Samenvatting
In this dissertation a model is built to predict flood risk in Flanders. Risk can be seen as a measure for the impact of a flood. The impact of the same flood on 2 different places will not be the same, and this difference can be seen in the risk. The model itself consists of 3 components: hazard, exposure and vulnerability.For the hazard component a first attempt was made by trying to create depth data based on altitude data and a 2-dimensional flood map. However this attempt failed and the flood surface area was chosen as a parameter. The exposure component exists of the number of buildings and the number of people in flooded areas. The determine the number of buildings in a flood area, the percentage overlap between the building and the flood area was determined. The threshold for which percentage a building would be flooded or not was selected based on surveys in 2 areas: the area Herne and Galmaarden and the area Puurs and Londerzeel. To the determine the number of persons in flooded areas a raster was used with squares of 22500 m². In this raster population data was stored based on cadastral data. The population was distributed over the buildings in each square. By looking at which houses were impacted by a flood, the number of people could be calculated. The vulnerability component was determined by using several socio- conomic variables. These variables are: percentage of people older than 75, percentage of single parents, percentage of foreigners, percentage of people without comfort (sanitary provisions), percentage of people without a car, percentage of caravans, percentage of unemployed people, median income and percentage of apartment buildings.
These 3 components can be combined by a multiplication to form a measure for risk. In this study the flood risk is determined for the province of Vlaams-Brabant, on the level of statistical sectors (the smallest administrative level in Belgium) and on the level of municipalities. After this a validation was performed by calculating the correlation between the flood risk, the different components and the amount of damage available from the Belgian disaster relief fund. Only a very small correlation was found between the exposure and the damage, and this only after correcting for outliers. However this low correlation does not mean that the model is invalid, as the damage data from the disaster relief fund contains less than 1% of the total.
| Datum prijs | 30 jun. 2014 |
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| Originele taal | English |
| Begeleider | Matthieu Kervyn De Meerendre (Promotor) |
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