabd-a79cde5015f3-1
00:25:36.876 --> 00:25:39.760
fish passage, even if it's on
private land.

e0c19e85-1f8b-4d78-a8da-8955c5ede43f-0
00:25:39.760 --> 00:25:44.403
And we've never actually had a
way to identify systematically

e0c19e85-1f8b-4d78-a8da-8955c5ede43f-1
00:25:44.403 --> 00:25:46.800
statewide culverts on all lands.

db0776e4-e0c4-423e-b6e9-81af9e84098b-0
00:25:46.800 --> 00:25:50.552
And so, we're really excited
about how we're going to bridge

db0776e4-e0c4-423e-b6e9-81af9e84098b-1
00:25:50.552 --> 00:25:54.243
this with some of our fish
passage data that our WDFW group

db0776e4-e0c4-423e-b6e9-81af9e84098b-2
00:25:54.243 --> 00:25:56.519
has, as well as our DOT
information.

1400a59f-dc26-4413-a5ad-7edd8a130a70-0
00:25:57.320 --> 00:26:01.263
And I know that some folks have
been really working on building

1400a59f-dc26-4413-a5ad-7edd8a130a70-1
00:26:01.263 --> 00:26:04.160
their culvert information to be
more accurate.

2438a9d7-60fd-4f2f-b1e8-cbe864cbe3c0-0
00:26:04.680 --> 00:26:07.000
We thought we had accurate
culvert information.

accb1a39-d97f-4447-8477-0b0de5ed9d85-0
00:26:07.200 --> 00:26:11.043
We weren't even close to what we
had here with over 8,000

accb1a39-d97f-4447-8477-0b0de5ed9d85-1
00:26:11.043 --> 00:26:11.640
culverts.

2b48cf59-4bdd-4894-8af5-96e4d91efd7c-0
00:26:11.640 --> 00:26:15.578
Many of these are in forested
lands and they're culverts

2b48cf59-4bdd-4894-8af5-96e4d91efd7c-1
00:26:15.578 --> 00:26:17.720
created through timber harvest.

08fc0e02-82ab-4d7e-b2dc-0cd2b2b176f8-0
00:26:18.040 --> 00:26:21.991
But we also found that just even
where we had information from

08fc0e02-82ab-4d7e-b2dc-0cd2b2b176f8-1
00:26:21.991 --> 00:26:25.943
local government, the data was
just not as accurate as what we

08fc0e02-82ab-4d7e-b2dc-0cd2b2b176f8-2
00:26:25.943 --> 00:26:29.080
were finding as a result from
our contractor NV5.

ccbd7ce8-51ad-416d-bb0b-bb852d59bbfe-0
00:26:30.760 --> 00:26:32.952
I'm not going to go into too
much detail on this and it's

ccbd7ce8-51ad-416d-bb0b-bb852d59bbfe-1
00:26:32.952 --> 00:26:33.520
still evolving.

6b9b44a4-6f99-4d47-ac42-c34d53b37194-0
00:26:33.520 --> 00:26:37.595
But this we were trying to talk
about what are the significant

6b9b44a4-6f99-4d47-ac42-c34d53b37194-1
00:26:37.595 --> 00:26:41.476
changes that impact Washington
State as we move from NHD to

6b9b44a4-6f99-4d47-ac42-c34d53b37194-2
00:26:41.476 --> 00:26:41.800
3DHP.

ca84776f-f0bd-4dde-a0ef-af4b9dc331be-0
00:26:41.800 --> 00:26:45.428
And I'll talk about this in
different ways for the next 15

ca84776f-f0bd-4dde-a0ef-af4b9dc331be-1
00:26:45.428 --> 00:26:45.920
minutes.

f56ed92a-8a97-4d93-9cb0-2db185aaa988-0
00:26:45.920 --> 00:26:50.067
But you know the change from
having a reach code which is

f56ed92a-8a97-4d93-9cb0-2db185aaa988-1
00:26:50.067 --> 00:26:54.000
what we used to use for
addressing, that's going away.

33372c9c-a1b2-45b3-a6c3-374d1fed2316-0
00:26:54.000 --> 00:26:57.280
So instead of reach codes, we're
going to have a mainstem ID.

0eb3d2d5-312d-44d4-ad92-d6cbf576f79f-0
00:26:57.280 --> 00:27:01.763
The Swamp/Marsh category is
going away with a plan to

0eb3d2d5-312d-44d4-ad92-d6cbf576f79f-1
00:27:01.763 --> 00:27:06.828
supplement wetlands into 3DHP
with NWI data from US Fish and

0eb3d2d5-312d-44d4-ad92-d6cbf576f79f-2
00:27:06.828 --> 00:27:08.240
Wildlife Service.

7c3d4869-4d40-48a4-bed5-fc0cd4f75bbc-0
00:27:09.760 --> 00:27:11.600
Ice and snow is another
category.

01548f67-1d08-4dec-94b1-f0bb2b18ce1e-0
00:27:11.600 --> 00:27:15.818
And then of course some of the
tools that ran in Arcmap Desktop

01548f67-1d08-4dec-94b1-f0bb2b18ce1e-1
00:27:15.818 --> 00:27:17.400
are no longer available.

2fe9116d-2e22-4393-86e2-0dfc0db8d64f-0
00:27:17.680 --> 00:27:21.143
The HEM tool, the Conflation
tool and the submission process

2fe9116d-2e22-4393-86e2-0dfc0db8d64f-1
00:27:21.143 --> 00:27:22.960
is going to be changing as well.

b9c9c95b-30d6-467c-ad14-147dd757082c-0
00:27:22.960 --> 00:27:27.093
So just wanted to make sure we
document some of the things that

b9c9c95b-30d6-467c-ad14-147dd757082c-1
00:27:27.093 --> 00:27:31.163
are changing so that we could
prepare how are we going to move

b9c9c95b-30d6-467c-ad14-147dd757082c-2
00:27:31.163 --> 00:27:31.679
forward.

3d2bd2aa-ec92-42d1-a4cc-4c9a164fcd95-0
00:27:32.800 --> 00:27:37.339
And I wanted to talk about some
of those changes and here's an

3d2bd2aa-ec92-42d1-a4cc-4c9a164fcd95-1
00:27:37.339 --> 00:27:42.023
example of the swamp/marsh that
where historically we've had the

3d2bd2aa-ec92-42d1-a4cc-4c9a164fcd95-2
00:27:42.023 --> 00:27:43.320
swamp area mapped.

8ff72db2-2aff-4a9a-b09b-c8fba57d27f7-0
00:27:43.840 --> 00:27:47.544
And when you remove that,
unfortunately if you're not

8ff72db2-2aff-4a9a-b09b-c8fba57d27f7-1
00:27:47.544 --> 00:27:51.524
careful, people may have the
false illusion that water is

8ff72db2-2aff-4a9a-b09b-c8fba57d27f7-2
00:27:51.524 --> 00:27:54.680
along that line and that there's
not an area.

20c2c0e1-562c-4835-8617-701216fe48ef-0
00:27:55.080 --> 00:27:57.778
And so that has implications
both for setbacks and

20c2c0e1-562c-4835-8617-701216fe48ef-1
00:27:57.778 --> 00:27:58.360
protection.

5d98a5f2-b353-43ae-be46-8e452ac5fde4-0
00:27:58.360 --> 00:28:02.650
And we want to make sure that
these wetland areas are for sure

5d98a5f2-b353-43ae-be46-8e452ac5fde4-1
00:28:02.650 --> 00:28:03.400
identified.

b5155a45-dbe5-471e-a7c7-f7bedf1f1084-0
00:28:03.680 --> 00:28:08.720
And so we are working on how do
we integrate that.

5c95aa10-e3af-446e-adcd-7bfeaf93122c-0
00:28:08.960 --> 00:28:12.127
And when we looked at NWI, we
found that you're just taking

5c95aa10-e3af-446e-adcd-7bfeaf93122c-1
00:28:12.127 --> 00:28:15.400
two very different data sets and
trying to put them together.

ba3dc01b-787e-4114-848a-02b79d3d6031-0
00:28:15.400 --> 00:28:19.705
So and they don't go together
naturally unless you make that

ba3dc01b-787e-4114-848a-02b79d3d6031-1
00:28:19.705 --> 00:28:20.200
effort.

4e0f53cf-cbe7-44cb-b4d6-8cdced44fa2c-0
00:28:20.200 --> 00:28:24.216
So, in this example we have the
NWI waterbody which is very

4e0f53cf-cbe7-44cb-b4d6-8cdced44fa2c-1
00:28:24.216 --> 00:28:26.560
different than the 3DHP
waterbody.

3180d324-8c4a-48d3-b8b0-02d7dd626475-0
00:28:26.560 --> 00:28:29.980
They're not even close to
alignment and that then has an

3180d324-8c4a-48d3-b8b0-02d7dd626475-1
00:28:29.980 --> 00:28:32.440
impact on where the wetland
boundary is.

436db584-d541-4fa6-9ac0-423fc2becc80-0
00:28:32.440 --> 00:28:36.566
And we can see over here on the
right hand side, the NWI stream

436db584-d541-4fa6-9ac0-423fc2becc80-1
00:28:36.566 --> 00:28:39.920
isn't even close now to where
the 3DHP streams are.

f85f2d90-b1ff-444e-9e01-4fe28591842b-0
00:28:40.280 --> 00:28:44.169
So we don't have solutions, but
this is something that we've

f85f2d90-b1ff-444e-9e01-4fe28591842b-1
00:28:44.169 --> 00:28:47.932
identified as a problem and
something we'd like to to work

f85f2d90-b1ff-444e-9e01-4fe28591842b-2
00:28:47.932 --> 00:28:49.080
on moving forward.

1bb24ae1-af8a-4c61-a899-3cdbb05516a9-0
00:28:49.920 --> 00:28:54.361
We also worked with NV5 to look
at integrating stormwater

1bb24ae1-af8a-4c61-a899-3cdbb05516a9-1
00:28:54.361 --> 00:28:55.280
information.

d731b0f8-81af-4992-85d5-19d51db36448-0
00:28:55.280 --> 00:28:59.528
And so we did a partnership with
Snohomish County who took

d731b0f8-81af-4992-85d5-19d51db36448-1
00:28:59.528 --> 00:29:03.848
collected data from several
different jurisdictions, worked

d731b0f8-81af-4992-85d5-19d51db36448-2
00:29:03.848 --> 00:29:08.240
with NV5 to get that data into a
3DHP model or an EDH model.

d690b8c5-e30f-4d06-b9ce-6398d8e4ad19-0
00:29:08.520 --> 00:29:12.214
I don't know if you can really
see and I'm sorry I actually

d690b8c5-e30f-4d06-b9ce-6398d8e4ad19-1
00:29:12.214 --> 00:29:16.031
don't have the right graphic
here to help illustrate, but the

d690b8c5-e30f-4d06-b9ce-6398d8e4ad19-2
00:29:16.031 --> 00:29:19.602
blue lines are the EDH data and
all the other data is the

d690b8c5-e30f-4d06-b9ce-6398d8e4ad19-3
00:29:19.602 --> 00:29:20.280
stormwater.

1f313c03-15fe-420f-8b77-b286a4416adc-0
00:29:20.280 --> 00:29:24.091
So if you were to look at this
area without storm water data,

1f313c03-15fe-420f-8b77-b286a4416adc-1
00:29:24.091 --> 00:29:27.779
there's actually less water
mapped than we have in the rest

1f313c03-15fe-420f-8b77-b286a4416adc-2
00:29:27.779 --> 00:29:28.640
of the region.

66a1fadb-2935-4c10-9ec1-680a09190aa6-0
00:29:29.120 --> 00:29:31.880
But that's because it's all
below ground.

4dc652f6-d3b2-43ab-9277-b1093cba8ac8-0
00:29:32.160 --> 00:29:35.814
And so we are feeling like this
is going to be a really

4dc652f6-d3b2-43ab-9277-b1093cba8ac8-1
00:29:35.814 --> 00:29:39.990
important way to connect some of
that subsurface human modified

4dc652f6-d3b2-43ab-9277-b1093cba8ac8-2
00:29:39.990 --> 00:29:42.600
water systems into our natural
systems.

009abdcb-6945-46c9-a15b-b56b299564be-0
00:29:43.240 --> 00:29:48.029
And it's not something that we
probably will fund, but we hope

009abdcb-6945-46c9-a15b-b56b299564be-1
00:29:48.029 --> 00:29:52.210
to help encourage local
jurisdictions to gather some -

009abdcb-6945-46c9-a15b-b56b299564be-2
00:29:52.210 --> 00:29:56.847
that won't be all - but some of
the major stormwater data to

009abdcb-6945-46c9-a15b-b56b299564be-3
00:29:56.847 --> 00:29:58.519
incorporate into 3DHP.

3a92d947-1f68-481f-9b9f-f009bcb1cbec-0
00:30:00.040 --> 00:30:04.445
We also were very interested in
aerial imagery, and this is, I

3a92d947-1f68-481f-9b9f-f009bcb1cbec-1
00:30:04.445 --> 00:30:08.360
will admit, that my background
is land cover and aerial

3a92d947-1f68-481f-9b9f-f009bcb1cbec-2
00:30:08.360 --> 00:30:08.920
imagery.

45c259f8-b626-4f9c-9f25-f5b31d10abb9-0
00:30:09.200 --> 00:30:13.608
We also recently acquired
statewide high resolution land

45c259f8-b626-4f9c-9f25-f5b31d10abb9-1
00:30:13.608 --> 00:30:15.000
cover from Ecopia.

ed558fda-86b2-4994-b6a3-8adbec16beb2-0
00:30:15.320 --> 00:30:17.680
So which is what I'm showing
here on the right.

61d28542-931c-451a-a874-f4a914161e45-0
00:30:18.160 --> 00:30:22.579
What's really interesting is
they have that open water

61d28542-931c-451a-a874-f4a914161e45-1
00:30:22.579 --> 00:30:27.160
category in which they try to
remove overlapping canopy.

03a50748-aa13-4c07-8007-a62710a71123-0
00:30:27.560 --> 00:30:33.465
So they map canopy as a separate
layer and try to model open

03a50748-aa13-4c07-8007-a62710a71123-1
00:30:33.465 --> 00:30:36.080
water separate from canopy.

268504a2-9f0b-4d96-97b1-a47a09ab5f9e-0
00:30:36.080 --> 00:30:39.902
And that's why we are able to
get some of this water

268504a2-9f0b-4d96-97b1-a47a09ab5f9e-1
00:30:39.902 --> 00:30:40.840
delineations.

cfe38b74-fa20-4918-863a-d77a0cf48f65-0
00:30:40.840 --> 00:30:43.700
And here you can see there's
building footprints and

cfe38b74-fa20-4918-863a-d77a0cf48f65-1
00:30:43.700 --> 00:30:44.240
driveways.

55ca897d-9dbd-40c5-86ec-c43045d5843f-0
00:30:44.640 --> 00:30:46.960
So all this seems like it could
be really helpful.

872f3b82-3a65-4153-9903-f6a9f49cfb73-0
00:30:48.160 --> 00:30:52.041
And the other thing we recognize
is that there can be a

872f3b82-3a65-4153-9903-f6a9f49cfb73-1
00:30:52.041 --> 00:30:55.923
significant delay from when
lidar was flown, processed,

872f3b82-3a65-4153-9903-f6a9f49cfb73-2
00:30:55.923 --> 00:30:59.596
processed again for 3DHP and
ingested into 3DHP, and

872f3b82-3a65-4153-9903-f6a9f49cfb73-3
00:30:59.596 --> 00:31:04.032
available to everyone, that that
could be a fairly large amount

872f3b82-3a65-4153-9903-f6a9f49cfb73-4
00:31:04.032 --> 00:31:07.359
of time and in that time water
can move around.

242c39d5-c49a-42f2-a369-05dc7a26a1ac-0
00:31:07.760 --> 00:31:12.873
So, as in this example, this was
in our study area where in 2017

242c39d5-c49a-42f2-a369-05dc7a26a1ac-1
00:31:12.873 --> 00:31:16.885
the elevation-derived hydro
mapped the water quite

242c39d5-c49a-42f2-a369-05dc7a26a1ac-2
00:31:16.885 --> 00:31:19.560
accurately, but it moved in
2021.

a01f53af-5357-4595-81ab-7ca4495d15c9-0
00:31:19.720 --> 00:31:25.080
So just in that span of four
years that water moved 250 feet.

30304d76-775e-4a7f-98e2-2ddd14e6a14a-0
00:31:25.320 --> 00:31:29.727
And what we're proposing is not
that we're going to modify 3DHP,

30304d76-775e-4a7f-98e2-2ddd14e6a14a-1
00:31:29.727 --> 00:31:33.930
but that this, similar to the
wetlands, could be another data

30304d76-775e-4a7f-98e2-2ddd14e6a14a-2
00:31:33.930 --> 00:31:38.338
layer that we help support or we
help provide, to give people an

30304d76-775e-4a7f-98e2-2ddd14e6a14a-3
00:31:38.338 --> 00:31:40.440
indication that water has moved

c7c36704-4f8d-4940-98ad-ed48036805e6-0
00:31:40.440 --> 00:31:44.960
and where. Again, it's an
awareness thing.

3d344e96-5843-4a25-a672-e63e5c364a75-0
00:31:44.960 --> 00:31:48.619
We're not trying to propose that
it gets ingested into 3DHP, but

3d344e96-5843-4a25-a672-e63e5c364a75-1
00:31:48.619 --> 00:31:51.828
that it could be an additional
data layer to be helpful,

3d344e96-5843-4a25-a672-e63e5c364a75-2
00:31:51.828 --> 00:31:54.080
particularly when you're doing
planning

1a0aa55f-0fc4-479a-ab86-e449d66b683b-0
00:31:54.800 --> 00:32:00.419
and in more of that detailed
analysis with hydrography. We

1a0aa55f-0fc4-479a-ab86-e449d66b683b-1
00:32:00.419 --> 00:32:05.849
also found that there was a
difference in what the state

1a0aa55f-0fc4-479a-ab86-e449d66b683b-2
00:32:05.849 --> 00:32:10.040
needs are for the extent of
those polygons.

7b8fcd91-807f-413e-b64e-f6badee9dd5b-0
00:32:10.040 --> 00:32:13.971
So, in Washington State, most of
our regulations are based on

7b8fcd91-807f-413e-b64e-f6badee9dd5b-1
00:32:13.971 --> 00:32:15.240
ordinary high water.

592a6ec2-44aa-4bee-a890-008e8cec522d-0
00:32:15.800 --> 00:32:18.896
To determine ordinary high water
you really need on the ground

592a6ec2-44aa-4bee-a890-008e8cec522d-1
00:32:18.896 --> 00:32:20.960
analysis and often times even a
surveyor.

27706dfc-1dad-41a6-9eca-667a4e12788a-0
00:32:21.400 --> 00:32:24.333
But we felt like we could
probably come up with an

27706dfc-1dad-41a6-9eca-667a4e12788a-1
00:32:24.333 --> 00:32:28.013
estimate of ordinary high water
with a bank full width and that

27706dfc-1dad-41a6-9eca-667a4e12788a-2
00:32:28.013 --> 00:32:31.291
is different than where the
water was at the time of the

27706dfc-1dad-41a6-9eca-667a4e12788a-3
00:32:31.291 --> 00:32:34.800
lidar flight, which is what the
contractor is mapping there.

2f277ac5-20fd-4d9b-ab94-bb8b3988c2b2-0
00:32:35.360 --> 00:32:38.950
If it was a 2017 and it was
done, the lidar was flown at a

2f277ac5-20fd-4d9b-ab94-bb8b3988c2b2-1
00:32:38.950 --> 00:32:41.080
time when there was very low
flow,

36055456-588c-47a5-97cf-341776154056-0
00:32:41.440 --> 00:32:44.713
your water area is going to be
much reduced than a bank full

36055456-588c-47a5-97cf-341776154056-1
00:32:44.713 --> 00:32:45.840
width at a high flow.

ca47f473-56dc-4dcb-a748-64ee6b6f4b1b-0
00:32:46.600 --> 00:32:52.514
So we worked with Tim Hyatt and
Tyson Waldo in Western

ca47f473-56dc-4dcb-a748-64ee6b6f4b1b-1
00:32:52.514 --> 00:32:54.880
Washington University.

7563c498-c51c-480e-a2f2-0365df30209d-0
00:32:55.240 --> 00:32:59.268
They came up with some
approaches to map ordinary high

7563c498-c51c-480e-a2f2-0365df30209d-1
00:32:59.268 --> 00:33:00.440
water estimates.

5d11e578-7791-4c68-a755-07cf01e94efa-0
00:33:00.440 --> 00:33:04.176
We're calling, we're calling it
a bank full width and that gives

5d11e578-7791-4c68-a755-07cf01e94efa-1
00:33:04.176 --> 00:33:07.280
us a little bit better extent of
that active channel.

dad6592c-4b4d-45c0-aca5-3886187054ea-0
00:33:07.360 --> 00:33:11.287
And so that is useful when we're
trying to talk about setbacks

dad6592c-4b4d-45c0-aca5-3886187054ea-1
00:33:11.287 --> 00:33:14.966
and measuring of riparian areas
because that's where those

dad6592c-4b4d-45c0-aca5-3886187054ea-2
00:33:14.966 --> 00:33:16.399
measurements come from.

b6c3c416-7df9-4e0e-93ff-203b27c42723-0
00:33:18.480 --> 00:33:23.005
So, I started to realize: boy,
3DHP is great for some things

b6c3c416-7df9-4e0e-93ff-203b27c42723-1
00:33:23.005 --> 00:33:27.381
but we have some additional
needs and I wanted to create a

b6c3c416-7df9-4e0e-93ff-203b27c42723-2
00:33:27.381 --> 00:33:30.720
bigger picture of how it all
comes together.

a3b9d4df-d341-4e45-97d5-439990d4cfc4-0
00:33:31.080 --> 00:33:35.023
And I love the USGS 3D image
that they have for 3DHP or

a3b9d4df-d341-4e45-97d5-439990d4cfc4-1
00:33:35.023 --> 00:33:37.840
actually it's actually the 3DNTM
image.

3de957f5-c018-4db2-9dcd-f7541fcabb64-0
00:33:39.000 --> 00:33:42.200
Esri has some really cool 3D
graphics.

baad3009-4723-41e7-a9d0-89eb7b3947f5-0
00:33:43.480 --> 00:33:47.760
I thought, I want to show
Washington OneHydro all of how

baad3009-4723-41e7-a9d0-89eb7b3947f5-1
00:33:47.760 --> 00:33:50.840
this all comes together in a 3D
graphic.

f4b8f05b-f517-48f9-8540-7d99910b78b7-0
00:33:51.200 --> 00:33:54.092
Unfortunately our graphic folks
were very busy and they said

f4b8f05b-f517-48f9-8540-7d99910b78b7-1
00:33:54.092 --> 00:33:56.985
they didn't have time to do it
and I struggled and struggled

f4b8f05b-f517-48f9-8540-7d99910b78b7-2
00:33:56.985 --> 00:33:59.973
and someone said why don't you
just just draw a sketch of what

f4b8f05b-f517-48f9-8540-7d99910b78b7-3
00:33:59.973 --> 00:34:00.400
you want.

e9d499a2-3414-4508-8c60-05661ff8ae15-0
00:34:00.960 --> 00:34:05.382
So, I did and when I finished
it, and I was trying, for the

e9d499a2-3414-4508-8c60-05661ff8ae15-1
00:34:05.382 --> 00:34:09.877
record I was trying, and I came
up with about a fourth-grade

e9d499a2-3414-4508-8c60-05661ff8ae15-2
00:34:09.877 --> 00:34:10.319
level.

1b7e0c72-0552-4688-af89-46a81aefca76-0
00:34:10.680 --> 00:34:13.680
So I thought, OK, I'm going to
run with it.

26259506-27de-4919-bce4-fb2f5c9c5919-0
00:34:14.080 --> 00:34:18.325
I am going to do Richard Scarry
theme of OneHydro. And I love

26259506-27de-4919-bce4-fb2f5c9c5919-1
00:34:18.325 --> 00:34:22.297
Richard Scarry, particularly
because Richard Scarry would

26259506-27de-4919-bce4-fb2f5c9c5919-2
00:34:22.297 --> 00:34:26.337
capture all these complex
scenes, whether it's a city or a

26259506-27de-4919-bce4-fb2f5c9c5919-3
00:34:26.337 --> 00:34:26.680
farm.

e0bbbd21-f512-4270-92d8-5402bf5189f3-0
00:34:28.200 --> 00:34:29.480
And I feel like that's what
we're doing.

83592a56-a810-457d-866b-b525f98b8056-0
00:34:29.720 --> 00:34:33.840
We're capturing kind of a
complex scene with hydrography.

61d675fd-9e42-4d2d-afd1-773f49cd725d-0
00:34:34.040 --> 00:34:38.928
So, this is the Richard
Scarry/Josh Greenberg approach

61d675fd-9e42-4d2d-afd1-773f49cd725d-1
00:34:38.928 --> 00:34:44.706
to OneHydro, the flow line that
stays the same from NHD to 3DHP,

61d675fd-9e42-4d2d-afd1-773f49cd725d-2
00:34:44.706 --> 00:34:46.040
not a big deal.

07d1e9fc-22eb-4228-87b8-6da385ba84f1-0
00:34:46.200 --> 00:34:48.764
We do have some discussions
about reach code versus

07d1e9fc-22eb-4228-87b8-6da385ba84f1-1
00:34:48.764 --> 00:34:51.280
mainstem, but you know we'll
deal with that later.

2707af64-a5a9-49ab-b3ee-9357dfd6e7f7-0
00:34:51.560 --> 00:34:52.960
We also have waterbodies.

407c4496-1dfd-43e7-af4c-6491263297c1-0
00:34:52.960 --> 00:34:56.787
So, the waterbodies are pretty
much staying the same between

407c4496-1dfd-43e7-af4c-6491263297c1-1
00:34:56.787 --> 00:35:00.300
the two. Wetlands, particularly
those wetlands that are

407c4496-1dfd-43e7-af4c-6491263297c1-2
00:35:00.300 --> 00:35:02.120
connected to the hydrography.

dde0f731-ce4f-404f-8b5d-f6dbd37947f2-0
00:35:02.120 --> 00:35:05.656
That is a concern of ours
because trying to figure out

dde0f731-ce4f-404f-8b5d-f6dbd37947f2-1
00:35:05.656 --> 00:35:09.836
where that boundary is of water
and the impact of that water and

dde0f731-ce4f-404f-8b5d-f6dbd37947f2-2
00:35:09.836 --> 00:35:12.280
how that water needs to be
protected.

bbfc1ff3-718b-4d9f-be48-bd838d81ea65-0
00:35:13.000 --> 00:35:16.851
I think those data layers need
to be done somewhat together or

bbfc1ff3-718b-4d9f-be48-bd838d81ea65-1
00:35:16.851 --> 00:35:20.520
they're just never going to
align as I was showing earlier.

7c46ca0e-fe5c-4103-a836-f7035d884eb9-0
00:35:21.880 --> 00:35:25.623
We also now have culverts and
culverts work great both for

7c46ca0e-fe5c-4103-a836-f7035d884eb9-1
00:35:25.623 --> 00:35:29.240
identifying them because they
can be a water constraint.

9ae0939c-804d-46e1-b6f8-1d2b429571d6-0
00:35:29.520 --> 00:35:32.538
They're also really great places
to do your field work because

9ae0939c-804d-46e1-b6f8-1d2b429571d6-1
00:35:32.538 --> 00:35:33.640
they're easy to get to.

869a9366-fca4-47c5-9a4e-bfaa67a87db4-0
00:35:33.640 --> 00:35:35.720
And so it helps verify where the
water is.

b3437589-40f1-47b1-aff4-2727a44e11b5-0
00:35:36.440 --> 00:35:40.616
But we also, like I mentioned in
Washington, we need to make sure

b3437589-40f1-47b1-aff4-2727a44e11b5-1
00:35:40.616 --> 00:35:43.400
that those culverts are not fish
blockages.

7b76c9f3-8054-4b5b-b817-ac05f35726a0-0
00:35:43.720 --> 00:35:47.559
They also can be places where
you get blowouts when you have

7b76c9f3-8054-4b5b-b817-ac05f35726a0-1
00:35:47.559 --> 00:35:48.000
floods.

2e3eeb6a-a17b-46ed-a692-79cf19b0bd7e-0
00:35:48.000 --> 00:35:52.358
And so I think identifying those
culverts is going to be really

2e3eeb6a-a17b-46ed-a692-79cf19b0bd7e-1
00:35:52.358 --> 00:35:53.040
important.

32888f65-853b-42f2-8754-2322d2d01ced-0
00:35:53.720 --> 00:35:56.937
And then I talked about the bank
ordinary high water or what

32888f65-853b-42f2-8754-2322d2d01ced-1
00:35:56.937 --> 00:35:58.520
we're calling bank full width.

a305bba7-0dcb-461e-b5b7-1eb7e6fd6c3f-0
00:35:58.880 --> 00:36:03.717
Having that polygon as well. And
again, stormwater to help map

a305bba7-0dcb-461e-b5b7-1eb7e6fd6c3f-1
00:36:03.717 --> 00:36:08.325
where water is moving within
urbanized areas is going to be

a305bba7-0dcb-461e-b5b7-1eb7e6fd6c3f-2
00:36:08.325 --> 00:36:11.320
very important for Washington as
well.

094f9432-7bd4-43fd-9ca1-9f41605a7035-0
00:36:12.400 --> 00:36:16.614
Throw on top of that the
catchments. We've always had the

094f9432-7bd4-43fd-9ca1-9f41605a7035-1
00:36:16.614 --> 00:36:21.120
WBD, but now we are getting much
more detailed catchments and

094f9432-7bd4-43fd-9ca1-9f41605a7035-2
00:36:21.120 --> 00:36:25.480
they work with that monotonic
DEM that is created for 3DHP.

16ef4dcb-cfb8-4bca-9070-ecd8265519d2-0
00:36:25.480 --> 00:36:29.273
So I know a lot of folks in
Washington are very excited

16ef4dcb-cfb8-4bca-9070-ecd8265519d2-1
00:36:29.273 --> 00:36:33.135
about how they can make use of
catchments both for their

16ef4dcb-cfb8-4bca-9070-ecd8265519d2-2
00:36:33.135 --> 00:36:37.200
analysis and how it can help
drive better science research.

b8bee2d7-e984-4013-aac5-48369c526377-0
00:36:38.200 --> 00:36:43.576
So that's it for my Richard
Scary approach. Trying to

b8bee2d7-e984-4013-aac5-48369c526377-1
00:36:43.576 --> 00:36:47.360
capture all this into a single
chart.

01f0cf82-fdb7-4dcf-9963-489b5dc1f78e-0
00:36:48.480 --> 00:36:51.828
This is kind of how we're
visioning the OneHydro. Across

01f0cf82-fdb7-4dcf-9963-489b5dc1f78e-1
00:36:51.828 --> 00:36:52.240
the top

7125c46b-a59f-4056-9a32-e3a81db54c4c-0
00:36:52.240 --> 00:36:57.990
we have USGS with the 3DHP. And
we have on the left part NHD, on

7125c46b-a59f-4056-9a32-e3a81db54c4c-1
00:36:57.990 --> 00:36:59.760
the right part 3DHP.

e0f5e921-1562-4c18-a9e2-25640139159f-0
00:37:00.200 --> 00:37:05.656
And in the box are not all the
changes, but things that were in

e0f5e921-1562-4c18-a9e2-25640139159f-1
00:37:05.656 --> 00:37:09.920
NHD that we do not see moving
directly into 3DHP.

90f6b76b-2783-4351-ae6f-f169d5d51f9e-0
00:37:10.280 --> 00:37:12.943
So, reach codes,
perennial/intermittent

90f6b76b-2783-4351-ae6f-f169d5d51f9e-1
00:37:12.943 --> 00:37:17.205
categories, the swamp/marsh, and
a geometric network. Those are

90f6b76b-2783-4351-ae6f-f169d5d51f9e-2
00:37:17.205 --> 00:37:21.067
all things that we will not see
in 3DHP for one reason or

90f6b76b-2783-4351-ae6f-f169d5d51f9e-3
00:37:21.067 --> 00:37:21.600
another.

811b9029-aed6-4d47-aa53-d2fd610c5d1d-0
00:37:22.200 --> 00:37:26.400
In 3DHP though, we will see
mainstem IDs and culverts.

5a3a0b9e-c884-4975-bd5f-a576c70c1008-0
00:37:26.400 --> 00:37:30.607
So those are some benefits. And
I know that USGS is working on

5a3a0b9e-c884-4975-bd5f-a576c70c1008-1
00:37:30.607 --> 00:37:34.413
how to calculate stream
permanence and I don't know when

5a3a0b9e-c884-4975-bd5f-a576c70c1008-2
00:37:34.413 --> 00:37:38.286
that will be ready, but I think
that's going to be really

5a3a0b9e-c884-4975-bd5f-a576c70c1008-3
00:37:38.286 --> 00:37:42.560
important for Washington State
because I'm pretty convinced not

5a3a0b9e-c884-4975-bd5f-a576c70c1008-4
00:37:42.560 --> 00:37:46.099
all of those blue lines are
lines that we want to do

5a3a0b9e-c884-4975-bd5f-a576c70c1008-5
00:37:46.099 --> 00:37:49.438
setbacks on or that apply
directly to our current

5a3a0b9e-c884-4975-bd5f-a576c70c1008-6
00:37:49.438 --> 00:37:50.240
regulations.

b8699ade-b228-4ee9-823b-70bf802cbcd0-0
00:37:50.240 --> 00:37:53.160
So we're going to have to come
up with some new ways.

b6e717fe-80a3-4b7b-a778-3a4d12458e19-0
00:37:53.160 --> 00:37:55.600
And so that gets us down to
Washington.

6f3e9744-7734-4dc1-a985-3af096db2b8c-0
00:37:55.600 --> 00:37:59.951
Now in Washington we always
would take the the NHD from USGS

6f3e9744-7734-4dc1-a985-3af096db2b8c-1
00:37:59.951 --> 00:38:04.445
and we would add stream order
and we would reproject it to our

6f3e9744-7734-4dc1-a985-3af096db2b8c-2
00:38:04.445 --> 00:38:08.440
state plane projection which was
our standard for data.

5f4c15f6-733a-4ed9-a208-b85c3ac3d948-0
00:38:08.760 --> 00:38:13.473
So those are things that we did
within NHD, and we'll probably

5f4c15f6-733a-4ed9-a208-b85c3ac3d948-1
00:38:13.473 --> 00:38:18.261
continue to do in 3DHP. But we
will also create a trace network

5f4c15f6-733a-4ed9-a208-b85c3ac3d948-2
00:38:18.261 --> 00:38:23.050
and that's not super complicated
if you have good data going in

5f4c15f6-733a-4ed9-a208-b85c3ac3d948-3
00:38:23.050 --> 00:38:27.015
and that will allow us to have
the geometric network

5f4c15f6-733a-4ed9-a208-b85c3ac3d948-4
00:38:27.015 --> 00:38:31.280
capabilities that we had in in
desktop ArcGIS. The trace

5f4c15f6-733a-4ed9-a208-b85c3ac3d948-5
00:38:31.280 --> 00:38:35.245
network is what's used in Pro to
allow you to do the

5f4c15f6-733a-4ed9-a208-b85c3ac3d948-6
00:38:35.245 --> 00:38:37.640
downstream/upstream assessments.

6999cd26-556a-4478-a7d3-f637a0ba378b-0
00:38:38.440 --> 00:38:41.040
So then we identified additional
layers.

c77c827d-f731-499c-b2a9-d4e40ef2a94f-0
00:38:41.240 --> 00:38:45.569
So, all of this together is what
we feel combines to make

c77c827d-f731-499c-b2a9-d4e40ef2a94f-1
00:38:45.569 --> 00:38:50.122
OneHydro a complete dataset that
will be useful to solve our

c77c827d-f731-499c-b2a9-d4e40ef2a94f-2
00:38:50.122 --> 00:38:54.676
hydrography needs. And we have
listed these in the Critical,

c77c827d-f731-499c-b2a9-d4e40ef2a94f-3
00:38:54.676 --> 00:38:59.528
Important, and Useful. The first
two we hope to support; meaning

c77c827d-f731-499c-b2a9-d4e40ef2a94f-4
00:38:59.528 --> 00:39:03.857
we want to encourage/we will
work on. And the last one we

c77c827d-f731-499c-b2a9-d4e40ef2a94f-5
00:39:03.857 --> 00:39:08.112
encourage. For the Critical:
stream permanence and if we

c77c827d-f731-499c-b2a9-d4e40ef2a94f-6
00:39:08.112 --> 00:39:12.964
don't have initiation points, we
hope to at least make sure that

c77c827d-f731-499c-b2a9-d4e40ef2a94f-7
00:39:12.964 --> 00:39:17.816
the data that different agencies
can use to determine initiation

c77c827d-f731-499c-b2a9-d4e40ef2a94f-8
00:39:17.816 --> 00:39:21.399
of a stream that that
information is available,

f2e85110-1fff-4157-8775-6806b1275d47-0
00:39:21.400 --> 00:39:25.697
because I think we recognize not
everyone has the same definition

f2e85110-1fff-4157-8775-6806b1275d47-1
00:39:25.697 --> 00:39:29.538
of stream initiation. For
Important, we have the bank full

f2e85110-1fff-4157-8775-6806b1275d47-2
00:39:29.538 --> 00:39:33.575
width and we've actually we were
fortunate after this project

f2e85110-1fff-4157-8775-6806b1275d47-3
00:39:33.575 --> 00:39:37.221
started that Puget Sound
partnership has agreed to fund

f2e85110-1fff-4157-8775-6806b1275d47-4
00:39:37.221 --> 00:39:39.240
that bank full width statewide.

1ffaff26-fc33-4326-b99b-4e892def718d-0
00:39:39.240 --> 00:39:42.760
And so that's a dataset that
will at least be done once and

1ffaff26-fc33-4326-b99b-4e892def718d-1
00:39:42.760 --> 00:39:46.514
that will allow us ways, after
that's done once, we can work on

1ffaff26-fc33-4326-b99b-4e892def718d-2
00:39:46.514 --> 00:39:50.093
thinking of maybe there's ways
that can be a little bit more

1ffaff26-fc33-4326-b99b-4e892def718d-3
00:39:50.093 --> 00:39:50.680
automated.

b373a967-b7c6-4dc4-aeed-7508433b50f5-0
00:39:51.040 --> 00:39:54.325
And if you're interested in
those approaches, Tim Hyatt has

b373a967-b7c6-4dc4-aeed-7508433b50f5-1
00:39:54.325 --> 00:39:57.555
a paper that was published I
think in 2022 and I could get

b373a967-b7c6-4dc4-aeed-7508433b50f5-2
00:39:57.555 --> 00:39:58.760
that citation for you.

ad3c4c2d-1c80-4c7c-86bc-526ca0b371c8-0
00:39:59.000 --> 00:40:00.800
It will also be in our final
report.

931f9dcd-e324-4685-b756-b48ab6b3026c-0
00:40:01.480 --> 00:40:04.209
But that's a that's an
interesting combination of

931f9dcd-e324-4685-b756-b48ab6b3026c-1
00:40:04.209 --> 00:40:05.520
aerial imagery and lidar

e05c7b1a-292b-460b-8786-95e1df69a048-0
00:40:06.120 --> 00:40:10.577
to delineate that bank full
width. We also hope to continue

e05c7b1a-292b-460b-8786-95e1df69a048-1
00:40:10.577 --> 00:40:15.257
working with wetlands to find a
way to integrate wetlands with

e05c7b1a-292b-460b-8786-95e1df69a048-2
00:40:15.257 --> 00:40:20.085
3DHP. Whether it's working with
the US Fish and Wildlife Service

e05c7b1a-292b-460b-8786-95e1df69a048-3
00:40:20.085 --> 00:40:22.240
or maybe NOAA's CCAP program,

59680b89-b5d9-4b0f-a92b-c7dc9a61a914-0
00:40:22.240 --> 00:40:25.807
because they also in their
high-resolution land cover, they

59680b89-b5d9-4b0f-a92b-c7dc9a61a914-1
00:40:25.807 --> 00:40:26.640
have wetlands.

bb79754a-630f-4e86-9c3d-9037f4ecc973-0
00:40:26.640 --> 00:40:28.240
So we're looking at those.

eb994070-bcee-42a1-ad0d-53c8b1f93ea3-0
00:40:28.240 --> 00:40:32.209
And then land cover data. We
have a 2021, but do we want to

eb994070-bcee-42a1-ad0d-53c8b1f93ea3-1
00:40:32.209 --> 00:40:35.120
continue paying to get that
updated or not?

5b2022d4-a4b2-4473-8389-357c7c1a8e8f-0
00:40:35.120 --> 00:40:39.283
And we also have a lot of land
cover work performed in our Fish

5b2022d4-a4b2-4473-8389-357c7c1a8e8f-1
00:40:39.283 --> 00:40:40.520
and Wildlife group.

a106c3e1-5b10-41be-b38f-31ed4d682008-0
00:40:40.520 --> 00:40:44.150
So maybe we can work with them
on coming on some of those

a106c3e1-5b10-41be-b38f-31ed4d682008-1
00:40:44.150 --> 00:40:47.656
updates. The Useful and
Encourage - stormwater. And the

a106c3e1-5b10-41be-b38f-31ed4d682008-2
00:40:47.656 --> 00:40:51.287
reason it's encouraged is
because we don't have the data.

a106c3e1-5b10-41be-b38f-31ed4d682008-3
00:40:51.287 --> 00:40:55.356
It's really up to local agencies
that have to have the data, has

a106c3e1-5b10-41be-b38f-31ed4d682008-4
00:40:55.356 --> 00:40:57.360
to be clean, has to be accurate.

723be476-7278-4f6f-8c9a-d0696fe34af2-0
00:40:57.680 --> 00:41:00.910
And so we said well we encourage
that but we really have no

723be476-7278-4f6f-8c9a-d0696fe34af2-1
00:41:00.910 --> 00:41:01.880
control over that.

f0081cc1-2a33-499e-b8e0-f0ffe2c17ab3-0
00:41:02.160 --> 00:41:06.176
And then we also threw in
channel migration zones and

f0081cc1-2a33-499e-b8e0-f0ffe2c17ab3-1
00:41:06.176 --> 00:41:10.787
floodplains and we feel like
those are important and could be

f0081cc1-2a33-499e-b8e0-f0ffe2c17ab3-2
00:41:10.787 --> 00:41:15.176
connected to the OneHydro model
and they're useful but not

f0081cc1-2a33-499e-b8e0-f0ffe2c17ab3-3
00:41:15.176 --> 00:41:15.920
necessary.

ad709978-f173-4767-8969-bb217e8ce06c-0
00:41:18.080 --> 00:41:22.728
Now coming back to tools, we are
actively working on tools that

ad709978-f173-4767-8969-bb217e8ce06c-1
00:41:22.728 --> 00:41:26.360
fall into three categories. One,
addressing data.

44308887-8307-41fc-b99c-040b96519ec4-0
00:41:26.680 --> 00:41:27.600
We have a lot of data.

84dfd58b-9bb5-4866-8d93-5e1d30174446-0
00:41:27.600 --> 00:41:32.555
We have millions of points that
are currently addressed and

84dfd58b-9bb5-4866-8d93-5e1d30174446-1
00:41:32.555 --> 00:41:33.960
connected to NHD.

cc327fc9-698f-48fb-bc2f-e22fc37091ff-0
00:41:34.120 --> 00:41:36.984
And we're trying to figure out
what is the best method of doing

cc327fc9-698f-48fb-bc2f-e22fc37091ff-1
00:41:36.984 --> 00:41:37.880
that moving forward.

fe35b25b-6785-4b25-85a3-6ae57e3a9f52-0
00:41:38.640 --> 00:41:42.880
There is the oh shoot it now I'm
spacing it.

69b6e594-3842-4d40-9097-ed5b546e592b-0
00:41:43.160 --> 00:41:51.840
Michael's, you guys, it's the
map spacing it all of a sudden.

91617b87-f6e1-4238-babf-0845eca83e91-0
00:41:51.840 --> 00:41:54.440
HydroAdd, that's it.

cd007295-5d27-456e-8ec6-b1edb5f693bf-0
00:41:54.680 --> 00:41:58.663
I was thinking map add, but it's
HydroAdd, which works for

cd007295-5d27-456e-8ec6-b1edb5f693bf-1
00:41:58.663 --> 00:42:02.781
smaller datasets, but we're
going to need something that can

cd007295-5d27-456e-8ec6-b1edb5f693bf-2
00:42:02.781 --> 00:42:05.280
work with larger datasets
statewide.

dff10493-af08-4bdd-88fb-91cb6b6bff29-0
00:42:05.280 --> 00:42:06.880
We have our fish distribution.

e9f9f704-0393-4cbf-928f-29d071b72125-0
00:42:07.120 --> 00:42:10.970
Like I said, we have tons of
water sample points in an

e9f9f704-0393-4cbf-928f-29d071b72125-1
00:42:10.970 --> 00:42:12.160
ecology database.

dc947531-acd5-460d-a4e3-9403c4162a27-0
00:42:12.200 --> 00:42:13.920
All of these need to be
addressed.

a0b128da-b403-4d05-885b-8c0469685754-0
00:42:14.480 --> 00:42:16.960
We're also interested in in
connecting data layers.

e19a2ab4-0df9-4bc2-9c46-61175b3a9fbe-0
00:42:16.960 --> 00:42:19.600
So I do have a graphic that
shows this.

0e2aa8b8-389c-4a32-856f-ff1f2d8cc6be-0
00:42:20.840 --> 00:42:23.666
It's one thing to have
information along the flowline,

0e2aa8b8-389c-4a32-856f-ff1f2d8cc6be-1
00:42:23.666 --> 00:42:26.390
but how do we get that
information out to either the

0e2aa8b8-389c-4a32-856f-ff1f2d8cc6be-2
00:42:26.390 --> 00:42:28.600
edge of the water or that bank
full width?

798ba2e1-a719-4bb1-b211-5253248bbf79-0
00:42:29.040 --> 00:42:32.680
Because if we want to know where
fish are, and we're going to do

798ba2e1-a719-4bb1-b211-5253248bbf79-1
00:42:32.680 --> 00:42:36.040
different setbacks based on
information on the flowline, we

798ba2e1-a719-4bb1-b211-5253248bbf79-2
00:42:36.040 --> 00:42:39.568
need to figure out ways to make
it easy for people to get that

798ba2e1-a719-4bb1-b211-5253248bbf79-3
00:42:39.568 --> 00:42:41.640
information out to the Polygon
data.

423f986f-bbb0-4727-95e2-00f07c72e7bd-0
00:42:41.960 --> 00:42:45.216
So, we're looking at ways of
connecting the different data

423f986f-bbb0-4727-95e2-00f07c72e7bd-1
00:42:45.216 --> 00:42:48.418
layers between each other.
Whether it's the wetlands, the

423f986f-bbb0-4727-95e2-00f07c72e7bd-2
00:42:48.418 --> 00:42:51.620
bank full width, the water
polygon; we want to have tools

423f986f-bbb0-4727-95e2-00f07c72e7bd-3
00:42:51.620 --> 00:42:53.000
that allow us to do that.

2d60f5fc-ee19-4229-b2c9-a45edb8c6ff4-0
00:42:53.000 --> 00:42:57.438
And lastly, we're hoping to do
some work with Esri to develop

2d60f5fc-ee19-4229-b2c9-a45edb8c6ff4-1
00:42:57.438 --> 00:43:02.020
some analysis tools that make it
easy to compare different data

2d60f5fc-ee19-4229-b2c9-a45edb8c6ff4-2
00:43:02.020 --> 00:43:06.315
layers on a single flowline or
compare the flowlines to the

2d60f5fc-ee19-4229-b2c9-a45edb8c6ff4-3
00:43:06.315 --> 00:43:06.960
polygons.

70bb6191-ac92-44bc-bdac-688b1a8b0097-0
00:43:08.720 --> 00:43:12.852
So, moving forward, we have a
lot of different jurisdictions

70bb6191-ac92-44bc-bdac-688b1a8b0097-1
00:43:12.852 --> 00:43:16.984
and I'm getting close to the
end, but I just want to wrap up

70bb6191-ac92-44bc-bdac-688b1a8b0097-2
00:43:16.984 --> 00:43:20.439
with the fact that we have a lot
of federal lands.

e05ff784-7379-4d4d-b65f-4df7fc333145-0
00:43:20.440 --> 00:43:24.250
And so, we've been working
closely with our US Forest

e05ff784-7379-4d4d-b65f-4df7fc333145-1
00:43:24.250 --> 00:43:28.626
Service because they have a lot
of interest, and they are the

e05ff784-7379-4d4d-b65f-4df7fc333145-2
00:43:28.626 --> 00:43:31.520
stewards for those Forest
Service lands.

61fbeda1-ad61-466a-bca9-9df62e1d8227-0
00:43:31.520 --> 00:43:35.922
But we want to make sure that
we're working together. The EDH

61fbeda1-ad61-466a-bca9-9df62e1d8227-1
00:43:35.922 --> 00:43:40.608
3DHP methodology works best at a
watershed scale, does not always

61fbeda1-ad61-466a-bca9-9df62e1d8227-2
00:43:40.608 --> 00:43:42.880
matter the jurisdictions, right?

27fb6cec-9fb7-4afc-8701-72ae2c7dde97-0
00:43:42.880 --> 00:43:45.440
It's a watershed level analysis.

307c4298-fd40-4aa5-8194-3362a50a2ce4-0
00:43:45.440 --> 00:43:49.303
And so it's really important now
more than ever to make sure that

307c4298-fd40-4aa5-8194-3362a50a2ce4-1
00:43:49.303 --> 00:43:52.698
we work with all the different
jurisdictions whether it's

307c4298-fd40-4aa5-8194-3362a50a2ce4-2
00:43:52.698 --> 00:43:55.040
cities and counties, tribal or
federal.

a64f94e4-e1fd-4587-9750-8193fb72fef8-0
00:43:55.200 --> 00:43:58.101
And so we are taking that
approach in Washington and

a64f94e4-e1fd-4587-9750-8193fb72fef8-1
00:43:58.101 --> 00:44:01.440
trying to make sure that we
communicate, share, and partner.

e0f7acd9-d748-44b6-b513-b5c1ac4f4cf3-0
00:44:02.360 --> 00:44:06.899
And to that end, we have
submitted to the state a request

e0f7acd9-d748-44b6-b513-b5c1ac4f4cf3-1
00:44:06.899 --> 00:44:11.594
for funding to remap the entire
state over five years using

e0f7acd9-d748-44b6-b513-b5c1ac4f4cf3-2
00:44:11.594 --> 00:44:14.960
elevation-derived hydro to feed
into 3DHP.

52d1c094-6d75-46e0-a622-1fd3b63802f5-0
00:44:15.720 --> 00:44:20.004
Our request is only, at this
point, only the stuff that would

52d1c094-6d75-46e0-a622-1fd3b63802f5-1
00:44:20.004 --> 00:44:24.220
feed 3DHP. The OneHydro are
things that we hope to build off

52d1c094-6d75-46e0-a622-1fd3b63802f5-2
00:44:24.220 --> 00:44:28.297
of in the future either through
partnerships or additional

52d1c094-6d75-46e0-a622-1fd3b63802f5-3
00:44:28.297 --> 00:44:29.680
requests of funding.

e837c46a-e1c0-4238-ae5f-83d2f4946530-0
00:44:29.880 --> 00:44:34.227
But we wanted to make sure that
we got that sound skeleton of

e837c46a-e1c0-4238-ae5f-83d2f4946530-1
00:44:34.227 --> 00:44:35.840
3DHP updated statewide.

e4ae38bf-d204-46eb-9275-cc7bd9b5aa0e-0
00:44:35.960 --> 00:44:38.884
We feel like that's super
important. And we're also

e4ae38bf-d204-46eb-9275-cc7bd9b5aa0e-1
00:44:38.884 --> 00:44:41.640
looking at how this transition
is going to work.

0f53a77a-dc3c-4ab0-9e5f-a5aaf4ad7972-0
00:44:41.960 --> 00:44:47.456
When we go from NHD to NHD data
in 3DHP, to updating it over the

0f53a77a-dc3c-4ab0-9e5f-a5aaf4ad7972-1
00:44:47.456 --> 00:44:52.530
years and ending up with a 3DHP
that is entirely derived by

0f53a77a-dc3c-4ab0-9e5f-a5aaf4ad7972-2
00:44:52.530 --> 00:44:54.560
elevation-derived hydro.

63e24dc4-93e9-4387-9c7a-7f6d5713e1f7-0
00:44:54.960 --> 00:44:58.786
Because we are going to have
reach codes and then at some

63e24dc4-93e9-4387-9c7a-7f6d5713e1f7-1
00:44:58.786 --> 00:45:00.040
point mainstem IDs.

e7c76fc1-4357-42fb-a8b7-7489bbd18f28-0
00:45:00.200 --> 00:45:02.040
But then we're going to lose the
reach codes.

e0e651f6-531c-4890-ad0b-17f5c0679450-0
00:45:02.400 --> 00:45:06.820
And just figuring out how do we
work as we do that update

e0e651f6-531c-4890-ad0b-17f5c0679450-1
00:45:06.820 --> 00:45:11.088
statewide, region-by-region to
make sure that we're not

e0e651f6-531c-4890-ad0b-17f5c0679450-2
00:45:11.088 --> 00:45:15.280
breaking all these processes
that we have established.

aa8024d0-65e4-4b70-b414-a26492bc68f2-0
00:45:16.360 --> 00:45:19.857
Our ongoing work is completing
our pilot review and I'm hoping

aa8024d0-65e4-4b70-b414-a26492bc68f2-1
00:45:19.857 --> 00:45:23.077
that by January 1st, that's
something that's available to

aa8024d0-65e4-4b70-b414-a26492bc68f2-2
00:45:23.077 --> 00:45:26.520
anyone on the call and we'll
share that through our web page.

bedd61dc-24b8-4dcc-867c-35e091d1d172-0
00:45:27.120 --> 00:45:30.848
We are also continuing to look
at the OneHydro concept, whether

bedd61dc-24b8-4dcc-867c-35e091d1d172-1
00:45:30.848 --> 00:45:34.460
it's the stormwater integration,
wetland mapping options, and

bedd61dc-24b8-4dcc-867c-35e091d1d172-2
00:45:34.460 --> 00:45:35.800
culvert collaborations.

a46c88e0-b6ee-4433-bcfb-aea8ce9acbdf-0
00:45:36.320 --> 00:45:41.160
We're working actively with Esri
on the tool development.

8ae903c9-3bbd-4a8a-a128-3d7e168208f2-0
00:45:41.160 --> 00:45:44.240
We've been working with Dan
Djokic and his ArcHydro team.

cf519772-8b3f-4aaa-bb87-9d3ad63439ac-0
00:45:44.480 --> 00:45:48.226
We've actually committed a fair
amount of advantage points to

cf519772-8b3f-4aaa-bb87-9d3ad63439ac-1
00:45:48.226 --> 00:45:50.040
help develop tool development.

1fe19ee0-cd41-40e1-be80-3d356ef1541d-0
00:45:50.360 --> 00:45:53.333
And as we get that a little bit
more advanced, I hope to reach

1fe19ee0-cd41-40e1-be80-3d356ef1541d-1
00:45:53.333 --> 00:45:56.164
out nationally because I think a
lot of these tools will be

1fe19ee0-cd41-40e1-be80-3d356ef1541d-2
00:45:56.164 --> 00:45:58.760
similar to what other folks are
going to want as well.

11109f5e-396e-4329-8300-439fbc0907d1-0
00:45:59.800 --> 00:46:03.563
We are working on the process of
contracting for this work. To

11109f5e-396e-4329-8300-439fbc0907d1-1
00:46:03.563 --> 00:46:07.029
having elevation-derived hydro
created and we're actually

11109f5e-396e-4329-8300-439fbc0907d1-2
00:46:07.029 --> 00:46:10.374
hoping to have a statewide
contract, a statewide master

11109f5e-396e-4329-8300-439fbc0907d1-3
00:46:10.374 --> 00:46:13.840
contract, that means it's easy
for us to purchase off of.

84a1ce3e-3268-4337-9618-37625e22b215-0
00:46:14.040 --> 00:46:17.079
But in the future if a local
jurisdiction wanted to do an

84a1ce3e-3268-4337-9618-37625e22b215-1
00:46:17.079 --> 00:46:20.485
update for their region because
of new Lidar, they would be able

84a1ce3e-3268-4337-9618-37625e22b215-2
00:46:20.485 --> 00:46:22.320
to use that as well to do
updates.

20993285-27a0-4cb1-bf0b-fbec5c15adf1-0
00:46:22.880 --> 00:46:27.248
And lastly, just making sure we
are working with future funding,

20993285-27a0-4cb1-bf0b-fbec5c15adf1-1
00:46:27.248 --> 00:46:31.416
whether it's the DCA process
through USGS, or other available

20993285-27a0-4cb1-bf0b-fbec5c15adf1-2
00:46:31.416 --> 00:46:35.314
grants, to make sure that we can
continue this to be done

20993285-27a0-4cb1-bf0b-fbec5c15adf1-3
00:46:35.314 --> 00:46:37.600
succinctly in a five-year
period.

c0080b2f-e364-4809-93d9-6993df0fe043-0
00:46:38.360 --> 00:46:41.319
Lastly, I just want to say how
important it is that we all work

c0080b2f-e364-4809-93d9-6993df0fe043-1
00:46:41.319 --> 00:46:44.279
together and that's why I really
appreciate this opportunity to

c0080b2f-e364-4809-93d9-6993df0fe043-2
00:46:44.279 --> 00:46:46.360
share what we're doing to get
your feedback.

595a3faa-0384-422c-8f23-b8ac6b2e45bf-0
00:46:46.600 --> 00:46:50.363
But also working with the local
jurisdictions, state agencies,

595a3faa-0384-422c-8f23-b8ac6b2e45bf-1
00:46:50.363 --> 00:46:53.828
tribal entities, federal
partners, USGS themselves. It is

595a3faa-0384-422c-8f23-b8ac6b2e45bf-2
00:46:53.828 --> 00:46:57.471
critical because this is such a
fundamental change in how we

595a3faa-0384-422c-8f23-b8ac6b2e45bf-3
00:46:57.471 --> 00:47:00.160
have done business with
hydrography mapping.

2d1a49bf-9431-4b1a-b6a2-2fc08a17057a-0
00:47:00.520 --> 00:47:03.679
But based on what we have seen
in our pilot project, we are

2d1a49bf-9431-4b1a-b6a2-2fc08a17057a-1
00:47:03.679 --> 00:47:06.944
really excited about this future
change and the benefits it's

2d1a49bf-9431-4b1a-b6a2-2fc08a17057a-2
00:47:06.944 --> 00:47:07.840
going to give us.

3bb4f495-a88a-4a71-b510-0f28c8fb6a43-0
00:47:09.200 --> 00:47:11.120
That's all that I have for my
talk.

eacef105-0bb3-4aa2-b076-bd8b72dff2e4-0
00:47:11.120 --> 00:47:14.400
I think we have ten minutes
left, Drew, That's my e-mail.

1cf1d356-4200-42b2-abed-72aea0a3e4d0-0
00:47:14.400 --> 00:47:15.320
I'm always happy.

ad86148f-d5b2-4300-95af-8af9cfbaeb63-0
00:47:15.320 --> 00:47:19.244
In case you can't tell, I am
very passionate about this, very

ad86148f-d5b2-4300-95af-8af9cfbaeb63-1
00:47:19.244 --> 00:47:20.320
excited about it.

58e413ea-23c2-41b1-be4d-d2f1208b998d-0
00:47:20.320 --> 00:47:24.729
I'm always looking to have
discussions. And we have some

58e413ea-23c2-41b1-be4d-d2f1208b998d-1
00:47:24.729 --> 00:47:28.984
information on our website now
and actually one of our

58e413ea-23c2-41b1-be4d-d2f1208b998d-2
00:47:28.984 --> 00:47:33.780
strategic plans is to reupdate
our pages, moving to sites and

58e413ea-23c2-41b1-be4d-d2f1208b998d-3
00:47:33.780 --> 00:47:36.720
having a lot of this new
information.

d0508524-3706-43ef-b017-438c659cb6dc-0
00:47:36.720 --> 00:47:40.782
But there are currently things
like our strategic plan. There's

d0508524-3706-43ef-b017-438c659cb6dc-1
00:47:40.782 --> 00:47:44.781
a one page, our two pager about
this project, and we also have

d0508524-3706-43ef-b017-438c659cb6dc-2
00:47:44.781 --> 00:47:48.907
some recordings that we've done
with our stakeholder meetings. A

d0508524-3706-43ef-b017-438c659cb6dc-3
00:47:48.907 --> 00:47:50.239
couple announcements.

ff7eb567-dce3-49e4-a8d3-24a8af50a8d2-0
00:47:50.240 --> 00:47:53.645
We will be having a link to the
recording of today's call out

ff7eb567-dce3-49e4-a8d3-24a8af50a8d2-1
00:47:53.645 --> 00:47:53.920
soon.

05174b4f-93e8-4081-a96e-839a5a93d23c-0
00:47:55.160 --> 00:47:58.708
Alex Jonesi with NGP Topographic
Data Services Group normally

05174b4f-93e8-4081-a96e-839a5a93d23c-1
00:47:58.708 --> 00:48:01.800
helps with these calls and
especially the video prep.

9dda15b8-9f25-4d0c-a206-d6f8d6925e62-0
00:48:02.240 --> 00:48:05.480
He's out today, but we'll get
this out to everybody shortly.

e679bfe1-2329-4c38-b378-e94c97fdf620-0
00:48:05.480 --> 00:48:09.440
I also wanted to mention. Note
that Karen Adkins, who's on the

e679bfe1-2329-4c38-b378-e94c97fdf620-1
00:48:09.440 --> 00:48:12.960
call today, will be managing
these calls in the future.

1f14bccd-247e-484b-a3c3-bce222f5ad30-0
00:48:13.120 --> 00:48:17.280
Karen is NGP User Engagement
Liaison Supervisor for the

1f14bccd-247e-484b-a3c3-bce222f5ad30-1
00:48:17.280 --> 00:48:21.365
Midcontinent and Northeast
Regions and the Hydrography

1f14bccd-247e-484b-a3c3-bce222f5ad30-2
00:48:21.365 --> 00:48:24.040
Focus Area Lead in User
Engagement.

87a05e20-31ef-4d8b-b0aa-97cf4b41e4e9-0
00:48:24.240 --> 00:48:27.625
So, many of you know Karen from
her previous role as a Senior

87a05e20-31ef-4d8b-b0aa-97cf4b41e4e9-1
00:48:27.625 --> 00:48:30.737
Hydrography Lead with USGS
National Geospatial Technical

87a05e20-31ef-4d8b-b0aa-97cf4b41e4e9-2
00:48:30.737 --> 00:48:31.720
Operations Center.

11fc9071-f2ce-4a2f-b1f9-da64ca5e97ec-0
00:48:31.720 --> 00:48:35.291
So we welcome Karen to join the
group here and of course Alex

11fc9071-f2ce-4a2f-b1f9-da64ca5e97ec-1
00:48:35.291 --> 00:48:38.920
and I will continue to provide
support to Karen and this call.

bb6103c0-59e4-4579-85aa-27a61a471a6f-0
00:48:39.280 --> 00:48:41.440
So thank you very much.

362b0551-f341-497d-acb1-6440c96ef213-0
00:48:41.520 --> 00:48:43.240
Thank you Josh for being on the
call.

43c1be2a-2e5c-4b5f-9291-dfb69bf5a93f-0
00:48:44.440 --> 00:48:46.960
We will have our next call by
the way in January.

064725db-f9fc-4977-86a6-313129cc60a2-0
00:48:46.960 --> 00:48:49.400
We're skipping the December one
because of the holidays.

3d6fdb73-37d4-47b4-8f13-f0800a35b678-0
00:48:49.600 --> 00:48:53.981
The next call will be on
Tuesday, January 23rd, 2024,

3d6fdb73-37d4-47b4-8f13-f0800a35b678-1
00:48:53.981 --> 00:48:58.200
most likely with the Corps of
Engineers, I believe.

7f7a3579-1f17-48ea-b1a4-4d57d6634b7f-0
00:48:58.720 --> 00:49:02.033
So, we'll have all this
information out to you shortly

7f7a3579-1f17-48ea-b1a4-4d57d6634b7f-1
00:49:02.033 --> 00:49:03.480
and other announcements.

bad826b2-75e6-495e-b786-49c02b950e1d-0
00:49:03.480 --> 00:49:05.440
So thanks very much for your
time today.

7fdd9470-fd2a-4675-8f41-772ee6861bc0-0
00:49:05.440 --> 00:49:07.480
And Josh, that was a great
presentation.