wisc exposure and vulnerability - copernicus...vulnerability curves per land cover class and...

Implemented by

WISC Exposure and Vulnerability Dr Elco Koks

Vrije Universiteit Amsterdam

pace23/06/2016, Introduction to WISC Indicators

Focus on the development of two indicators

Total sectorial insuredlosses

Total amount of losses per sectorwithin Europe due to the occurrence of wind storms.

Yearly / pan-European

Total windstorm risk per sector due to windstorms

Total windstorm risk, as a function of hazard, exposure and vulnerability per sector

Yearly/ pan-European

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Total windstorm risk per sector due to windstorms

Total windstorm risk, as a function of hazard, exposure and vulnerability per sector. Total losses are part of the risk

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Requirements

Hazard Data on the severity of the hazard (gust speed)

Exposure Data on exposed assets in wind-proneareas, preferabiliy per land-use

Vulnerability Data on the susceptibility of assets, preferability per land-use

Probability Probability of occurence for a given hazard


Methodology

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Exposure database 10mx10m resolution CORINE land cover data

http://www.eea.europa.eu/data-and-maps/data/corine-land-cover-2006-raster-3

Openstreetmap data www.osm.org Freely available, allowing for more detail in exposure data. Very good

coverage for EU, shapefile format (will be rasterized when combined with CORINE) 80% coverage or so

Sectors considered similar to Perils: Agricultural Residential Commercial/Industrial (same class, but we know the percentage of each) Horticulture The greenhouses are in the building footprints, but its not a seperate class in

CORINE.

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http://www.eea.europa.eu/data-and-maps/data/corine-land-cover-2006-raster-3

http://www.osm.org/


Exposure data steps: Amsterdam Example

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Vulnerability database

Depth-damage curves will be developed and applied. A first set of curves is based on avaiable literature. E.g.:

Feuerstein et al. (2008) Heneka and Ruck (2008)

But, calibration with sample sets is required (and will be done)

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Per country we know the building type for urban residential, non-urban residential, urban non-residential and non-urban non-residential. This will improve the detail of the calculation. PAGER database (mainly used for earthquakes)

We have data on maximum reconstruction costs in Europe, scaled to GDP. But calibration is required (as stated before)

Almost all of the literature uses proxies to assess the building losses (because they do not have/use building footprint data). This would mean that this is the first study that does so! And that’s why the 10x10m resolution is wanted!

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Vulnerability curves per land cover class and building type within Europe

Maximum losses per curve will rescaled based on GDP per NUTS3 (available via Eurostat)

Set of curves can be made country specific (e.g. wood vsconcrete vs brick buildings)


Total sectorial insured losses per year due to windstorms

Combine the storm data with the improved land-use data and use the curves to calculate the losses

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Greater Manchester example

V_crit of 25 (according to Heneka and Ruck, 2008) with the storm of March 11, 2008

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Thank you

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wisc exposure and vulnerability - copernicus...vulnerability curves per land cover class and...

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