1. 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 Ispra

2. 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

3. 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

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

5. 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

6. 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

7. 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)

8. 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 Assessment using LUCAS (land use/cover area frame statistical survey), EEA Technical report No 7/2006.

9. 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)

10. Comparing flood damage models

11. 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 Comparative flood damage model assessment: towards a European
Approach. NHESS, 12, 3733–3752.

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

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

14. 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 Comparative flood damage model assessment: towards a European
Approach. NHESS, 12, 3733–3752.

15. 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

16. Thank you