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Modern techniques to monitor
the state of the Gulf of Finland
Urmas Lips, Inga Lips, Villu Kikas, Taavi Liblik,
Nelli Rünk, Aet Meerits, Andres Trei, Peeter Laas
Marine Systems Institute
Tallinn University of Technology
Background
• In order to achieve good ecological status of the Baltic Sea
(including Gulf of Finland) measures have to be taken
• HELCOM has approved Baltic Sea Action Plan, EU has
adopted Marine Strategy Framework Directive
• Appropriate measures can be agreed and their
effectiveness can be assessed only on the basis of reliable
knowledge on the state and functioning of the marine
ecosystem
• Thus scientifically sound monitoring and assessment
system must be in place
Marine Systems Institute
Tallinn University of Technology
2
GoF 2014 Scientific Forum
21 January 2014, Helsinki, Finland
Background
• In 2011-2013 an Interreg IVA project GES-REG (Good
environmental status through regional coordination and
capacity building) has been conducted
• One of the aims of the project was to propose a joint
monitoring and assessment scheme in our sub-region
(including Gulf of Finland)
• Project contributed to the HELCOM monitoring revision
and a new HELCOM monitoring and assessment strategy
was adopted to better coordinate monitoring activities
and underline the benefits for joint monitoring and
assessment
Marine Systems Institute
Tallinn University of Technology
3
GoF 2014 Scientific Forum
21 January 2014, Helsinki, Finland
HELCOM monitoring and assessment
strategy
Marine Systems Institute
Tallinn University of Technology
4
GoF 2014 Scientific Forum
21 January 2014, Helsinki, Finland
Why and what modern techniques have
to be applied?
• It is clear that better (in terms of confidnece) information on
the state of the marine ecosystem is needed, taking into
account the high natural variability both in space and time
• Cost-effectiveness analysis of different monitoring methods was
conducted
• It was found that Ferrybox type of monitoring is the most costeffective monitoring method (including autonomous in-situ
measurements and water sampling along the ferry lines)
• Autonomous buoy stations and vehicles – the most suitable way
to acquire data from the water column (and near-bottom layer)
• Remote sensing applications
• Use of models for assessment
Marine Systems Institute
Tallinn University of Technology
5
GoF 2014 Scientific Forum
21 January 2014, Helsinki, Finland
How to reduce the costs?
• The most efficient way to reduce the costs is cooperation
between the neighbouring countries, both in regard of
investments and required activities to serve the autonomous
stations and produce common assessment products, e.g. On
the basis of remote sensing information
• Collaboration and joint investments in the Ferrybox systems
(e.g. St. Petersburg line)
• Joint investments in the network of autonomous buoys (both
unattended measurements and laboratory analyses of samples)
• Joint tests of gliders, floating profilers and new sensors or
monitoring approaches (if tests are carried out nationally,
information could be made available to others)
Marine Systems Institute
Tallinn University of Technology
6
GoF 2014 Scientific Forum
21 January 2014, Helsinki, Finland
Measurement systems
Towed undulating system
measuring T, S, Chl a and
phycocyanin
Measurements of vertical
profiles of T, S, Chl a
Marine Systems Institute
Tallinn University of Technology
7
GoF 2014 Scientific Forum
21 January 2014, Helsinki, Finland
Ferrybox systems
•
•
•
Marine Systems Institute
Tallinn University of Technology
Autonomous measurements, water intake from the
surface layer (4 m) – sampling rate 20 s (spatial
resolution about 150 m) - temperature , salinity, Chl
a fluorescence and turbidity, PCO2, O2, nutrients etc
Near real time data delivery
Water samples nutrient and Chl a analyses;
phytoplankton counting
8
GoF 2014 Scientific Forum
21 January 2014, Helsinki, Finland
Spring bloom dynamics – GoF
Spring bloom dynamics and
heterogeneity is influenced by
physical forcing – prevailing
circulation in the surface layer and
the development of stratification,
including upward and downward
movement of the seasonal
thermocline.
Chl a and carbon biomass dynamics
(“phytoplankton”) differ
Lips et al., 2013, JMS
Marine Systems Institute
Tallinn University of Technology
9
GoF 2014 Scientific Forum
21 January 2014, Helsinki, Finland
2009dynamics
Nutrient
The estimated ratio of
nitrogen to phosphorus (N:P)
consumption during the
growth phase of the spring
bloom was close to the
Redfield ratio (16:1) during
both springs – 15.7:1 in 2009
and 15.9:1 in 2010
After the nitrites-nitrates
depletion
from the rubra
surface
Myrionecta
layer the
carbon biomass of
biomass
“phytoplankton” continued
to grow; regenerated
production, and consumption
2010
of deeper nitrate reserves are
suggested as nitrogen
sources
Marine Systems Institute
Tallinn University of Technology
10
GoF 2014 Scientific Forum
21 January 2014, Helsinki, Finland
Ferrybox on board R/V Salme
Marine Systems Institute
Tallinn University of Technology
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GoF 2014 Scientific11Forum
21 January 2014, Helsinki, Finland
Profiling stations
• Vertical profiles are acquired with a
predefined time step and depth
range
• Temperature, salinity, Chl a
fluorescence and other parameters
are recorded
• Used since 2009 in the Gulf of
Finland, interval 3-6 hours, depth
range from 2 to 50 m
• New system (developed in Estonia
by Flydog) , additional sensors and
configuration options (in addition
turbidity, dissolved oxygen,
phycocynin)
• Data transmitted in real time via
GSM connection
Electrochemical
antifouling system
Marine Systems Institute
Tallinn University of Technology
12
GoF 2014 Scientific Forum
21 January 2014, Helsinki, Finland
Combined analysis of
buoy and ferrybox data
Temperature
Salinity
1. Low variability in case of weak wind conditions
2. Moderate upwelling near the northern coast; variability in temperature and salinity
increasing
3. Strong upwelling near the southern coast; high variability in temperature and salinity
both in horizontal and vertical directions
Marine Systems Institute
Tallinn University of Technology
13
GoF 2014 Scientific Forum
21 January 2014, Helsinki, Finland
Co-operation in regard of autonomous buoys
Marine Systems Institute
Tallinn University of Technology
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GoF 2014 Scientific14Forum
21 January 2014, Helsinki, Finland
Scanfish survey on 22 July 2010
Layered vertical distribution of salinity and
especially Chl a was observed. Patches of high
Chl a were related to meso- and submesoscale
features in the thermocline. Most intense
subsurface maxima were situated within the
anticyclonic mesoscale eddies and filaments.
Lips & Lips, 2013, Deep-Sea Res II
Marine Systems Institute
Tallinn University of Technology
15
GoF 2014 Modelling WS
19 September 2013, Helsinki, Finland
Glider
Glider purchased, will be in operation starting from spring 2014
In addition new meteorological stations, ADCP-s with additional
sensors etc
Marine Systems Institute
Tallinn University of Technology
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GoF 2014 Scientific16Forum
21 January 2014, Helsinki, Finland
Use of models
Marine Systems Institute
Tallinn University of Technology
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GoF 2014 Scientific17Forum
21 January 2014, Helsinki, Finland
Use of models
Marine Systems Institute
Tallinn University of Technology
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GoF 2014 Scientific18Forum
21 January 2014, Helsinki, Finland
Integration
High temporal
and horizontal
resolution
High number of
variables and
high vertical
resolution
Research vessels
Satellite remote sensing
-
Temperature
Turbidity
Chlorophyll
Cyanobacterial blooms
-
Hydrography
Nutrients
Plankton
Benthos
Buoys
-
Mathematical Models
Temperature
Salinity
Oxygen
Turbidity
Chlorophyll
Cyanobacterial
pigments
By Juha-Markku Leppänen
High temporal
and vertical
resolution
Human sensors
-
Plankton blooms
Bladerwrack
?
Good temporal
and spatial
resolution
Ferrybox
-
Temperature
Salinity
Oxygen
Turbidity
Chlorophyll
Cyanobacterial pigments
Nutrients
Phytoplankton
High horizontal and
temporal
resolution moderate
number of
Marine Systems Institute
parameters
Tallinn University of Technology
19
GoF 2014 Scientific19Forum
21 January 2014, Helsinki, Finland
Thank you for attention!
Urmas Lips, Inga Lips, Villu Kikas, Taavi Liblik,
Nelli Rünk, Aet Meerits, Andres Trei, Peeter Laas
Marine Systems Institute at Tallinn University of Technology
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