monitoring the environmental changes in europe · significant and measurable improvement in...

february 2007 METIER Graduate Course n°2 -

Information Management in

Environmental Sciences

1

Territories, Environment, Remote Sensing & Spatial Information Joint Research Unit Cemagref - CIRAD - ENGREF

Monitoring the Environmental Changes in Monitoring the Environmental Changes in

EuropeEurope

EEA data organisation towards spatial assessments

METIER METIER GraduateGraduate Training Course n°2 Training Course n°2 –– Montpellier Montpellier -- februaryfebruary 20072007

Information Management in Information Management in EnvironmentalEnvironmental SciencesSciences

february 2007 METIER Graduate Course n°2 - Information Management in Environmental Sciences 2

Monitoring the Environmental Changes in EuropeMonitoring the Environmental Changes in Europe European Environment

Agency

Presentation mapPresentation map

1. What is the EEA?2. European needs (policy effectiveness, economy, etc. ): from

questions to organisation3. Data architecture and infrastructures to meet different needs4. Spatial assessments: a Platform as superstructure to the EEA

data infrastructure

5. Examples of applications1. Land accounts

2. Ecosystem accounts

3. River fragmentation

4. Stratification of catchments data

6. Developments, research and Networking. Questions and clarifications: Debate



Agency

The EEA mandateThe EEA mandate

• Who are we? The EEA was set up as a legally independent Community body under EC Regulation 1210/90, adopted in May 1990 and revised in 1999. The Agency started working in Copenhagen in 1994.

• Mandate: To deliver timely, targeted, relevant and reliable information for environmental policy-making and for the assessment of environmental achievements and outcomes.

• Purpose: To support sustainable development and to help achieve significant and measurable improvement in Europe’s environment.

• Means: To build indicators, assessments and data flows to organise information and produce knowledge. To this end, the EEA is the European node of EIONET (European Information and Observation NETwork)

• Means of information: www.eea.europa.eu opens to reports, data, links

1



Agency

EEA assessments and reporting are EEA assessments and reporting are

based on the DPSIR modelbased on the DPSIR model

• They follow the MDIAK steps:– Monitoring

– Data

– Information

– Assessment

– Knowledge

• And are based on:– Exploiting literature,

– Carrying out its own assessments from data, raising methodological

and policy relevance issues

1

DRIVERS PRESSURES STATE IMPACTS RESPONSES

Economic

activities

Impacts on the

economy

Demographic

and social

drivers

Impacts on the

population

Natural driversImpacts on the

ecosystem

Synthesis

environmental

indicators

Warning

Abstraction of

resources,

Land use,

Emissions,

Generation of

waste

Quantity,

Structure,

Quality,

Functionning

Protection,

Control,

Economic

instruments,

Participation

Protection,

restoration

Prevention,

abatement

Economic

instruments

Participation

Sustainability

assessment

Key pressure

indicators

Compensation of

damage



Agency

Europe’s needs are to manageEurope’s needs are to manage

� The cost of environmental protection � the “burden” issue

� The Environmental performance of the economy � the “decoupling” issue

� The cost of insufficient environmental protection � the “externalities” issue

� The Assessment of policies � the “effectiveness/efficiency” issue

� The conservation of comparative advantages � the “natural capital” issue

2



Agency

European needs can be satisfied if…European needs can be satisfied if…

� Relevant information is available (relationships economy / environment, etc.),

� Information is comprehensive (areas adequately covered),

� Projections can be done accurately (scenarios, forecasts),

� Reporting is made through adequate frameworks (Environmental accounts, etc.)

� Making cooperation between different institutions more effective: structuring this cooperation is prerequisite.

2



Agency

The European cooperation for the The European cooperation for the

environment environment

� Relevant information is available (relationships economy / environment, etc.),

� Information is comprehensive (areas adequately covered),

� Projections can be done accuratelly (scenarios, forecasts),

� Reporting is made through adequate frameworks (Environmental accounts, etc.)

� Making cooperation between different institutions more important: structuring this cooperation is prerequisite.

2



Agency

The European cooperation for The European cooperation for

environmental monitoring…environmental monitoring…

2

Intern.Conv.

M SPublic

EEA

COM

Member StatesData

Information Users

UsefulInformation

Compliance

checking

Policy

Effectiveness

SoE

Trends An.

Purposes for reporting

Drivers for data collection

Data

treatment

and

aggregation

Data treatment

and aggregation



Agency

The Data Centre conceptThe Data Centre concept

• The main institutions: DG Environment, DG Estat, DG JRC and the EEA (‘Go4’) contribute, each in its domain, to the building of environmental assessment towards sustainable development,

• Sharing data and data processes is the logical next step,

• The Go4 decided to develop ‘Data centres’ at the EU level to avoid duplication of efforts, as components of the Shared European Environmental Information System (SEEIS):

– Water, air, CC, biodiversity, land use are EEA responsibility,

– Soil, Forests, Chemicals are JRC responsibility

– .. Is Estat responsibility

2



Agency

TheThe Data Centre concept as Data Centre concept as strategicstrategic

component SEIScomponent SEIS

• Data Centres deal with dynamic information, and builds upon Spatial Data Information (SDI) and aims at using Reportnet to populate all topics,

• SDI is the infrastructure of baseline information on supports, driven under Inspire,

• The assessments are carried out through spatial platform, (nicknamed ‘SPAICE’) that uses infrastructure, dynamic data and assessment tools.

2



Agency

Infrastructure to meet needsInfrastructure to meet needs

� For example, land coverage structures the relationships between ecosystems and human activities, which is assessed, inter alia, by CORINE Land cover,

� It poses the question of different data sets and resolution scales, that in turn drive the infrastructure

Land UseEcosystems Health….

3



Agency3Some data sets Some data sets

typestypes……

“Image 2000” Corine LC

LC Changes

Parcellisation Stratification

Connectivity Natura 2000

MonitoringStatistics

Emission /surplus

Land accountsCORRESPONDANCE BETWEEN LAND COVER CHANGES (CLC LEVEL 3) AND THE LAND COVER FLOWS

132 133 141 142 211 212 213 221 222 223

Dump sites Construction

sites

Green urban

areas

Sport and

leisure

facilities

Non-irrigated

arable land

Permanently

irrigated land Rice fields Vineyards

Fruit trees

and berry

plantations

Olive groves

243 Land principally occupied by

agriculture w ith significant areas

of natural vegetation

Extension of

dumpsitesConstruction

Development of

green urban

areas

Extension of

sport and

leisure f acilities

Intensive

conversion of

marginal land to

agriculture

Intensive

conversion of

marginal land to

agriculture

Intensive

conversion of

marginal land to

agriculture

Intensive

conversion of

marginal land to

agriculture

Intensive

conversion of

marginal land to

agriculture

Intensive

conversion of

marginal land to

agriculture

244 Agro-forestry areasExtension of


Development of

green urban

areas

Extension of

sport and

leisure f acilities

Intensification

of agriculture

Intensif ication

of agriculture

Intensif ication

of agriculture

Planting of

vineyards, fruit

and olive trees

over arable &

pasture

Planting of

vineyards, fruit

and olive trees

over arable &

pasture

Planting of

vineyards, fruit

and olive trees

over arable &

pasture

311 Broad-leaved forestExtension of


Development of

green urban

areas

Extension of

sport and

leisure f acilities

Intensive

conversion of

forest to

agriculture

Intensive

conversion of

forest to

agriculture

Intensive

conversion of

forest to

agriculture

Intensive

conversion of

forest to

agriculture

Intensive

conversion of

f orest to

agriculture

Intensive

conversion of

f orest to

agriculture

312 Coniferous forestExtension of


Development of

green urban

areas

Extension of

sport and

leisure f acilities

Intensive

conversion of

forest to

agriculture

Intensive

conversion of

forest to

agriculture

Intensive

conversion of

forest to

agriculture

Intensive

conversion of

forest to

agriculture

Intensive

conversion of

f orest to

agriculture

Intensive

conversion of

f orest to

agriculture

313 Mixed forestExtension of


Development of

green urban

areas

Extension of

sport and

leisure f acilities

Intensive

conversion of

forest to

agriculture

Intensive

conversion of

forest to

agriculture

Intensive

conversion of

forest to

agriculture

Intensive

conversion of

forest to

agriculture

Intensive

conversion of

f orest to

agriculture

Intensive

conversion of

f orest to

agriculture

321 Natural grasslandExtension of


Development of

green urban

areas

Extension of

sport and

leisure f acilities

Intensive

conversion of

marginal land to

agriculture

Intensive

conversion of

marginal land to

agriculture

Intensive

conversion of

marginal land to

agriculture

Intensive

conversion of

marginal land to

agriculture

Intensive

conversion of

marginal land to

agriculture

Intensive

conversion of

marginal land to

agriculture

322 Moors and heathlandExtension of


Development of

green urban

areas

Extension of

sport and

leisure f acilities

Intensive

conversion of

marginal land to

agriculture

Intensive

conversion of

marginal land to

agriculture

Intensive

conversion of

marginal land to

agriculture

Intensive

conversion of

marginal land to

agriculture

Intensive

conversion of

marginal land to

agriculture

Intensive

conversion of

marginal land to

agriculture

Infrastructures

Apportionment

4

3

1

2



Agency

…and other…and other

Monitoring

Corine LChabitats

Natura 2000

Meteo data

Pedology

Climate /soil

Functional SMAquifers

Emission /surplusGW in

hydrosystem

Ecosystem account

CORRESPONDANCE BETWEEN LAND COVER CHANGES (CLC LEVEL 3) AND THE LAND COVER FLOWS

132 133 141 142 211 212 213 221 222 223

Dump sites Construction

sites

Green urban

areas

Sport and

leisure

facilities

Non-irrigated

arable land

Permanently

irrigated land Rice fields Vineyards

Fruit trees

and berry

plantations

Olive groves

243 Land principally occupied by

agriculture w ith significant areas

of natural vegetation

Extension of


Development of

green urban

areas

Extension of

sport and

leisure f acilities

Intensive

conversion of

marginal land to

agriculture

Intensive

conversion of

marginal land to

agriculture

Intensive

conversion of

marginal land to

agriculture

Intensive

conversion of

marginal land to

agriculture

Intensive

conversion of

marginal land to

agriculture

Intensive

conversion of

marginal land to

agriculture

244 Agro-forestry areasExtension of


Development of

green urban

areas

Extension of

sport and

leisure f acilities

Intensification

of agriculture

Intensif ication

of agriculture

Intensif ication

of agriculture

Planting of

vineyards, fruit

and olive trees

over arable &

pasture

Planting of

vineyards, fruit

and olive trees

over arable &

pasture

Planting of

vineyards, fruit

and olive trees

over arable &

pasture

311 Broad-leaved forestExtension of


Development of

green urban

areas

Extension of

sport and

leisure f acilities

Intensive

conversion of

forest to

agriculture

Intensive

conversion of

forest to

agriculture

Intensive

conversion of

forest to

agriculture

Intensive

conversion of

forest to

agriculture

Intensive

conversion of

f orest to

agriculture

Intensive

conversion of

f orest to

agriculture

312 Coniferous forestExtension of


Development of

green urban

areas

Extension of

sport and

leisure f acilities

Intensive

conversion of

forest to

agriculture

Intensive

conversion of

forest to

agriculture

Intensive

conversion of

forest to

agriculture

Intensive

conversion of

forest to

agriculture

Intensive

conversion of

f orest to

agriculture

Intensive

conversion of

f orest to

agriculture

313 Mixed forestExtension of


Development of

green urban

areas

Extension of

sport and

leisure f acilities

Intensive

conversion of

forest to

agriculture

Intensive

conversion of

forest to

agriculture

Intensive

conversion of

forest to

agriculture

Intensive

conversion of

forest to

agriculture

Intensive

conversion of

f orest to

agriculture

Intensive

conversion of

f orest to

agriculture

321 Natural grasslandExtension of


Development of

green urban

areas

Extension of

sport and

leisure f acilities

Intensive

conversion of

marginal land to

agriculture

Intensive

conversion of

marginal land to

agriculture

Intensive

conversion of

marginal land to

agriculture

Intensive

conversion of

marginal land to

agriculture

Intensive

conversion of

marginal land to

agriculture

Intensive

conversion of

marginal land to

agriculture

322 Moors and heathlandExtension of


Development of

green urban

areas

Extension of

sport and

leisure f acilities

Intensive

conversion of

marginal land to

agriculture

Intensive

conversion of

marginal land to

agriculture

Intensive

conversion of

marginal land to

agriculture

Intensive

conversion of

marginal land to

agriculture

Intensive

conversion of

marginal land to

agriculture

Intensive

conversion of

marginal land to

agriculture

InfrastructuresSediment budget

7

6

5

3

Data sets are the pieces structured

by the architecture, their use

(sketched by the blocks) is done

through the ‘spatial platform’ that

handles data, models and

assessments.



Agency

SPAICE designed primarily around SPAICE designed primarily around

land, biodiversity and waterland, biodiversity and water

Water

Quality

Pesticides

to rivers

Intensive

agriculture

Wetland

drainage

Forest

manage

ment

Eutrophi

cationSpecies

dynamics

Frameworks for

monitoring & data

collection

Environmental

Accounts

Geographical

Information

System

DPSIR

Data

Integration &

Modelling

Analytical &

Predictive

Modelling

Assessment of Policy

Effectiveness/

Efficiency

Regular Reporting on

State & Trends

Indicators

Eco-Environmental

Performance

AssessmentCosts/ benefits

Analysis of projects

WEB-based Data

Dissemination to the

Public

Cost of

environmental

damages and risks

GIS Analysis

at the various

scales

SPAICE* is understood as a base for data assimilation,

integration and modelling for policy making

and a knowledge-

making system that can grow

4

Spatial Platform for Assessing and Integrating Components of the Environment



Agency

The structure of SPAICEThe structure of SPAICE

• GIS (administrative,

hydrosystems, land cover, natural areas, …)

• Assimilation tools (harmonise statistics, monitoring, and produce aggregates)

• Assimilated data (for further uses, dissemination and modelling)

4



Agency

Current development of SPAICECurrent development of SPAICE• GIS (semi-static)

– Rivers and catchments: CCM (delayed), wetlands, TéléAtlas®, new version based on national data sets and CCM. Key issues are geometrical accuracy (to snap objects), connectivity and routing (to model phenomena) and comprehensive coverage (to encompass whole Europe).

– Administrative & transport: TéléAtlas®, GISCO– LandCover: CORINE land cover

– Aquifers, soils, bedrock (not yet available, on going, …)– …

• Assimilated data (rather dynamic)– Land Cover changes),– Dams (Eldred2 data base)– WaterBase (aggregated), volunteer countries (raw data),– Population (raster), emissions (EPER, …), agricultural balances (models, statistics)– WFD reported data,– Rainfall patterns and climatic data (from reanalysed data, under discussion),– …

• Assimilation tools– NOPOLU for river quantity, quality, fluxes, agri-surplus, water accounts, stratification of layers

(catchment ready, on going),– LEAC data system…

For the time being, data is partly populated and the assimilation tool only partly implemented.

The volume of information is very large, its comprehensiveness poor and the harmonisation rather difficult.

4



Agency

Land Land covercover accountsaccounts. . Background and Background and

OverviewOverview

• There is a growing demand for

spatially explicit indicators for to support policies for

– nature,

– regional development,

– agriculture,

– transport,

– coastal management …

5.1

Source: Source: JeanJean--Louis Weber, EEA, Louis Weber, EEA,

[email protected]@eea.europa.eu



Agency

Background and OverviewBackground and Overview

• Supported by Eurostat (= DG Estat), the EEA has carried out the feasibility study of land cover accounts, in the continuation of the pioneer work at UNECE in the 1990’s and part of the development of the SEEA 2003. Using the two Corine land cover data sets, the EEA has published a first set of accounts 1990-2000 for 24 countries.

• EEA has demonstrated that at European scales land accounts can be constructed in ways that are:

– Conceptually robust

– Capable of being maintained ‘operationally’; and

– ‘Fit for purpose’, in both the scientific and policy arenas

• The work also provides an important platform for future developments in relation to:

– The construction of integrated ecosystem accounts

– Making sustainability impact assessments

– Modelling and scenario development

– Support to almost all other development on spatial assessment

5.1



Agency

Accounting conceptual model applied to Accounting conceptual model applied to

land accounts land accounts

Do gains compensate for losses? Can gain

substitute to losses?

Loss of stocke.g. by deforestation

Gain in stocke.g. by afforestation

Has the quality of the stock been maintained?

5.1



Agency

Accounting for Stocks & FlowsAccounting for Stocks & Flows

Land cover changes matrix Land cover x land use matrix

ΣΣΣΣ ΣΣΣΣ

Land cover

(initial state)

ΣΣΣΣ

Land cover (final state)

ΣΣΣΣ

Land cover core account

Land use x activities matrix

economic

decisions

natural

causes

multiple

causes ΣΣΣΣ

La

nd

co

ver

Ac

tiv

itie

s/ s

ecto

rsΣΣΣΣ ΣΣΣΣ

Land cover flows

due to Final

state

Land cover (final state)

Land use functions

Land use functions

La

nd

co

ver

(i

nit

ial

sta

te)

La

nd

co

ver

flo

ws

Initial

state

Land use accounts and

Ecosystem accounts

Land use accounts and

Ecosystem accounts

Basic land cover stocks

and flows accounts

Basic land cover stocks

and flows accounts

5.1



Agency

Data infrastructuresData infrastructures

CORINE Land Cover 1990 and 2000CORINE Land Cover 1990 and 2000

Enables us to map stock and change…Enables us to map stock and change…

… and to construct stock and flow accounts

… and to construct stock and flow accounts

…and to report them using a range of

different geographical frameworks

…and to report them using a range of

different geographical frameworks

5.1



Agency

Data infrastructures… and flowData infrastructures… and flow

Smallest

mapping unit for

stock 25ha

Change mapped at 5ha

Smallest

mapping unit for

stock 25ha

Change mapped at 5ha

5.1



Agency

The approach used to generate The approach used to generate

the LEAC record for stockthe LEAC record for stock5.1



Agency

Stock and changeStock and change

A stock and change account for European land cover, 24 countries, 1990-2000A stock and change account for European land cover, 24 countries, 1990-2000

Hierarchical classification of land cover, 44 classes

at most detailed level

Hierarchical classification of land cover, 44 classes


Stocks 1990 & 2000, Formation and consumption of land cover, Net change and rates of Turnover

Stocks 1990 & 2000,

Formation and consumption of land cover, Net change and rates of Turnover

Corine land cover types 1 2A 2B 3A 3B 3C 4 5

Land cover flows

Art

ific

ial are

as

Ara

ble

lan

d &

perm

an

en

t cro

ps

Pastu

res &

mo

saic

s

Fo

reste

d lan

d

Sem

i-n

atu

ral

veg

eta

tio

n

Op

en

sp

aces/ b

are

so

ils

Wetl

an

ds

Wate

r b

od

ies

Total land cover 1990, km² 161860 1174325 820109 1030635 264932 52593 46915 45854 3597223

Total Consumption of 1990 land cover, km² 1843 24608 17607 39899 9018 2304 1413 381 97074

Total Formation of 2000 land cover, km² 10556 18144 15333 45343 4177 1858 383 1280 97074

Net Formation of Land Cover (formation-consumption) 8712 -6463 -2275 5444 -4842 -446 -1030 899

Net formation as % of initial year 5.4 -0.6 -0.3 0.5 -1.8 -0.8 -2.2 2.0

Total turnover of land cover (consumption+formation) 12399 42752 32940 85242 13195 4162 1796 1661 194148

Total turnover as % of initial year 7.7 3.6 4.0 8.3 5.0 7.9 3.8 3.6 5.4

No land cover change 160016 1149717 802502 990736 255914 50289 45502 45473 3500149

No land cover change as % of intial year 98.9 97.9 97.9 96.1 96.6 95.6 97.0 99.2 97.3


To

tal, k

m²

Corine land cover types12A2B 3A3B3C45

Art

ific

ial are

as

Ara

ble

lan

d &

p

erm

an

en

t cro

ps

Pastu

res &

m

osaic

sF

ore

ste

d lan

dS

em

i-n

atu

ral

veg

eta

tio

nO

pen

sp

aces/ b

are

so

ils

Wetl

an

ds

Wate

r b

od

ies

5.1



Agency

Summary indicatorsSummary indicators5.1



Agency

From changes to flowsFrom changes to flows

LCF3

LCF1

LCF2

LCF5

LCF4

LCF7

LCF6

LCF8

Change Matrix(44x43=1932

possible changes)summarized into

flows by aggregation

LCF9

Land cover flows

LCF1 Urban land management

LCF2 Urban residential sprawl

LCF3 Sprawl of economic sites and infrastructures

LCF4 Agriculture internal conversions

LCF5 Conversion from other land cover to agriculture

LCF6 Withdrawal of farming

LCF7 Forests creation and management

LCF8 Water bodies creation and management

LCF9 Changes due to natural & multiple causes

1990

20005.1



Agency

Flow accountsFlow accounts

A flow account describing processes of land cover change

in Europe, 24 countries, 1990-2000

A flow account describing processes of land cover change

in Europe, 24 countries, 1990-2000Corine land cover types 1 2A 2B 3A 3B 3C 4 5

Land cover flows

Art

ific

ial a

reas

Ara

ble

lan

d &

pe

rma

ne

nt

cro

ps

Pa

stu

res

&

mo

sa

ics

Fo

reste

d l

an

d

Se

mi-

na

tura

l

ve

geta

tio

n

Op

en

sp

ac

es

/ b

are

so

ils

We

tla

nd

s

Wa

ter

bo

die

s

LCF1 Urban land management 737 15 19 0 8 0 0 780

LCF2 Urban residential sprawl 1924 1867 200 145 8 3 2 4149

LCF3 Sprawl of economic sites and infrastructures 77 2728 1595 665 451 35 22 53 5627

LCF4 Agriculture internal conversions 17252 10062 27314

LCF5 Conversion from other land cover to agriculture 273 935 1796 1734 155 96 50 5039

LCF6 Withdrawal of farming 2393 2860 5253

LCF7 Forests creation and management 254 35803 5166 1048 1063 3 43337

LCF8 Water bodies creation and management 191 252 253 117 190 17 21 1042

LCF9 Changes due to natural & multiple causes 311 44 15 1317 1323 1041 229 252 4534

Total Consumption of 1990 land cover, km² 1843 24608 17607 39899 9018 2304 1413 381 97074

No Change 160016 1149717 802502 990736 255914 50289 45502 45473 3500149


LCF1 Urban land management 780 780

LCF2 Urban residential sprawl 4149 4149

LCF3 Sprawl of economic sites and infrastructures 5627 5627

LCF4 Agriculture internal conversions 15695 11619 27314

LCF5 Conversion from other land cover to agriculture 2450 2590 5039

LCF6 Withdrawal of farming 1124 2792 1244 23 70 0 5253

LCF7 Forests creation and management 42547 766 24 43337

LCF8 Water bodies creation and management 21 1021 1042

LCF9 Land Cover due to natural & multiple causes 4 2167 1790 313 260 4534

Total Formation of 2000 land cover, km² 10556 18144 15333 45343 4177 1858 383 1280 97074

No Change 160016 1149717 802502 990736 255914 50289 45502 45473 3500149


To

tal, k

m²

Hierarchical classification

of land cover, 44 classes


Hierarchical classification

of land cover, 44 classes


Hierarchical classification of flows ~the

processes of land cover change…

Hierarchical classification of flows ~the processes of land cover change…

5.1



Agency

Artificial land uptakeArtificial land uptake5.1



Agency

PlayingPlaying atat thethe ad hoc ad hoc scalescale

• The LEAC database is open to the public, but itsuse is not trivial.

• The database is stored at the ETC/LUSI web site

5.1



Agency

Comparison of artificial land uptake by countriesComparison of artificial land uptake by countries

5.1



Agency

Mapping flowsMapping flows

Patterns of urban sprawl

across Europe,

24 countries, 1990-2000, 1km x 1km grid

Patterns of urban sprawl

across Europe,

24 countries, 1990-2000,

1km x 1km grid

5.1



Agency

Mapping flows: urban sprawl, by gridMapping flows: urban sprawl, by grid5.1



Agency

Mapping flows: urban sprawl, by regionsMapping flows: urban sprawl, by regions

Intensity of urban

sprawl, 1990-2000, by NUTS 2/3 region;

sprawl is now expressed

on a unit area basis

Intensity of urban

sprawl, 1990-2000, by NUTS 2/3 region;

sprawl is now expressed

on a unit area basis

5.1



Agency

Main change in land use by agricultureMain change in land use by agriculture5.1



Agency

Extension of forest territory by creation or removal of farmingExtension of forest territory by creation or removal of farming5.1



Agency

Mapping & analysing flowsMapping & analysing flows

Data held on a standardised 1km x 1km Europe wide grid which

enables construction of a different

‘zonal accounts’ including those for:•Regions

•Biogeographical zones•Mountain areas

•Coastal zones

•Major sea basins •Dominant landscape types…

Data held on a standardised 1km x 1km Europe wide grid which

enables construction of a different

‘zonal accounts’ including those for:•Regions

•Biogeographical zones

•Mountain areas

•Coastal zones

•Major sea basins •Dominant landscape types…Sprawl of artificial areas 1990-2000 on Europen coasts,

by dominant land cover types, km²

0

100

200

300

400

500

600

700

800

900

North Sea

Mediterra

nean

Black Sea

Baltic

Atlantic

D1 - Composite landscape

C2 - Open semi-natural or

natural landscape

C1 - Forested landscape

B2 - Rural mosaic and

pasture landscape

B1 - Broad pattern

intensive agriculture

A2 - Dispersed urban

areas

A1 - Urban dense areas

Sprawl of artificial areas 1990-2000 on Europen coasts,

by dominant land cover types, km²

0

100

200

300

400

500

600

700

800

900

North Sea

Mediterra

nean

Black Sea

Baltic

Atlantic

D1 - Composite landscape

C2 - Open semi-natural or

natural landscape

C1 - Forested landscape

B2 - Rural mosaic and

pasture landscape

B1 - Broad pattern

intensive agriculture

A2 - Dispersed urban

areas

A1 - Urban dense areas

e.g

Dominant Landscape Types

5.1



Agency

Towards Ecosystem accountingTowards Ecosystem accounting

• Open questions– Can ecosystems be accounted?

– Accountable variables: habitats, ecosystem services, energy fluxes,

etc.

• Tentative assessments– Focus on threshold effects (resilience, see B. Walker paper)

– Key drivers of existence are geographical, geological, climatological

and edaphic factors that can be modelled through probabilistic

approaches…

– …and compared to species distribution in view to provide reference

population of habitats, ecosystem services, etc.

• Documentation available on CIRCA

5.2



Agency

River fragmentation by obstaclesRiver fragmentation by obstacles

• Continental waters are used for different activities: water supply, transport, energy production, through the building of dams, abstractions, etc.

• This resulted is fragmentation of river systems having consequences which must be accurately analysed at the European level.

• EEA took the initiative of developing the analysis of fragmentation as a component of the spatial assessment, collecting data and building calculation tools

5.3



Agency

Definitions of fragmenting devicesDefinitions of fragmenting devices

• Longitudinal: between a river and its annexes on the flood plain, situated along river banks (not addressed here), results from encroachments for example,

• Transversal: clips the water course and the catchments into more or less separated segments, is mainly the result of damming and water abstractions

• The definition of what makes an “obstacle“ is quite open and is contextual to the target to assess (difficulty to keep neutral approach and the level of aggregation where fragmentation matters positively or negatively and if the considered target exists or not).

5.3



Agency

Example of dams making or not Example of dams making or not

fragmentation of riverfragmentation of river

Dam Savarière on the Jaunay river (France): obstacle to fish, etc.

Dam new Emosson on the Barberine river (Switzerland / France): does not fragment vs. fish (cascade damming).

5.3



Agency

River fragmentation indicator issuesRiver fragmentation indicator issues

• Indicators are part of the SoE reporting (not addressed in the legislation)

• Three families of environmental targets:1. Hydrologic fragmentation

• Change in hydrological cycle (from hourly cycles to inter-annual terms)• Discontinuity in river flow (diversion, abstractions, etc.)

2. Sediment budgets fragmentation• Sediment trapping by damming• Dam clogging by sediments• Sediment movements impeded by bed modifications

3. Ecological fragmentation• Sea � river reproductive migrations• River � river / annexes reproductive & trophic migrations• River valleys as corridors

• Fragmentation is not the mirror of connectivity...!• Fragmentation is the counterpart of equipments made for beneficial

uses

5.3



Agency

Organisation of descriptors buildingOrganisation of descriptors building

• Building fragmentation indicators for the EEA requires:– Defining the message to be presented within the DPSIR framework (status

e.g.. km of.. , pressure e.g. km of ... / kW produced, etc.),

– Defining the descriptors required and their calculation procedure,– Building the data sets needed by the calculation of descriptors.

– Assessing consistency and uncertainty (incld. bias) of descriptors, in relation with data availability and modelling capabilities.

• State of the art– Large dams database (almost completed), non-large dams inclusion very

partial

– Rivers GIS (under development)– Calculation module (under development, presented)

– Ancillary data (to be collected)

– Indicators definition (still to be discussed).

5.3



Agency

Defining descriptors: fish issuesDefining descriptors: fish issues

• Long-distance migrators– Reach the target river areas in due time, sufficient number and

good condition from sea

– Spend life-cycle in river in good conditions,

– Reach back sea areas in (due time), sufficient number and good

condition

– Capacity of passing obstacles between 0 to 2 (3?) metres height.

• “Resident” fish– Having enough life space at their disposal, represented by length of

river open for circulating

– Limited capacity of passing obstacles

5.3



Agency

How to analyse fragmentation?How to analyse fragmentation?Salmo

1

2

3

4

5

5.3



Agency

Data issuesData issues

• Obstacles– Position,

– Characteristics (date commissioning, destruction, heights, fish passing equipments / facilities / possibilities, etc.)

– Linking dam to lake (and identifying natural lakes)

• River systems– River routes,

– Connectivity

– Geometrical accuracy (snapping obstacles)

• Fish data– Usual (define) routes & apportionment of migrators

– Capacities / requirements per species

– Other threats (predation, etc.)

– Is a “functional fish” acceptable interim solution?

5.3



Agency

Large dams: number and volumeLarge dams: number and volume

Cumulated volume reaches close to 400 billion m3, yielding an average 65 hm3 per large dam. 77 dams storing at least 1 billion m3 represent a total capacity of ~212 billions m3 (2.7 on the average), including the 42 billions m3 Atatürk dam.

Cumulated volume reaches close to 400 billion m3, yielding an average 65 hm3 per large dam. 77 dams storing at least 1 billion m3 represent a total capacity of ~212 billions m3 (2.7 on the average), including the 42 billions m3 Atatürk dam.

Problems to solve: 1. Correcting inaccuracies and Relating

to hydrosystems,2. Assessing what matters,3. Evaluating pros and cons in a

sustainable development perspective (water cycle & supply, sediment, ecology, energy and security).

4. Assessing if large dams are enough…

Problems to solve: 1. Correcting inaccuracies and Relating

to hydrosystems,2. Assessing what matters,3. Evaluating pros and cons in a

sustainable development perspective (water cycle & supply, sediment, ecology, energy and security).

4. Assessing if large dams are enough…

5.3



Agency

DesigningDesigning thethe correct dams correct dams databasedatabase

• Accurate identification– “large dams” provided by Icold…

– … but no positioning, history lost, few data on lake

• Organise dams and reservoir database– Derived from Eldred (1998),

– Manages input from Dampos and outputs to GoogleEarth

• Positioning dams is prerequisite to:– Local database management (Eldred2) and inserting proxy

coordinates,

– Web tool (Dampos [http://dampos-demo.eea.europa.eu]) for positioning vs. ground image, with the help of Icold specialist

5.3



Agency

This dam is not accurately located. Place

cursor where the position seems to be

and click...

Then confirm new point and, if necessary

complete comments and other data

New position is recorded and coordinates ready for collection by the DB

administrator.

Overview of any country is available also, it allows as well to reanalyse a dam by clicking on

its position

5.3



Agency

Can be displayed on public Can be displayed on public

GoggleEarth…GoggleEarth…Almost 4000 dams already positioned with variable accuracy among ~6600

The latest version of

Eldred2 allows collecting

position from GoggleEarth

file as well

5.3



Agency

Are large dams enough to carry out Are large dams enough to carry out

assessments?assessments?

• Currently ~7000 large dams in Europe,

• On the single Loire and Brittany district, ~10,700 dams recorded, most mattering vs. fish issues

• Main difficulty are:– Getting information (CEMAGREF does not exist in all European

countries…)

– Reformatting information and inserting into Eldred

5.3



Agency

Inserting dams in the HydrosytemInserting dams in the Hydrosytem

• Finding / building the reference system– Two river systems, to simplify:

• CCM2: geometrically incorrect (not all!), connected, poorly routed, homogeneous,

• ERC2 (on development): geometrically accurate, poorly connected,deeply routed, heterogeneous.

– On the way to blend both

– National systems more and more available, quality variable

• Matching dam, lake and river:– River inexistent or not in system,

– River geometry inaccurate

– Dam not on river (dam error)

Maulde river

5.3



Agency

Dam not on river?Dam not on river?• GIS does not

replace attribute analysis

• Not on river may be on canal or may be dyke. Example the Oraison dam (France)

5.3



Agency

Present or Present or

Inexistent Inexistent

reservoir?reservoir?

In both In both

cases cases

many many

sources sources

involvedinvolved

Icold + Dampos dam

Fr Bd-Carthage river

Image2000 © lake area

Corine Lc lake

TeleAtlas© lake area

Image2000 © lake area

Icold + Dampos dam

EU CCM2 river

5.3

Dam not inserted:

commissioned after

last Icold release…



Agency

River data processing: Analysis of the River data processing: Analysis of the

WFD specificationsWFD specifications

• Demands programme of measures:– to “prevent deterioration of the status” and achieve “good status...

at the latest 15 years”, and “bring the bodies of water progressivelyto the required status”,

– Following “coherent and comprehensive overview of water status”, and survey it

– Through identification of “significant | main” pressures and

– Assessment of status at the “water body type” level, minimizing the impact of seasonal variability ..... Reflect “...changes in the WB as a result of changes...” {pressures}

• All terms pose practical and theoretical questions about their accuracy and uncertainty– Some questions still under development

– Necessary compromise to use available data (subset of existing data)

5.3



Agency

Uncertainty in the data process. The Uncertainty in the data process. The

position of the EEAposition of the EEA

data Monitoring

Processing Assessing

data

Other factors

Decision

Other factors

MeasuresImplementing

5.3



Agency

Why Analysing trends?Why Analysing trends?

• Trend analysis contributes to responding to

WFD requirements

• Stratified statistics were carried out considering:– Catchments as statistical population, (comprehensive). Poses fundamental

question: what is the adequate catchment definition?

– Pressures through aggregates of land cover, population and livestock,

defining strata in the catchments population, (significant pressures, WB

types)

– Nitrate, phosphate and ammonium developments with time (progressively)

– On annual unbiased averages (...seasonal..)

• To compute time trends and year of target meeting (achieve... at the latest...)

5.3



Agency“Thickness of the line”

Data dispersion frame

Reporting Reporting

uncertaintiesuncertainties

Non compliant observations post target meeting

5.3



Agency

Sample resultsSample results–Intra strata variability,–Inter-years variability–Source data uncertainty–Stratum uncertainty–Orphan strata assessment–Increasing uncertainty with reduction in size–Stationarity, linearity?–Reporting choices

5.3



AgencyComparing Driving Forces and Comparing Driving Forces and

emissions (e.g., surplus vs. strata)emissions (e.g., surplus vs. strata)

DF, national

criteria and

thresholds

Stratification (with

respect to Agri. And

Urban drivers

Surplus calculation

results of agri. Stats, CL

cover and Ifen /EEA

model

3



Agency

Developments, research and Developments, research and

NetworkingNetworking

• SPAICE is just starting, and backs on developed methodologies / data sources. Next steps include completing hydrosystem issues and starting to build interrelationships with terrestrial habitats

– Fragmentation of terrestrial systems,– Relationships agriculture / ecosystems at large scales– Developing water accounting (quality, quantity), raising some theoretical questions about

quality assessment and trend analysis– etc.

• Major identified important adding are:– As data: Rainfall and climatic (on standard grid for example)– As layers:

• Aquifers (delineation, functional information, refilling areas, outlets, etc.), completing JRC work• Soil functions and characteristics• Geological background

– As assimilation tools: building the relationships with other data and layers

• EEA networking opens more and more to thematic and generic organisations, to enlarge the EIONET concept to expertise and science.

5



Agency

Thanks for your attention…Thanks for your attention…

Floor open to questions and Floor open to questions and

clarifications!clarifications!

• www.eea.europa.eu

• [email protected]



Agency

Trends in groundwater Nitrate concentrations: Nitrate

pollution of groundwater appears stable at the European level. However, when the data is broken down by country, 24 % (out of 142) individual groundwater bodies show decreasing nitrate concentrations while in 19 % concentrations are increasing.

But…

Example of indicator: Nitrate in GWExample of indicator: Nitrate in GW• Is the assessment representative?

• Is the assessment relevant?

• Is the phenomenon dynamics understood in the DPSIR? (is it related to policy effectiveness or to natural / uncontrolled conditions?)

• Are there possible relationships with other environmental issues? (e.g. river quality, wetlands, mass discharge to the sea, etc.)

E1



Agency

Example on Rivers: historical outcomesExample on Rivers: historical outcomes

• Lessons from the "Dobris" assessment lead to:– Addressing representativity issues,

– Considering the scope of classical methods,

– Finding appropriate responses, that do not cover all issues related

to reporting on rivers.

• This outcome could be quite general.

Is this representative?

Is this

comprehensive?

Is this

relevant ?

Despite accurate questioning, this

first work initiated a process of

revisiting traditional approaches

and lead to more comprehensive

addressing river issues through

relevant and representative

methodologies.

E2

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