- Welcome everyone to Wednesday
Nite @ the Lab.
My name is Bea Mumm.
I am a science outreach educator
at UW-Madison Biotechnology Cent
er.
On behalf of the Biotechnology Ce
nter,
UW Division of Extension, Wiscon
sin Public Television,
the Wisconsin Alumni Association
,
and the UW-Madison Science Alli
ance,
I would like to thank you for co
ming out tonight
to Wednesday Nite @ the Lab.
We do this every Wednesday night,
50 times a year.
Tonight it is my pleasure to int
roduce Dave Hart.
He is a hydrogeologist and pr
ofessor
in the Department of Environm
ental Sciences,
University of Wisconsin Divi
sion of Extension.
Dr. Hart completed his bachelors
in physics and mathematics
from Luther College in Decorah,
Iowa.
He served in the Peace Corps
as a science teacher in Botswana.
He then earned both his mast
ers and doctorate
in geophysics from UW-Madison.
Throughout his journey to get
ting his PhD,
Dr. Hart held various positions
as teaching and research assista
nts
through the Department of Geolog
y and Geophysics.
In 2000, he completed his postdo
ctoral work
through the UW-Madison
Department of Geology and Ge
ophysics
and accepted a position as a
hydrogeologist.
These positions have led Dr. Hart
to play a vital role
in informing the decisions regard
ing water quality.
He now focuses on both resea
rching water
and teaching other educators abou
t his work.
Tonight, Dr. Hart will provide a
review
of his water quality testing cano
e,
his journey to how he finalized
this comprehensive
and rapid method of testing,
and the importance of this inform
ation.
Ladies and gentlemen, please
join me in welcoming Dr. Hart.
[audience applauding]
- I'm gonna talk about
some multi-instrument stream sur
veys we did
on some small streams across Wis
consin,
kind of the purpose, why we do it
,
and kind of what we found out,
what was the value that we saw th
ere.
There's a large cast of characte
rs.
I'm Dave Hart with
the Wisconsin Geological Natura
l History Survey.
I want to recognize Professor Su
e Swanson from Beloit,
Jake Westrich, a summer stud
ent from Beloit.
There's Jake in the back of the
canoe.
Catherine Christenson in the fron
t of the canoe there.
And standing there was a student
in the Geoscience Department
who really,
much of what I'm doing here,
maybe most of what I'm doing here
, Catherine really led
the charge on and did a wonderfu
l job.
Susie Richmond, also another stu
dent
in the civil engineering.
Designed a lot of the electronic
s
that we used for this research.
Doctors Jean Bahr and Mike Cardif
f and Dante Fratta
are all professors at the UW.
Again, I felt really fortunat
e to be able to tie in
a wide cast of characters and th
eir expertise.
Andy Leaf at the USGS also provid
ed
a lot of really great input.
All right, so the issue that I th
ink we see facing us
and this issue's only going to b
ecome more acute
is our natural resources are,
the decisions we have to make are
gonna rely on
ever more complex modeling and d
ata
to support that modeling.
And so for an example, there'
s ELOHA.
It's got a really kind of a grea
t name,
ecological limits of hydrolog
ic alteration.
How far can we push the syst
em before a species
don't want to be there anymore?
We mostly worry about trout, but
I think
we could also worry about,
I think this is a redbelly dace
as well too.
How much alteration do we see
before we don't see the creature
s,
before we lose diversity in our s
ystem?
And so if we're gonna do that,
we may have a groundwater fl
ow model
that groundwater and the streams
are connected.
And so we may want to predict ho
w that's gonna occur.
So let's base, we've got a ground
water flow model.
Stream temperature is one of the
most essential things
to predict whether or not a fi
sh species will be around.
And so we put this into our mode
l of whether or not
a species is gonna be here,
our stream flow, our temperat
ure, land use,
and we put in some of these othe
r things.
We want to get these models right
so that we can do predictive stu
ff.
What happens if we get more rainf
all?
What happens if the temperature
changes significantly?
We can work on doing predictions
for this.
And there are people in my offic
e
and across the university
who are thinking about these
questions.
These models require more and bet
ter data
to constrain the models.
This is kind of an inside joke.
This is often how people say geop
hysicists view the world.
Data is equal to a model operatin
g on some parameters,
but we need observations if we're
gonna do modeling.
We need good data.
And early on in my career, I did
more modeling,
but what I saw is that we have a
lot of people,
really good people doing modeling
.
And what I saw is also Cliff Thur
ber in geoscience
has one of the best books on d
oing inverse modeling,
fitting parameters to models, to
data.
Professor Dante Fratta, also
of UW does this.
Mary Anderson at UW, recently re
tired hydrogeologist
and Randy Hunt at the USGS, all
of these folks
are doing modeling, they're doin
g all this work on modeling
and I thought well, we want to
catch up.
So why don't I work on this side?
This side's getting a lot of wor
k
that's working on getting more
data.
More and better data that we can
support the modeling
so we can support decisions.
So the second one is okay, we're
gonna go out
and collect data.
Then the second one was, we
need to be able to communicate
our science and result, and don'
t be such a scientist
I guess can be summed up in don't
,
you have to tell a story with you
r data.
And one of the things,
so we need to be able to communic
ate our science.
In Wisconsin Geological Natu
ral History Survey,
one of the most important th
ings we do
is communicate our science to
town boards and county boards.
I often think those people shou
ld all have geologic,
should be forced to take geology
in high school,
because so many land use decisi
ons are dependent
on that understanding.
And so we really kind of want to
be able
to communicate things.
And so that's one of the other is
sues that we want.
Citizen science is also a part of
that,
getting folks involved in unders
tanding and caring
about the science that we have.
So looking at those two issues t
hat I'm dealing with
and other people in my office ar
e dealing with every day,
there's several trends that occu
rred in the last decade
or two decades really since I st
arted at the survey.
Locating data is now easy.
That's where I was when I was ma
king this presentation.
I pulled up my phone, it opened u
p Google Maps,
took a screenshot, and put it in
here.
It's incredibly easy.
20 years ago, it was super hard t
o know
where I got that data from, now
it's almost trivial.
20 years ago, what did I get,
now I can get data within 10 feet
.
20 years ago I was happy I can
make a mark on a map,
maybe it's 100 feet, maybe it's
200 feet
is how accurate things are.
Storage large amounts of data is
low cost.
In fact, it's so kind of absurd,
you kind of need this adapter
so you can actually handle that 6
4 gigabyte thing.
It's so tiny, that little tiny
thing is like a little chip.
I'm glad they make the adapters,
I'm not gonna be able to read tha
t in a few years.
Then the other thing is inex
pensive videos everywhere.
We can capture what we were doin
g really quite easily
with our iPhones.
Here's a Hero GoPro and I just,
I was gonna google GoPro on a can
oe
but I didn't get far enough, and
you can see what pops up.
GoPro on a dog, turtle, fish
, cat, shark,
bird, catfish, eagle, RC car, an
d helmet.
So that's another trend.
10, 20 years ago that wasn't ther
e.
We can make use of this for our i
ssues.
And then it's easier
to develop prototype instruments
now too.
I am kind of on a lower budg
et where I'm at.
And so we now have low-cost micro
controllers,
a wide range of sensors that we
can plug into them,
and we can see how to build thin
gs on internet project hubs.
You might not be so familiar wit
h this,
I'm gonna spend a little bit o
f time
kind of going through that.
That last bullet is,
there's kind of a maker cult
ure out there,
which is a combination of do-it-y
ourself hacker
and artisan cultures.
It's a cut and paste approach
to standard hobbyist technologies
,
and it's really kind of a neat t
hing
that we can go out and build
it ourselves.
If you google makerspaces in
Madison,
we end up with three.
UW-Madison Makerspace, The Bodger
y, and Sector 67,
and here's where they're located.
And so I just went to the Bodger
y's webpage
and pulled some stuff off of tha
t.
I'm not recommending anyone over
another,
but they've got woodworking shop
, welding,
blacksmithing, sewing studio, 3D
printing,
electronics lab, et cetera et ce
tera.
And then we have this gentleman h
ere
who built a longboard.
You can quickly and easily bui
ld a board
that goes 30 miles an hour
and 10 or more miles.
It all depends on your budget.
On his budget, he went one that c
an go 70 miles
and up to 26 miles per hour.
I'll tell you as a father, I wish
he had a helmet.
[all laughing]
I saw that and thought, "Oh
God, okay."
So then the internet's also kind
of revolutionized
about what we, the things we ca
n do.
I just google Arduino, which is a
brand of microprocessor,
and temperature, and I come up
with all sorts of things.
And this is just an example.
And so this page explains what
materials are needed,
the code that you need to record
temperature on the Arduino.
We worked with this sensor a l
ittle bit,
I've used it for some other thing
s.
But it's accurate, waterproof, ea
sy to install,
and you only need a single port.
And social media is kind of also
part of this.
You can click on "respect this."
I don't see it somewhere, but th
ere's a button
you can click on, "respect t
his project."
And so the more respect you get,
the more, it's a very simila
r sort of thing.
But that's another tool that'
s available.
We didn't have that available.
Maybe you could look stuff up i
n a book.
It was a lot more specialized.
So the research question then,
look, thinking about those issues
,
thinking about the changes that w
e have,
we're gonna design a method to co
llect
spatial and temporally dense,
that's that low cost memory.
Geo-located, that's the, having G
PS everywhere,
sets of hydrologic data on small
streams
to understand stream quality
and groundwater/surface wate
r interaction.
That's that low cost sensor that
's gonna collect data
to support our modeling.
And so then, getting into backgr
ound of what we do now
and there's no reason to change
that,
here's one of my colleagues, Anna
Fehling,
up in northern Wisconsin
collecting some water qualit
y data.
And she's doing that the old-
fashioned way.
She's at a point in the stream,
she's got a single measurement
that's kind of integrating everyt
hing going on upstream.
And she's got a sensor and she's
recording data.
And then she's gonna record it
in this very extremely stable
platform
called a field notebook.
[audience laughing]
These things are field tested
, tried and true.
They last for centuries.
I'm not sure, the digital data i
s gonna
require some more care to mak
e that happen.
So this is generally what we do,
and it's not gonna be replaced
because we know where we were,
we knew when we were there,
we have all sorts of good data,
and we know how to do this.
So sometimes we'll put a stat
ion in here,
something that will just record o
ver time as well too.
And so the data volume and lo
cations are limited by cost.
It would be difficult to collect
hundreds of measurements in a day
on these streams.
You can see it's pretty rock
y as well too.
Okay, so with those things in mi
nd,
what were we gonna do?
Let's collect multiple datase
ts simultaneously
from a canoe or kayak.
We're gonna geolocate everything
,
we're gonna collect it on the sca
le of seconds.
So you know how a canoe goes abo
ut a meter a second
or a couple of meters a second
depending on how ambitious you ar
e.
And so we're gonna be on a deci
meter to meter scale,
how fast we're going.
We're gonna look at groundwater
and small stream interactions.
Groundwater because that's what
I've been trained in
and something I can understand,
and I want to understand
how groundwater is interacting
with these small streams.
These small streams are most sus
ceptible to impacts.
They don't have a lot of flow.
When you get dry years, the head
waters may dry up
and the stream recedes.
Wet years, it's gonna move arou
nd a little bit more.
We're gonna see the most variati
on
in water chemistry, why?
Because if you have a small spri
ng flowing into this stream,
you might get something measurab
le,
a small spring flowing into the W
isconsin River,
you're not gonna be able to meas
ure that,
you're not gonna be able to see i
t.
And they also support a large am
ount of diversity
and native species too.
So we can kind of tie all those
things together.
So we want this data to support
groundwater models,
and we are guessing that this st
uff
will be informative for other pu
rposes.
Maybe not something that a hydrog
eologist will understand,
but there are other experts out
there who might use this.
So this is what we are doing,
this is what we hope to do.
Just kind of pure and simple.
We hope to collect a nice long r
each of a river
all in the course of a couple of
hours.
And so that's what it was concept
ually.
This is Lulu Lake, here's our st
ream that we're going up.
There's our canoe.
You can kind of get a sense of
what a really pleasant day th
is can be
if everything's going right.
You can see Jake barely,
you can maybe see Jake there smi
ling.
Being in the back's where you wa
nt to be,
because you're not worried ab
out all the instrumentation.
Catherine up front is not smiling
because she's trying to manag
e all the data
and make sure everything's worki
ng.
So what five streams were we goin
g to do?
We're gonna look at our criteria,
we're gonna look at previously s
tudied streams:
Marengo, Allequash, Little Plover
River, Grant River,
and the Mukwonago.
These streams all had smaller
flows,
they're all across Wisconsin
in different geographic provinces
.
And so what are the parameters
that we're going to collect here?
We're going to collect water qual
ity parameters,
temperature, dissolved oxygen,
pH, specific conductance,
how well does the water cond
uct electricity,
nitrate and chloride, and all th
at will be geolocated.
It'll all have a location, that l
ong stamp on it.
Ecological, maybe GoPro video,
and then geophysical will collect
how well the ground conducts the
electricity,
we'll collect the depth of the w
ater,
and we'll try ground-penetrating
radar.
So location, both all those will
be geolocated.
And then we were gonna try RT
K GPS, real-time kinetic GPS
which is very accurate.
It gives you centimeter horizonta
l
and close to centimeter vertical.
Now you just take your, boop, it
's really kind of magical
for someone who had to use a su
rveying total station
for the first 10 years of my care
er.
This is kind of a magical way
to go.
That was so much more work, this
is super easy.
And the reason I wanted to do tha
t
is I wanted to get the stage
of the stream.
How does the stream elevation ch
ange
as I go downstream or upstream?
How do things vary?
And so we didn't do the ground-p
enetrating radar,
we discovered that's a ton of wor
k,
the batteries keep dying, it's a
lot of effort,
and all we really are doing is g
etting a radar wave
bouncing off the bottom sediment.
We're not getting a lot of infor
mation.
So we said that's too much work,
we're not gonna do it.
We already have a lot of measur
ements we're making,
and we're not gonna do that real-
time kinetic GPS.
It sounds pretty cool, sounds
pretty fancy,
but now we have LiDAR.
I can go download an elevation a
nd get
the stream elevation if I want.
It's available to all of us in th
is room for almost,
I think there's only a few count
ies
that don't have it available.
So I can get the elevation of eve
ry stream
and its gradient as I go.
I would also say I kind of was,
didn't want to miss seeing either
one of these go.
This was maybe worth 20 or 30K r
eplacement value,
and this was worth 20K replac
ement value.
We're in a canoe, so I don't want
things to get wet.
And so that reduced, that took a
way like two-thirds
of the total cost of swamping.
And this was also on loan from
the USGS.
And so swamping someone else
's equipment
is also not something I wanted t
o do.
So we're gonna collect a lot
of things.
I should say we're following the
work
of a lot of other folks and folk
s from Wisconsin.
For the geophysics professor who'
s,
Wu and Fratta did some work i
n Lake Superior.
Bill from UW-Madison, Bill Kean
and his student,
Mike Baierlipp from UW-Milwaukee
, did a study
in the Fox River and Waukesha.
Eric Compas from Whitewater
and Suzanne Wade from UW Extensi
on
did a really neat study
where they went down the Rock Ri
ver
and you could see the data come
in in real time,
and the water quality data, re
ally neat study.
And then of course there's th
e FLAM group,
fast limnological automated
measurements
from UW-Madison Center of Limnol
ogy
and these guys have a nation
al reach and reputation.
They go all around and collect
data.
And then there's video, I wasn't
the first person
to put a GoPro on a canoe or a k
ayak.
Those are generally relaxing.
However, you can find many much
less relaxing GoPro videos.
They're absolutely terrifying Go
Pro videos as we go.
So here's kind of the canoe, kin
d of tricked out.
This is one of our earlier survey
s,
we're in the Waubesa Wetlands her
e.
There's kind of the, we're sitti
ng,
Lake Waubesa is off to the back.
You can see we've got our camera
, our fish finder.
This was an early one as I said.
We don't have the, we thought I
was gonna have
a little more heft to me than I
did.
We thought that was gonna be u
nderwater,
it wasn't underwater.
We wanted it to be underwater.
So we fixed that, and here's the
EM31
measuring ground conductivity.
We'll revisit this again here.
The canoe's plastic because we'r
e using
an electromagnetic meter and we w
ant to be able
to get the signal through the
canoe.
Plastic canoe works, aluminum can
oe not at all.
And I think even, I wasn't abl
e to swing
a nice sweet new Kevlar 'cause I
think
they still had even too much
metal in them.
So we went with all plastic,
100% plastic.
It also allowed us to modify the
canoe with a saw
if we needed to, so we can fit mo
re stuff in and around.
It's easier to work.
Okay, here's the fish finder and
back.
Again earlier on, here's some zi
p ties,
and here's kind of our flow-throu
gh cell with pump
and we've got some electronics.
we'll talk more about that a lit
tle bit.
Just want to give you a sense an
d there's that fish finder.
So first off, the first system
if we want to think about it,
was for the water chemistry.
And so we used Arduino,
there's also a cleverly name
d Arduino's,
is an Italian company.
There's also, Raspberry Pi is a
nother microprocessor
that's often used in science.
And so that's that open-source
so we couldn't use the Uno,
which was the basic small model
of the Arduino.
We had to use the Mega.
And so here's the Mega here.
We needed more ports and inputs
with all of those water chem
istry parameters
that we were gonna measure in the
location.
So here's the board, it's gonna
read all of the sensors
and it's gonna store the data.
It's gonna connect with the GPS
and do all of that communication.
Here's the little GPS, they c
all it a shield
that connects on here, that's
the antenna.
This GPS works way better than my
phone
and it cost, I think you can ge
t this card for like $15.
And you get something that's real
ly quite accurate.
And then here's the sensors that
we measured,
pH, nitrate chloride, conductivi
ty,
dissolved oxygen, and temperatur
e.
This one, I'm not quite sure
that I'm done with this one yet.
We thought we'd try Turbidity.
That sensor is quite inexpensive.
They're mass-produced and if you
have a dishwasher
or a clothes washing machine,
its turbidity,
when is it done rinsing your clo
thes,
when is it done cleaning out
the suds,
is being measured by a sensor l
ike this.
Kevin Fermanich at UW-Green Bay
has told me he's getting some dec
ent data
from a sensor like this that
can read pretty low turbidity,
how cloudy is the water.
They can read water that loo
ks pretty clear
but still has some turbidity in i
t that's blocking light.
And so we might crank that one b
ack up.
You'll hear why we didn't use th
at in a second too.
This is something I can affo
rd on my budget.
If I were to go and buy a sy
stem like this,
I'd be looking at $20,000, an
d it wouldn't be geolocated.
That said, it's really nice t
o have somebody
engineer things for you, bec
ause otherwise,
we went through a lot of trial a
nd error
getting things to work, and you'
ll see some of that.
Our success rate in the beginning
on getting all the data
was maybe 50% or 20%.
At the end, it was more like
around 100%.
So it was very difficult getting
everything
to work together.
Here's our flow-through cell.
Water would be pulled out of the
stream,
flow into the cell here, outlet a
t the top,
go through a tubing in this o
ne out the top,
tubing out in the top.
Why did we put it into three p
ieces?
Well, it's because the nitrate
fights with the chloride,
fights with the electrical condu
ctivity.
All three of these probes put out
a voltage
and so one, so they all think so
mething else is going on,
but it's just the other probe in
terfering with it.
So we split 'em into three
and then we put a little copper t
ube that we grounded
in between each one.
And that pretty much eliminated t
he interference
between the three transducers.
And so there's our flow-through
cell
where the water's gonna move thr
ough,
where this fills up with wat
er completely.
That's gonna make our measuremen
ts.
And then here's our Arduino syst
em.
There's the Mega, there's the GP
S, and here's the,
kind of all the signal condition
ers
for all the different things.
This looks like a mess, but I
was really pretty pleased with
what a nice job Susie did with k
eeping it clean.
But it still looks all right.
We also discovered in one of our
trial and errors
that the antenna does not work we
ll
when placed beneath the canoe se
at
with someone on top of it.
[audience laughing]
So we had to get an antenna, we g
ot an external antenna
and that improved the accuracy e
ven more.
It worked quite well after we did
that.
All right, the geophysical method
s
we put in the ground conductivi
ty meter,
again we used Arduino.
This is an older unit, older
instrument.
They've been around since the 80
s.
This one has also been around
since the 80s.
But gee, it has a pin out here s
o you can record,
it gives you the signal.
Susie came up with a little, anot
her Arduino system
that measured location and re
corded the data
out of the EM31, and we'll talk a
bout that data
in a little bit.
Don't get too concerned about th
at.
But again, it all just dumps
it on an SD card,
records time, data, and locati
on.
And that's run off a little 9
-volt battery,
that'll run it all day.
The other water quality system t
hat I just showed,
that runs off a little six double
-A and nine volts.
That'll run it all day as well to
o.
And then here's our GoPro camera
, kind of standard.
These things I think are kind of
engineering marvels.
It's so tiny, can record a couple
hours' worth of video
on a card, super-high resolution
, 1440.
At 30 frames.
And so here's an example of wh
at we get with that video,
with the GoPro.
If you look there, that is a
dogfish or bowfin
and that's from the Mukwonago,
kind of on the upper part of Mukw
onago.
I was like, "What is that big f
ish doing
"in this little tiny stream?"
But it's apparently quite common
there.
Then the next one, let's see if I
can get this to go.
[splashing]
[all laughing]
So you saw the canoe shake,
that wasn't from the mighty migh
ty beaver's splash.
That was from me reacting.
I had no idea that thing was comi
ng upstream.
But again, I could tell you exact
ly
where that beaver did that, if y
ou really wanted
and needed to know.
So anyway, that's how the vi
deo kind of works and looks.
We just used an off-the-shelf de
pth finder
with chirp sonar technology.
This is probably the most sophis
ticated thing on the boat,
and it probably costs just about
the least,
because there's a big market for
these things.
I was a little disappointed.
I was hoping to get something th
at only went to like
a few inches of depth, but appare
ntly fishermen
don't need that information.
[audience chuckling]
So kind of stuck with,
it kind of stops working at one f
oot depth,
but it would have been nice to h
ave the whole thing.
And so that data is also geolocat
ed and stored.
That's just part of the softwa
re package
that you can get with them.
Here's the track, that's where th
e location,
here's the data that was coming o
ut of it.
That red represents the stream b
ottom.
So you can see the variation ther
e.
All right, just to sort of summ
arize
how the canoe's set up.
Here's Catherine and Susie again.
We have a camera in front, we've
got one in back.
This time below water, we lea
rned something.
We've got fish finder here connec
ted back behind.
We've got a water inlet taped
with Gorilla Tape,
that stuff works great.
It's temporary, it's perfect for
what we want to do.
Taped underneath on the bott
om of the canoe,
we've got a pump here that moves
the water.
It goes to our flow-through cell
tucked under the front seat.
You can see it sitting right ther
e.
Comes out of that flow-through
cell and gets ejected here.
And then we've got our EM31 strap
ped in the canoe.
And seven batteries that can't
fail for two to three hours,
which is a harder test than it m
ight sound right there.
Again, we got good at managing
our batteries toward the end.
So how do we know how well our
data quality, our assurance?
We did three things, we cali
brated our sensors,
we had a standard protocol before
every survey,
depended on the sensors,
we compared to grab samples that
we just collected
while we were going down the str
eam
where we just collected the
bottle and a sample
and sent it to a lab for analysis
.
And then were the data reprodu
cible?
We'd go upstream, then downstrea
m.
Or you circle the lake clockwise
,
and then you turn around
and go counterclockwise.
A lot of times we found like,
temperature varies
when you do this, but the other
parameters don't.
The sun warms things as you
go through the day.
And the temperature is also o
ne of the things
we didn't worry about quite as m
uch.
So here's kind of our, here's our
measurements,
and here's our calibration pr
ocedure.
We just used standards and ki
nd of did
what the manufacturer recommende
d,
and what we kind of thought we n
eeded to do.
But we did this before every tri
p.
Here's laboratory values versus s
urvey float values.
Here's the conductivity micron
lab sample, is shown in red.
And the stream float samples are
shown in blue.
And the time that those thin
gs were collected
is shown along the bottom.
You can see there's a spread in
the stream flow
and in the float data.
That's because there's a little b
it of a lag time
getting through those flow-throu
gh cells as we go.
And so there is some smear in our
data.
When I started I was like, "We ca
n measure this
"every tenth of a meter."
I think we're actually,
because we have the smear, we
're more like
measuring things every five,
several meters,
maybe even 10 meters depending
on how fast we're going.
The slower we go, the better our
accuracy.
So I'm still pretty happy with 1
0 meters,
that's pretty good location
and can really help us inform th
ings.
One of the things we found is the
chloride probe
didn't work very well.
It was fussy, and that kind of s
hows up with the data.
We're getting okay matches but no
t...
This is about as good as the ch
loride probe got.
It's an ion-specific probe, and t
hey're just not
quite so easy to use and get grea
t data out of.
And then reproducibility.
So we circled the lake, so w
e started here,
this is Plainfield Lake about
a year ago.
So we started here, we went c
ounterclockwise,
got to here, and then went back.
When I say we, I mean Susie and
Catherine,
I stood on the shore, answered
email or did something,
I don't know.
And so you can see that we're lo
oking at dissolved oxygen,
where green is lower saturated
percentage and red is higher.
And you can see those two things
are pretty reproducible.
There's a pretty low dissolved ox
ygen
over on this west side.
The biologist at this site suspec
ts
there's a lot of decaying plant
matter here.
This lake was nearly dry five y
ears ago.
There's a lot of vegetation there
.
That's now very much under water
.
So it's probably, the DO,
there's a lot of biological ox
ygen demand going on here.
So we felt good about that measu
rement.
Here's the Grant River track th
at Bea was talking about.
And apparently Bea's been down t
his several times.
So here's the Grant River.
We're gonna look at specific
conductances.
The red points are where we colle
cted samples.
And you can see the track here,
and then the specific conduc
tance is related
to the amount of total dissolved
solids or salts,
and it's kind of a proxy for wate
r quality.
If you've got really low specific
conductance,
often that water's of higher qu
ality
than very high specific condu
ctances.
And this we think illustrates th
e value
of collecting the continuous dat
a.
So keep those points in mind.
Here's what we got from the lab s
amples.
Here's our scale, everything
's kind of bracketed
between 5 and 600 microsiemens p
er centimeter.
You don't have to worry abou
t the units there,
but that's a pretty narrow range
.
That's about our drinking water i
n Madison
a lot of the time.
Maybe it gets down to 400 depend
ing on your well.
But then if we look at its extent
,
up here where it's blue, it's l
ower.
Blue is lower values and yellow i
s higher values.
So you can see there's a peak her
e and a peak here,
and this is really kind of the lo
west.
So this took like an hour to col
lect,
and we can already see something'
s going on here,
and something's going on here and
even down here.
We didn't really test this m
uch but this is,
there's a big spring, beautiful
little spring house park
called Klondike Park down in Gran
t County.
I highly recommend checking it ou
t.
But you can see if we look at th
at data plotted
with time again, so here's the co
nductivity versus time
rather than distance,
you can see there's a lot more
going on in that data
in those streams than was just
recorded in the five samples.
I wouldn't do one without the ot
her always,
but they're really complementing
each other right there.
The fact that most of these are
lining up pretty well,
this one, don't know what happe
ned here,
but that gives me more assurance
in the data quality as well too.
And so where do we see those peak
s?
We see the peaks where Rogers
Branch comes in.
Let me go to the next slide.
There's a small, unnamed trib
utary here
and Rogers Branch comes in here.
And so those two have a litt
le bit lower water quality
as they join in, and so that
's these two peaks.
And if we zoom in, here's Borah C
reek
with the lower specific condu
ctivity.
Rogers Branch has a higher specif
ic conductivity.
I can tell you which tributary to
the Grant River
I'm gonna go trout fishing in.
I also know that there were
trout fishermen on Borah Creek
whenever I was there.
There were quite often trout
fishermen.
So this is a little bit high
er quality water
and we can see that, and we can s
ee that comes in
and then as it goes down,
there's some mix, we finally
get some mixing
and get to an intermediate value
.
So that's the other thing.
We can get a sense of how long
it takes for things to mix
in the system too.
If we look at the other.
So let's move on and look at the
Mukwonago Watershed,
is kind of another one of our exa
mples
down in southwestern Wisconsin he
re,
or southeastern excuse me.
And this is really kind of a pre
tty, kind of a gem
of a small little stream.
Here's an example on some nature
conservancy land.
Here's a couple of images that
we collected with the GoPro
going here as well too.
So if we look at temperature.
This up here's a beautiful little
spring pool
or actually a very large spring p
ool.
We went down, this is actual
ly Crooked Creek.
I think this is unnamed and wh
en we get to here this is,
we call the Mukwonago.
And so we start up here in the
spring pool, go downstream,
and then out across Lulu Lake
and out at a landing there.
And so let's see if this will sta
rt.
And so you can see in that spring
pool,
there's a lot of groundwater
discharge,
just beautiful crystal clear wate
r.
The other thing to note is t
his water's cold,
as you might expect groundwater
to be
when we did this in June, late Ju
ne.
It's a warm time of year.
Groundwater is cold and it warms
up as we go downstream,
and we have a record of how t
hings warmed up
as we went downstream here.
Went from 11 degrees C up to over
20 in the lake as we go.
So you can see cold and we can se
e how it's warming up.
All right, now if we look at the
next.
Next one is dissolved oxygen.
The groundwater generally is dep
leted in oxygen,
the oxygen reacts with the min
erals,
and so if it's been in the ground
for a long time,
usually dissolved oxygen is pret
ty low.
This is kind of intermediate, so
it's blue,
it's this kind of light blue, an
d then it goes up.
Green is higher dissolved oxygen
.
Because cold water can take more,
can hold a higher percentage of
oxygen.
So this water is still cold, it h
asn't warmed up yet.
So colder water has a higher per
centage of oxygen
and now it's warming up and we s
ee the oxygen drop.
And there's probably also a biol
ogical component
to this signal as well too,
that I would like to eventually t
ease out,
and then the lake's get a little
bit higher as we go.
The specific conductance is hig
h in the spring pool.
There's a lot of dissolved calciu
m carbonate,
the water's a calcium bicarbonat
e water.
And so when that comes to the sur
face,
the CO2 is out of equilibriu
m, it shifts
and you get mineral deposited.
And so you have a high specif
ic conductance
because you've got a lot of ca
lcium carbonate dissolved.
As you come into equilibrium with
the atmosphere,
that calcium carbonate's gonna co
me out of solution.
So the specific conductance is g
oing to go
from a high value with lots of io
ns to a low value
with fewer ions, and that's what
we see here.
I'm very curious about what's
going on.
There's a railroad trestle here
kind of separating these two,
and there seems to be a jump.
I'm very curious about what's
going on there.
There's another interesting sign
al that we see with the pH.
Again the pH when it comes out, i
t's slightly acidic,
becomes more basic.
Blue is more acidic, green is mor
e basic.
So it's slightly more acidic.
That's the excess carbonic acid,
the carbon dioxide in the water.
That comes out of solution, thin
gs become more basic.
And then we get this funky signal
again down here,
and I suspect that isn't
have anything to do with geochem
istry.
It's probably biochemistry.
There's probably some sort of bio
logical activity
making that more acidic.
We would have no idea about any
of these questions
except for we've got too much
data perhaps.
Model limitations.
So this is not a total panacea,
there are limitations here.
Site accessibility and conditions
.
This is not an awesome place
to take a canoe
with lots of expensive equipment.
Here was Catherine's solution for
this location.
She's got the battery and the pu
mp in a backpack,
and she's got her flow-throu
gh cell here
doing the measurements.
This worked okay but again,
you're not going a meter per seco
nd like you are in a canoe.
It's hard to cover a large amount
of territory.
Tag alder is not your friend
when you're trying to do this.
You may have a lot of stream that
you want to get through,
but you need to get out the lopp
ers
if you really want to get through
that.
And then I've got, over the coup
le of years of this project,
we've taken a lot of ribbing ab
out the flotation devices
that are filled with certain beve
rages
behind the canoe, which we never
did.
But I just want to show those pe
ople this picture.
It's not all fun and games all
the time.
You can, mosquitoes.
On this day it rained all day,
and we were in northern Wisconsin
and mosquitoes were in full hatch
.
And so you can't get comfortable.
Again, I showed up after the end
of this day
and met these guys for lunch
and they were,
and one of my colleagues, Pe
te Chase,
who's an extremely experienced fi
eld person,
actually said "Dave, that was ac
tually a really hard day,"
and he doesn't ever say things l
ike that.
So you can see Catherine's lo
oking a little ragged there.
So that's the water quality,
kind of the summary of what
we saw with the water quality.
If we look at stream bed electric
al conductivity,
again, electrical conductivity i
s how well
does the material conduct electr
ical current?
And we're gonna use this to maybe
let us know
what's underneath the streambed.
A higher electrical conductivity
indicates more clay,
silt, and organic material,
and that corresponds to a low hy
draulic conductivity.
The water can't move easily thro
ugh these materials
so it's kind of inverse.
High electrical conductivity, lo
w hydraulic conductivity.
Low electrical conductivity, sand
and gravel
gives us a higher hydraulic
conductivity.
So the idea is then with this to
ol,
we can map the entire stream and
get indications
of where there's good connection
to groundwater,
'cause we have the streambeds at
high
hydraulic conductivity, low elec
trical conductivity
and vice versa.
All right, here's kind of it
laid out again.
We're getting ready to go.
This is in Borah Creek, upstr
eam there,
and here's again the unit.
How does this thing work?
Well, it seems a little magical.
You don't need to put anything i
nto the ground.
It works because you have a coil
on your transmitting end.
That coil has an alternating curr
ent through it,
that current produces a magnetic
field,
that alternating magnetic field
produces current
in the ground.
That current in the ground
produces a magnetic field
that the receiver sees.
So this is, and what you do i
s you have to,
the electronics mostly are trying
to separate out
the magnetic field from the trans
mitter
from the magnetic field in the g
round.
They're shifted in phase so that
helps.
But if you get more induced curr
ent in the ground,
that means you have a better con
nector.
So this is kind of a wonderful
tool,
it's very mature technology.
It's been around for a long time,
and you can just kind of float ov
er the water with it
and it will record the stream
bed conductance.
There are issues though because
we've got this, before,
we've got this water in the way,
and it's going to contribute to t
he overall electrical,
to that signal that we see.
But we're lucky because we'v
e measured
the water conductivity with t
he water quality
with the Arduino thing and re
corded it,
and we've got a depth finder that
recorded the depth.
And so with these two things,
we can remove the waters, the
stream's contribution,
the stream water's contribution t
o the EM reading.
What we have left over
is the streambed electrical condu
ctivity.
And here's that for the Grant Ri
ver.
We collected sediment samples at
all these locations
and I'll show you, we'll look at
11, 12, 14, and 15.
Low electrical conductivity is b
lue, that would be,
we would hope that's more s
and and gravels.
High electrical conductivity
is yellow.
Those are the silts and organics
.
And so yellow, that's not any pla
ce
I'd want to step out of the canoe
.
Yellow, that's maybe not quite as
bad,
but still a little mucky.
And then we've got gravels, whic
h I'm gonna want
to make sure I want to have sanda
ls at 11 and 15.
So we do see a pretty decent cor
relation.
These are probably the best examp
les,
often it's a little more sub
tle than that.
But in general, we can correlate
electrical conductivity
to sediment and we know that
's gonna correlate
to how well the stream is connec
ted to the surface.
All right, and then the last pie
ce,
and this is maybe the piece th
at we,
that's maybe unique to what we'v
e done,
is putting it all together.
And we did that using a software
called Dashware,
Why would anybody use software c
alled Dashware
for a ecological study?
Well, it's made to take your race
car,
put your GoPro camera on your da
shboard,
and record the g-forces,
record your velocity, record
your lap speeds,
all these things, and then play
it
for your buddies in a video.
I thought well, instead of g-forc
es and velocities,
we'll do dissolved oxygen and el
ectrical conductivity
and we won't worry about g-forces
.
So we can put this in, it's a bit
of a stretch,
you kind of have to fool the prog
ram a little bit.
There's another one called Race
Render
that we'll also use too.
And so here's the Grant River su
rvey on the YouTube,
and I'll just show a little bit o
f that movie.
Yeah, and so here we, this is th
e same data that you see.
- Woman: All right.
- Dave: So here's us getting read
y to go,
and we're going downstream.
So let's go down and look, so you
can see
here we are up in Borah Creek.
This is just the time, you ca
n see this video
is about an hour and a half long.
As we go here, this is water tem
perature,
WT is water temperature.
This is electrical conductivity,
that's the fluid electrical,
water electrical conductivity,
and then here is dissolved oxygen
as we go here as well too.
So you can see how these things a
re varying
as we go down the stream.
So I can, and one of the other t
hings
is I can move this ahead,
and you can see right at this fe
nce,
we kind of go from high dissolved
oxygen
to low dissolved oxygen.
I don't know what is going on
and why we saw such a dramat
ic change there,
but that's what we saw.
So the dissolved oxygen goes low.
Then we're gonna see a bunch
of spikes here,
and I think those spikes have to
do with the riffles.
So if we go along, maybe the diss
olved oxygen goes up,
the electrical conductivity is s
till pretty low,
but it's higher.
We were up in Borah Creek and no
w we're downstream
a little bit more,
it looks like our water quality'
s
decreased a little bit.
Now let's go down a little bit f
arther.
And you can see that big jump in
water temperature here
as we're going, we're kind of go
ing.
Things seem kind of stable.
I think this riffle is gonna give
us a little pop
in our dissolved oxygen.
I don't think we've got an hour a
nd a half here but...
[audience chuckling]
And so you can see, that's going
up,
and then we're gonna cruise alon
g a little bit more.
We're gonna go around a corner,
and I'm gonna get us kind of
right to where,
so you can see the temperature'
s gonna jump up
and the electrical conductivity
is also gonna jump up.
And we're gonna have low DO.
And what are we doing?
Right there, we're in the conflu
ence of Borah Creek
and Rogers Branch.
There's Rogers Branch there.
As we go right there, we're gonn
a go up Rogers Branch
and you can see the water temper
ature
is significantly higher in R
ogers Branch.
And then we'll back out of Rog
ers Branch
and then we end up going downst
ream.
And you can see the temperature'
s kind of a mix
of Borah Creek and Rogers Branch.
It's kind of in between.
Kind of similar with the electri
cal,
here's Borah Creek, Rogers Branc
h
and we're kind of in between.
So we can kind of see the mix,
we can kind of see how these tw
o things are interacting.
And then our DO went back up righ
t there too.
It went back up a little bit mor
e.
If we keep going down,
we can see another little spike
in that electrical conductivity.
Remember I mentioned a small unna
med tributary.
So let's see if we can get to it
.
You can see it's gonna show u
p right here.
This little tiny tributary is gon
na be responsible
for this bump in electrical condu
ctivity,
and we stayed here and just coll
ected data for a while,
so we could get a sense of it.
So that's really kind of the high
lights of this video,
and kind of the power.
We did a similar thing for Pl
ainfield Lake,
a similar thing for the Mukw
onago as well too.
Kind of giving us some insight
into how things vary spatially,
which was kind of the whole pl
an and idea for the study.
Okay, let's go back and see
where we're at with the presentat
ion.
If you want to spend more time,
you can google Grant River Float
and I think this will show up on
YouTube.
You probably can't click that lin
k,
but if you google Grant River
Float,
you'll probably find it in YouTu
be.
All right, so we developed a me
thod that's low cost,
easy, pretty easy to process comp
ared to other methods.
It provides guidance.
We know some places that we'd l
ike to instrument
on the Grant River now.
We have some idea after doin
g those surveys.
Maybe these repeated floats can h
elp us
understand variations in quality
under different conditions,
and I think the movies help m
e understand
what I'm looking at a lot of the
time.
They also help me remember what w
e were doing too,
it provides a good record of the
survey.
I'd like to last acknowledge the
funding source,
the Wisconsin Department of Natur
al Resource
funded this project through
the Groundwater Coordinating
Council's
Joint Solicitation Program.
So that's what I've got, thank y
ou.
[audience applauding]