monitorização de sistemas ambientais
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http://mosam.org
Monitorização de Sistemas Ambientais
J. Gomes Ferreira
http://ecowin.org/
2 de Novembro 2017
Universidade Nova de Lisboa
Bloco 1 – Água e Ecossistemas
Monitorização de Sistemas Ambientais
i. Compreender a ligação entre monitorização e planeamento em sistemas aquáticos,
particularmente no contexto DPSIR;
ii. Distinguir entre os conceitos de "outputs" e "outcomes" na elaboração e
implementação de planos de monitorização;
iii. Participar na elaboração de um caderno de encargos para planeamento de
monitorização em sistemas aquáticos e/ou avaliação de propostas;
iv. Participar na elaboração de um plano de amostragem, incluindo formulação de
hipóteses, dimensionamento espacial e temporal, e aspectos financeiros e logísticos;
v. Aplicar e interpretar modelos simples para a avaliação da qualidade de um sistema
aquático com base nos resultados de planos de monitorização;
vi. Enquadrar os pontos acima no contexto legal da União Europeia, optimizando os
meios existentes em Portugal face aos desafios das Directivas Europeias.
"Learning outcomes"
http://mosam.org
Após completar com sucesso esta parte da disciplina, um estudante será capaz de:
Ecossistemas Aquáticos – João Gomes Ferreira
Monitorização de Sistemas Ambientais
i. Conceitos gerais: tipos de sistemas e variabilidade, objectivos de
monitorização, amostragem;
ii. Enquadramento na legislação ambiental, em particular na Directiva-Quadro
da Água e Directiva-Quadro da Estratégia do Meio Marinho - comparação
com modelos externos à União Europeia;
iii. Elaboração de planos, com exemplos concretos de casos de estudo
(Portugal e EUA).
Três sessões teóricas e três sessões práticas (2/11, 9/11, 16/11)
Ecossistemas Aquáticos – João Gomes Ferreira
Objectivos e âmbito
http://mosam.org
Monitorização de Sistemas Ambientais
i. Ferreira et al, 2011. Overview of eutrophication indicators to assess environmental
status within the European Marine Strategy Framework Directive. Estuarine Coastal
and Shelf Science, 93, 117-131
ii. Ferreira et al, 2007. Monitoring of coastal and transitional waters under the EU Water
Framework Directive. Environmental Monitoring and Assessment, 135 (1-3), 195-216
iii. References cited in both papers, particularly the second one;
iv. Portuguese WFD monitoring plan, http//monae.org
v. Tilamook Bay monitoring plan, linked in the above site
vi. Barnegat Bay monitoring plan, linked in the above site
Recommended reading
http://mosam.org
http://mosam.org
Monitorização de Sistemas Ambientais
J. Gomes Ferreira
http://ecowin.org/
Universidade Nova de Lisboa
Conceitos gerais - tipos de sistemas aquáticos, objectivos,
amostragem
Lecture outline
1. System equilibria, natural- and human-derived change, DPSIR
framework and limitations
2. Monitoring at different scales: the big directive scale (WFD example),
small-scale (e.g. aquaculture licensing)
3. Spatial and temporal variability
4. Sampling methods (water quality, plankton, sediment…)
5. Getting it right and saving cash: scales and variability
6. Summary
Lecture 1
http://mosam.org
Sustainability criteria: foundation in classical ecology
可持续的标准:在经典生态学中的依据
Drivers
Agriculture – loss of fertilizer, etc
Urban and industrial discharges
Aquaculture
Atmospheric deposition
Internal (secondary) sources (e.g. P from sediments)
Advection from offshore (e.g. N and P, certain types of HAB)
Response
Fertilizer reduction
WWTP (sewage, industry)
Emmission controls
Sediment dredging etc
Time...
Interdiction (e.g. HAB events)
Pressure
N and P loading to the
coastal system
HAB phytoplankton
“loading” from offshore
State
Primary symptoms
Decreased light availability
Increased organic decomposition
Algal dominance changes
Secondary symptoms
Loss of SAV
Low dissolved oxygen
Harmful algae
Monitoring model
DPSIR
Impact
Fisheries
Aquaculture
Tourism
Non-use value
Human impact on the Chesapeake Bay, U.S.A.
http://ian.umces.edu/neea/
14 million people, millions of lawns, 500 million chickens.
http://www.baystat.maryland.gov/
Eutrophication in European seas
Diaz, R.J. and R. Rosenberg. 2008. Spreading dead zones and consequences for marine ecosystems. Science 321:926-928
Coastal eutrophication is a widespread phenomenon in Europe.
Human influence and uncertainty
Understanding
Oil spill
Phytoplankton
biodiversity
Hum
an influence
MoreLess
More
Less
Elevated nutrients
HAB
Type 2
HAB
Type 1Harmful algal blooms (HAB)
of various types (see text)
Some issues are easier to link to human pressure, and to understand.
The Peter Pan syndrome
Duarte et al., 2007. Estuaries and Coasts
Resilience…
One-way systems also exist in nature.
Water Framework Directive
Water categories
Surface
waters
Lakes
Groundwater
Rivers
Transitional
waters
Coastal
waters
Monitoring must deal with interconnected systems.
WFD surface water categories
A comparative analysis
Parameter Rivers Lakes/reservoirs Transitional
waters
Coastal
waters
Depth Low High Medium High
Salinity 0 0 0-35 35
Turbidity High Low High Low
Water clarity Low High Low High
River input Yes Yes Yes No
Tides No No Yes Yes
Residence time Low High Medium High
Variability Seasonal Seasonal Daily Seasonal
Nutrients Low-High Low-High Low-High Low
Phytoplankton Low Low-High Low-High Low
Macroalgae Low Low-High Low-High Low
Different physics, different biogeochemistry, different monitoring.
Loading and internal processing
Diffuse pollution
from catchmentAtmospheric
deposition
Outflow
Direct
discharge
Sedimentation
Mw
Min
Mout
In the 1960s and 1970s, models such as Vollenweider or Dillon &
Rigler were widely used to predict water quality in lakes.
http://www.lwa.org/des_report/htm/dillon.riglerpermissibleloadingmodel.htm
Aquaculture growth in Brazil (1994-2009)
0
20000
40000
60000
80000
100000
120000
140000
1995 1997 1999 2001 2003 2005 2007 2009
An
nu
al p
rod
uct
ion
(to
n)
21 % annualized
growth
• Many reservoirs are used for tilapia cultivation – steel cages keep the
piranhas at bay;
• Typical culture practice: stocking density of up to 300 kg m-3, harvest at
800 g after a 9 month growth period;
• Carrying capacity is determined as 1/6 of the total allowable phosphorus
(30 mg L-1), determined using the Dillon & Rigler (1974) model.
High growth, high impact, fragile assessment.
Typical production
250 cages per hectare
200 kg m-3, 6 m3 cages:
300 ton ha-1 cycle-1
Point-source discharge
Main concerns are usually coastal effects, e.g. on bathing beaches.
Wave-break area
Amplitude (h) = z/1.3
Outfall
Outfall
plume
OCEAN
Thermal stratification
Plume mixes with cold water and is retained beneath the mixed layer.
Warm layer
Outfall
Outfall
plume
OCEAN
Thermocline
Cool layer
Plume dispersion – offshore wind
Offshore wind causes coastal upwelling of colder water.
Warm
layer
Outfall
Outfall
plume
OCEAN
Cool
layer
Offshore wind
Offshore current
Upwelling
Plume dispersion – onshore wind
Onshore wind causes downwelling of warm water on the shore.
Warm
layer
Emissário
submarino
Outfall
plume
OCEAN
Cool
layer
Onshore wind
Onshore current
Downwelling
Offshore current
General scheme of an estuary
Estuaries are the most complex surface water systems on the planet.
River Ocean
Low tide level
High tide level
Tidal prism
Q (m3 s-1)
Advection
& dispersionTide
http://insightmaker.com/insight/6659
Longitudinal distribution of salinity
The salinity gradient from river to mouth is not constant.
RiverOcean
510
25
15
35
Uniform transverse section
Laterally stratified estuary
The isohalines suggest the ebb occurs mainly in the southern part of the system.
RiverOcean
510
25
15
35
Vertical distribution of salinity in an estuary
A significant input of freshwater is needed to impose vertical stratification.
River
Ocean
5 10 2515 35
Vertical
stratification
S
Z (m)
Halocline
Well-mixed water column
Monitoring parameters
Different matrices for different substances.
• Physical – e.g. temperature, salinity, morphology,
current velocity;
• Chemical – e.g. dissolved oxygen, nutrients,
suspended particulate matter, xenobiotics, etc;
• Biological – e.g. phytoplankton, benthic grabs,
fish.
Sampling techniques 1
Bottles are lowered by rope to a set depth, closed by means of a messenger.
Sampling bottles: Niskin, Nansen, Van Dorn…
Sampling techniques IShipboard measurements using Niskin bottles
Water quality sampling in the North Sea.
Sampling techniques IIShipboard measurements using CTD deployment in Hawaii
In large operations, CTDs are mechanically and electronically operated.
Sampling techniques IIIShipboard measurements - CTD lab operations
Much of the processing is automated, with data being quality-controlled and
uploaded to databases.
Sampling techniques IVShipboard measurements - CTD recovery
A CTD is recovered from deep water in bad weather.
Sampling techniques VShipboard measurements using plankton net tows in Hawaii
Nets may be towed horizontally or vertically.
Sampling techniques VIAcoustic Doppler Current Profiler (ADCP) deployment
A sophisticated technique for obtaining current profiles in the water column.
This animation shows the ADCP
time-series data at the HOTs station
off Hawaii from March 24-28, 1996.
The layer depths are 30m, 50m,
100m, 200m from the sea surface.
The vertical profile fluctuates highly
in time and sometimes shows a
clockwise rotation, probably showing
inertial oscillations.
The current at 200m layer is highly
variable as well as in the upper
layers where the current should have
big time-dependent components
induced by wind drive currents or
Ekman currents
Sampling techniques VIISmith-McIntyre grab for benthic sampling
Benthic sampling in the Tagus Estuary.
Sediment traps
Different designs, same idea
http://jpac.whoi.edu/atsea/instrument.html
http://smithlab.ucsd.edu/Antarctic/
htt
p://w
ww
.fim
r.fi/
Sediment traps
Capture larger particles (faecal
pellets, etc) which fall at a rate of
hundreds of metres per day
Should not be placed too near the
bottom (resuspension) or too
near the surface (mixing)
May be scavenged by deep-sea
organisms
“Inhibitors” may be added to reduce
this effect
0
200
400
600
800
1000
1200
125 62 31 16 8 4F
all
ve
locity (
m d
-1)
Particle diameter (mm)
Copepod fecal pellet
Ø = 50-100 mm
Isotopic markers may be used to identify particle sources, using fallout
tracers and other approaches
Marine snow is the mechanism which accounts for rapid transport of
organic material to the deep sea and benthos.
Eulerian sampling approach
Fixed stations sampled over a tidal cycle.
Fixed station
Eulerian sampling - integration
Integration of velocity gives information on tidal excursion.
Peak flood velocity
t (s)
V (ms-1)
0
Peak ebb velocity
Slack tide
V dt = h/3 (y0+4y1+2y2+...+4yn-1+yn)
Sampling period and actual period
Actual period is double the apparent period.
-1.5
-1
-0.5
0
0.5
1
1.5
200 400 600 800
Sampling window
Actual period
Apparent period
Sampling period and event occurrence
Event occurs seasonally (every 3 months) but appears to occur every six months.
2 4 6 8 10 12
Sampling occasions
Event
Month
0
Aerial surveys for bloom detectionEyes over Puget Sound (Wa., USA)
Aerial surveys for bloom detectionEyes over Puget Sound (Wa., USA)
Aerial surveys for bloom detectionEyes over Puget Sound (Wa., USA)
State of the art phytoplankton analysisFlowCAM – Eyes over Puget Sound (Wa., USA)
Image analysis is coming of age for biological monitoring.
http://www.ecy.wa.gov/programs/eap/mar_wat/eops/EOPS_2014_10_29.pdf
Data from long-term mooringsEyes over Puget Sound (Wa., USA)
Genetic probesAlexandrium is a genus of dinoflagellate than can cause paralytic shellfish
poisoning (PSP). Some species are toxic and some are not
Accumulation by shellfish results in closure of fishery for a period of time – in
Maine that costs hundreds of jobs and millions of dollars every year
Toxic species are part of the High Toxicity Low Biomass group, and are therefore
hard to detect
NCCOS project (2011-2014) has developed peptide nucleic acid probes and
other biosensors for rapid detection of Alexandrium
This will enable more rapid detection and safer shellfish
Toxic algal blooms are a challenge worldwide – the major effects on humans
are routed through the food chain.
http://coastalscience.noaa.gov/projects/detail?key=45
http://oceandatacenter.ucsc.edu/PhytoGallery/Dinoflagellates/alexandrium.html
Alexandrium catenella
Produces saxitoxin, a
highly potent neurotoxin
Case study: Welfaremeter operational model
Oppedal F., T. Dempster, L. H. Stien, 2010. Environmental drivers of Atlantic salmon
behaviour in sea-cages: a review. Submitted to Aquaculture.
• Coupled monitoring and modelling for
finfish cages
• A cage can contain one million USD of
fish, but little investment in monitoring of
environment and fish behaviour
• Automated assessment of fish welfare
in sea cages
• Instrumentation such as profiling CTD,
DO, echosounders
• Database for secure data storage and
retrieval
• Expert system software for data
analysis and modelling
• Web interface for easy visualisation of
data and expert system outputs
• Similar systems developed for gilthead
and bass in the east Mediterranean
Web application
Easy communication
between fishfarmer
and system
Database
Secure storage of data
Expert system
Automatic analysis of
fish welfare
Echosounder
Monitors fish behaviour
and fish position
Profiling CTD (SD204)
CTD-probe with additional
sensors for oxygen
saturation, turbidity and
fluorescence
Other
sensors
Loss of mangroves
in Nicaragua
Expansion of shrimp ponds
over a 13 year period in
Estero Real, Nicaragua
(UNEP, undated)
Real time modelling of wind patterns
Global models can complement local data.
Site suitability analysis for pond culture in Thailand
MCE based on slope, pH, land use, water temperature, water availability, towns and roads.
Jaguaribe Estuary (Ceará, Brazil)
The Jaguaribe has a huge
watershed, with over 4000
impoundments;
8 spatial stations and two fixed
stations, along 17 km of the
estuary (total of 34 km, limited by
a weir upstream);
upper estuary (Aracati) and
lower estuary (Fortim);
Two main urban centres.
Nutrient sources: urban
discharges, tilapia (from the
impoundments), shrimp culture,
cattle, agriculture.
Based on the area of shrimpponds, and predictions from the
POND model, an annual dischargeto the estuary of 60 tonnes N is
estimated, about 20% of the total nitrogen load
Source: Eschrique & Braga, 2011
Farm-scale models used to
improve loading estimates.
Underwater sensors and wifi communication
Realtime Aquaculture – salmon farming in Canada.
Sensors at Catalina Sea Ranch
Monitoring of environmental parameters – med mussel farm.
Synthesis
• Aquatic systems vary widely – in complexity, in time, and
in space
• Aquatic systems are interconnected, this is an important
management constraint
• Monitoring (like modelling) is never an objective. It is an
approach
• If you use a ship, that’s your highest cost – leverage it
• Data acquisition is rapidly changing (e.g. RNA probes,
smart dust)
Systems, objectives, and sampling
Concepts and science change more slowly than methods.
The two centimeter
probes float freely
underwater, measure
local temperatures
down to a millionth
of a degree Kelvin,
and send it all back
wirelessly.
http://mosam.org
Monitorização de Sistemas Ambientais
J. Gomes Ferreira
http://ecowin.org/
Universidade Nova de Lisboa
Enquadramento na Directiva-Quadro da Água, Directiva-Quadro da
Estratégia do Meio Marinho, e outras "visões" (e.g. E.U.A.)
Lecture outline
1. The legislative framework: EU, US, China
2. Europe: older generation (sectorial) directives, integrative directives
3. Monitoring framework of the WFD
4. Sampling frequency requirements, interpretation, costs
5. WFD and the Marine strategy
6. Summary
Lecture 2
http://mosam.org
International legislation
EU: Water Framework Directive (WDF), Habitats, Nitrates, Urban Wastewater Treatment Directive (UWWTD), Shellfish Directives, Marine Strategy Framework Directive;
http://europa.eu.int/eur-lex/
US: Clean Water Act, State legislation. The CWA established basic structureregulating discharges of pollutants into US waters. It gave EPA the authority to implement pollution control programs such as setting wastewater standards for industry; establish TMDLs. CWA continued requirements to set water qualitystandards for all contaminants in surface waters. The Act made it unlawful for any person to discharge any pollutant from a point source into navigable waters, unless a permit was obtained. Funded the construction of sewage treatmentplants and recognized the need for planning to address the critical problemsposed by nonpoint source pollution;
China: Sea Water Quality Standard (1998), Marine Environmental Protection Law (2000), Fisheries Law and its application measures (2000), Water Quality Standard for Fisheries (1990), Integrated Wastewater Discharge Standards (1998).
WFD - key points
Spatial integration, variable thresholds, cost of water.
protects all waters, surface and ground waters in a holistic
way
good quality (‘good status’) to be achieved by 2015
integrated water management based on river basins
combined approach of emission controls and water quality
standards, plus phasing out of particularly hazardous
substances
economic instruments: economic analysis, and getting the
prices right - to promote prudent use of water
gets citizens and stakeholders involved: public participation
Concept
Integration of first generation directives (e.g. UWWTD and Nitrates).
urban waste Watertreatment
nitrates IPPC &
otherindustrydischarges
chemicals
pesticides
biocides
landfills
sewagesludge
drinking water
bathing water
Measures under
Water Framework Directive
Coordination of all other measures
Some key WFD Definitions
"Transitional waters" are bodies of surface water in the vicinity of river mouths which are partly saline in character as a result of their proximity to coastal waters but which are substantially influenced by freshwater flows;
"Coastal water" means surface water on the landward side of a line every point of which is at a distance of one nautical mile on the seaward side from the nearest point of the baseline from which the breadth of territorial waters is measured, extending where appropriate up to the outer limit of transitional waters;
Member States should aim to achieve the objective of at least good water status by defining and implementing the necessary measures within integrated programmes of measures, taking into account existing Community requirements. Where good water status already exists, it should be maintained.
Water categories, types, water bodies
More types, more reference conditions, more water bodies, more €€€
Typology reality check
(a) regulatory reality
What the regulator likes: one size fits all.
Symptom level
Fre
qu
en
cy
(sp
ati
al/
tem
po
ral
vari
ab
ilit
y)
Natural
conditions
Stressors
(pressure)
Thresholds
Typology reality check
(b) ecosystem reality
What ecosystems really are: diverse and sometimes unique.
Symptom level
Fre
qu
en
cy
(sp
ati
al/
tem
po
ral
vari
ab
ilit
y)
Natural
conditions
Stressors
(pressure)
Threshold A
A
B
C
Threshold C
A
B
C
Biological and supporting quality elements
An ecosystem approach: BQE, then SQE, then hydromorphology.
Do the estimated values
for the biological quality
elements meet reference
conditions?
Do the estimated values for
the biological quality
elements deviate only
slightly from reference
condition values?
Classify on the basis of the
biological deviation from
reference conditions
No
No
Do the physico-chemical
conditions meet high
status?
Do the physico-chemical
conditions (a) ensure
ecosystem functioning
and (b) meet the EQSs for
specific pollutants?
Is the deviation moderate?
No
No
Yes
Yes
Yes Classify as
moderate status
Classify as
bad status
Is the deviation major?Classify as poor
status
Yes
Greater
No
Yes
YesDo the hydro-
morphological
conditions meet high
status?
Classify as good
status
No
Classify
as high
status
Yes
BQE
SQE
BQE
SQE
BQE
SQE
BQE
SQE
BQE
SQE
Yes
BQE
SQE
BQE
SQE
Greater
Water Framework Directive
Quality indices
If the EQR is below Good Status, there is an associated cost.
Ecological Quality Ratio (EQR),
i.e. the ratio between measured
value and reference condition
for High Status
The EQR must be between 0
(worst) and 1 (best)
Maps prepared in GIS for each
water body with the
classification for ecological
status and chemical status
Reporting of results EQR
EQR =
Colour code
High
Good
Moderate
Poor
Bad
Measured value
Ref. condition
WFD River Basin Management Plans
In general, every six years, one year surveillance monitoring.
Article 13
6. River basin management plans published at the latest nine years after date of WFD.
7. River basin management plans reviewed and updated at the latest 15 years after date of WFD and every six years thereafter.
Annex V
Surveillance monitoring carried out for each monitoring site for a period of one year during period covered by a river basin management plan for:
• parameters indicative of all biological quality elements,
• parameters indicative of all hydromorphological quality elements,
• parameters indicative of all general physico-chemical quality elements,
• priority list pollutants which are discharged into the river basin or sub-basin, and
• other pollutants discharged in significant quantities in the river basin or sub-basin,
unless previous surveillance monitoring exercise showed water body reached good status and there is no evidence from the review of impact of human activity in Annex II that the impacts on the body have changed. In these cases, surveillance monitoring shall be carried out once every three river basin management plans.
Monitoring
Relating pressure, state and response
Data to information, information to knowledge, knowledge to wisdom?
▪ Data conversion to information (e.g. indicators)
▪ Indices e.g. ASSETS, COMPP, AMBI, ITI...
▪ Model change in pressure (due to response)
▪ Model state (choose appropriate state variables,
e.g. DO, Chl a, xenobiotics)
▪ Compare to monitoring data and assess success
of measures
Monitoring caveats
i. What, where, when, how, and… why?
ii. Deus ex machina – monitoring for its own sake;
iii. Bias – e.g. no bacterial analysis on Fridays?
iv. Rote measurements – frequency should be
determined by gradient (variance) – but how do
we flag gradient?
Ask the right questions
Caveat emptor – buyer beware
Avoid the usual pitfalls, be creative, spend money wisely.
Types of monitoring
Different tools, different aims. Investigative monitoring = research
Surveillance monitoring1. Supplementing and validating the impact assessment procedure detailed in
Annex II2. The efficient and effective design of future monitoring programmes3. The assessment of long-term changes in natural conditions4. The assessment of long-term changes resulting from widespread
anthropogenic activity.Operational monitoring1. Establish the status of those bodies identified as being at risk of failing to
meet their environmental objectives2. Assess any changes in the status of such bodies resulting from the
programmes of measures.Investigative monitoring1. Where the reason for any exceedances is unknown2. Where surveillance monitoring indicates that the objectives set out in Article 4
for a body of water are not likely to be achieved and operational monitoring has not already been established, in order to ascertain the causes of a water body or water bodies failing to achieve the environmental objectives
3. To ascertain the magnitude and impacts of accidental pollution
Decision-tree for monitoring priorities
Monitoring is resource-limited. Spend money wisely.
Identification of water bodies at risk and
verification of measures
Verification is challenging due to natural variability and non-linearity.
▪ The first objective ( screening) is concerned with further investigation
into a water body which is at risk of non-compliance with environmental
objectives, i.e. which appears from surveillance monitoring data to be at
moderate, poor or bad status for one or more quality elements.
Operational monitoring is interpreted in MONAE to be applicable mainly
for water bodies diagnosed as being at moderate status, where more
detailed studies will help establish the status of the water body.
▪ The second objective ( verification) is to verify post-facto if
management measures are working, i.e. from a Pressure-State-
Response perspective, if a reduction in pressure due to management
response has resulted in the expected change in state.
Operational monitoring
Water Framework Directive
Sampling frequency
Sampling frequency is not sufficient to correctly classify a water body.
Biological quality element Frequency
Phytoplankton abundance, biomass, and
composition (ABC)
6 months
Composition and abundance of other aquatic
flora
3 months
Composition and abundance of benthic
invertebrates
3 years
Composition and abundance of fish populations
(ichthyofauna) – only transitional waters
3 years
Water Framework Directive
Sampling frequency
Sampling frequency is not sufficient to correctly classify a water body.
Supporting quality element Frequency
Morphology 6 years
Water temperature 3 months
Dissolved oxygen 3 months
Salinity (only transitional waters) 3 months
Nutrients 3 months
Priority substances monthly
Substances discharged in significant quantities 3 months
Monitoring frequency in TCW
For Portugal, MONAE proposed higher frequencies.
Annual monitoring costs
Portugal has spent much more, to little effect.
PPP€ measures the number of units of a country’s currency required to buy the same amount of goods and
services (in the domestic market) that the euro would buy in Europe. PPP€ has the same purchasing power
in the domestic economy as €1 has in Europe.
Costs over an 18 year period (3 RBMPs)
The overall net present costs for an 18 year period, discounted at Portugal’s long-term
interest rate of 4.2% would indicatively be €7,000,000 at 2004 PPP€ prices, assuming
operational and investigative monitoring is also carried out only for one year in every six;
The total cost of monitoring over an eighteen year cycle (three river basin management
plans) would be under 1€ per capita for the current (ten million) population of Portugal.
WFD Classification of rivers and lakes (EEA 2015)
Percentage of freshwater bodies affected by pressures.
WFD Classification of T&C waters (EEA 2015)
Percentage of T&C bodies affected by pressures.
European Environment Agency verdict 2017“The main aim of EU water policy is to ensure that a sufficient quantity of good quality water is
available for people’s needs and the environment. The Water Framework Directive (EU, 2000)
stipulates that EU Member States should aim to achieve good status in all bodies of surface
water and groundwater by 2015 unless there are grounds for exemption. The 7th EAP mirrored
this objective and called for all European water bodies to reach ‘good’ status by 2020.”
https://www.eea.europa.eu/airs/2016/natural-capital/surface-waters
Directive 2008/56/EC
Marine Strategy Framework Directive
The WFD and MSFD are two very different directives.
Marine waters: from the seaward side of the baseline from which territorial waters
are measured to the outmost reach of MS jurisdiction (1-3.1);
Preparation: (i) Status and impact assessment (2012); (ii) Good status classification
(2012), (iii) Environmental targets and indicators (2012); Monitoring programme
(2014). Measures: (i) Programme of measures (2015); (ii) Implementation of plan
(2016). Good status by 2020 (1-1.1, but see 29)
Ecosystem-based approach to management of human activities, enabling a
sustainable use of ecosystem goods and services (8, 1-1.3);
Exceptions: natural causes/force majeure (e.g. HAB Western Iberia) and
transboundary problems (Baltic, southern North Sea...) (30, 31);
No explicit typology like WFD, but MS should define Good threshold by marine
regions/subregions. Only two classes (Environmental Status), not five (WFD
Ecological Status) (13, 1-5, 1-6, 1-9.3);
Eleven holistic descriptors, based on functional principles such as biodiversity, food
webs, and eutrophication.
Marine Strategy Framework Directive
(2008/56/EC)
Ten descriptors have detailed guidance reports.
The MSFD is a complex legislative instrument
Criteria and methodological standards to be used by the Member States, which are designed to amend non-essential elements of this Directive by supplementing it, shall be laid down, on the basis of Annexes I and III
EC commissioned ICES/JRC to facilitate this procedure
Task Groups were set up for eight GES descriptors, work took place over 2009, with a final meeting in September 2009
The aim was to develop common understanding of GES, and how it should be quantified
The aim was not to prescribe boundaries between good and bad
Human-induced eutrophication is minimised, especially adverse effects
thereof, such as losses in biodiversity, ecosystem degradation, harmful
algae blooms and oxygen deficiency in bottom waters.
ETG (Task Group 5)
MSFD - eleven descriptors of state
• Biological diversity
• Non-indigenous species
• Populations of commercial fish and shellfish
• Marine food webs
• Eutrophication
• Sea floor integrity
• Alteration of hydrographic conditions
• Contaminants
• Contaminants in marine food
• Marine litter
• Energy and noise
Develop common understanding of GES, and how it should be
quantified. Not prescribe boundaries between good and bad.
Dissecting Annex I
Models can help, but only to an extent.
Loch Creran, Scotland Ria Formosa, PortugalDungarvan Harbour, Ireland
Definition Potential tools
Biological diversity is maintained WISE
Population distribution = healthy stock ERSEM, EcoWin
Balanced marine food webs Atlantis, EcoPath
Human-induced eutrophication ASSETS, EcoWin
FARM
Contrasting spatial scales
The difference in scale is enormous (200 nm to 1 nm). The ocean is 3D.
WFD MSFD
Fringing
coastline (1nm)
Open water
Watershed
Spatial Scope – Maritime boundaries (JRC)
Portugal has the largest MSFD zone in the EU.
MyOcean – A European site
Salinity, temperature, currents, chlorophyll…
Eutrophication Descriptor Group Tasks
• Interpretation (key terms, links, policy)
• Literature review and methods
• Spatial and temporal scales
• Framework for Environmental Status
• Monitoring for assessment of GES
• Research needs
Ten of the descriptors were analysed using this approach,
which then led to a COM decision.
MSFD eutrophication guidance Effective guidance must be inclusive
Topic Comments
Oceanography Shallow/ deep water, high/low tidal range, big differences in
residence time, vertical mixing, seasonal runoff, and fetch
Temporal growth
patterns
Strongly seasonal in northern Europe; all year round in southern
Europe
Spatial variation Baltic and southern North Sea, eutrophication is a significant
concern; Mediterranean, parts are eutrophic at the WFD scale, but
at the MSFD scale the Mediterranean is oligotrophic
Symptoms vary Well beyond freshwater eutrophication criteria; SAV in shallow
water, offshore HAB
Methods Convention driven: OSPAR COMPP (N. Sea, NE Atlantic),
HELCOM HEAT (Baltic); Barcelona and Black Sea (?), national
methods, e.g. IFREMER, TRIX; non-EU, e.g. U.S. ASSETS model
Transboundary EEZ borders drive harmonization of criteria and methods; scale of
the issue varies greatly (no significant neighbours, EU neighbours,
EU and other countries)
From Poland to Portugal, something for everyone…
What is ‘Good Environmental Status’?
GES is achieved when the biological community
remains well-balanced and retains all necessary
functions in the absence of undesirable
disturbance associated with eutrophication, and/or
where there are no nutrient-related impacts on
sustainable use of ecosystem goods and services.
Upscaling Quality Descriptors
Combining descriptors into one final classification – a real challenge.
Quality
descriptors1 2 3 … n-1 n
Not good
Good
Broad class
range
Overall MSFD
status
Relationships – Handle with care
Dependence of global warming on piracy.
Bathers Non-bathers
Diseased 33 15
Healthy 27 25
Total 60 40
Probability Bathers Non-bathers
Diseased 0.55 0.375
Healthy 0.45 0.625
Total 1 1
No
swimming!
Water-borne diseases
Children Adults
Bathers Non- Bathers Non-
bathers bathers
Diseased 30 6 3 9
Healthy 20 4 7 21
Total 50 10 10 30
Probability Bathers Non- Bathers Non-
bathers bathers
Diseased 0.6 0.6 0.3 0.3
Healthy 0.4 0.4 0.7 0.7
Total 1 1 1 1
60 40
Water-borne diseases
The effect of bathing has disappeared!
Human impact on San Francisco Bay, U.S.A.
http://ian.umces.edu/neea/
Agricultural and urban nutrient loading in northern California.
Suisun
San Pablo
South Bay
S. Francisco Bay (South Bay) – Chlorophyll a
No decadal trends. More samples, higher maxima.
01
234
56
78
01
234
56
78
0
5
10
15
20
25
30
05
1015202530354045
1977 1978 1979
1980
0
10
20
30
40
50
60
1982
02468
1012141618
1984
05
101520
2530
3540
1985
0
2
4
6
8
10
12
14
1987
0
10
20
30
40
50
60
1989
05
101520
2530
3540
0 100 200 300 400
1996
0
20
40
60
80
100
120
0 100 200 300 400
1998
0
5
10
15
20
25
0 100 200 300 400
1999
#3
0 -
Red
wo
od
Cre
ek, 3
7o3
3.3
’N, 1
22
o11.4
’W, z
= 1
2.8
m
Max: 6.9
Max: 6.9 Max: 27.7
Max: 38.1 Max: 50.6 Max: 16.2
Max: 36.6
Max: 34.2
Max: 12.3
Max: 21.3?
Max: 53.2
Max: 113.31990s
1980s
1970s
Chlorophyll maximum as a function of
number of samples
In South Bay, like everywhere else, the more you measure…
Station 30 - Redwood Creek, 37o33.3’N, 122o11.4’W, z= 12.8m
PredictedObserved
0
20
40
60
80
100
120
0 10 20 30 40 50Samples per year
Cchlo
rophyll
a(m
g l
-1)
y=-1.3+1.24x
r=0.6 (P>0.99)
Synthesis
• Activities are regulated by legal frameworks – monitoring
is no exception
• In Europe, in the area of water those frameworks are the
WFD (2000/60/EC) and MSFD (2008/56/EC)
• The baseline is given by surveillance monitoring,
compliance is verified by operational monitoring, and what
you don’t know is a subject for research
• The two directives differ in scale, scope, and synthesis
approaches – one out all out is highly debatable
• How (when, where, what) you sample changes the results
you get
Legal frameworks
Surface water monitoring is legally binding in Portugal. Do it.
http://mosam.org
Monitorização de Sistemas Ambientais
J. Gomes Ferreira
http://ecowin.org/
Universidade Nova de Lisboa
Case studies, preparation of monitoring plans
Lecture outline
1. Eutrophication as a case study
2. Different methods require different monitoring schemes
3. A detailed look at ASSETS
4. A review of the Portuguese situation
5. Monitoring plans worldwide
6. Presentation of results
Lecture 3
http://mosam.org
The Eutrophication Process
富营养化发生的过程
http://www.eutro.us http://www.eutro.org/register
From: Bricker et al.2007. National Estuarine Eutrophication Assessment Update
This dense bloom of cyanobacteria (blue-green algae) occurred in the Potomac River estuary
downstream of Washington, D.C. Photo courtesy of W. Bennett USGS.
Elevated phytoplankton biomass
Harmful algal bloomsNoctiluca bloom– California, U.S.A.
Courtesy P.J.S. Franks, WHOI
In Florida Bay, this macroalgal bloom smothered seagrasses. SAV subsequently disappeared,
causing a loss of ecosystem goods and services. Courtesy Brian Lapointe, Harbor Branch
Oceanographic Institute.
Macroalgal blooms and loss of submerged aquatic vegetation
Florida bioluminescent HABs (Post 2014.10.27)
Nitrogen seepage from leaking septic tanks—developers oppose WWTP for cost reasons.
A model for harmful algal blooms from offshore
HAB development is highly complex and a serious challenge
to model. Monitoring is critical e.g. In shellfish waters.
Upwelling supplies a physical mechanism for
supporting larger cells (diatoms) and a chemical
mechanism for supply of nitrate from deep water
Upwelling relaxation stabilizes the water column (larger
cells sink, dinoflagellates outcompete them), and
dominant form of nitrogen is reduced (ammonia, urea)
There is considerable evidence that the increased supply of
reduced inorganic nitrogen (e.g. ammonia) and dissolved organic
nitrogen contribute to the development of harmful algal blooms
Secondary symptoms of eutrophication
Extension of hypoxic bottoms
0
10,000
20,000
30,000
40,000
50,000
Pristine Today
km
2
Six-fold increase!
2005
1905-06
Savchuk et al. 2008
Baltic Sea – dissolved oxygen
富营养化的次级症状——缺氧(波罗的海)
Indicators used by various assessment methodsIndicators (评价指标) Nutrient
Index I*
Nutrient
Index II*
EPA
NCA
OSPAR
COMPP
ASSETS
Nutrient (N,P) load, conc. X X X X X
Chemical oxygen demand X X
Chlorophyll a X X X X
Dissolved oxygen X X X X X
Water clarity X
HABs (nuisance/toxic) X X
Phytoplankton indicator sp. X
Macroalgal abundance X X
Seagrass loss X X
Zoobenthos-fish kills X
Temporal focus Unspecified Unspecified Summer Spring/winter Full year
Integration Additive Ratio Ratio Integration PSR
Methods with red crosses fall short of a full eutrophication assessment.
* Commonly applied in China
Adapted from: Xiao et al. 2007, Estuaries. and Coasts 30:901-918
MSFD guidance synthesisEutrophication assessment models
Method Biological
Indicators
Physico - Chemical
Indicators
Load related
to WQ
Integrated
final rating
TRIX Chlorophyll (Chl) DO, DIN, TP No Yes
EPA NCA
WQ Index
Chl Water clarity, DO, DIN, DIP No Yes
ASSETS Chl, macroalgae,
seagrass, HAB
DO Yes Yes
LWQI/TWQI Chl, macroalgae,
seagrass
DO, DIN, DIP No Yes
OSPAR COMPP Chl, macroalgae,
seagrass, PP indicator
spp.
DO, DIN, DIP, TP, TN, Yes Yes
UK “WFD” Primary production, Chl,
macroalgae, benthic
invertegrates, seagrass
Water clarity, DO, DIN, DIP,
TN, TPNo Yes
HEAT Chl, macroalgae, benthic
invertegrates, seagrass,
HAB
Water clarity, DO, DIN, DIP,
TN, TP, CNo Yes
IFREMER Chl, seagrass,
macrobenthos, HAB
Water clarity, DO, DIN, SRP,
TN, TP, sediment organic
matter, sediment TN, TP
No Yes
Some methods do not consider pressure-state relationships.
各种富营养化评价模型
Ferreira et al. 2011, Estuarine Coastal and Shelf Science, 93, 117-131.
Phase 1 Approach: Nutrient Indices
Nutrient Index I
Nutrient Index II
Ni =CCOD CTN CTP CChla
SCOD STN STP SChla+ + +
Ni =CCODCDINCDIP
SC
Where: CCOD, CTN, CTP, CChla are measured concentrations of chemical oxygen demand (COD), TN, TP
(all in mg l-1) and Chla (ug l-1)
SCOD, STN, STP, and SChla are standard concentrations of COD (3 mg l-1), TN (0.6 mg l-1), TP (0.03 mg l-1)
and Chla (10 ug l-1)
Ni > 4is eutrophic
Ni > 1is eutrophic
Where: CCOD, CDIN, CDIP are measured concentrations of chemical oxygen demand (COD), DIN, DIP (mg l-1)
SC is mean product of standard concentrations of COD (1-3 mg l-1), DIN (0.2 – 0.3 mg l-1), DIP (0.01 – 0.02 mg
l-1), constant value of 4.5 x10-3
From: Xiao et al. 2007, Estuaries. and Coasts 30:901-918
Phase 1 methods ignore key symptoms of eutrophication.
第一阶段评价方法:营养盐指标
ASSETS screening model
A second generation framework for eutrophication assessment.
Key aspects of the ASSETS approachThree stages...
S.B. Bricker, J.G. Ferreira, T. Simas, 2003. An integrated methodology for
assessment of estuarine trophic status. Ecol. Modelling 169: 39-60.
The ASSETS approach may be divided
into three parts:
✓Division of coastal systems
into homogeneous areas
✓Evaluation of data completeness
and reliability
✓Application of indices
Tidal freshwater (<0.5 psu)
Mixing zone (0.5-25 psu)
Seawater zone (>25 psu)
Spatial and temporal quality of
datasets: completeness
Confidence in results:
sampling and analytical
reliability
Influencing Factors (IF) index
Eutrophic Condition (EC) index
Future Outlook (FO) index
Pressure
State
Response
ASSETS Influencing Factors (Pressure)
Bricker, S.B., Ferreira, J.G. & Simas, T. - An Integrated Methodology for
Assessment of Estuarine Trophic Status. Ecol. Modelling 169: 39-60.
Calculate mh, the expected nutrient concentration due to land based sources (i.e. no ocean sources);
Calculate mb, the expected background nutrient concentration due to the ocean (i.e. no land-based sources);
Calculate OHI as the ratio of mh/(mh+mb);
Equations are based on a simple Vollenweider approach, modified to account for
dispersive exchange:
o
eseab
s
smm
o
eoinh
s
ssmm
Anthropogenic inputs Ocean inputs
Estuary
Class Thresholds
Low 0 to <0.2
Moderate low 0.2 to <0.4
Moderate 0.4 to < 0.6
Moderate high 0.6 to < 0.8
High >0.8
ASSETS – Assessment of State
Combinatorial matrix for primary and secondary symptoms.
Eutrophic condition
MODERATE
Primary symptoms high
but problems with more
serious secondary
symptoms still not being
expressed
MODERATE HIGH
Primary symptoms high
and substantial
secondary symptoms
becoming more
expressed, indicating
potentially serious
problems
levels indicate serious
MODERATE
Level of expression of
eutrophic conditions is
substantial
conditionsin causing the conditions
LOW
Level of expression of
eutrophic conditions is
minimal
Low secondary
symptoms
Moderate secondary
symptomsHigh secondary
symptoms
0 0.3 0.6 1
Low
prim
ary
sym
pto
ms
Modera
te p
rim
ary
sym
pto
ms
Hig
h p
rim
ary
sym
pto
ms
0.3
0.6
1
MODERATE
Primary symptoms high
but problems with more
serious secondary
symptoms still not being
expressed
MODERATE HIGH
Primary symptoms high
and substantial
secondary symptoms
becoming more
expressed, indicating
potentially serious
problems
levels indicate serious
HIGH
High primary and
secondary symptom
eutrophication
problems
HIGH
High primary and
secondary symptom
eutrophication
problems
MODERATE
Level of expression of
eutrophic conditions is
substantial
HIGH
Substantial levels of
eutrophic conditions
occuring with secondary
symptoms indicating
serious problems
HIGH
Substantial levels of
eutrophic conditions
occuring
symptoms indicating
serious problems
MODERATE HIGH
High secondary
symptoms indicate
serious problems, but
low primary indicates
other factors may also
be involved in causing
MODERATE HIGH
High secondary
symptoms indicate
serious problems, but
low primary indicates
other factors may also
be involved in causing
conditionsin causing the conditions
LOW
Level of expression of
eutrophic conditions is
minimal
Low secondary
symptoms
Moderate secondary
symptomsHigh secondary
symptoms
0 0.3 0.6 1
Low
prim
ary
sym
pto
ms
Modera
te p
rim
ary
sym
pto
ms
Hig
h p
rim
ary
sym
pto
ms
0.3
0.6
1
factors may be involved factors may be involved
MODERATE LOW
Moderate secondary
symptoms indicate
substantial eutrophic
conditions, but low
primary indicates other
MODERATE LOW
Moderate secondary
symptoms indicate
substantial
conditions, but low
primary indicates other
MODERATE LOW
Primary symptoms
beginning to indicate
possible problems
but still very few
secondary symptoms
expressed
MODERATE LOW
Primary symptoms
beginning to indicate
possible problems
but still very few
secondary symptoms
expressed
ASSETS Future Outlook matrix
Takes into account susceptibility and planned management actions.
Susceptibili
ty
in causing the conditions
0 0.3 0.6 1
Hig
hM
od
era
teLow
0.3
0.6
1
in causing the conditions
0 0.3 0.6 1
0.3
0.6
1
Future nutrient pressures
Decrease No change Increase
ImproveHigh
Worsen High
WorsenLow
Worsen Low
No change
ImproveLow
ImproveLow
No change
No change
ASSETS Approach: Pressure - State - Response
Moderate
Moderate
Low
Low
Moderate
High
Moderate
Low
High
Moderate
High
Moderate
Low
Influencing Factors (IF)
Nutrient Pressures
Low Moderate High
Low
Modera
teH
igh
Su
sc
ep
tib
ilit
y
Moderate
Moderate
Low
Low
Moderate
High
Moderate
Moderate
Low
High
High
Moderate
High
Eutrophic Condition (EC)
Secondary Symptoms
Low Moderate HighLow
Modera
teH
igh
Pri
ma
ry S
ym
pto
ms Improve
High
Improve
Low
Improve
Low
No
Change
No
Change
No
Change
Worsen
Low
Worsen
Low
Worsen
High
Future Outlook (FO)
Future Nutrient Pressures
Decrease No Change Increase
Hig
hM
odera
teLow
Su
sc
ep
tib
ilit
y
Susceptibility
Nutrient pressure changes
population , management,
watershed use (particularly
agricultural)
Susceptibility
dilution & flushing
+
Nutrient Inputs
land based or
oceanic
Influencing Factors
Primary Symptoms
Chl and Macroalgae
Average of ratings
Secondary Symptoms
D.O., HABs, SAV
change
Worst case
IF + EC + FO = ASSETS
Full accounting of eutrophication symptoms, including time and space.
Adapted from: Bricker et al. 2003, Ecological Modelling, 169(1), 39-60
ASSETS scoring system for PSRGrade 5 4 3 2 1
Pressure (IF) Low Moderate low Moderate Moderate high HighState (EC) Low Moderate low Moderate Moderate high HighResponse (FO) Improve high Improve low No change Worsen low Worsen high
Metric Combination matrix Class
P
S
R
5 5 5 4 4 4
5 5 5 5 5 5
5 4 3 5 4 3
High
(5%)
P
S
R
5 5 5 5 5 5 5 4 4 4 4 4 3 3 3 3 3 3
5 5 4 4 4 4 4 5 5 4 4 4 5 5 5 4 4 4
2 1 5 4 3 2 1 2 1 5 4 3 5 4 3 5 4 3
Good
(19%)
P
SR
5 5 5 5 5 4 4 4 4 4 4 4 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 1 1
3 3 3 3 3 4 4 3 3 3 3 3 5 5 4 4 3 3 3 4 4 4 4 4 3 3 3 2 3 3
2 1 5 4 3 2 1 5 4 3 2 1 2 1 2 1 5 4 3 5 4 3 2 1 5 4 3 5 5 4
Moderate
(32%)
P
S
R
4 4 4 4 4 3 3 3 3 3 3 3 2 2 2 2 2 2 1 1 1 1 1
2 2 2 2 2 3 3 2 2 2 2 2 3 3 2 2 2 2 3 3 3 2 2
5 4 3 2 1 2 1 5 4 3 2 1 2 1 4 3 2 1 3 2 1 5 4
Poor
(24%)
P
S
R
3 3 3 3 3 2 2 2 2 2 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 2 2 2 1 1 1 1 1
5 4 3 2 1 5 4 3 2 1 3 2 1 5 4 3 2 1
Bad
(19%)
ASSETS
Tagus Estuary
http://eutro.org/
ASSETS – Strangford Lough, N. Ireland
High status system, classified as an SAC under UK law.
Indices
Influencing
Factors (IF)
ASSETS: 5
Eutrophic
Condition (EC)
ASSETS: 5
Future Outlook
(FO)
ASSETS: 4
Methods
Susceptibility
Nutrient inputs
Primary
Secondary
Future nutrient
pressures
Parameters Rating Expression
Dilution potential High Lowsusceptibility
Flushing potential Moderate
Low
Chlorophyll a Moderate
ModerateMacroalgae Problems
observed
Dissolved Oxygen No problems
Submerged Aquatic Losses Vegetation observed Low
Nuisance and Toxic NoBlooms
Future nutrient pressures decrease
Index
LOW
LOW
Improve Low
ASSETS: HIGH
ASSETS applicationUsed all over the world
Minimal data requirements, five languages, powerful analysis.
ASSETS multiple site comparisons
http://ian.umces.edu/neea http://www.eutro.us
The most recent assessment shows problems in the NEA and Gulf of Mexico.
ASSETS systems and gradesDistribution by region and classification
More information at http://eutro.org
Web-based ASSETS – Boston Harbor
eutro.org and eutro.us provide data on eutrophication of U.S. coastal systems.
ASSETS Pressure-State-Response
Influencing
Factors
Eutrophic
Condition
Future
Outlook ASSETS
Huang HeSanggou
Jiaozhou
Chiangjiang
Huangdun
Sanmen
Xiamen
DayaZhujiang
Worsen High
Worsen Low
No Change
Improve Low
Improve High
Unknown
Bad
Poor
Moderate
Good
High
Unknown or Not Applicable
High
Moderate High
Moderate
Moderate Low
Low or No Problem
Unknown
(WFD)
Top-down control
shellfish
aquaculture
贝类养殖的下行控制效应
压力 状态 反馈 ASSETS结果
ASSETS
Combination of research and screening models
Eutrophic
Condition (OEC)
ASSETS OEC: 4
Eutrophic
Condition (OEC)
ASSETS OEC: 4
Eutrophic
Condition (OEC)
ASSETS OEC:
Methods
PSM
SSM
PSM
SSM
PSM
SSM
Parameters Value Level of expression
Chlorophyll a 0.25
Epiphytes 0.50 0.57Macroalgae 0.96 Moderate
Dissolved Oxygen 0Submerged Aquatic 0.25 0.25Vegetation LowNuisance and Toxic 0Blooms
Chlorophyll a 0.25
Epiphytes 0.50 0.58Macroalgae 1.00 Moderate
Dissolved Oxygen 0Submerged Aquatic 0.25 0.25Vegetation LowNuisance and Toxic 0Blooms
Chlorophyll a 0.25
Epiphytes 0.50 0.42Macroalgae 0.50 Moderate
Dissolved Oxygen 0Submerged Aquatic 0.25 0.25Vegetation LowNuisance and Toxic 0Blooms
Index
MODERATE
LOW
MODERATE
LOW
MODERATE
LOW
28% lower
4(5)
Current monitoring status
In recent years, this situation has degraded, e.g. bivalve area classification.
At present, regular coastal
monitoring programmes are
carried out in Portugal for the
management of:
(i) Fisheries;
(ii) Biotoxins;
(iii) Priority substances;
(iv) Quality control of beaches;
(v) Hydro-morphology.
Institution Activities
IPMA TAC
Weekly fish-market “lota” sampling
2X year cruises pelagic/demersal, 90 samples
IPMA Weekly/fortnightly samples
between Minho & Guadiana estuaries.
Coastal water, estuaries and lagoons.
INAG Subcontracted to IH and IPIMAR,
heavy metals and organics
estuaries, lagoons and outfalls
Sampled twice-yearly
DRA/DRS Fortnightly, from 15 days before
the start of the bathing season
IH Hydromorphology, continuous tide
gauges, wave climate and water
temperature buoys
Stored data for Portuguese systems - BarcaWin
There are lots of data for Portuguese transitional and coastal systems.
Overview of system classification
Systems divided according to size.
Water bodies for Portuguese transitional
and coastal systems
More water bodies, lower quality, more sampling costs.
Questions a monitoring plan should address
The full DPSIR model is included in a monitoring plan.
Guidance for development of monitoring plans
WFD: Three different kinds of monitoring with different objectives.
Monitoring plans – Hypotheses and yardsticks
Any manager must ask questions, any plan must (aim to) answer them.
•Which questions should a specific monitoring plan address? An alternative
statement is: Which hypotheses should a plan test?
•Which is the most cost-effective approach to answering these questions? An
alternative statement is: Which Biological Quality Element(s) or Supporting
Quality Element(s) and approach (field sampling, experimental, modelling) is
best suited to understand the problem?
•What are the yardsticks of success in a monitoring plan? Two types: (i)
Implementation, i.e. are programme goals being met ? e.g. are the
designated parameters being measured? (ii) Effectiveness, i.e. does the plan
adequately identify whether the management measures are leading to
environmental success – e.g.: does the plan successfully identify whether
shellfish/finfish areas are increasing/decreasing?
Aims, indicators, indices and activities
Different publics, different approaches.
Aims
e.g. Establish
quality status
of waterbody
Indicators
e.g. Phytoplankton
composition, etc
Activities
e.g. Technical sampling program for Public participation in visual
chlorophyll a and species analysis or other types of sampling
Government, public
• Water Quality
• Conservation
• Human Use
Managers
• Biological Quality Elements
• Supporting Quality Elements
Indices
e.g. ASSETS,
AMBI, others
recommended in
TICOR etcTechnicians
• Biological Parameters
• Supporting Chemical
Parameters
• Hydromorphology
• Habitat
• …
Targets
Ag
gre
ga
tio
nD
eta
il
Objectives
Management objectives
Competing uses make for difficult compromises.
• Water quality objectives – e.g. (i) Restore and maintain a
productive ecosystem with no adverse effects due to
pollution; (ii) Minimize health risks associated with contact
water uses; (iii) Estimate adverse impacts of eutrophication;
• Conservation objectives – e.g. (i) Maintain on a landscape
level the natural environment of the watershed; (ii) Protect
existing habitat categories within the watershed - biodiversity;
• Human use objectives – e.g. (i) Support water-related
recreation and economic viability of commercial endeavours;
(ii) Encourage sustainable lifestyles within the watershed; (iii)
Empower citizens in the protection and stewardship of the
estuary and its watershed.
Targets which people understand and value
Sexy indicators help sell policy decisions.
• Tagus estuary – Restoration of the oyster
fishery (and export market) to the levels of the
1960’s
• Sado estuary – Conservation and
expansion of the bottlenose dolphin
population
• Guadiana estuary – Reappearance of
sturgeon
Primary and secondary indicators
Primary indicators appeal to the public and to managers.
Barnegat Bay (NJ) monitoring plan (abridged list)
Primary Indicators
(high-profile indicators)
Secondary Indicators
(internal indicators)
Submerged aquatic vegetation (SAV)
distribution, abundance, and health
Temperature and salinity
Land use/land cover change Dissolved oxygen and nutrients
Signature species Turbidity
Watershed integrity Phytoplankton ABC
Shellfish beds Shellfish & finfish abundance
Bathing beaches Macrophyte abundance
Freshwater inputs Benthic community structure
Water-supply wells/drinking water Xenobiotics in biota and sediments
Harmful Algal Blooms (HAB) Rare plant & animal populations
Monitoring - outputs and outcomes
Good outputs do not guarantee good outcomes, but it’s a start.
• Programme implementation (outputs). Verifiable targets related to the
plan terms of reference, i.e. are the goals and objectives of the plan
being met. Answers programmatic questions such as: (a) Is the
sampling covering the estuaries/coastal systems specified in the plan?
(b) Is the strategy defined for a particular system (e.g. sampling
according to a salinity gradient being followed?
• Programme effectiveness, i.e. environmental success (outcomes). A
distinct set of targets, based around specific ecological quality
achievements, must answer questions such as: (a) Are shellfish/finfish
areas increasing/decreasing? (b) Are salt marsh areas
increasing/decreasing? (c) How is the frequency/spatial scope of
elevated chlorophyll a evolving?
Tillamook Bay,
Oregon, USA
A small bay on the US NW
coast, about 10 X 3 km,
with depths of up to ~8 m.http://ocsdata.ncd.noaa.gov/BookletChart/18558
_BookletChart.pdf
Tillamook Bay monitoring plan - Outputs
Detail on parameters, time and space, methods, archiving, and cost.
Item Detail
Monitoring
Parameters
Terrestrial plants Sand/gravel, Green algae Mud/sand, Dense mixed algae Organic debris, Dense eelgrass Developed, Sparse eelgrass Water, Sparse mixed algae on dark substrates, Sparse mixed algae on light substrates
Stations The survey covers the extent of Tillamook Bay.
Frequency Aerial surveys at least every five years.
Sample Collection Multispectral sensor imaging on aircraft. Four hours during extreme low tide, high
resolution (~1 meter) images. Three spectral bands mimic bands 1 (blue), 3(red), and 4
(infrared) of Landsat TM. More than 300 separate frames collected and georeferenced.
Color photographs at the same time to improve the classification of digital files.
Guidelines or imaging specify images taken only at low tide, during maximum
delineation of submerged aquatic vegetation (SAV), periods of low turbidity and low or
no wind and clouds, sufficient identifiable land area to assure accurate plotting of beds.
Ground-truthing for eelgrass extent and distribution to correlate with imaging will occur
through the Eelgrass, Oyster, and Burrowing Shrimp Study and incidentally by other
agencies, organizations, and individuals (e.g., during fish or benthic studies, or other
research).
Data Management ArcInfo/ArcView GIS
Related Monitoring
Programs
Coordinate with Ecological Interactions Among Eelgrass, Oysters, and Burrowing Shrimp. Coordinate with Riparian Assessment. Coordinate with Tidal Wetlands Assessment. Benthic Invertebrate Inventory (Bay) Fish Use of the Estuary
Anticipated Cost $40,000/survey
Tillamook Bay monitoring plan - Outcomes
Ask the right questions, state verifiable management objectives.
Item Detail
Program Objective
(Core)
Track the abundance and distribution of eelgrass beds in Tillamook Bay.
Monitoring
Question(s)
Is the spatial extent of eelgrass beds in the estuary changing over time scales of years to
decades?
Are there changes in eelgrass density or other visual indicators of changes in eelgrass
health over time scales of years to decades?
Plan Objective No net decline in eelgrass beds (baseline = 363 hectares).
Program
Description
Eelgrass (Zostera spp.) meadows contribute to estuarine water quality and provide
habitat for many aquatic species, including salmonids. Eelgrass has also been identified
as Essential Fish Habitat. In 1995, the TBNEP used a prototype airborne imaging system
to collect multispectral data for Tillamook Bay at a 1-meter spatial resolution to:
(1) accurately map eelgrass beds throughout Tillamook Bay in order to establish an initial
baseline of eelgrass bed density and distribution and (2) identify a means of monitoring
the Bay environment in terms of cover and substrate that is both accurate and cost
effective.
Vegetation was assigned to one of six classes, and substrate was assigned to one of
four classes. During this survey, eelgrass beds were found to cover nearly 11% of the
area (approximately 363 hectares) of Tillamook Bay with the majority of the dense beds
in the northern half of the bay. Field surveys as part of the eelgrass monitoring project
and as part of related benthic surveys verified the accuracy of this assessment.
Tillamook Estuaries Partnership - Outcomes
PEM determines if actions result in improved conditions.
Displaying the resultsHow can we use GIS techniques?
Web has generated an abundance of online GIS.
• Choice of technology depends on
• Audience
• What we want to do
• GoogleEarth
• Good for general displays and for outreach
• Easy to produce high quality visualisations
• Large existing user base
• ArcGIS
• More sophisticated and powerful
• Expensive
• Has a range of web extensions
Combination of GIS and Google Earth
Oyster trestle mapping data draped on a satellite image.
Dungarvan Bay,
southern Ireland
Google Earth – simple image display
Progressive zoom on chorophyll in Sanggou Bay.
Courtesy – Plymouth Marine Laboratory Remote Sensing Group
Google Earth visualizations
Huangdun Bay land classification draped over topography.
Courtesy – Plymouth Marine Laboratory Remote Sensing Group
Google Earth visualizations
Huangdun Bay sampling stations and ID data in a relational database.
Courtesy – Plymouth Marine Laboratory Remote Sensing Group
Courtesy – PML
Remote Sensing
Group
Linking Google Earth to the SPEAR database in
situ ammonium sampling locations
Google Earth visualizations
Huangdun Bay chlorophyll time series linked to spatial data.
Courtesy – PML
Remote Sensing
Group
Linking Google Earth to the SPEAR database in
situ ammonium sampling locations
Courtesy – PML
Remote Sensing
Group
In situ sampling locations – dynamic link
to database
Google Earth visualizations
Free apps such as Google Earth can be used to enhance visualisation.
Courtesy – PML
Remote Sensing
Group
Linking Google Earth to the SPEAR in situ
chlorophyll-a sampling locations
Google Earth visualizations
Representation of chlorophyll a in Huangdun Bay, China.
Courtesy – PML
Remote Sensing
Group
Display of chlorophyll-a
Google Earth visualisations
Courtesy – PML
Remote Sensing
Group
Web-based GIS – Ria Formosa
Use of ManifoldTM for displaying and exploring monitoring data.
goodclam.org/GIS
GIS for aquaculture sites
Shellfish aquaculture mapped out in GIS – Long Island Sound.
Aquaculture Mapping Atlas - Connecticut
GIS for WFD transitional water bodies
Live website from the European Environment Agency (DISCOMAP).
Data per country compiled in the WISE project
SPEAR – Model for Huangdun Bay, China
Presentation of multiple data layers from monitoring and modelling.
Assembly of key data layers
• Water quality bay and boundaries
• Currents
• Bathymetry
• Hydrology
• Aquaculture practice
• Aquaculture mapping
• Land cover
• Meteorology
• 湾内和边界的水质• 水流• 高程图• 水文• 养殖活动• 养殖图• 地表植被• 气候
DISMAR server – Web GIS layout
Modelling and monitoring of chlorophyll in Ireland (Bantry Bay)
Layers
Overview,
zoom, pan,
scale,
Updates,
Notes (inc
legend) or
News (RSS
feed)
Viewer
Courtesy –
Plymouth Marine
Laboratory Remote
Sensing Group
DISMAR server – HAB in the Skagerrak
Modelling and monitoring of aquaculture and HAB interactions
Courtesy – PML
Remote Sensing
GroupSatellite chl-a (PML) Ferrybox chl-a and in situ
HAB measurements (NIVA)
Aquaculture locations (blue) Modelled surface current (red) and
flagellates (green): both met.no
Displaying monitoring data
Triangles are easy to visualise.
Adaptation of the Sediment Quality Triad
1 1
22
3 3
1
10
100Total coliforms
Macrobenthos Heavy metals
Cala do Norte
Upstream channel
Tagus estuary
Chapman et al., 1997. General guidelines for using the Sediment Quality
Triad. Marine Pollution Bulletin 54(6):368-372
Displaying monitoring data
An amoeba has a weird shape, suggesting undesirable conditions.
The Amoeba
Reference condition
(circle)
Seals
DO
Example of application: Wefering, F.M., Danielson, L.E., White, N.M., 2000. Using the
AMOEBA approach to measure progress toward ecosystem sustainability within a shellfish
restoration project in North Carolina. Ecological Modelling, 130 (1-3) 157-166.
SAVPCBs
Deviation from reference
(amoeba)
Tillamook Estuaries Partnership – Reporthttp://www.tbnep.org/
Report cards are widely used in the USA.
Connecting people and dataEyes over Puget Sound (Wa., USA)
Flagging unusual patterns with a colour scale.
http://www.ecy.wa.gov/programs/eap/mar_wat/eops/EOPS_2014_10_29.pdf
Synthesis
• Beware of misleading data, and drawing the wrong
conclusions
• The importance of choosing the right model
• Converting monitoring data into information – examples
for eutrophication assessment
• Outputs and outcomes – make sure you get your money’s
worth
• Presenting information. If you can’t do it effectively, you’ve
lost the battle
Case studies and monitoring plans
Monitoring is much more than measuring.
The Holy Grail
Information
Data
Knowledge
Wisdom
Expensive to acquire
Time
Days Years Decades Centuries
Expensive to process
Soci
etal
inve
stm
ent
Mo
reLe
ssN
on
e
Consolidated experience
Rare and misunderstood
Somewhere between information and knowledge, things start to get useful.
top related