Flood Vulnerability Analysis

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Presentation transcript:

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

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

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

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

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

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

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

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

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

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: 29.000 € (buildings) 31.000 € (assets) 24.000 € (utilities) Source: Kreibich et al. (2005) Risk Analysis Flood Vulnerability Analysis

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

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

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

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

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

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 1988 ) 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 0.0002 PAR Risk Analysis Flood Risk Analysis

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