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Variations of inherent optical properties in case
of harbour dredging in Estonian coastal sea
Liis Sipelgas
Tallinn University of Technology
Marine Systems Institute
Outline
• Study sites and collected IOP dataset at the time of dredging
• Examples of data
• Use of MERIS imagery for monitoring SPM distribution
• Plans for upcoming PECS project “Environmental monitoring of
harbour dredging”
18 19 20 21 22 23 24 25 26 27 28 29 30
57
57.5
58
58.5
59
59.5
60
60.5
EstoniaRussia
Latvia
Finland
Baltic Sea
Gulf of Finland
Gulf of Riga
Muuga harbour
Paldiski south harbour
Paldiski south harbour
•Harbours belong to the Port of Tallinn which is one of
three biggest cargo handlers in the Baltic Sea
•Maintenance of the harbours requires dredging of the
shipping channel and aquatory after every second year
Muuga harbour
The dataset of IOP-s have been collected during the monitoring of SPM
distribution at the time of port dredging. The data was used for detailed
description of SPM distribution near the dredging site for later evaluation of
environmental impact. The dataset contains:
•Vertical profiles of attenuation and absorption coefficient with WetLabs ac -
spectra
•Concentrations of SPM and Chlorophyll a
There are approximately 30 days of data from different sites collected during
years 2007-2010.
400 500 600 700wavelength, nm
0.5
1
1.5
2
2.5
3
3.5
sca
tte
rin
g c
oeff
icie
nt, m
-1
Graph 1St_1
St_2
St_3
St_4
St_5
St_6
St_7
St_8
St_9
St_10
St_11
St_12
St_13
Scattering coefficient 9_09_2009, Muuga Bay
24.8 24.85 24.9 24.95 25 25.05 25.1 25.15
Longitude
59.44
59.46
59.48
59.5
59.52
59.54
59.56
59.58
59.6
59.62
Latitu
de
S1
S2S3
S4
S5S6
S7
S8
S9
S10
0.3
0.5
0.7
0.9
1.1
1.3
1.5
1.7
1.9
2.1
dredging site
harbour
TSM mg/L
24.8 24.85 24.9 24.95 25 25.05 25.1
Longitude
59.46
59.48
59.5
59.52
59.54
59.56
59.58
59.6
59.62
Latitu
de
2.62
2.86
3.092.38
2.38
3.57
3.33
2.14
3.09
5.47
2.62
2
2.5
3
3.5
4
4.5
5
5.5
Chl mg/m-3
Dredging in Muuga 9_09_2009
400 500 600 700wavelength, nm
0
1
2
3
4
sce
cific
sca
tte
rin
g c
oe
ffic
ien
t, L
m-1m
g-1
Graph 1St_1
St_2
St_3
St_4
St_5
St_6
St_7
St_8
St_9
St_10
St_11
St_12
average
Fit 2: Power
Specific scattering coefficient, 9_09_2010, Muuga Bay
Fit 2: PowerEquation ln(Y) = -0.5281589405 * ln(X) + 3.927085499Alternate Y = pow(X,-0.5281589405) * 50.75882524
Coef of determination, R-squared = 0.887161
24.8 24.85 24.9 24.95 25 25.05 25.1
Longitude
59.46
59.48
59.5
59.52
59.54
59.56
59.58
59.6
59.62
La
titu
de
S1
S2
S3
S4
S5
S6
S7
S8
S9
S10
S11
S12
S13S14
S15
Sp
0.5
1
1.5
2
2.5
3
3.5
4
4.5
5
5.5
6
TSM mg/L
harbour dredging site
24.8 24.85 24.9 24.95 25 25.05 25.1
Longitude
59.46
59.48
59.5
59.52
59.54
59.56
59.58
59.6
59.62
Latitu
de
7.14
8.57
13.1
9.04
13.6
12.9
9.04
10.9
10.9
14
9.04
16.9
16.98.81
12.6
9.76
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
Chl mg/m3
400 500 600 700wavelength, nm
0.8
1.2
1.6
2
2.4
sca
tteri
ng c
oe
ffic
ien
t, m
-1
Graph 1S_1
S_2
S_3
S_4
S_5
S_6
S_7
S_8
S_9
S_10
S_11
S_12
S_13
S_14
S_15
Scattering coefficient 28_04_2010, Muuga Bay
Dredging at the time of spring
bloom in Muuga Bay
28_04_2010
400 500 600 700wavelength, nm
0.3
0.4
0.5
0.6
0.7
sp
ecific
scatt
erin
g c
oe
ffic
ien
t, L
m-1m
g-1
Graph 1S_1
S_2
S_3
S_4
S_5
S_6
S_7
S_8
S_9
S_10
S_11
S_12
S_13
S_14
S_15
average
Fit 3: Power
Specific scattering coefficient 28_04_2010, Muuga Bay
Fit 3: PowerEquation ln(Y) = 0.1596440467 * ln(X) - 1.728228851Alternate Y = pow(X,0.1596440467) * 0.1775986852Coef of determination, R-squared = 0.325869
0 1 2 3 4 5TSM (water samples), mg/L
0
1
2
3
4
TS
M (
ME
RIS
) m
g/L
2.084
3.039
0.65
0.38 0.4
1.17
0.414
0.710.62
0.78
1.718
1.455
1.7331.646
1.107
1.285
1.6881.6
2.315
1.7171.599
1.6931.789
1.509
1.666
1.439
Fit 1: Linear (for september)Equation Y = 1.368312343 * X - 0.09731612091Coef of determination, R-squared = 0.869024
Fit 1: Linear (for april)Equation Y = -0.1837222386 * X + 2.192029246Coef of determination, R-squared = 0.207206
28_04_2010
9_09_2009
Comparison of MERIS TSM
vs TSM water samples
• If the Chl content is low and
particles are mainly
resuspended MERIS TSM
product is reliable.
• In case of high Chl content the
MERIS TSM is underestimated.
23.94 23.98 24.02 24.06 24.1 24.14
Longitude
59.26
59.28
59.3
59.32
59.34
59.36
59.38
59.4
59.42
Latitu
de
2
6
910
12131416
17181920
222324
0.5
1.3
2.1
2.9
3.7
4.5
5.3
6.1
6.9
7.7
30
SPM, mg/L
23.94 23.98 24.02 24.06 24.1 24.14
Longitude
59.26
59.28
59.3
59.32
59.34
59.36
59.38
59.4
59.42
Latitu
de
5.5
5.5
6.213
6.714106
5.55.264
6.766.9
4
5.5
7
8.5
10
11.5
13
Chl mg m-3
Dredging Pakri Bay 5.09.2008
400 500 600 700wavelength, nm
0
0.5
1
1.5
2
2.5
3
sca
tteri
ng c
oeff
icie
nt, m
-1
16
18
20
22
24
26
sca
tte
rin
g c
oeffic
ien
t m
-1,
st
12
Graph 1St_2
St_6
St_9
St_10
St_12
St_13
St_14
St_16
St_17
St_18
St_19
St_20
St_22
St_23
St_24
Scattering coefficient 5_09_2008, Pakri Bay
400 500 600 700wavelength, nm
0
0.2
0.4
0.6
0.8
1
sp
ecific
sca
tte
rin
g c
oe
ffic
ien
t, L
m-1m
g-1
Graph 1St_2
St_6
St_9
St_10
St_12
St_13
St_14
St_16
St_17
St_18
St_19
St_20
St_22
St_23
St_24
average
Fit 2: Power
Specific scattering coefficient 5_09_2008, Pakri Bay
Fit 2: Power
Equation ln(Y) = -0.2774951811 * ln(X) + 0.7703492946Alternate Y = pow(X,-0.2774951811) * 2.16052078Coef of determination, R-squared = 0.712334
23.96 24 24.04 24.08 24.12
Longitude
59.26
59.28
59.3
59.32
59.34
59.36
59.38
59.4
59.42
Latitu
de
6.7
8.3
5.2
8.6119.5
2.63.851.7
3.33.87.9
0
3
5
6.5
8
9.5
11
12.5
Chl a, mg m-3
23.98 24.02 24.06 24.1
longitude
59.26
59.28
59.3
59.32
59.34
59.36
59.38
59.4
59.42
latitu
de
12
5
6
91011
12131415
181920
0.5
1.3
2.1
2.9
3.7
4.5
5.3
6.1
6.9
7.7
SPM, mg/L
400 500 600 700wavelength, nm
0.8
1.2
1.6
2
2.4
sca
tteri
ng c
oeff
icie
nt, m
-1
Graph 1St_2
St_5
St_6
St_9
St_10
St_11
St_12
St_13
St_14
St_15
St_18
St_19
St_20
Scattering coefficient 25_07_2008, Pakri Bay
Dredging Pakri Bay 25.07.2008
400 500 600 700wavelength, nm
0.3
0.4
0.5
0.6
0.7
0.8
sce
cific
sca
tte
rin
g c
oe
ffic
ient,
L m
-1m
g-1
Graph 1St_2
St_5
St_6
St_9
St_10
St_11
St_14
St_15
St_18
St_19
average
Fit 2: Power
Specific scattering coefficient 25_07_08, Pakri Bay
Fit 2: Power
Equation ln(Y) = -0.47227858 * ln(X) + 2.33238219Alternate Y = pow(X,-0.47227858) * 10.30245473Coef of determination, R-squared = 0.93384
Dredging Pakri Bay 21_11_2008
WN wind 8-10m/s,
very low phytoplancton content
chlorophyll a concentration less
than 0.3μg/L
400 500 600 700wavelength, nm
2
3
4
5
6
7
8
sca
tteri
ng c
oeff
icie
nt, m
-1
Graph 1St_1
St_2
St_3
St_4
St_5
St_6
St_7
St_8
St_9
Scattering coefficient 21_11_2008, Pakri Bay
23.96 24 24.04 24.08 24.12
longitude
59.25
59.3
59.35
59.4
latitu
de
12
345678
9
0.5
1.5
2.5
3.5
4.5
5.5
6.5
7.5
TSM, mg/L
400 500 600 700wavelength, nm
0.5
0.6
0.7
0.8
0.9
1
sp
ecific
sca
tteri
ng c
oeff
icie
nt, L
m-1 m
g-1
Graph 1St_1
St_2
St_3
St_4
St_5
St_6
St_7
St_8
St_9
Average
Fit 2: Power
specific scattering coefficient 21_11_2008, Pakri Bay
Fit 2: PowerEquation ln(Y) = -0.6391894809 * ln(X) + 3.657421566Alternate Y = pow(X,-0.6391894809) * 38.76127054Coef of determination, R-squared = 0.9911883
0 1 2 3 4 5TSM(water samples), mg/L
0.8
1.2
1.6
2
2.4
2.8
Sca
tteri
ng c
oeff
icie
nt 5
55n
m, m
-1
1.759
2.713
1.063
0.9453
1.041
1.424
1.146
0.9361
1.0371.047
1.353
2.278
1.476
1.5991.66
1.414
2.306
1.691
1.346
1.417
1.521
1.637
1.411
1.586
1.779
1.316
1.439
Muuga Bay
Fit 1: Linear (september)Equation Y = 0.8259146341 * X + 0.5969433537Coef of determination, R-squared = 0.877689
Fit 1: LinearEquation Y = 0.3135433218 * X + 0.6032899913Coef of determination, R-squared = 0.729111
400 500 600 700wavelength, nm
0.5
0.6
0.7
0.8
0.9
1
coe
rre
letio
n c
oe
ffic
ient,
R
Graph 1R_Muuga 9_09_09
R_Pakri_5_09_08
R_Pakri_21_11_08
R_Muuga_28_04_10
R_Pakri_25_07_08
TSM(water samples) vs scattering coefficient (402-730nm)0 2 4 6 8 10TSM (water samples) mg/L
0
2
4
6
8sca
tte
rin
g c
oeff
icie
nt 5
55n
m,
m-1
1.426
1.7381.688
1.328
1.9781.747
1.5261.441
1.1031.177
1.6221.696
0.40250.4148
2.189
1.365
0.969
0.69070.63540.60790.57040.61990.56020.46760.50180.5018
3.414
4.09
4.983
5.255
5.612
6.334
5.86
4.969
3.703
Pakri Bay
Fit 1: Linear
Equation Y = 0.277384589 * X + 0.7808843179Coef of determination, R-squared = 0.42306
Fit 1: Linear
Equation Y = 0.4049322394 * X - 0.06595408231Coef of determination, R-squared = 0.86091
Fit 1: Linear
Equation Y = 0.577706255 * X + 0.7795352423Coef of determination, R-squared = 0.943193
MERIS case-2 processor products are reliable for describing the SPM
distribution in case when dominant particles in water are resuspended
particles.
In PECS project “Environmental monitoring of harbour dredging” are
planed:
1. Analysis of SPM distribution in two largest harbours in Estonia using
entire MERIS mission data (from CoastColour database) for detection of
long term changes. Relating the data to ship traffic intensity and dredging
activities.
Interesting datasets:
- SPM maps for cloud free days
- If possible some estimate of particles size distribution would be very
interesting for the environmental impact evaluation.
2. Interactive software tool for harbour authorities with dataset from:
(1)MERIS, (2) in situ measurements and (3) hyrdodynamical model for
monitoring SPM distribution during dredging operations.