E3S Web Conf.
Volume 7, 20163rd European Conference on Flood Risk Management (FLOODrisk 2016)
|Number of page(s)||12|
|Section||Hazard analysis and modelling|
|Published online||20 October 2016|
Impact of modelling scale on probabilistic flood risk assessment: the Malawi case
1 CIMA Research Foundation, Via Armando Magliotto, 2, I-17100 Savona, Italy
2 Deltares, P.O. Box 177, 2600 MH Delft, The Netherlands
3 Institute for Advanced Study of Pavia, Palazzo del Broletto, Piazza della Vittoria, 15, I-27100 Pavia, Italy
a Corresponding author: firstname.lastname@example.org
In the early months of 2015, destructive floods hit Malawi, causing deaths and economic losses. Flood risk assessment outcomes can be used to increase scientific-supported awareness of risk. The recent increase in availability of high resolution data such as TanDEM-X at 12m resolution makes possible the use of detailed physical based flood hazard models in risk assessment. Nonetheless the scale of hazard modelling still remains an issue, which requires a compromise between level of detail and computational efforts. This work presents two different approaches on hazard modelling. Both methods rely on 32-years of numeric weather re-analysis and rainfall-runoff transformation through a fully distributed WFLOW-type hydrological model. The first method, applied at national scale, uses fast post-processing routines, which estimate flood water depth at a resolution of about 1×1km. The second method applies a full 2D hydraulic model to propagate water discharge into the flood plains and best suites for small areas where assets are concentrated. At the 12m resolution, three hot spots with a model area of approximately 10×10 km are analysed. Flood hazard maps obtained with both approaches are combined with flood impact models at the same resolution to generate indicators for flood risk. A quantitative comparison of the two approaches is presented in order to show the effects of modelling scale on both hazard and impact losses.
© The Authors, published by EDP Sciences, 2016
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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