Fluorescent particle tracers in surface hydrology

Transcription

Hydrol. Earth Syst. Sci., 16, 2973–2983, 2012
www.hydrol-earth-syst-sci.net/16/2973/2012/
doi:10.5194/hess-16-2973-2012
© Author(s) 2012. CC Attribution 3.0 License.
Hydrology and
Earth System
Sciences
Fluorescent particle tracers in surface hydrology:
a proof of concept in a semi-natural hillslope
F. Tauro1,2,3 , S. Grimaldi1,3,4 , A. Petroselli5 , M. C. Rulli6 , and M. Porfiri1
1 Department
of Mechanical and Aerospace Engineering, Polytechnic Institute of New York University, Brooklyn,
NY 11201, USA
2 Dipartimento di Ingegneria Civile, Edile e Ambientale, Sapienza University of Rome, Rome 00184, Italy
3 Honors Center of Italian Universities, Sapienza University of Rome, Rome 00184, Italy
4 Dipartimento per l’Innovazione nei Sistemi Biologici, Agroalimentari e Forestali, University of Tuscia, Viterbo 01100, Italy
5 Dipartimento di Scienze e Tecnologie per l’Agricoltura, le Foreste, la Natura e l’Energia, University of Tuscia,
Viterbo 01100, Italy
6 Dipartimento di Ingegneria Idraulica, Ambientale, Infrastrutture Viarie, Rilevamento, Politecnico di Milano,
Milano 20133, Italy
Correspondence to: S. Grimaldi (salvatore.grimaldi@unitus.it)
Received: 17 March 2012 – Published in Hydrol. Earth Syst. Sci. Discuss.: 3 April 2012
Revised: 2 August 2012 – Accepted: 3 August 2012 – Published: 24 August 2012
Abstract. In this paper, a proof of concept experiment is conducted to assess the feasibility of tracing overland flow on
an experimental hillslope plot via a novel fluorescent particle tracer. Experiments are performed by using beads of
diameters ranging from 75 to 1180 µm. Particles are sensed
through an experimental apparatus comprising a light source
and a video acquisition unit. Runoff on the experimental
plot is artificially simulated by using a custom-built rainfall system. Particle transits are detected through supervised
methodologies requiring the presence of operators and unsupervised procedures based on image analysis techniques. Average flow velocity estimations are executed based on travel
time measurements of the particles as they are dragged by
the overland flow on the hillslope. Velocities are compared
to flow measurements obtained using rhodamine dye. Experimental findings demonstrate the potential of the methodology for understanding overland flow dynamics in complex
natural settings. In addition, insights on the optimization of
particle size are presented based on the visibility of the beads
and their accuracy in flow tracing.
1
Introduction
Hillslope overland flow controls multiple phenomena in
natural watersheds, including surface runoff contributing
to the basin hydrologic response (Scherrer et al., 2007;
Gomi et al., 2008a; McGuire and McDonnell, 2010; Uchida
and Asano, 2010), rill development and erosion mechanics influencing soil roughness (Berger et al., 2010; Ghahramani et al., 2011; Mügler et al., 2011), and pollutant
diffusion and nutrient loss affecting agriculture and soil
management (Ticehurst et al., 2007).
Major challenges in the implementation of flow measurement systems in hillslopes are due to the ephemeral nature
of microchannels along with shallow water depths and high
turbidity, the presence of small scale vegetation, and often
poor geographical accessibility (Hudson, 2004; Rosso et al.,
2007). Overland flow is experimentally monitored by excavating small trenches in hills (Dunjó et al., 2004; Hopp and
McDonnell, 2009; Sadeghi et al., 2012; Jost et al., 2012) and
collecting samples of water for laboratory or sediment analysis (Budai and Clement, 2011; Vacca et al., 2000; Rulli et al.,
2006; Hussein et al., 2007). On the other hand, runoff discharge and flow rate measurements require more invasive
procedures, wherein v-notch weirs and gauging flumes are
installed in excavated trenches at the borders of experimental
Published by Copernicus Publications on behalf of the European Geosciences Union.
2974
F. Tauro et al.: Fluorescent particle tracers in surface hydrology
plots (Domingo et al., 2001; Gomi et al., 2008a,b; Doody
et al., 2010; Mayor et al., 2011). Real time flow rate and water stage estimates can be computed by deploying sensors
in such flumes, whereas overland flow rate can be automatically recorded by using tipping buckets (Johnson et al., 1996;
Fiener and Auerswald, 2005; Léonard et al., 2006; Laloy
and Bielders, 2008; Ghahramani et al., 2011). Erosion and
runoff experimental studies are also conducted through physical sampling of overland flow water in tapped containers after precipitation events (Mathys et al., 2005; Armand et al.,
2009; Patin et al., 2012). Such procedures are highly invasive for the environment and are hardly implemented on large
scale plots. In addition, they are not adequate for real-time
estimations in micro-channel flows (Tatard et al., 2008).
In overland flow settings, tracing techniques are valid alternatives to stream flow measurement systems, such as water gauging, electromagnetic, and acoustic sensors (Lee et al.,
2002; Puleo et al., 2012). In particular, experiments on natural or semi-natural hillslopes are often based on tracers, including chemicals, naturally occurring water isotopes, dyes,
and salts (Dunkerley, 2001; Lange et al., 2003; Planchon
et al., 2005; McGuire et al., 2007; Berman et al., 2009;
McMillan et al., 2012). Tracer dispersion issues and losses
are minimized by conducting experiments on small scale
plots (Tatard et al., 2008; Li, 2009; Mügler et al., 2011).
Nonetheless, the tracer detection requires the deployment of
probes or the collection of water samples, which can be hampered by the exiguous depths of natural rills (Tatard et al.,
2008; Gomi et al., 2008b).
Interestingly, novel sensing instruments are recently being proposed for overland flow rate estimates. Specifically,
in Dunkerley (2003) spot measurements of surface flow rates
are computed through an optical device exploiting reflectivity of floating objects. In Qu et al. (2007), a sensor for
sediment-laden flow rate is developed to estimate sediment
concentration in runoff. Such promising devices provide local information on overland flows, yet their implementation
is restricted to small scale and supervised experimental plots
due to their limited resilience. In Legout et al. (2012), large
scale particle image velocimetry (LSPIV) is coupled with
laser scanning to estimate overland flow velocity and experimental results are compared against both hot film anemometry and salt tracing. This comparison suggests that LSPIV
is a less invasive approach, which can also be easily automated (Muste et al., 2008). Nonetheless, techniques based
on image analysis are affected by ambient illumination, presence of patterns on the water surface (Muste et al., 2011;
Jodeau et al., 2008), and image distortions (LeCoz et al.,
2010), which pose severe challenges in their implementation
in uplands environments.
In this paper, a novel tracing methodology based on the
deployment and observation of enhanced fluorescence particles for surface flow measurements is proposed. Such an approach aims at mitigating practical limitations of traditional
techniques for monitoring overland flows. Specifically, the
insolubility of the particles minimizes tracer adhesion to natural substrates and, therefore, is expected to reduce the requisite quantity of tracing material as compared to liquid dyes.
Further, the enhanced visibility of the fluorescent particles
allows for non-intrusively detecting the tracer through imaging techniques without deploying bulky probes and samplers
in the water. These features along with the use of basic and
resilient equipment provide grounding for applying the proposed methodology in an ample spectrum of scenarios, such
as ephemeral micro-channels, high-sediment load flows, and
heavy floods.
The feasibility of using buoyant fluorescent particles in
static and dynamic water conditions in both daylight and
dark is demonstrated in Tauro et al. (2010, 2012b) for laboratory settings. The transition of the methodology to natural environments is addressed through a proof of concept
experiment performed in the Rio Cordon stream in the Italian Alps (Tauro et al., 2012a). This study mainly assesses the
performance of the particles in stream flow settings, where
high velocity regimes, presence of foam, and light reflections pose serious challenges to bead detection. Particles are
therein used to conduct flow measurements at a stream crosssection and travel time experiments in stream reaches of up
to 30 m. Bead diameters of a few millimeters are selected to
compensate for high flow rates.
In this paper, the proposed methodology is used for a
proof of concept overland flow study on a semi-natural
hillslope plot under high turbidity loads and soil and rain
drops interaction. Such complex settings require the use of
much smaller beads as compared to the stream flow analysis. Therefore, ad-hoc experiments are performed to assess
the visibility and detectability of the particle tracers in these
severe environmental conditions and their feasibility in estimating overland flow velocities. Experiments are conducted
by using particles of varying diameters ranging from 75 to
1180 µm. The particle detection system, placed across a natural rill at the outlet of the studied experimental plot, hosts a
light source for exciting the beads’ fluorescence and a waterproof digital camera for video acquisition. Videos of beads’
transit are processed through both supervised and unsupervised techniques to estimate average surface velocities of water flowing in the rill.
The rest of the paper is organized as follows. In Sect. 2,
the following elements are technically elucidated: the particle tracer and the in house-built experimental detection system; the experimental site including the plot preparation; the
image-based analysis procedures used for data processing;
and the rainfall simulator. Moreover, in Sect. 2, a detailed
description of the experimental procedures is presented. In
Sects. 3 and 4, results and comments on experimental findings are reported. Conclusions and remarks are presented in
Sect. 5.
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Italy,
aa background
∑ andαparticle images, respectively. The
∑
3
(cii)pixel
)α nnii intensity classes from 0 to 255
3
semi-natural
hillslope
is
prepared
out
of
40m
of
soil,
see
term
the
a 4msemi-natural
long centralhillslope
rill is formed
in the plot
the ex-of soil,
(c
is prepared
outand
of 40m
seeci represents
i∈I
Hydrol.
Earth
Syst. Sci., 16, 2973–2983, 2012
i∈I
Figure
The
m long,
long,
and 3m
3mwhere
wide the power
∑
is introduced
to{i
a higher statisntal detection
located
at its6.5
terminal
part,
{0,1,...,255}
>0},
0},
G=
= α∑
I=
=
{iassign
Figure 3.
3. apparatus
The plot
plot is
is 1.7m
1.7m high,
high,
6.5
m
and
wide
::nnii>
G
,, I
∈∈{0,1,...,255}
n
i
n
i
and
itit is
covered
by
grass
only
10%.
Thetogranulomegranulometical weight to the i∈I
exiguous
number of bright pixels in the
gure 3.
The
of the
is approximately
equal
and
isslope
covered
byhill
grass
only for
for the
the 10%.
The
i∈I
try
of
the
soil
is
provided
in
Table
2.
In
the
center
of
the
plot
try of the soil is provided in Table 2. In the center of the plot
2976
Table 1. Classes of particle diameters used for the experiments.
Class
1
2
Diameter (µm)
75–90
106–125
3
4
5
6
7
8
9
150–180
250–300
355–425
500–600
710–850
850–1000
1000–1180
F. Tauro et al.: Fluorescent particle tracers in surface hydrol
Table 2. Granulometry of the experimental plot. The soil used for
the plot can beIn
classified
as sand according
o the particles.
particular,
the to the International Society of Soil Science (ISSS).
ughout the whole set of experiSoil type
Clay
Silt
Sand
pixels against the
background.
Portion (%) 11.55 21.76 66.69
he exponent is motivated
by the
HH22-M 3/8 nozzle
ation and environmental condiParticle detection procedure
ming a 2.3
preliminary
analysis on
HH7-M 3/4in nozzle
Travel time experiments are conducted by synchronizing parue of theticleexponent
is varied unManometer
deployment and video acquisition. Particle travel time
identified as
the time the beads
dex are isclearly
identified.
It take
is to flow from the deployment section on the plot to the detection apparatus along
es are obtained
from
the oforigithe 4 m long rill.
The arrival
the particles at the detection
setup
refers
to
when
the
particles
enter the field of view of
m-hat transformation, (Haralick
Fig. 4. View of the rainfall simulator. Water jets are sprayed from
the camera. The transit of the particles is identified through
3/8 in and one HH7-M 3/4 in nozzles.
4. Viewtwo
ofHH22-M
the rainfall
simulator. Water jets are sprayed f
Fig. videos
, 2004).image-based
Peaks analysis
in thetools
index
G captured
by converting
into RGB frames and then analyzing the soletwo
greenHH22-M
chan3/8in and one HH7-M 3/4in nozzles.
rames where
brightness is maxnel where particle emissions are more evident. In particular,
presence of external and uncontrolled light sources, water
gray-scaleare
frames
are processed
the particles
more
likelyby using
to a modified version surface reflections, and extraneous objects and sediments.
of the following index G defined by Tauro et al. (2010):
P
(ci )α ni
i∈I
G= P
, I = {i ∈ {0, 1, ..., 255} : ni > 0},
(1)
ni
Specifically, a moving average of the time trace of the index
is computed for each experimental video by using subsets of
ten consecutive images. For convenience, such filtered time
trace is referred to as G. Then, peaks in the signal are automatically detected by fitting G with a gaussian function.
This fit is first implemented using windows of 50 values of
the filtered time history. In the fitting procedure, the length
of the fitted window is iteratively increased up to 150 values
to capture eventual occurrences of elongated particle trains.
Fitting is executed by constantly skipping 15 values of the filtered time trace. The nonlinear least square method is used to
perform the fitting. Goodness of the procedure is ascertained
by imposing that the coefficient of determination is equal or
greater than a threshold value equal to 0.85.
The sequence of frames identifying the transit of the particles are found by imposing further constraints on the fitted
window which presents the highest coefficient of determination. In particular, the mean value of the fitting gaussian function is required to lay in the interval [m − 0.15l, m + 0.15l],
where m is the mean time in the window of interest and l
corresponds to the length of the window. In addition, constraints are imposed on the minimum and maximum values of G in the analyzed window. Specifically, the presence
of a peak in the intensity is assessed by imposing 0.4 ≤
(max G − min G)/ max G ≤ 1 in the2fitted interval. Experimental videos satisfying such constraints lead to the identi−1
fication of particle transits. As the brightest frame sequences
litecnico di Milano based on the prototype by (Riley
or the identification of the beads
Hancock, 1997). The basic structure of the simulator c
er signal noise
due to the presi∈I
prises a telescopic aluminum tripod connected to a s
olled light
sources,
water surface
p
p
with ni = ni − nbi . Here, nbi and ni refer to the pixel count
plate. TheThree hoses are riveted to the plate and wate
the sediments.
background and particle
images, respectively.
objects for
and
Specifterm ci represents the pixel intensity classes from
0 to 255 through a system of three nozzles as displaye
sprayed
the time
trace
ofα the
indexto assign
is a higher
where
the power
is introduced
statistical
4. Specifically, an HH7-M 3/4in nozzle is moun
weight by
to theusing
exiguoussubsets
number of bright
pixelsFigure
in the entire
ental video
of
image corresponding to the particles. In particular, the expoon the central hose whereas two smaller HH22-M 3/8in n
convenience,
filteredthetime
nent α is setsuch
to 10 throughout
whole set of experiments to
emphasize brighter pixels against the background.
rel- placed onto the lateral hoses. Three cut-off va
zlesTheare
hen, peaks
in the signal are auatively high value of the exponent is motivated by the parallow
for selectively activating the nozzles and control
ticularly
illumination
and environmental
conditions.
ng G with
a adverse
gaussian
function.
It is found by performing a preliminary analysis
on
a
single
intensity. Water is supplied to the hoses throug
using windows
ofvalue
50 ofvalues
of is variedrainfall
video where the
the exponent
until evenreinforced tube connected to the steel plate thro
tual procedure,
peaks in the indexthe
are clearly
identified. Itplastic
is noted that
the fitting
length
background images are obtained from the original ones by
coupling. Rainfall intensity is regulated by usin
al., 1987;
applying a bottom-hat
transformation,
ively increased
up to 150
values(Haralickaetsleeve
Gonzalez et al., 2004). Peaks in the index G correspond
to se- gauge. Water is jetted from an height of appr
pressure
ces of elongated
particle
trains.
quences of frames
where brightness
is maximized and there2.7m from the ground and can homogeneously co
fore where
particles of
are the
more fillikely to be mately
(Tauro et al.,
ntly skipping
15thevalues
2010).
an
area of approximately 5 × 5m . Rainfall intensities
ar least square
method
is for
used
to
An automatic
procedure
the identification
of the beads
introduced to partially filter signal noisebe
duevaried
to the from a minimum of 40mmh
by using the
s of the isprocedure
is ascertained
smaller nozzles to 140mmh−1 by operating the three n
ent of determination
is
equal
or
zles simultaneously.
e equal to 0.85.
dentifying the transit of the par-
o et al.:F. Fluorescent
particle tracers in surface hydrology
Tauro et al.: Fluorescent particle tracers in surface hydrology
6
a)
b)
c)
d)
e)
f)
g)
h)
i)
j)
k)
l)
m)
n)
o)
Fig. 5. Beads of smaller diameters trapped at the outside bend of the
rill, see red dashed ellipse.
Beads of smaller diameters trapped at the outside
bend ofq)
p)
see red are
dashed
ellipse.
determined,
the frame order number corresponding to the
first value of G in the fitted window is divided by the camera
acquisition frequency and used to calculate the beads travel
time.
2977
Fig. 7. Beads of larger d
r)
presence
of sediments an
1 cm
Fig. 6. Sequence of snapshots depicting the transit of a cloud of particles flowing in the rill below the detection apparatus. The diameter of
the beads lays in the range 75 − 90µm.
Fig. 6. Sequence of snapshots depicting the transit of a cloud of particles flowing in the rill below the detection apparatus. The diameter
of the beads lays in the range 75–90 µm.
Conversely, particle
l length2.4 ofRainfall
the simulator
rill by the particle travel time.
disperse as they are de
plot rainfall
consists of a pressurized
nozzle and depth of
re and The
after
eachsystem
experiment,
the width
50 mm h−1 to produce a water head of a few centimeters in
rainfall simulator (Esteves et al., 2000; Pérez-Latorre et al.,
ofat larger
diam
the rill.
The particle detection particles
apparatus is placed
the flat
The simulator
is designed
and developed
at the Po- the
at the 2010).
strikes
sections
and
underneath
detection
base of the hillslope, that is, at the terminal section of the rill
litecnico di Milano based on the prototype by Riley and Hanand subrills
with sediment
the bullet camera and thesediments
lamp unit at approximately
(1997). The basic
of the simulator
comprises a and
us are cock
measured
tostructure
account
for erosion
20 cm from the rill bed. To prevent excessive distortion in the
telescopic aluminum tripod connected to a steel plate. Three
particles
videos, theIn
camera
70◦ from the horizontal.
The that a
rt phenomena
and
toplate
monitor
bed
evolution.
ad-is angled atisolated
hoses are riveted
to the
and water is rill
sprayed
through
a
simulator nozzles are placed at an height of approximately
system of three nozzles as displayed in Fig. 4.
due to their relatively
experiments
area HH7-M
performed
one
month
2.3 mand
from thedursoil on the top of the hillslope.
Specifically,
3/4 in nozzleover
is mounted
on the
For each experiment, a sample
of 4–5 gthe
of particles
of a of iso
central hose, whereas two smaller HH22-M 3/8 in nozzles
plays
transit
ny days
in absence
strong
wind
to limit
possible
selected
diameter class is deployed at the rill onset at apare placed
onto the lateralof
hoses.
Three cut-off
valves allow
proximately 4 m from the detection
apparatus. The
instant
for selectively activating the nozzles and controlling rainfall
diameter.
In
this case,
n the uniformity
of
the
simulated
rainfall.
To
prevent
of
deployment
and
the
beginning
of
the
video
are
synchrointensity. Water is supplied to the hoses through a plastic renized with a precision of approximately
0.1 s.entire
Such precision
and its
passage i
tube
connectedand
to the sediment
steel plate throughwash-off,
a sleeve
tive rillinforced
bed
erosion
the
plot
is
is
achieved
by
using
a
chronometer
synchronized
with the
coupling. Rainfall intensity is regulated by using a pressure
transit
oftenthe
sample is
camera. For each class of particle
diameters,
repetitions
Water is jetted from
an height
of approximately
2.7 m
d with agauge.
waterproof
cloth
during
rainy
days.
are
performed.
The
rainfall
simulator
is
active
for
the
entire
from the ground and can homogeneously cover an area of apparticles
in the
duration of the experiments. Once
videos are taken,
framescamera
proximately 5 × 5 m2 . Rainfall intensities can be varied from
−1
are
processed
to
estimate
surface
flow
velocity
by
dividing
a minimum of 40 mm h by using the two smaller nozzles to
Particles
the total length of the rill by the particle
travel time. of intermed
140 mm h−1 by operating the three nozzles simultaneously.
Before and after each experiment, the width and depth of
to 600µm,
the rill at the strikes’ sections 250
and underneath
the detection are a
sults 2.5 Experiment description
apparatus are measured to account for erosion and sediment
formerly
described
beh
Travel time experiments are conducted by activating the
transport phenomena and to monitor
rill bed evolution.
In addition, experiments are performed over one month and during
rainfall simulator at the constant intensity of approximately
sample tends to occur
upervised Analysis
asSci.,
for16, the
7102012
− 1180µ
Hydrol. Earth Syst.
2973–2983,
are not distinctly visibl
eos for each class of bead diameters are converted to
2978
5
7
a)
b)
c)
d)
e)
f)
g)
h)
i)
j)
k)
l)
m)
n)
o)
p) due to theq)
Beads of larger diameters diffuse in the channel
e of sediments
and
subrills,
seeto red
dashed
ellipses.
sunny days in
absence
of strong wind
limit possible
biases
1 cm
r)
Fig. 7. Beads of larger diameters diffuse in the channel due to the
presence of sediments and subrills, see red dashed ellipses.
in the uniformity of the simulated rainfall. To prevent destructive rill bed erosion and sediment wash-off, the plot is
covered with a waterproof cloth during rainy days.
Fig. 8. Sequence of snapshots depicting the transit of single particles flowing in the rill below the detection apparatus. Diameters of the
beads are in the range 1000 − 1180µm. Only the green channel is reported for clarity.
Fig. 8. Sequence of snapshots depicting the transit of single particles flowing in the rill below the detection apparatus. Diameters of
the beads are in the range 1000–1180 µm. Only the green channel is
reported for clarity.
Results
versely,3 particles
ranging from 710 to 1180µm tend to
3.1 are
Supervised
analysis in the rill, see Figure 7, where
e as they
deployed
recognizable against the background even though water turTen videos
for each class ofdisperse
bead diameters are
converted
to
bidity and suspended
s of larger
diameters
due
to the
presence
of sediment load are remarkable.
frames and manually analyzed to observe the transit of the
Conversely, particles ranging from 710 to 1180 µm tend to
nts andparticles.
subrills.
Thevisual
samples
travel thein the
form
This supervised
analysis demonstrates
disperse
as they of
are deployed in the rill, see Fig. 7, where
enhanced detectability of the fluorescent particles in complex
particles of larger diameters disperse due to the presence of
d particles
thatSpecifically,
are still
visible
at the
detection
section
conditions.
particles
from all classes
are genersediments
and subrills. The samples travel in the form of isoally visible in the area captured by the camera despite poor
lated particles that are still visible at the detection section due
heir relatively
8 disto their relatively
large size.
image quality. large size. In particular, Figure
Three different behaviors can be observed by visually anIn particular, Fig. 8 displays the transit of isolated partihe transit
of isolated particles of 1000 − 1180µm
in
alyzing recorded videos according to the specific dimensions
cles of 1000–1180 µm in diameter. In this case, the particle
of the particle
particles of diameters
from
train
is highly elongated and its entire passage is difficult to
er. In this
case,tracer.
theFor particle
trainranging
is highly
elongated
75 to 180 µm, deployed samples appear as a white powder as
identify. Specifically, the transit of the sample is detected as a
they flow alongis
thedifficult
rill, see Fig. 5,to
where
beads are trapped
sequence of independent
entire passage
identify.
Specifically,
the particles in the camera field of view.
at the rill outside bend into small vortical structures. Particles
Particles of intermediate sizes, that is, beads ranging from
are then released
downstream from
that are visible
250 to 600 µm, are affected by a combination of the two
of the sample
is detected
astheabend
sequence
of independent
in the detection section depending on the size of the bead
formerly described behaviors. In particular, dispersal of the
s in thecloud.
camera field of view.
sample tends to occur from the very deployment into the rill
Figure 6 displays the transit of a cloud of 75–90 µm beads
as for the 710–1180 µm. On the other hand, such particles are
as
captured
by
the
camera.
The
powder
crosses
the
region
of
not distinctlyfrom
visible when reaching the detection apparatus
cles of intermediate sizes, that is, beads ranging
interest, that extends for approximately 8 cm, in 18 frames.
due to their rather small dimensions. These factors critically
600µm,
aresnapshots
affected
bynot aorthorectified.
combination
of the
thedetection
twoof the particles by visual inspection.
Note that
in Fig. 6 are
Therein,
affect
the particle cloud compactly travels throughout the entire
Travel times computed through visual inspection are oby described
behaviors.
In particular,
dispersal
the the frame where beads first appear
length of the
region of interest making
the beads easily detained by of
identifying
tectable by the operator. In addition, fluorescence is clearly
in the camera’s region. Since the camera acquisition and
tends to occur from the very deployment into the rill
Earth Syst. Sci.,
16, 2973–2983,
2012 hand, such particles
he 710Hydrol.
− 1180µm.
On
the other
distinctly visible when reaching the detection appara-
F. Tauro
et al.:
Fluorescent
particle
tracers
in surface
hydrology
F. Tauro
et al.:
Fluorescent
particle
tracers
in surface
hydrology
21
21
21
10
GG
GG
10
GG
10
2979 9
10
20
10
0
500
1000
1500
Frame order number
2000
20
20
10
0
500
1000
1500
Frame order number
a)
b)
2000
0
500
1000
1500
Frame order number
2000
c)
9. Index
G as
obtained
fromEq.
Eq.1 (1)
(a) beads
of−
75–90
µm;b)(b)
1000–1180
µm; and
500–600
µm. Moving
averaged
index,
G, isG, is
Fig.Fig.
9. Index
G as
obtained
from
for for
a) beads
of 75
90µm;
1000
− 1180µm;
and(c)
c) 500
− 600µm.
Moving
averaged
index,
presented
in red.
presented
in red.
particle deployment
are synchronized,
theettime
the
a supercritical
flow velocity
regime (Tatard
al., taken
2008).byThis
particle to reach the detection apparatus is easily found by
condition produces the formation of small hydraulic jumps
dividing the frame order number by the camera acquisition
and pools where sediments are massively transported from
frequency. Velocity is then obtained by dividing the travel
higher-gradient regions, that is, the top of the hillslope plot,
time by the approximate length of the rill, that is, 4 m.
to downstream
tracts.travel
The rill
towards
a small
scale
Two additional
timeevolves
experiments
with
rhodamine
step-and-pool
microchannel
where
velocity
alternates
from
WT dye are conducted to compare the presented methodplacid
zones
to
faster
reaches.
In
such
settings,
samples
floatology with more commonly used approaches. Experiments
ingwith
in therhodamine
rill tend toare
remain
trapped
pool sections.
Isolated
conducted
by in
releasing
0.5 ml of
dye at
beads
are
then
gradually
released
from
the
pools.
This
the deployment section and by synchronizing the release phewith
nomenon
tends toofaffect
mostly
the visibility
particles
of
the acquisition
the digital
camera.
The timeofthe
dye takes
smaller
diameters
are harder
to seeby
in converting
small quantities.
to flow
along thewhich
4 m long
rill is found
experimental videos
into frames
and then manually
analyzing
the
Despite
such adverse
environmental
conditions,
results
images.
first frame
at which
the presence
of thefor
dyeenis
support
theThe
feasibility
of using
fluorescent
particles
observed isapplications.
then divided In
by particular,
the acquisition
frequency of
of the
vironmental
the strengths
digital camera
the travel
methodology
cantoberecover
summarized
as time.
follows: i) particles as
Estimations
of
the
travel
time
through
inspection
are
small as 75µm are detected through both visual
supervised
and ungenerally
possible
for
videos
depicting
transits
of
the
1000–
supervised procedures; ii) reliable velocity estimates are ob1180for
µmthe
particles.
this case,
the1000
analysis
gives an and
average
tained
largest In
sizes,
that is,
− 1180µm;
iii)
−1 over the ten experimental repetitions
velocity
of
0.33
m
s
particle transits are successfully captured
by
an
ad-hoc
inwith a standard deviation of 0.02 m s−1 . This value is in good
troduced index computed on the videos for most of larger
agreement with velocity obtained by using the rhodamine
diameters and for the 150
− 180µm beads.
dye, that is, 0.34 m s−1 with standard deviation 0.01 m s−1 .
Interestingly,
velocity
estimates
thelead
1000
1180µm
Experiments with smaller particles for
do not
to −
accurate
esparticles
are ofintravel
goodtime
agreement
with
timations
due to the
poormeasurements
visibility of thetaken
first
withbeads
rhodamine
arrival. dye and are comparable to visual inspection
analysis. Such promising results suggest that the beads allow3.2
for experimenting
longer flow paths as compared to
Unsupervised with
analysis
tests performed with rhodamine WT. In particular, adsorption
losses
and Gilley,
the presence
of more
The(Finkner
above discussion
on 1986)
particleand
visibility
is supported
by
advanced
deployment
detection
constitute
serithe calculation
of theand
index
G and systems
its filtered
version G
on
ousexperimental
limitations (Tatard
al., 2008) to
large
scale implemenvideos.etSpecifically,
Fig.
9 displays
the index
tation
of three
dyes.representative
Further, particle
transits are
capG for
experiments
for successfully
particles of diamtured
by equal
the index
for the
1000
− 1180µm
− 180µm
eters
to 75–90
µm,
1000–1180
µm,and
and150
500–600
µm,
beads,
thus suggesting
this diameter
successrespectively.
The peakthat
at frame
1366 in could
Fig. 9abepertains
to
fully
for tracing
flowsofinparticles
small rills,
provided
vistheused
passage
of the cloud
depicted
in Fig.the
6. Two
peaks
values
the index are
observed from
frame
ibility
ofand
thehigher
particles
is of
improved.
Therefore,
improving
694
to
frame
791
in
Fig.
9b,
relative
to
the
snapshots
shown
on the experimental apparatus and exploring alternative fluin Fig. 8.
the other
hand,
Fig. 9c, no
peakbeads
is clearly
orophores
to On
further
enhance
theinvisibility
of the
may
evident.
Such
findings
confirm
that
the
index
successfully
significantly help the bead detection through the fitting procedure.
On
the other hand, the illustrated preliminary proof-ofwww.hydrol-earth-syst-sci.net/16/2973/2012/
concept experiment has allowed to identify limitations of
Table 3. Velocities obtained through the image analysis procedure,
the proposed instrumentation that will be objective of future
IM Velocity, and visual analysis, VA Velocity. VA velocities are restudies. In particular, the methodology results are affected by
ported for the larger classes of diameters since experiments with
the limited
visibility
of theforbeads
which
is,time
in turn,
influenced
smaller
particles
do not allow
accurate
travel
estimations.
by the illumination conditions and by the meagre quantity of
deployed material,
is,Velocity
only 4 −VA
5g.Velocity
With regards to imDiameter thatIM
age quality, the
beads may
µm synthesis
m of
s−1highly fluorescent
m s−1
be particularly
beneficial.
In
addition,
investigation
of more
75–90
0.08
n.a.
biocompatible and biodegradable
materials
may
allow
for in0.11
n.a.
creasing the150–180
amount of tracer.
0.11
n.a.
0.18
n.a.
0.11
n.a.
1.47
n.a.
5 Conclusions
0.46
n.a.
710–850
0.05
n.a.
In this paper,
a novel fluorescent
particle0.33
tracer has been used
1000–1180
0.29
to perform a proof of concept
experiment
0.28
0.31 to estimate overland flow velocity on a hillslope
plot.
Experiments
have been
0.26
0.34
performed to evaluate the accuracy and efficiency of the tracing methodology under the following adverse conditions: i)
high turbidity loads; ii) interaction of the particles with soil
detects
the transit
bright clusters
particles
if it
sediments;
and iii)ofinteraction
of rainofdrops
witheven
the flow.
likely
fails tohave
identify
arrival while
of the flowing
first beads
Particles
beenthe
detected
in of
thesmall
rill undiameters.
is also observed
peakcomprising
intensity values
Fig. 9band
derneath aItdetection
apparatus
lightinsource
are
lower
than peakunits.
values in
Fig. 9a. Higher
indexhave
values
in
video
acquisition
Experimental
results
demonFig.
9b
are
more
likely
to
pertain
to
isolated
particles
flowing
strated the feasibility of using the particles for environmental
through the region of interest as anticipated from the superapplications and have led to the identification of optimal divised analysis. Finally, particles of intermediate sizes are not
ameters, namely, 1000 − 1180µm, for flow measurements in
detected by the index.
the described hillslope plot.
The unsupervised image analysis described in Sect. 2.3
Future ameliorations
theten
illustrated
methodology
is implemented
on each oftothe
experimental
repetitionswill
encompass
enhanced
biodegradableobtain
particle
recorded
for the
the design
studied of
diameters
to automatically
tracers and
of time.
the hardware
of of
thethe
detection
particle
travel
Only thecomponents
green channel
images apparatus.
thepreliminarily
following directions
be adis
analyzedSpecifically,
and frames are
cropped towill
restrict
dressed:search
i) newto biocompatible,
biodegradable,
andthe
low
particle
the portion of the
image depicting
rillcost
fluorescent particles will be fabricated and laboratory and
bed.
Experimental
videos
fulfillingto the
constraints
imposed
field
tests will be
performed
assess
their performance.
through
the
fitting
procedure
are
reported
in
Table
3.
Such particles will be deployed in larger amountsSpecifiin the encally,
two videos
fitted for their
the 75–90
µm, five
for thethe
150–
vironment,
thus are
facilitating
detection
through
unsu180
µm,
one
for
the
710–850
µm,
and
three
for
the
1000–
pervised procedure; ii) different fluorophores will be experi1180
µmwith
diameters.
Travel
time is estimated
from
frame
mented
to allow
fluorescence
excitation
at athe
broad
range
of wavelengths. This amelioration will allow for enhancing
bead visibility,
usingEarth
moreSyst.
portable
and reducing
Hydrol.
Sci., lamps,
16, 2973–2983,
2012 total costs; iii) miniature cameras will be tested to mitigate the
2980
order number corresponding to the first value of G in the
fitted window and velocities relative to each fitting are presented in Table 3.
Results in Table 3 show that unfeasible velocities are obtained for the smaller particles and therefore confirm that the
index is not able to detect first arrivals for beads of diameters
of 150–180 µm and smaller. Nonetheless, the fitting procedure can be used to sense the transit of particle clouds of
small dimensions. Notably, four experiments out of the five
reported in Table 3 for 150–180 µm diameters pertain to the
actual transit of the beads, whereas the velocity value equal to
1.47 m s−1 is biased by reflections on the water surface. On
the other hand, larger particles, such as the 1000–1180 µm
beads, are easier to detect and estimated velocities are comparable to values obtained from visual analysis and experiments with rhodamine. This finding is also confirmed from
analysis of Fig. 9. Indeed, the group of 75–90 µm beads in
Fig. 9a is likely not the first cluster of particles to arrive at
the detection apparatus since the peak only occurs 37 s after
sample deployment, thus yielding an equivalent yet unfeasible, flow velocity of 0.11 m s−1 . Conversely, Fig. 9b captures
the whole transit of the particles as higher values of the index
are measured for approximately 3–4 s. It is further observed
that larger fitted windows correspond to larger diameters due
to the fact that particle samples of larger dimensions tend to
diffuse in the rill and, therefore, bead trains take longer times
to cross the region captured by the camera.
As evidenced by the supervised and unsupervised analysis, the 1000–1180 µm beads can be identified as the optimal
particles to be adopted for the experimental settings of this
study. In particular, velocities obtained from the automatic
procedure are only 15 % lower than estimates from visual
analysis and results from both methodologies are close to the
velocity estimated with the rhodamine dye. Promising results
are also found for four out of ten experiments with the 150–
180 µm beads, see Table 3. Specifically, the index is able to
capture the passage of groups of particles of such small diameters for half of the experiments.
4
Discussion
Experimental findings demonstrate remarkable challenges in
detecting the particles. Specifically, bead groups tend to dismember once deployed in the rill due to an array of concurring factors. Most importantly, the complex structure and
morphology of the rill bed and the presence of severe sediment loads are relevant causes of particle dispersal. After an
initial phase when runoff mainly occurs in the form of sheetflow on the soil surface, the onset of rilling develops through
a supercritical flow velocity regime (Tatard et al., 2008). This
condition produces the formation of small hydraulic jumps
and pools where sediments are massively transported from
higher-gradient regions, that is, the top of the hillslope plot,
to downstream tracts. The rill evolves towards a small scale
step-and-pool microchannel where velocity alternates from
placid zones to faster reaches. In such settings, samples floating in the rill tend to remain trapped in pool sections. Isolated
beads are then gradually released from the pools. This phenomenon tends to affect mostly the visibility of particles of
smaller diameters which are harder to see in small quantities.
Despite such adverse environmental conditions, results
support the feasibility of using fluorescent particles for environmental applications. In particular, the strengths of the
methodology can be summarized as follows: (i) particles as
small as 75 µm are detected through both supervised and
unsupervised procedures; (ii) reliable velocity estimates are
obtained for the largest sizes, that is, 1000–1180 µm; and
(iii) particle transits are successfully captured by an ad-hoc
introduced index computed on the videos for most of larger
diameters and for the 150–180 µm beads.
Interestingly, velocity estimates for the 1000–1180 µm
particles are in good agreement with measurements taken
with rhodamine dye and are comparable to visual inspection
analysis. Such promising results suggest that the beads allow for experimenting with longer flow paths as compared
to tests performed with rhodamine WT. In particular, adsorption losses (Finkner and Gilley, 1986) and the presence of
more advanced deployment and detection systems constitute
serious limitations (Tatard et al., 2008) to large scale implementation of dyes. Further, particle transits are successfully
captured by the index for the 1000–1180 µm and 150–180 µm
beads, thus suggesting that this diameter can be successfully
used for tracing flows in small rills, provided the visibility of
the particles is improved. Therefore, improving on the experimental apparatus and exploring alternative fluorophores to
further enhance the visibility of the beads may significantly
help the bead detection through the fitting procedure.
On the other hand, the preliminary proof-of-concept experiment has allowed to identify limitations of the proposed
instrumentation that will be objective of future studies. In
particular, results are affected by the limited visibility of the
beads which is, in turn, influenced by the illumination conditions and by the meagre quantity of deployed material, that
is, only 4–5 g. With regards to image quality, the synthesis
of highly fluorescent beads may be particularly beneficial. In
addition, investigation of more biocompatible and biodegradable materials may allow for increasing the amount of tracer.
5
Conclusions
In this paper, a novel fluorescent particle tracer has been
used to perform a proof of concept experiment to estimate
overland flow velocity on a hillslope plot. Experiments have
been performed to evaluate the accuracy and efficiency of
the tracing methodology under the following adverse conditions: (i) high turbidity loads; (ii) interaction of the particles
with soil sediments; and (iii) interaction of rain drops with
the flow.
Particles have been identified while flowing in the rill underneath a detection apparatus comprising light source and
video acquisition units. Experimental results have demonstrated the feasibility of using the particles for environmental
applications and have led to the identification of optimal diameters, namely, 1000–1180 µm, for flow measurements in
the described hillslope plot.
Future ameliorations to the illustrated methodology will
encompass the design of enhanced biodegradable particle
tracers and of the hardware components of the detection apparatus. Specifically, the following research directions will
be pursued: (i) new biocompatible, biodegradable, and low
cost fluorescent particles will be fabricated and laboratory
and field tests will be performed to assess their performance.
Such particles will be deployed in larger amounts in the environment, thus facilitating their detection through the unsupervised procedure; (ii) different fluorophores will be experimented with to guarantee fluorescence excitation for broad
range of wavelengths. This amelioration will allow for enhancing bead visibility, using more portable lamps, and reducing total costs; (iii) miniature cameras will be tested to
mitigate the illumination problem. Specifically, cameras will
be located below the lamp unit in the particle detection apparatus, thus reducing the negative effects of light reflections; (iv) extensive field campaigns will be planned to quantify the uncertainty of the observations, provide a more extensive validation of presented results, and fully automate the
detection procedure.
Acknowledgements. This work was partially supported by the
MIUR Project PRIN 2009 N. 2009CA4A4A “Studio di un tracciante innovativo per le applicazioni idrologiche”, by the National
Science Foundation under Grant Nos. CMMI-0745753 and CMMI0926791, and by the Honors Center of Italian Universities (H2CU
Sapienza Università di Roma). The authors would like to greatly
thank G. Ubertini for conducting the granulometry analysis and
R. Rapiti, G. Cipollari, I. Capocci, G. Mocio, and C. Pagano for
the realization of the experimental apparatus and help with the
experiments.
Edited by: N. Romano
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Fluorescent particle tracers in surface hydrology

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