time of attendance: tuesday, february 13, 2018 04:00 pm...
TRANSCRIPT
Better Understanding of the Biogeochemical Buffering Capacity of Ria Formosa,
Portugal to Future Scenarios of Global Changes
Time of attendance: Tuesday, February 13, 2018 04:00 PM - 05:00 PM
Background:Estuaries and Coastal Lagoons: Most productive ecosystems on Earth, providing multiplegoods and ecosystem services. Protection and conservation are vital.
Accurate modeling and prediction of the effects of climate change and variability, and themonitoring of their impacts, require sustained and extended observations of theseecosystems.
What do these tell about ?
• Differences between seasons are not strictly marked• Temperature in Summer reflects upwelling events shown in Fig. 3.• Extreme DO values at WB5 - the shallowest place at the eastern edge of Ria Formosa,
low values during early morning (< 60%).• Chl-a max in Summer, after upwelling confirmed by satellite images (Fig.3).• NO3 max at WB5-R, in antiphase with tide and salinity, associated with the highest
freshwater input, in Summer by upwelling and globally lower in Autumn, byconsumption.
• Provide observations to support the numerical model calibration andcontinuous validation.
Alexandra Cravo a ([email protected]), José Jacob a, Alexandra Rosa a, Marta Rodrigues b, João Rogeiro b
a CIMA/Universidade do Algarve, Faro, Portugal; b Laboratório Nacional de Engenharia Civil, Lisboa Portugal
E24A-0255
RESULTS:
A Real Time Observation (RTO) station – Innovative approachContinuously record every 15 min (Fig. 2), from May 17-Jan 18 (8 months): Temperature, salinity, pH, Dissolved oxygen (Fig. 3), and chlorophyll a and turbidity (not shown)
Fig. 1. Location of Ria Formosa, on south coast ofPortugal, sampling stations , deployment of PressureTransducers (PT) and real time observation station(RTO), and the limits of the water bodies (WB)identified by different colors.
Acknowledgements: UBEST Project is funded by the Fundação para a Ciência e a
Tecnologia, PTDC/AAG-MAA/6899/2014
Atlantic Ocean
Study area:Ria Formosa productive coastal lagoonon the south coast of Portugal (Fig. 1).
Vision: Advancing the prediction of global changes in the Ria
Formosa ecosystem
Implementation of an integrative “observatory”: - Data from continuous real time observations;- Discrete in-situ field campaigns, at sites representative of the water bodies
under Water Framework Directive;- Hydrodynamic-biogeochemical mechanistic models (ongoing calibration and
validation):- System of numerical models SCHISM (Semi-implicit Cross-scale
Hydroscience Integrated System Model), to simulate the hydrodynamics and biogeochemical processes;
- Development: customizable and integrative WebSIG platform (access to observations, real-time forecasts and future scenarios to stakeholders/end-users).
What can we learn from it?
B SEASONAL SEMI-DIURNAL TIDAL CYCLES
SP
RIN
GA
UT
UM
NS
UM
ME
R
Sampling: Spring: 5/30/2017; Summer: 9/14/2017; Autumn: 10/25/2017
• 7 sites (Fig. 1), complete semi-diurnal tidal cycles (~13 h), every 2 h: T, S, DO, Chl-a, NO3 (Fig. 4), NH4, PO4, SiO4, SS, pH (not shown)
-1.5
-1.0
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Tid
al
heig
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(m)
Salin
ity
Sampling hour
Boundary WB1WB2 WB3WB4 WB5-RWB5 Tide
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Tid
al
heig
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(m)
O2 S
atu
rati
on
(%
)
Sampling hour
Boundary WB1WB2 WB3WB4 WB5-RWB5 Tide -1.5
-1.0
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Tid
al
heig
ht
(m)
Ch
loro
ph
yll a
(µ
g/L
)
Sampling hour
Boundary WB1WB2 WB3WB4 WB5-RWB5 Tide
-1.5
-1.0
-0.5
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56
:30
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Tid
al
heig
ht
(m)
NO
3-(µ
M)
Sampling hour
Boundary WB1WB2 WB3WB4 WB5-RWB5 Tide
-1.5
-1.0
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Tid
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heig
ht
(m)
Salin
ity
Sampling hour
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Tid
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(m)
O2 S
atu
rati
on
(%
)
Sampling hour
-1.5
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Tid
al
heig
ht
(m)
Ch
loro
ph
yll a
(µ
g/L
)
Sampling hour
-1.5
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Tid
al
heig
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(m)
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3-(µ
M)
Sampling hour
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Sampling hour
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Tid
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O2 S
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rati
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(%
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Sampling hour
-1.5
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Tid
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heig
ht
(m)
Ch
loro
ph
yll a
(µ
g/L
)
Sampling hour
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Sampling hour
UBEST Project Goals• Improve global understanding of the biogeochemical functioning and buffering capacity
of 2 distinct Portuguese estuaries (Tagus estuary, and Ria Formosa lagoon - Fig. 1).
• Susceptibility to future scenarios of anthropogenic inputs and climate change.
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Tid
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Tem
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ture
(ºC
)
Sampling hour
Boundary WB1WB2 WB3WB4 WB5-RWB5 Tide
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Tem
pera
ture
(ºC
)
Sampling hour
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ture
(ºC
)
Sampling hour
• Capture of seasonal signatures• Capture of episodic events and marine processes
• Upwelling events by in temperature• Salinity in Summer• pH in Summer, accompanying DO• DO, lowest in Summer at night, with values < Minimum Allowable Value (MAV in Fig. 3)• Chl-a (not shown) globally < 5 g/L, max in Summer followed by Autumn, by satellite images (Fig. 3)• Turbidity (not shown), some outliers data to ignore, globally < 15 NTU
• Important observational data coupled with modeling can be translatedinto information useful for end-users and decision makers.
Facilitate the better understanding of the functioning of thisecosystem, and contribute to its short and long-term management andprotection, imperative to building knowledge‐based societies.
Final Remarks
Fig. 3. TOP: Temperature, salinity, pH and % saturation of dissolved oxygen data acquired by RTO, from May to Jan 2018 with indication of the sampling date of the seasonal semi-diurnal tidal cycles (indicated in B) for Spring (SP), Summer (SU) and Autumn (AU). MAV=Minimum Allowable Value.
BOTTOM: 8-day composite SST (left) and Chl-a (right) satellite images from OceanColor (https://oceancolor.gsfc.nasa.gov/) at periods typical of the sampled seasons (indicated by 1 to 3).
ATLANTIC OCEAN
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Tid
e (
m)
Tem
pera
ture
(ºC
)
Date
SP SU AU
25 May-01 Jun25 May-01 Jun1 -
SP
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e (
m)
pH
Date
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13-21 Sep13-21 Sep2B-
SU
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e (
m)
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rati
on
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)
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MAV=70%
24-31 Oct24-31 Oct3 -
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e (
m)
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ity
Date
SP SU AU
29 Aug-05 Sep29 Aug-05 Sep2A-
SU
1 2A
2B3
Fig. 4. Variability of temperature, salinity, % Dissolved Oxygen, Chl-a and NO3 along the complete tidal cycles conducted in Spring, Summer and Autumn tidal cycles.
Fig. 2. RTO location, multiparametric probe with sensors and datalogger