Land Management and Natural Hazards Unit Guido Schmuck (Head of Unit)

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1 Land Management and Natural Hazards Unit 1 Land Management and Natural Hazards Unit Guido Schmuck (Head of Unit) land-management-and-natural-hazards-unit.html

2 Mission Land Management and Natural Hazards Unit 2 To support EU policies and programs linked to sustainable land management practices in the fields of forestry, soils and weatherdriven natural hazards with a particular focus on the development of environmental information systems The unit directly supports European policies in the fields of Environment and Sustainability, Forestry and Soils, Regional Development, and Civil Protection

3 Activities Land Management and Natural Hazards Unit 3 Forestry Establishment of the European Forest Data Centre - a single focal point for forest data and information for the Commission Customers: DG ENV*, DG AGRI**, DG REGIO***, DG ENTR****, EEA*****, Forest services in Member States Soil Establishment of the European Soil Data Centre - a single focal point for soil data and information for the Commission Customers: DG ENV, DG AGRI, EEA Desertification, Land Degradation and Droughts Development of tools for the implementation of policies and conventions related to drought and desertification in Europe and worldwide. Customers: DG ENV, DG DEV******, DG REGIO, DG AGRI, DG EuropAid Natural Hazards Development of a better capacity for early warning, monitoring and damage assessment systems for weather-driven natural hazards, as well as for tools for assessing climate change effects, land use change effects, risk mapping and adaptation to extreme events Customers: DG ENV, DG REGIO, DG ENTR, EEA, National hydrological and meteorological services *Environment, **Agriculture, ***Regional Policy, **** Enterprise and Industry, ***** European Environment Agency, ****** Development

4 Land Management and Natural Hazards Unit 4 Forestry International organisations: Ministerial Conference for the Protection of Forests in Europe (MCPFE) Food and Agriculture Organisation of the United Nations (FAO) United Nations Economic Commission for Europe (UNECE) International Co-operative Programme on Assessment and Monitoring of Air Pollution Effects on Forests (ICP Forests) United States Department of Agriculture - Forest Service (USDA-Forest Service) United States Environment Protection Agency (US-EPA) Research organisations: Over 50 research organisations (on e.g. forestry, forest fire modelling, remote sensing, information systems, socio-economic analysis, climate change, emissions)

5 Reference data Land Management and Natural Hazards Unit 5 European forest map Classes Masked Non-Forest Forest ±

6 Land Management and Natural Hazards Unit 6 Forest spatial pattern (changes in core forest ) Applications Impact of fires on forest connectivity (functional biodiversity) Emissions from Forest fires Forest and Climate Change

7 Management and coordination Land Management and Natural Hazards Unit 7 European Forest Inventory Network Member States National Forest Services Forest data from other sources (research projects, LIFE+ project, etc.) National Forest Fire and civil protection services JRC Data from related JRC actions (e.g. GHG- AFOLU) International Data Providers Food and Agriculture Organization (FAO) European Forest Data Centre (EFDAC) European Soil Data Center Ministerial Conference for the Protection of Forests in Europe (MCPFE) Ancillary data from other data centers (EEA, EUROSTAT) Data Centers Fire Danger forecast MODELS Image segmentation algorithms Forest fire emissions Burnt area mapping algorithms Forest spatial pattern analysis Forest growth models Climate change modelling European Forest Data Centre (EFDAC)

8 Land Management and Natural Hazards Unit 8 Soil International organisations: Food and Agriculture Organisation of the United Nations (FAO) United States Department of Agriculture Soil Conservation Service Australia's Commonwealth Scientific and Industrial Research Organisation (CSIRO) United Nations Environment Programme (UNEP) United Nations Convention on Biological Diversity (UNCBD) African Soil Science Society (ASSS) European Confederation of Soil Science Societies (ECSSS) European Environment Agency (EEA) European Society for Soil Conservation (ESSC) International Soil Reference and Information Centre (ISRIC) International Union of Soil Sciences (IUSS) International Soil Conservation Organisation (ISCO) Soil and Water Conservation Society (SWCS) Research organisations: Within Europe, collaboration with national soil survey organisations, leading universities and research institutes, soil science experts is carried out through the JRC s European Soil Bureau Network. Currently around 80 organisations are members of the foremost network of soil experts in Europe

9 Reference Data Land Management and Natural Hazards Unit 9 European soil map

10 Applications Land Management and Natural Hazards Unit 10 Soil Erosion Risk Soil Crusting Organic Carbon (%) No Data > 35 Wind Erosion Risk Topsoil Organic Carbon Content

11 Management and Coordination Land Management and Natural Hazards Unit 11 Member States National Soil Data Centers European Soil Bureau Network (ESBN) Soil data from other sources (research projects, etc.) Regional Soil Data Centers JRC Data from related JRC actions European Soil Data Centre (ESDAC) European Forest Data Center Data Centers EIONET EuroGeoSurveys Ancillary data from other data centers (EEA, EUROSTAT) Soil Erosion MODELS Greenhouse Gas Emissions Fertiliser Application Rates Urbanisation Microbial Activity Fertility Soil Water Retention European Soil Data Centre (ESDAC)

12 Land Management and Natural Hazards Unit 12 Natural Hazards International organisations: European Centre for Medium Range Weather Forecast (ECMWF) International River Basin Commissions (IKSO - Oder, IKSE - Elbe, IKSD/ICPDR - Danube) World Meteorological Organisation (WMO) Research organisations: Bristol University (UK) Bundesanstalt für Gewässerkunde (BfG, DE) Delft Hydraulics (NL) University of Utrecht (NL) University of Washington State, Seattle (USA)

13 Forecasting Land Management and Natural Hazards Unit 13 European Forest Fire Information System (EFFIS) European Drought Observatory (EDO) European Flood Alert System (EFAS) Platform for drought detection, monitoring, forecasting, and information exchange Commonly agreed products Multi-scale approach, integrating Subsidiarity principle

14 Risk Mapping Land Management and Natural Hazards Unit 14 FIRE RISK CLASSIFICATION Risk Class LOW MEDIUM HIGH NO FIRE DATA Forest Fires Risk = hazard * exposure * vulnerability Floods

15 Future risk under climate change conditions Land Management and Natural Hazards Unit 15 Research: Estimated change in potential flood damage of a 100-year flood for SRES* A2 scenario Underlying data/models: - 12 km A2 scenario DMI - LISFLOOD model setup - SRTM DEM** - CORINE*** landcover - damage curves countries * Special Report on Emissions Scenarios, ** Shuttle Radar Topography Mission Digital Elevation Database, *** Coordination of the Information on the Environment

16 Damage assessment Land Management and Natural Hazards Unit 16 Floods and industrial installations Forest Fires and NATURA 2000 sites

17 Land Management and Natural Hazards Unit 17 Desertification International organisations: United Nations Convention to Combat Desertification (UNCCD) United Nations Environment Programme/Division of Global Environment Facility Coordination (UNEP/GEF) United Nations University International Network on Water, Environment & Health (UNU- INWEH) Consultative Group on International Agricultural Research (CGIAR, ICARDA/ICRISAT Centres) Research organisations: DesertNet International (Network of Global Desertification Research Institutions, 283 members from 47 countries) Nucleo di Ricerca di Desertificazione (NRD) (Sassari, Italy) Estación Experimental de Zonas Aridas (CSIC) (Almeria, Spain) More than 30 universities and research centres in Europe, NW-Africa, Asia and S-America as partners in competitive research projects

18 Examples of basic input data Land Management and Natural Hazards Unit 18 Vegetation Cover Population & Trends (WRI) Land Surface Albedo Bio-physical & socio-economic datasets Global Land Cover Dominant Soil Types Cattle Densities (FAO)

19 Application Examples Land Management and Natural Hazards Unit 19 Increasing Likeliness Analysis of the Status and Trend of Degradation Indicators Example Rain Use Efficiency (RUE) Combining bio-physical and socio-economic models and data to analyse probabilities of land degradation (Syndrome Models) Example Rural Exodus Syndrome

20 Management and coordination Land Management and Natural Hazards Unit 20 Illegal Mining and Logging EU Africa Partnerships Land degradation and desertification Food Security Assessment and mapping Natural Risks Reduction Climate Change DLD-IS* Vulnerability Assessment Marine Resources & Fisheries Renewable Energies Biodiversity Protection Crisis Response & Humanitarian Aid Desertification, Land Degradation, Drought ONLINE PORTAL Benchmarks & Indicators Global Monitoring and Assessment UNCCD Data & Information * DLD-IS: Desertification, Land Degradation, and Drought Information System

21 Scientific Output Land Management and Natural Hazards Unit 21

22 Monitoraggio dei suoli in Europa e Metalli Pesanti Parma, 30 settembre 2008 Ciro Gardi, Luca Montanarella, Luis Rodríguez-Lado Sistemi informativi Analisi e Gestione del Territorio 1

23 La contaminazione dei suoli La mobilizzazione di inquinanti dalle loro riserve naturali e la successiva dispersione nell atmosfera, el suolo e nelle acque, costituisce uno dei principali impatti delle attivita antropiche sull ambiente. Gran parte dei suoli di vaste aree dei paesi industrializzati sono caratterizzati da contenuti di elementi e composti, considerati tossici, in concentrazioni notevolmente superiori a valori di fondo naturali. I metalli pesanti rappresentano una importante fonte di contaminazione dei suoli. In molti casi tuttavia, sopratutto in Europa, risulta difficile definire dei valori di fondo riferibili alla condizione originaria del suolo. 2

24 La Strategia Tematica per il Suolo Il suolo è praticamente una risorsa naturale non rinnovabile, e svolge funzioni cruciali per le attività umane e gli ecosistemi Proposta di direttiva quadro sul suolo (COM(2006)232 definitivo, ) La protezione del suolo e la conservazione delle sue capacità di svolgere una qualsiasi delle seguenti funzioni ambientali, economiche, sociali e culturali: produzione di biomassa, in particolare nei settori dell agricoltura e della silvicoltura; stoccaggio, filtrazione e trasformazione di nutrienti, sostanze e acqua; riserva di biodiversità, ad esempio habitat, specie e geni; ambiente fisico e culturale per le persone e le attività umane; fonte di materie prime; stoccaggio di carbonio; sede del patrimonio geologico e archeologico. 3

25 La proposta di Direttiva e la contaminazione del suolo Prevenzione della contaminazione Definizione di Sito Contaminato: un sito nel quale sia stata confermata la presenza di sostanze pericolose di origine antropica ad un livello tale che gli Stati membri ritengono possa comportare un rischio significativo per la salute umana o per l ambiente. Il rischio è valutato alla luce dell utilizzo attuale e dell utilizzo futuro approvato del terreno Inventario dei Siti Contaminati 4

26 Le concentrazioni di riferimento di metalli pesanti nei suoli Europei Geochemical baseline background value Attivita iniziata nel 1997 da 26 Stati Membri, con il coordinamento del FOREGS (Forum of European Geological Surveys) Il prodotto finale e costituito dall Atlante Geochimico d Europa 5

27 Elaborazioni sul Dataset FOREGS 1558 punti relativi a campioni di suolo Concentrazioni di As, Cd, Cr, Cu, Hg, Ni, Pb e Zn Estrazione con Acqua Regia (tranne mercurio) Analisi con ICP-AES (tranne mercurio) Utilizzazione di variabili ausiliarie nel processo di interpolazione 6

28 Carte distribuzione dei metalli pesanti 7

29 Perche la geostatistica? Consente di ottenere stime obiettive: della concentrazione dei metalli della incertezza associata Offre la possibilita di utilizzare un numero elevato di variabili ausiliarie (predittive) Consente di effettuare stime accurate delle concentrazioni di metalli pesanti nel suolo. Le procedure possono essere automatizzate (R scripts) 8

30 FOREGS soil database 9

31 Variabili obiettivo 8 metalli pesanti nel suolo: As, Cd, Cr, Cu, Hg, Ni, Pb, Zn 10

32 11 FOREGS soil database: Analisi esplorativa AS CD CR CU HG foregs$as foregs$cd foregs$cr foregs$cu foregs$hg NI foregs$ni PB foregs$pb ZN logas logcd logcr logcu loghg log(foregs$as) log(foregs$cd) log(foregs$cr) log(foregs$cu) log(foregs$hg) logni log(foregs$ni) logpb log(foregs$pb) foregs$zn logzn TAS TCD TCR TCU THG foregs$tas foregs$tcd foregs$tcr foregs$tcu foregs$thg TNI foregs$tni TPB foregs$tpb log(foregs$zn) TZN foregs$tzn

33 12 logas logcd logcr logcu loghg logni logpb FOREGS soil database: Analisi esplorativa log(foregs$as) log(foregs$cd) log(foregs$cr) log(foregs$cu) log(foregs$hg) log(foregs$ni) log(foregs$pb) logzn TAS TCD TCR TCU THG TNI TPB foregs$tas foregs$tcd foregs$tcr foregs$tcu foregs$thg foregs$tni foregs$tpb log(foregs$zn) TZN foregs$tzn TAS = ln(as stand /1-AS stand ) AS stand = (AS-AS min )/(AS max -AS min )

34 Principal Component Analysis PC1 PC TAS TCD TCR TCU THG TNI TPB TZN FOREGS soil database: Analisi esplorativa Principal Component Analysis PC1 PC AS CD CR CU HG NI PB ZN

35 Regression-kriging Regressione multipla lineare Y j 14 Y j = a 1 X 1 + a 2 X a n X n + ε j Variabile incognita j Kriging γ εj Semi-varianza Continue Dati ausiliari i Puntuali distanza (m) residui j (processo di interpolazione realizzato sulla base dell autocorrelazione tra le varibili) a i X i i Somma tra le due carte regressione Dati ausiliari kriging residui regressionkriging Variabili incognite

36 Variabili ausiliarie 15

37 PCA delle variabili ausiliarie Principal Component Analysis 16

38 PCA delle variabili ausiliarie Multiple Regression Analysis 17

39 Analisi della struttura spaziale: il semivariogramma 18

40 Risultati 19

41 Risultati: Pb 20

42 Confronto tra Kriging Ordinario e Regression Kriging 21

43 Risultati: Ni 22

44 Correlazioni Ni 3DPlot of Ni content over PC2, PC4 & PC14 23

45 Risultati: Cd 24

46 Concentrazione complessiva di metalli in Europa 25 (1) Liege (Arrondissement) (BE), Attiki (GR), Darlington (UK), Coventry (UK), Sunderland (UK), Kozani (GR), Grevena (GR), Hartlepool & Stockton (UK), Huy (BE), Aachen (DE) (As, Cd, Cu, Hg and Pb) (2) central Greece and Liguria region in Italy (Cr and Ni).

47 Stima dell errore 26

48 Disponibilita dei dati 27

49 Validazione Confronto tra Kriging Ordinario e Regression Kriging Abbastanza buono: Ni, Pb Medio: As, Cd, Hg Debole: Cr, Cu, Zn 28

50 Conclusioni FOREGS e un esempio di dataset paneuropeo idoneo all applicazione di metodi geostatistici. In molti casi la distribuzione spaziale dei metalli pesanti e strettamente correlata ad altri fattori, quali geologia, urbanizzazione, copertura vegetale. 29

51 Conclusioni La disponibilita di cartografia di maggior dettaglio, relativa alle variabili ausiliarie, e di ulteriori dati, consentira di ottenere risultati piu accurati nel processo di interpolazione spaziale: Dati puntuali aggiuntivi Basi di dati GIS Luis Rodrguez Lado, Tomislav Hengl, Hannes I. Reuter. Heavy metals in European soils: a geostatistical analysis of the FOREGS Geochemical database, Geoderma (In Press) 30

52 Grazie per l attenzione 31