Forest Resources and Climate Unit Institute for Environment and Sustainability IES European Commission Joint Research Centre José I Barredo EU Loss Data Workshop Progress towards guidelines on sharing loss data among EU countries ID: 1003246
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1. Flood damage models – Scope and limitationsForest Resources and Climate UnitInstitute for Environment and Sustainability (IES)European Commission - Joint Research CentreJosé I. BarredoEU Loss Data Workshop: Progress towards guidelines on sharing loss data among EU countries and state of the art of recording loss data at local level30-31 March 2015 - Ispra
2. Assessing flood disaster lossesTo account for the direct losses produced by floodsDirect economic damage is the tangible economic loss associated with a flood’s impact as determined after the eventThese losses occur after floods as a result of the physical contact of the flood waters with damageable propertyIndirect (i.e. secondary and tertiary) and intangible damages (i.e. loss of human life, Ill-health of floods victims), as well as longer-term macroeconomic effects are not considered
3. Flood damage modelsUseful for assessing economic flood impactThese models produce estimates of flood damageBut the estimation of flood damage is a complex process involving a large number of hydrologic and socio-economic factorsModels: structure, inputs (data) and outputs. These depend on the purpose of the model
4. Flood damage modelsBaseline structure and data:Land coverFlood delineationWater depthCopernicus – EMSSatellite imageryCORINE data
5. Flood damage modelsEconomic lossesGrid cell (100*100m):Land cover class: 111Water depth: 2.0 mGrid cell (100*100m):Economic losses: 2,016,500 Euro
6. Flood damage functionsFlood damage functions measure the susceptibility of assets to certain inundation characteristics, in this case specifically inundation depthFlood water depth is the determining factor in almost all models in use today However other flood water parameters influence damage:Flood duration: few minutes, days …Water flow velocity: flash floods in mountain areas, narrow valleysSediment (and solid components) concentration in waterPollutant content in water
7. Land cover limitationsCORINE land cover: Pan-European map44 land cover classesAvailable at 100 and 250 m grid sizeMinimum mapping unit: 25 ha* !!!Linear (e.g. infrastructure) or small features are not well represented or not represented at all !!!* 4 cells (250m); 25 cells (100m)
8. Land cover limitationsCORINE (100*100m)111 – Continuous urban fabric50% residential18% transport17% other5% commercial5% construction5% unusedSee: EEA 2006 The thematic accuracy of Corine land cover 2000 - Assessment using LUCAS (land use/cover area frame statistical survey), EEA Technical report No 7/2006.
9. Flood water delineation limitationsFlood delineation and water depthCopernicus Emergency Management Service:Important support for flooded area mappingRemote sensing limitations: lack of imagery (clouds), partial coverage, acquisition time of imagery (too early, too late) , …Water depth computationThis is a critical parameter that is usually not available:Computation from EU-wide flood hazard map (100-yr return period flood)Assumptions based on ancillary information (minimum / maximum depth)
10. Comparing flood damage models
11. Comparing flood damage modelsWe compared seven flood damage models:FLEMO (Germany)Damage Scanner (The Netherlands)Rhine Atlas (Rhine basin)Flemish Model (Belgium)Multi-Coloured Manual (United Kingdom)HAZUS- MH (United States) JRC Model (European Union)20022005Source: Jongman et al 2012. Comparative flood damage model assessment: towards a EuropeanApproach. NHESS, 12, 3733–3752.
12. ResultsThe models produced different results:Modelled damageRelative distribution: residential, industry & commerce and infrastructureSource: Jongman et al 2012. Comparative flood damage model assessment: towards a EuropeanApproach. NHESS, 12, 3733–3752.
13. Uncertainty should be considered… Source: Jongman et al 2012. Comparative flood damage model assessment: towards a EuropeanApproach. NHESS, 12, 3733–3752. Results
14. Summary of resultsModel output are very sensitive to uncertainty in both vulnerability (damage functions) and exposure (asset values)The first has large effect than the latterEstimation of residential and commercial building damage is the best developed part of the modelsCare needs to be taken when using aggregated land use data for flood risk/damage assessmentIt is essential to adjust assets values to the regional economic situation and property characteristicsSource: Jongman et al 2012. Comparative flood damage model assessment: towards a EuropeanApproach. NHESS, 12, 3733–3752.
15. ConclusionsResults of models are estimations Check with reality e.g. claims from insurance companies customersLand use data: Varying density of assets at local levelAssets share inside each land use categoryFlood damage functions: source, verification with reality, testing, sensitivity analysisInfrastructure losses are usually underestimatedRegional/national variations in assets value
16. Thank you