Natural Hazards

, Volume 92, Issue 3, pp 1633–1648 | Cite as

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

  • María Bermúdez
  • Andreas Paul Zischg
Original Paper


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.


Inundation modelling Micro-scale Building representation Flood loss estimation 



The authors thank the Swiss Federal Office for Statistics for providing the residential register, the Swiss Federal Office for Topography for providing the building dataset and the Canton of Bern, Switzerland for providing the Lidar terrain model. María Bermúdez gratefully acknowledges financial support from the Spanish Regional Government of Galicia (postdoctoral Grant reference ED481B 2014/156-0). Andreas Paul Zischg gratefully acknowledges financial support from the Swiss National Foundation (Grant No. IZK0Z2_170478/1).

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.


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Copyright information

© Springer Science+Business Media B.V., part of Springer Nature 2018

Authors and Affiliations

  1. 1.Water and Environmental Engineering GroupUniversity of A CoruñaA CoruñaSpain
  2. 2.Institute of Geography, Oeschger Centre for Climate Change Research, Mobiliar Lab for Natural RisksUniversity of BernBernSwitzerland

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