1. Flood Vulnerability Analysis
Session 2
Dr. Heiko Apel
Risk Analysis
Flood Vulnerability Analysis

2. Flood Vulnerability Analysis
Learning objectives
Get familiar:
With the principles of flood vulnerability analysis
With the elements at risk
Learn:
The exposure mapping of elements at risk
Systematic classification of flood losses
How to collect food loss data and build flood loss models in general
Specific insights in the flood loss analysis of buildings, agriculture and lives
Understand:
The importance of impact and resilience on flood losses
Risk Analysis
Flood Vulnerability Analysis

3. Vulnerability analysis provides
Understanding of vulnerabilities in order to identify efficient measures to reduce them and to minimize impact of future floods
The foundation for cost-effective planning of flood mitigation
The inputs for realistic flood scenario modeling emergency planning
Data for risk mapping to be used to improve public flood risk awareness, which can motivate precautionary measures
Input for financial appraisals
for (re-)insurance to determine insurance rates, estimate probable maximum loss (PML)
to support disaster response and governmental decisions about loss compensation immediately after floods
Data for the quantitative comparison of different risks within community or region
Risk Analysis
Flood Vulnerability Analysis

4. Flood Vulnerability Analysis
Elements at Risk
Economic sectors
Housing
Infrastructure (traffic, power supply, water supply, administration)
Food production
Transport
Trade
Cultural sectors
Cultural heritage
Daily life
Social sectors
Population
Health care
Food supply
Mobility
Environmental Sectors
Ecosystem stability
Environmental health (Pollution)
Biodiversity
Risk Analysis
Flood Vulnerability Analysis

5. Flood Vulnerability Analysis
Exposure Databases
Data should reflect the location and value of the assets at risk
Use analog maps or preferably GeoInformationSystems (GIS) for spatial reference, display and intersection
Explore the capabilities of remote sensing (RS) products for mapping of elements at risk
Most commonly used satellite imagery libraries: MODIS, LandSAT, ASTER, Quickbird, SPOT
Utilize statistical databases and spatial disaggregation methods to distribute aggregated values (e.g. dasymetric mapping)
Risk Analysis
Flood Vulnerability Analysis

6. Exposure Databases (cont.)
Examples:
Micro-scale: detailed topography and building location
Meso-scale: CORINE land use data set
Risk Analysis
Flood Vulnerability Analysis

7. Increase of flood plains and losses
Loss increase in the last decades:
Caused by:
Increasing number of disasters
River training
Increasing use of floodplains (urbanization, population growth)
The accumulation of valuable goods
Decreasing awareness of flood risk
Risk Analysis
Flood Vulnerability Analysis

8. Flood impact classification
Direct
Tangible
Property Damage, Infrastructure, Agriculture
Intangible
Fatalities, Evacuees, Ecosystems, Cultural Heritage
Indirect
Disruption of Trade and Traffic
Psychological Stress, Migration
Risk Analysis
Flood Vulnerability Analysis

9. Factors affecting flood loss
Example: flood loss of buildings
Impact and resistance should be defined for every element at risk
Source: Thieken et al. (2005)
Risk Analysis
Flood Vulnerability Analysis

10. The role of awareness and preparedness
Significantly reduces flood losses
Example: loss in private households in the flood of 2002 in Germany (questionnaire results, n  2150)
Mean damage reduction due to precautionary measures:
€ (buildings) € (assets) € (utilities)
Source: Kreibich et al. (2005)
Risk Analysis
Flood Vulnerability Analysis

11. Scales of loss estimation
Scale of analysis determines data and methods:
Micro-scale
Object specific
Detailed input datasets (direct surveys) required
Cities, communes, counties
Results aggregated, but detailed results available
Meso-scale
Regional to national
Aggregated input data (statistics, census data, land use units)
Cumulated loss estimates, no site specific interpretation possible
Risk Analysis
Flood Vulnerability Analysis

12. Flood loss data collection
Is the first step for establishment and evaluation of loss models:
Problem: data availability and compatibility
Different stakeholders (e.g. insurance industry, science, public administration) collect data on flood losses with different methods:
Methods to collect data
Building Surveyors – high level of standardization, consistent data quality, limited set of parameters, expensive method (100 € per case*)
Questionnaires – answers dependent on respondents, unknown data quality, representativeness via sampling, lower cost (25-40 € per case*)
* Prices refer to Germany
Risk Analysis
Flood Vulnerability Analysis

13. Flood loss assessment - buildings
Region specific
Damage types:
Structural damage
Contents
Differentiated into
Building types: construction, materials, size, stories
Building uses: private, commercial, industrial
Loss estimation
Absolute or relative damage
Loss functions: functional relationship between flood indicators and damage (be careful to consider all factors)
Solution: rule based loss model
Risk Analysis
Flood Vulnerability Analysis

14. Flood loss assessment – buildings (cont.)
Rule-based flood Loss Estimation Model FLEMO (GFZ)
Step 1: damage ratio estimation by water depths and rule based model FLEMOps (step functions)
Step 2: modification of loss ratio (FLEMOps+)
Private Precaution
None
Good
Very Good
Contamination
0.92
0.64
0.41
Moderate
1.2
0.86
0.71
Severe
1.58
---
Source: Büchele et al. (2006)
Risk Analysis
Flood Vulnerability Analysis

15. Flood loss assessment - agriculture
Two-step process:
Relative loss estimation respective to season
Estimation of regional market value of crops
Loss of wheat crops in an early summer flood in East Germany
Risk Analysis
Flood Vulnerability Analysis

16. Flood loss assessment – loss of life
Data-based empirical approach (based on flash flood and dam failure data in USA, LOL = f(PAR)*, Source: Brown & Graham )
Process-based approaches (simulates exposure of people in buildings etc., evacuation possibilities and survival rates)
*Loss of life (LOL), Population at risk (PAR)
Warning time
Loss of life
Less than 15 min
0.5 PAR
15 min – 1.5 h
PAR0.56
More than 1.5 h
PAR
Risk Analysis
Flood Risk Analysis

17. Flood loss assessment– loss of life (cont.)
Example of processed-based approach:
Hydraulic experiments by REDSCAM (2000), Helsinki University of Technology, Finland
Risk Analysis
Flood Risk Analysis