Flood damage models – Scope and limitations 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 and state of the art of recording loss data at local level 30-31 March 2015 - Ispra

Assessing flood disaster losses To account for the direct losses produced by floods Direct economic damage is the tangible economic loss associated with a flood’s impact as determined after the event These losses occur after floods as a result of the physical contact of the flood waters with damageable property Indirect (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 http://ec.europa.eu/environment/nature/knowledge/ecosystem_assessment/pdf/2ndMAESWorkingPaper.pdf

Flood damage models Useful for assessing economic flood impact These models produce estimates of flood damage But the estimation of flood damage is a complex process involving a large number of hydrologic and socio-economic factors Models: structure, inputs (data) and outputs.  These depend on the purpose of the model

Flood damage models Baseline structure and data: Land cover Flood delineation Water depth CORINE data Copernicus – EMS Satellite imagery

Flood damage models Economic losses Grid cell (100*100m): Land cover class: 111 Water depth: 2.0 m Grid cell (100*100m): Economic losses: 2,016,500 Euro

Flood damage functions Flood damage functions measure the susceptibility of assets to certain inundation characteristics, in this case specifically inundation depth Flood 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 valleys Sediment (and solid components) concentration in water Pollutant content in water

Land cover limitations CORINE land cover: Pan-European map 44 land cover classes Available at 100 and 250 m grid size Minimum 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)

Land cover limitations 50% residential 18% transport 17% other 5% commercial 5% construction 5% unused CORINE (100*100m) 111 – Continuous urban fabric See: 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.

Flood water delineation limitations Flood delineation and water depth Copernicus Emergency Management Service: Important support for flooded area mapping Remote sensing limitations: lack of imagery (clouds), partial coverage, acquisition time of imagery (too early, too late) , … Water depth computation This 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)

Comparing flood damage models

Comparing flood damage models We 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) 2002 2005 Source: Jongman et al 2012. Comparative flood damage model assessment: towards a European Approach. NHESS, 12, 3733–3752.

Results The models produced different results: Modelled damage Relative distribution: residential, industry & commerce and infrastructure Source: Jongman et al 2012. Comparative flood damage model assessment: towards a European Approach. NHESS, 12, 3733–3752.

Results Uncertainty should be considered… Source: Jongman et al 2012. Comparative flood damage model assessment: towards a European Approach. NHESS, 12, 3733–3752.

Summary of results Model output are very sensitive to uncertainty in both vulnerability (damage functions) and exposure (asset values) The first has large effect than the latter Estimation of residential and commercial building damage is the best developed part of the models Care needs to be taken when using aggregated land use data for flood risk/damage assessment It is essential to adjust assets values to the regional economic situation and property characteristics Source: Jongman et al 2012. Comparative flood damage model assessment: towards a European Approach. NHESS, 12, 3733–3752.

Conclusions Results of models are estimations  Check with reality e.g. claims from insurance companies customers Land use data: Varying density of assets at local level Assets share inside each land use category Flood damage functions: source, verification with reality, testing, sensitivity analysis Infrastructure losses are usually underestimated Regional/national variations in assets value

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