This document presents a European flood risk model used to analyze climate change adaptation strategies. The model evaluates current and future flood risk across Europe under different climate and socioeconomic scenarios. It assesses exposure and vulnerability to estimate expected annual flood damage. The results show that socioeconomic changes may increase risk more than climate change by 2050. Adaptation strategies like improving flood protections and adapted building designs could significantly reduce risk and damage, demonstrating the benefits of adaptation. Next steps include assessing costs of adaptation measures.

1. A European flood risk model and its
use for analyzing climate change
adaptation strategies
Andreas Burzel, Friederike Holz, Hessel Winsemius,
Karin de Bruijn and Laurens Bouwer
IAHR World Congress, The Hague

2. Why do we need a European Flood Risk Model?
• Evaluation of current flood risk at a European level
• EU28 + 11 EEA member states
• Impact of new climate change scenarios (RCPs), and new
socioeconomic scenarios (SSPs)
• Estimating costs and benefits of adaptation measures, including
links to local scale adaptation
• structural flood protection measures (dikes, adapted buildings)
• Part of the FP7 BASE project (“Bottom-Up Climate Adaptation
Strategies Towards a Sustainable Europe”)
• Application of the new Flood Impact Assessment Tool
(Delft-FIAT)
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3. Methodology: Hazard modeling
Inundation depth
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Flood hazard modelling
Flood hazard
Hydrology: PCRGLOBWB DynRout
Inundation: GLOFRIS (1x1 km)
Flood extents for RP 1, ... 1000 yrs
RCP4.5 and 8.5 climate projections
Definition of flood risk in this study:
Flood risk = f (hazard, exposure, vulnerability)

4. Methodology: Exposure assessment
Flood hazard modelling
Provided by BASE project
(PCR-GLOBWB)
Potential maximum monetary damage
Exposed assets
CORINE land cover 2006
(product of EEA, 44 land use
classes, covering most of EU)
5 most relevant impact categories:
Residential, commercial, industrial,
infrastructure, agriculture
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Exposure assessment

5. Methodology: Exposure assessment
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CLC classes (shapefiles)
(http://sia.eionet.europa.eu)
Grid files showing
%-share per grid
cell for each of the
5 impact
categories
5
Overlay of the 5 impact categories

6. Methodology: Vulnerability assessment
Exposure assessment
Vulnerability assessment
Potential maximum monetary damage
Using EU-average
relative depth-damage
functions (Huizinga, 2007)
Exposed assets
CORINE land cover 2006
(product of EEA, 44 land use
classes, covering most of EU)
5 most relevant impact categories:
Residential, commercial, industrial,
infrastructure, agriculture
Maximum damage values
Maximum damage values per
impact category (Euro/sqm) from
Huizinga, 2007
Scaled by GDP per capita to
regional level
Residential 824
Commercial 682
Industrial 587
Infrastructure 26
Agriculture 0.85
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Flood hazard modelling
Provided by BASE project
(PCR-GLOBWB)

7. Methodology: Flood risk assessment
Exposure assessment
Vulnerability assessment
Potential maximum monetary damage
Using EU-average
relative depth-damage
functions (Huizinga, 2007)
Exposed assets
CORINE land cover 2006
(product of EEA, 44 land use
classes, covering most of EU)
5 most relevant impact categories:
Residential, commercial, industrial,
infrastructure, agriculture
Maximum damage values
Maximum damage values per
impact category (Euro/sqm) from
Huizinga, 2007
Scaled by GDP per capita to
regional level
Residential 824
Commercial 682
Industrial 587
Infrastructure 26
Agriculture 0.85
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Flood hazard modelling
Provided by BASE project
(PCR-GLOBWB)
Flood risk
Risk expressed as
expected annual damage (EAD)
Damage-probability curve
Damage calculated for
9 return periods
Building a damage-probability
curve to obtain flood risk

8. Flood protection standards
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Source: Messner et al. 2007
Source: Modification of figure by Jongman et al., 2014
Damage-probability curve
8
Kilometers

9. Results – Change of flood risk – climate change
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Climate change scenario RCP 4.5
(Mean of 5 climate models, NUTS2
level, 2010-2049)
Climate change scenario RCP 8.5
(Mean of 5 climate models, NUTS2
level, 2010-2049)
Flood Risk as %-change to baseline
-50
-50 - -25
-25 - -5
-5 - 0
0 - 5
5 - 10
10 - 25
25 - 50
> 50
Neighbouring
countries

10. Results – Change of flood risk – GDP growth
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GDP growth scenario SSP2
(NUTS0 level, 2010-2049)
GDP growth scenario SSP5
(NUTS0 level, 2010-2049)
Flood risk as %-change to
0
0 - 25
25 - 50
50 - 75
75 - 100
100 - 125
> 125
Neighbouring
countries

11. Results – Flood risk as % of GDP
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NUTS 0 NUTS 2
Flood risk as % of
GDP
0 - 0.05
0.05 - 0.1
0.1 - 0.25
> 0.25
Neighbouring
countries

12. Adaptation strategies
• Flood prevention:
• Improve protection level to at least 1/100 years
• Adapted building:
• Flood proofing to 1,5 metres (upper end estimate) for areas
with flood RP 10-50 yrs (residential, commercial, industrial)
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Damage functions adapted from Huizinga (2007)

13. EU: 127 billion Euros (2011) per year
Uniform protection standards 1/1
Flood Risk (expected annual damage)
Baseline scenario (1960-1999)
Results – Different protection standards
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EU: 15.6 billion Euros (2011) per yearEAD [million Euro per year]
0 - 5
5 - 10
10 - 25
25 - 50
50 - 100
100 - 150
> 150
Neighbouring
countries
Regional protection standards
basin level, minimum 1/10
Flood Risk (expected annual damage)
Baseline scenario (1960-1999)
EU: 8.3 billion Euros (2011) per year
Minimum protection standards 1/100
Flood Risk (expected annual damage)
Baseline scenario (1960-1999)

14. Areas relevant for adapted building
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15. Current risk without adaptation
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16. Current risk with adaptation
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17. Effect of adaptation measures
• Risk prevention to RP 1/100:
• Expected annual damages baseline: 15.6 bn
• Expected annual damages adjusted prevention: 8.3 bn
(reduction of 47%)
• Risk reduction dry-proof:
• Expected annual damages baseline: 15.6 bn
• Expected annual damages adapted buildings: 9.8 bn
(reduction of 37%)
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18. Conclusions
• Impacts from socioeconomic change larger than climate change
(time slice (2010-2049))
• Substantial effects (benefits) from adaptation measures
• Improving prevention
• Adapted building
• Next steps:
• Establish a do-nothing scenario
• Run adaptation measures for future time slices
• Assess costs of adaptation measures
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19. References
BASE (2015). Research project website, see www.base-adaptation.eu
Delft-FIAT Wiki (2015): https://publicwiki.deltares.nl/display/DFIAT/Delft-FIAT+Home
Holz, F. (2014). “A European-scale approach to flood risk assessment. A land use based appraisal
of present and future flood risk as support for climate change adaptation and disaster risk
reduction” Masterthesis, Deltares / Christian-Albrechts-Universität zu Kiel, Delft and Kiel.
Huizinga, H. J. (2007). “Flood damage functions for EU member states.” Technical report. Technical
report, HKV Consultants. Implemented in the framework of the contract 382441-F1SC awarded
by the European Commission-Joint Research Centre.
Jongman, B., Hochrainer-Stigler, S., Feyen, L., Aerts, J. C. J. H., Mechler, R., Botzen, W. J. W.,
Bouwer, L. M., Pflug, G., Rojas, R., and Ward, P. J. (2014). “Increasing stress on disaster-risk
finance due to large floods.” Nature Climate Change, advance online publication.
Messner, F., Penning-Rowsell, E., Green, C., Meyer, V., Tunstall, S., and Van der Veen, A.
(2007). “Evaluating flood damages: Guidance and recommendations on principles and
methods.” Report Number: T09-06-01, Revision Number: 2_2_P44.
Winsemius, H. C., Van Beek, L. P. H., Jongman, B., Ward, P. J., and Bouwman, A. (2013). “A
framework for global river flood risk assessments.” Natural Hazards and Earth System
Sciences, 17(5), 1871–1892 HESS.
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