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Analyzing the sensitivity of a flood risk assessment model towards its input data

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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.
Keywords
HAZARD, UNCERTAINTY, GIS

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Chicago
Glas, Hanne, Greet Deruyter, Philippe De Maeyer, Arpita Mandal, and Sherene James-Williamson. 2016. “Analyzing the Sensitivity of a Flood Risk Assessment Model Towards Its Input Data.” Natural Hazards and Earth System Sciences 16 (12): 2529–2542.
APA
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. NATURAL HAZARDS AND EARTH SYSTEM SCIENCES, 16(12), 2529–2542.
Vancouver
1.
Glas H, Deruyter G, De Maeyer P, Mandal A, James-Williamson S. Analyzing the sensitivity of a flood risk assessment model towards its input data. NATURAL HAZARDS AND EARTH SYSTEM SCIENCES. 2016;16(12):2529–42.
MLA
Glas, Hanne, Greet Deruyter, Philippe De Maeyer, et al. “Analyzing the Sensitivity of a Flood Risk Assessment Model Towards Its Input Data.” NATURAL HAZARDS AND EARTH SYSTEM SCIENCES 16.12 (2016): 2529–2542. Print.
@article{8500349,
  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.},
  author       = {Glas, Hanne and Deruyter, Greet and De Maeyer, Philippe and Mandal, Arpita and James-Williamson, Sherene},
  issn         = {1561-8633},
  journal      = {NATURAL HAZARDS AND EARTH SYSTEM SCIENCES},
  keyword      = {HAZARD,UNCERTAINTY,GIS},
  language     = {eng},
  number       = {12},
  pages        = {2529--2542},
  title        = {Analyzing the sensitivity of a flood risk assessment model towards its input data},
  url          = {http://dx.doi.org/10.5194/nhess-16-2529-2016},
  volume       = {16},
  year         = {2016},
}

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