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Flood Risk Assessment for Emergency Preparedness and Response. Paolo Reggiani & Nathalie Asselman WL | Delft Hydraulics Symposium on Multihazard Early Warning Systems for Integrated Disaster Risk Management WMO- Geneva 23-24 May 2006

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Definition of Flood Risk: Risk = damage x probability

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Damage Damage is function of: type and number of buildings land use infrastructure flooding characteristics….

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Important flooding characteristics: time of inundation (winter / summer) rate of rise duration of inundation water depths flow velocities Flooding characteristics

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Damage and casualties model developed at Delft Hydraulics for the Dutch situation

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General Development of a standard method to compute costs and casualties caused by flooding. Implemented in a Hydrological Information System (HIS). Initiated by Road and Hydraulic Engineering Division, Directorate-General of Public Works and Water Managementm, The Netherlands. The method is applicable for situations world- wide.

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Aim and applicability Modelling system to estimate/predict damage caused by low-frequency floods. Floods and inundations originating from “larger” water bodies. YES: dike breaks. NO: local inundation from sewage systems. No difference between salt and fresh water.

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What is modelled? Casualties Damage loss of capital goods (houses, infrastructure, etc.) reduced productivity loss of income (businesses, shops, restaurants, etc.)

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Procedure Model damage functions Data land use type nr of inhabitants etc. Flooding scenario damage damage function water depth land use

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Total damage estimation: with: i = damage-factor for category i (e.g. houses, roads, etc.) n i = number of units in category i D i = max. damage per unit in category i

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Damage factor i Varies from 0 to 1 Function of: depth of inundation (critical) flow velocity storm(waves) rate of rise (important for number of casualties)

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Problems: Number of casualties depends on water depth and flow velocities after dike break, but also on possible warning and evacuation beforehand Damage relations for other categories mainly based on theory as little ‘experimental’ data are available form previous flood experience Use of experimental data still poses problems

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Utrecht Amsterdam Den Haag Rotterdam North Sea Rhine Meuse

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December 1993 - January 1995

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Damage claims

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Damage data private properties: houses

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Damage data private properties: furniture

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Why are the costs for the second flood lower ? People take measures to reduce the damage: tiled floor instead of parquet floor put furniture on first floor when probability for flooding increases --> difficult to include in damage model !!

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Improvement of the damage models: current research adjust damage functions economic – loss of income (TU Twente) houses and roads (TNO) environmental risks (Alterra, TNO, GeoDelft, CSO, WL) casualties / victims (WL, DWW)

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Case study area ‘Zuid-Holland’

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Flooding characteristics: water depth

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Flooding characteristics: flow velocities

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Isochrones of inundation (in hours after dike break)

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Is it possible to escape ? based on evacuation model for different area empirical relationshi ps establishe d for different areas

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Percentage of inhabitants that are able to escape (based on data on road network)

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Estimated number of casualties (based on 1953 flood data, Zeeland province)

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The Problem – time to escape

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First estimate City (suburb)Rotterdam- Hilligersberg available time (hours)60 routeA20 Gouda distance (km)27 driving speed (km/h)20 driving time needed (hours)1,5 time elapsed before departure (hours) 4 total time (hours)5,5 risk ?very low

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Second estimate City (suburb)Rotterdam- Hilligersberg bottleneckroad to highway, highway available time (hours)1 distance to bottleneck (km)1,5 total time needed (hours)4,1 risk ?very large !

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Main lesson learned? A traffic / transport model is needed to obtain the most realistic estimate of potential number of casualties Good instructions beforehand may reduce the risk of wrong decisions with respect to choice of route

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