Pan-European assessment of weather driven natural risks

Carlo Lavalle, José I. Barredo, Ad De Roo, Luc Feyen, Stefan Niemeyer, Andrea Camia, Roland Hiederer, Paulo Barbosa

European Commission DG Joint Research CentreInstitute for Environment and SustainabilityLand Management & Natural Hazards Unit

e-mail: carlo.lavalle@jrc.itweb : http://natural-hazards.jrc.it , http://moland.jrc.it , http://effis.jrc.it

Outline• The Institutional Context

• Hazards, Vulnerability and Risk analysis for the EU– Floods, droughts, forest-fires and heatwaves

• Approaches for forecasting and mitigation of natural hazards : integrated scenario modelling

• Brief outlook of next steps

Natural Hazards: the institutional context

• Within the European Commission, the JRC provides scientific and technical advice/support for policies related to:– “Flood risk management, flood prevention, protection and

mitigation” [COM(2004) 472]

– “Winning the Battle Against Global Climate Change” [COM(2005) 35 final]

– Monitoring of forests and environmental interactions in the Community (Forest Focus), regulation No 2152/2003

– 6th Environmental Action Plan

– The definition process of the Strategic Guidelines for the Programming period 2007-2013

Risk assessment for Natural Hazards

The Approach

Exposure Vulnerability HazardThe present assets:

Population InfrastructureSettlementsEcological values….

The resistance to damaging forces:GDP/ capitaPlanning regulationsProtection measuresWarning systemsInsurance mechanisms…

The threatening event:FloodsDroughtsForest FiresHeatwaves

Risk

CombinationMethods

Risk = hazard x exposure x vulnerability

Note : exposure and vulnerability are hazard-specific.

The Quantification of Hazards

• Floods– Maps (intensity and frequency) produced by hydrological modelling

(LISFLOOD) and validated with actual data (when/where available) – LISFLOOD ingests data from meteo forecast and/or climate scenarios

and is the basis of the European Flood Alert System (efas.jrc.it)

• Droughts– Maps produced by hydrological modelling (LISFLOOD) and based on

a quasi-climatogical data analysis

• Forest Fires– Data from Member States (the EU Forest Fire Data Base, built upon

the Common Core Database) + Model (European Forest Fire Information System (effis.jrc.it)) + Observed fires (remote sensing)

• Heatwaves– Meteorological and climatological data

The making of flood risk map

+ +

= =>

hazard exposure vulnerability

Risk (grid) Risk (NUTS-3)

Ref.: Barredo, et al. (2005). European flood risk mapping. S.P.I.05.151.EN, European Commission

Potential Drought Hazard MapsSoil Water Stress MapsLISFLOOD model run on 44 years (1957/2002)of ECMWF ERA40 meteorological data

A ‘quasi-climatological’ analysis

Daily maps of the forecasted soil moisture development in Europe (seven days trend) available on line

Burned Forest:From EU Fire database

Wildland:From CORINE 2000

Fire densityFire density

Burned Wildland FractionBurned Wildland Fraction

Forest Fire Hazard Maps

YEARS of DataPortugal: 10Spain: 10France: 10 Italy: 10Greece: 10Germany: 6Cyprus: 5Latvia: 1Czech R. 1Slovakia: 1Poland: 10Lithuania: 1Hungary: 3Sweden: 9Romania: 1

Ref.: Meeting of the Group of Experts on Forest Fires – Brussels 24 Mar 2006

Risk Indicator:Vulnerable Population Exposed to Heatwave

Heatwave Extent

Vulnerable Population ExposureNo. of people over 65 years exposed to

HUMIDEX exceeding 35 during June, July and August 2003

Population Number

Population Exposed

Vulnerable Population Group

+

+

Natural HazardsLISFLOOD

EFFIS

Climate ChangeGCM/RCM

Risk Prevention

Scenarios (adaptation)

Current ClimateMeteo Data

Soil, Vegetation

Land UseSocio-eco Stats

ImpactAnalysis

Cost / BenefitAppraisal

Integrated scenario modelling

Land use MOLAND

Pilot area in the Upper Danube – Preliminary resultsIncrease of flood impacts for Climate Change Scenarios

Tentative estimate upper Danube:

Current Climate: 45 Billion Euro damage (theoretical maximum for a 100-yr flood) A2 Scenario 40 % increase in total damage, 11 % increase in exposed population B2 Scenario 19 % increase in total damage , 6 % increase in exposed population

Limitations: a) Uncertainties due to emission scenarios and downscaling procedures

b) Cost estimation made per land use classes with approx. depth-damage curves

Next steps: include land use simulations and adaptation measures

Change in annual avg max 5-day precipitation Change in flood water depth

Outlooks• Refinement of EU 25+ maps of risk:

– More detailed quantification of impacts (pre- and post-event)– Improved resolution– Definition and analysis of macro-regions

• Proper inclusion of adaptation activities in the scenario modeling;– Products of EU Flood GIS Project (EP funded)

• Further development of downscaling methods for Climate Change Models (from GCM to ‘dedicated’ RCM);

– quantitative assessment of changes in hydrological extremes – quantitative assessment of changes in forest species distribution and forest fire risk – Improve understanding and prediction of extreme weather events

• Further development of climate change/territorial development– Feed back interactions in Moland– Completion of scenarios on pilot areas (for flood/fire/drought based on a multi-scale approach)

• Subjects for collaboration with Regions and Local Authorities (e.g. via INTERREG)

• Data exchange, Transfer of methods and tools, Exchange of good practices• Exchange of visiting staff• Pilot experiments