The CORFU project was a 4-year European Commission-funded project from 2010-2014 that assessed flood impacts and resilience strategies in 11 cities across Europe and Asia. It developed models to simulate flooding under future scenarios of economic development, urban growth, and climate change. The project evaluated the effectiveness of resilience measures using a Flood Resilience Index. It also created a flood damage assessment tool to analyze impacts to buildings and infrastructure for cities like Barcelona, Beijing, and Dhaka. The project facilitated collaboration between European and Asian researchers and cities to improve flood management and create more resilient urban areas.

1. Albert S. Chen
Collaborative Research on Flood
Resilience in Urban areas (CORFU)
18 Oct 2016 CIWEM SW Branch
Flood Resilience and Sustainable Water Management in Urban Areas

2. Outline
• CORFU overview
• Key methodologies
• Concluding remarks

3. The CORFU project
• Funded by the European Commission through Framework
Programme 7, Grant Number 244047
• Four-year project 2010-2014
• Europe-Asia angle
• €3.5m budget
• www.corfu7.eu

4. CORFU Team

5. Project aims
• Assess flood impacts for future scenarios
– Economic development
– Urban growth
– Climate change
• Evaluate resilience measures and strategies
– Flood resilience index
– Cost-effectiveness of resilience measures

6. Project aims
• Facilitate learning between Europe and Asia
– Two-way process
– Collaborative research
– Improved mutual understanding
• Help create flood resilient cities
– Better planning
– Reduction of impacts
• Saving lives
• Minimizing losses
• Preserving infrastructure
– Faster recovery

7. Case study cities
Barcelona Beijing Dhaka
Hamburg Mumbai Nice
TaipeiSongdoSeoul

8. Drivers (WP1)
• Socio-economic pathways
– Common global assumptions
– Regional scenarios for each city
• Combined with plausible climate futures
– Based on 4th IPCC scenarios and regional studies
– Envisaged changes in rainfall patterns

9. Population growth & urbanisation

10. 201020152020202520302035204020452050205520602010-2060
Dhaka
Models based on:
satellite images
land use
DTM
thematic maps
distance relations

11. Modelling (WP2)
• Various models used
– 1D, 2D, 1D/2D
• Areas up to 1,000
km2
• Calibration
• Real-time warning
systems

12. Validation of surface flow
 Comparison between flow depths provided by model simulations and youtube video recorded during
the event of 30/07/2011
0.4 m
Modelling (WP2)

13. Health impact

14.  Flood hazard assessment was carried out for the Raval district according to specific criteria achieved
for flooded streets during heavy storm events
 High hazard conditions were defined for velocities above 1.88 m/s and flow depths above 10 cm,
while for moderate hazard, 1.5 m/s and 6 cm were considered as thresholds.
Hazard level Flow conditions
(for flow depths between 9 and 16 cm)
High v  1.88 m/s
Moderate 1.51  v < 1.88 m/s
Low v < 1.51
Pedestrian Safety

15. Flood impact typology (WP3)
Tangible Intangible
Direct • Physical damage to assets
Buildings
Contents
Infrastructure
• Loss of life
• Injuries
• Diseases
• Loss of ecological goods
Indirect • Loss of industrial production
• Traffic disruption
• Inconvenience of recovery
• Vulnerability of population
• Flood damage assessment tool

16. 16
Damage on buildings in mega cities
• Challenges in modelling:
– Volume of data and computational cost
– Optimal resolution of 2D models
– “Merging” of buildings
– Locally valid depth-damage curves
• Flood damage assessment tool
– Add-on in ArcGIS
– Interacts with data using built-in geo-
processing functions and executables
– Transferable algorithms

17. Chen et al. 2016, Natural Hazar
Barcelona Taipei Nice
Beijing
Dhaka

18. Flood damage to buildings in Dhaka

19. Traffic modelling

21. Natural
dimension
Topography
flood intensity
flood frequency
natural
environment
Degradation
Physical
dimension
Land use
Urban functions
and services,
Warning system
and evacuation,
History
Location
Accessibility
Social
dimension
Population
Health status
Education and
awareness
Social capital
Knowledge and
awareness
Economic
dimension
Income,
Employment
Households
Assets
Access to
financial service
Savings and
insurance,
Budget and
subsidy
Institutional
dimension
Internal
institutions and
development
plan
Effectiveness of
internal
institutions,
External
institutions and
networks
Institutional
collaboration and
coordination
• Flood Resilience Index (FRI)
Evaluation of resilience (WP4)

22. Concluding remarks
• CORFU approach presented
• Overall project conclusions yet to be formulated
• Details of implementation in case studies depended on:
– Data quality and availability
– Dominant drivers
– Adopted models
– Critical impacts
– Applicable measures

23. a.s.chen@exeter.ac.uk
AlbertChenExeter
@AlbertChen_CWS
Contact
Questions?
Dr Albert S. Chen
www.exeter.ac.uk/cws