- [Announcer] Tools and Technology contributed talks room.
We are about to have our last presentation
from Melissa Czarnowski
with the Connecticut Department of Energy
and Environmental Protection.
She'll be presenting on "Monitoring Stream Connectivity
with Trail Cameras."
- [Melissa] Hi everyone, my name is Melissa Czarnowski.
I've worked for the Connecticut Department of Energy
and Environmental Protection.
And today I'm gonna be presenting on a project
that we've been working on for the past five years,
which is "Monitoring Stream Connectivity
with Trail Cameras."
I realized this is a forest ecosystem conference
so I'm not entirely sure how much
of this will apply to your work,
but hopefully you will leave this presentation
with some good ideas for your own projects.
Before I get started I just wanna say
that we recently published this article,
A Novel Method to Evaluate Stream Connectivity
Using Trail Cameras in River Research and Applications,
which goes into depth about our methods
while evaluating stream connectivity through pictures.
If you wanna dig into our research after this presentation.
And I just wanna acknowledge the main author
Chris Bellucci and coauthors,
Mary Becker and Corinne Fitting.
And in addition, Allie Hibbard and Laura Robbins
who have been instrumental in helping me
with the field work.
So I've provided the link to that article
right here in this corner in case you're interested.
Today I'm going to go over a brief background
of why we decided to start using trail cameras
to monitor stream connectivity,
our method, how we evaluate stream flow
from the pictures,
the metrics we use to evaluate stream flow impairment
and the few examples of what we've seen so far.
So why monitor stream flow with pictures?
Well, first and foremost, pictures speak a thousand words.
All of these pictures were taken on August 21st, 2020.
Two of these streams are completely dry
as you can see on the left
and two of these streams have flowing water on the right.
The two streams that are completely dry
are located within the vicinity of water withdrawals
which leads me to my second point.
We began this project to document the effects
of water withdrawals on stream flow.
One of deeps responsibilities is to regulate water usage
over 50,000 gallons per day through a permanent program
that was established in 1982.
Any water diversion that existed prior to 1982
was allowed to continue withdrawing
as much water as they registered for
without any kind of environmental assessment
or public review.
These are known as registered diversions.
Today we're observing some of these streams dry up
next to these diversions, like these two shown here.
So we knew that they were a problem
but we didn't really have a good handle
on the scope of the problem.
Like when does it go dry and for how long?
And since stream gauges are few and far between
we needed to figure out a better way
to document stream flow differently.
Our solution was to use trail cameras.
One thing that I wanna emphasize is that photos are data
that provide a record of conditions.
The photos need to be clear, centered
and without any obstructions.
Without this we wouldn't be able to qualitatively
and semi-quantitatively assess the stream flow.
Stream connectivity is important for the ecological health
of the stream and downstream waters.
We define stream connectivity
as hydrologically connected pools and riffles
that link stream habitat along the longitudinal continuum,
so that's upstream to downstream.
While also recognizing the lateral dimension,
the connection to the flood plane
and vertical connection to groundwater.
We focus on the rear end growth file period
which is from July 1st through October 31st.
These are the flows that are needed to sustain aquatic life.
And also typically the season of highest conflict
with human uses such as lawn irrigation.
This diagram shows our method for how we go from pictures
to metrics to help inform decision-makers.
I'll go into detail on a few
of these in the next couple of slides,
but in general we select a location on a stream
that captures at-least one referral pool sequence.
When we deploy the trail camera,
we set it's take one picture per hour.
When we download the images back in the office
we assign the stream connectivity category to each image,
which I'll go into more detail in the next slide.
And then based on those categories
we calculate the average daily stream connectivity metrics
which I will also go into more detail on.
So this helps us to visualize the data
and it helps us to inform stream management.
We developed a six category system
to describe the variations in stream connectivity observed
using trail camera images.
Category one is completely dry.
Category two has some pools of standing water but no flow.
Category three has a minimal flow
in which some pools and riffles are disconnected
and some habitat types are not accessible.
Category four has flows with well-connected pools
and riffles,
Category five is where the flow fills the stream channel
at or just below bank full discharge.
And category six is when the flows
are above the bank full discharge and into the flood plane.
Once we download the pictures from the field
we assigned each picture one of these categories.
We then use the categorical data to calculate metrics
that quantify stream connectivity.
We developed 30 stream connectivity metrics
to represent this data.
The duration metrics represent a period of time
and images associated with a category.
For example,
the average number of consecutive days in category one.
The frequency metrics represent how often an images
is in a category such as number of days in category one.
The magnitude metrics provide a statistical summary
of the category such as the average flow category,
and the timing metrics describe
when category occurs temporarily,
such as the Julian day of the first observation
in category one.
So here's an example of the timing and duration metrics.
Here, we have seven streams that we monitored
with trail cameras.
The bars represent the stream flow
from July through October,
the blue sections of the bars
show when the stream was connected,
the pink section show when the stream was disconnected
and the red section show when the stream was completely dry.
As you can see from this fig here,
four of the streams that we monitored stayed connected
throughout the study period,
two of these streams jumped back and forth
between connected, disconnected and dry.
And one of these streams clearly had a gradual decrease
in stream flow until they remained dry
throughout the study period.
Here's an example of one of the frequency metrics.
The number of days from July through October
in which the flow was dry.
Here you can see that Chidsey Brook
had the most number of days, almost 50, in which it was dry,
followed by Mill River and Cobble Brook.
The four other streams had no days in which the flow was dry
as this was also represented on the previous figure.
And here's an example of the magnitude metrics.
The average flow from July through October.
This figure shows that four of these streams
had an average flow category of four,
whereas the other streams had an average flow category
between two and three.
This metrics example is a little more complicated
but I think it's worth explaining.
Here we have the seven streams that we've been looking at
in the previous examples.
Each line represents the change in stream flow
from July 1st through October 31st.
The white areas of the bars represent connected flow
and the gray areas of the bars represent disconnected flow.
Now the blue sections of the lines,
show when the USGS reference gauges
had normal to high flows.
The black sections of the lines
show when the USGS reference gauges had low floats.
So we would expect the blue sections of the lines
to be in the white areas of the bars
and the black sections of the lines
to be in the gray areas of the bars.
We mostly wanna focus on the blue sections of the lines
being in the gray areas of the bars,
since we are specifically looking for flow impaired streams.
I just wanna point out a few examples
of where this occurred.
As you can see, these three streams
were observed to have disconnected the stream flow
when the USGS preference gauges
had normal to high flows.
Adding data to the conclusion
that these three streams are flow impaired.
And these are the same three streams that we've been seeing
as flow impaired in the previous examples.
Now, I just wanna take you through an example
of one of our trail cameras
located near a USGS stream gauge.
This is a short period from September 7th
through October 2nd of 2016,
and if you pay attention to this little red star
on the hydrograph,
you'll see how it correlates with the stream flow
in the picture.
So here we have September 7th
with a stream flow of 2.7 cubic feet per second.
September 10th 2.20 cubic feet per second.
And now it's dropping to 1.2 CFS,
and you can see that clearly in the stream flow
in the picture.
It jumps up to 3.2 CFS,
goes back down to 0.97 CFS,
jumps up to 4 CFS after a rain event.
Goes back down to 1.4 CFS.
And ends with 2.4 cubic feet per second.
As I mentioned at the beginning of this presentation
before we began this project we didn't have a good handle
on the scope of the issue of flow impaired streams.
The department is required to identify flow impairments
with the integrated water quality report,
which is a report that goes to the EPA every two years.
In 2014, we had identified 34 miles
of flow impaired streams throughout the state.
And in 2016, after we began this project
we identified 159 miles of full impaired streams.
And finally, as an added bonus to this trail camera project
we get lots of wildlife images
which is always fun to look at.
All of the source code and data for this project
are freely available and open source at this link right here
github.com/marybecker/streamconnectivitymetrics.
And with that I would just like to say,
thank you for taking the time to listen
to my presentation today and I will take any questions.
- [Announcer] Do you see this as a monitoring technique
you will be maintaining as a regular part of business
moving forward?
- [Melissa] Hi Jim.
Yeah for the foreseeable future
I think that we will be continuing monitoring
with trail cameras.
We are specifically looking at the impact
of water withdrawals to near streams.
So we're in the process of actually getting water use data.
So it would be really interesting
to see what the pictures look like
when we have the water use data as well.
So for the foreseeable future we will,
but I'm not sure about a long-term project.
- [Announcer] And John McCann asked,
was there any consideration of putting staff plates
in the field of view to track stage as well?
- [Melissa] So we monitor probably about 40 streams
throughout the state of Connecticut
and we just don't have the resources
to do that for all of the streams that we're looking at,
but it is a good consideration.
- [Announcer] And Sarah Nelson asked,
do you think this would work well
in high gradient streams/mountainous sites?
- [Melissa] I think it would be kind of difficult
just because a lot of high gradient sites
have a lot of boulders and cobbles
that might make it more difficult
to see what the stream flow is actually like
in the pictures,
just from my experience of going out to the site
and seeing it in person comparing it to the picture.
If we have a really cobbly stream,
we might rate the picture a little bit lower
than what it actually is in person,
just because that view is obstructed by all the cobbles.
- [Announcer] Andy Wood is asking,
do you have any issues with cameras being tampered with?
- [Melissa] For the most part we've lucked out.
We've had a couple cameras that have been stolen
and a few cameras that have been attempted to be stolen.
We lock all of our cameras with a lock
and tether it to the tree.
And we also put a little tag on it that says,
"This camera belongs to the department for research purposes
please don't tamper."
I'm not sure if that works or not,
but so far we've been pretty lucky.
- [Announcer] And there's a comment from John McCann.
It would be interesting to know if NDVI
along the stream tracked
with the connected/disconnected patterns you see.
And it says maybe more of a comment.
- [Melissa] Okay, thank you.
- [Announcer] Jim Duncan has a question.
This is really in the weeds,
but how are you dealing with the storage
and preservation of images
after you have extracted the info you need from them?
- [Melissa] That's a really good and important question
and it's something that we are working on.
So right now we luckily don't have a storage space issue
on our network.
So we've been able to save all the images
but having a way to query all the data
has been a little bit more challenging
and that's something that we are working on.
I know Chris Bellucci is on the call
if he has any thing further to say to that.
- [Chris] Yeah. Thanks, Melissa.
I will just say that that is a really
and important consideration,
just like any continuous data where you collect hourly,
for example stream temperature
or anything else you guys might be involved with.
It soon adds up very quickly and Melissa mentioned,
at any given year we have 30 to 40 cameras
collecting hourly images and it adds up
and so I think if you're gonna pursue this type of thing
you might think about having a server dedicated to it.
Not only for storage of the pictures
cause the pictures really are the data,
but also for processing and querying
and trying to do any analysis with the data,
very important consideration.