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Sensitivity of flood loss estimates to building representation and flow depth attribution methods in micro-scale flood modelling
Sensitivity of flood loss estimates to building representation and flow depth attribution methods in micro-scale flood modelling
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Sensitivity of flood loss estimates to building representation and flow depth attribution methods in micro-scale flood modelling
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Sensitivity of flood loss estimates to building representation and flow depth attribution methods in micro-scale flood modelling
Sensitivity of flood loss estimates to building representation and flow depth attribution methods in micro-scale flood modelling

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Sensitivity of flood loss estimates to building representation and flow depth attribution methods in micro-scale flood modelling
Sensitivity of flood loss estimates to building representation and flow depth attribution methods in micro-scale flood modelling
Journal Article

Sensitivity of flood loss estimates to building representation and flow depth attribution methods in micro-scale flood modelling

2018
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Overview
Thanks to modelling advances and the increase in computational resources in recent years, it is now feasible to perform 2-D urban flood simulations at very high spatial resolutions and to conduct flood risk assessments at the scale of single buildings. In this study, we explore the sensitivity of flood loss estimates obtained in such micro-scale analyses to the spatial representation of the buildings in the 2D flood inundation model and to the hazard attribution methods in the flood loss model. The results show that building representation has a limited effect on the exposure values (i.e. the number of elements at risk), but can have a significant impact on the hazard values attributed to the buildings. On the other hand, the two methods for hazard attribution tested in this work result in remarkably different flood loss estimates. The sensitivity of the predicted flood losses to the attribution method is comparable to the one associated with the vulnerability curve. The findings highlight the need for incorporating these sources of uncertainty into micro-scale flood risk prediction methodologies.