Over het archief
Het OWA, het open archief van het Waterbouwkundig Laboratorium heeft tot doel alle vrij toegankelijke onderzoeksresultaten van dit instituut in digitale vorm aan te bieden. Op die manier wil het de zichtbaarheid, verspreiding en gebruik van deze onderzoeksresultaten, alsook de wetenschappelijke communicatie maximaal bevorderen.
Dit archief wordt uitgebouwd en beheerd volgens de principes van de Open Access Movement, en het daaruit ontstane Open Archives Initiative.
Basisinformatie over ‘Open Access to scholarly information'.
Analyzing the sensitivity of a flood risk assessment model towards its input data
Glas, H.; Deruyter, G.; De Maeyer, P.; Mandal, A.; James-Williamson, S. (2016). Analyzing the sensitivity of a flood risk assessment model towards its input data. Nat. Hazards Earth Syst. Sci. 16(12): 2529-2542. https://dx.doi.org/10.5194/nhess-16-2529-2016
In: Natural Hazards and Earth System Sciences. Copernicus Publications: Göttingen. ISSN 1561-8633; e-ISSN 1684-9981, meer
| |
Auteurs | | Top |
|
- Mandal, A.
- James-Williamson, S.
|
|
Abstract |
The Small Island Developing States are characterized by an unstable economy and low-lying, densely populated cities, resulting in a high vulnerability to natural hazards. Flooding affects more people than any other hazard. To limit the consequences of these hazards, adequate risk assessments are indispensable. Satisfactory input data for these assessments are hard to acquire, especially in developing countries. Therefore, in this study, a methodology was developed and evaluated to test the sensitivity of a flood model towards its input data in order to determine a minimum set of indispensable data. In a first step, a flood damage assessment model was created for the case study of Annotto Bay, Jamaica. This model generates a damage map for the region based on the flood extent map of the 2001 inundations caused by Tropical Storm Michelle. Three damages were taken into account: building, road and crop damage. Twelve scenarios were generated, each with a different combination of input data, testing one of the three damage calculations for its sensitivity. One main conclusion was that population density, in combination with an average number of people per household, is a good parameter in determining the building damage when exact building locations are unknown. Furthermore, the importance of roads for an accurate visual result was demonstrated. |
IMIS is ontwikkeld en wordt gehost door het VLIZ.