Exploring the potential of multivariate depth-damage and rainfall-damage models

Luc van Ootegem, K. van Herck, T. Creten, E. Verhofstadt, Loris Foresti, E. Goudenhoofdt, Maarten Reyniers, Laurent Delobbe, Damian Murla, Patrick Willems

Research output: Contribution to journalJournal articleResearchpeer-review

21 Citations (Scopus)

Abstract

In Europe, floods are among the natural catastrophes that cause the largest economic damage. This article explores the potential of two distinct types of multivariate flood damage models: ‘depth-damage’ models and ‘rainfall-damage’ models. We use survey data of 346 Flemish households that were victim of pluvial floods complemented with rainfall data from both rain gauges and weather radars. In the econometrical analysis, a Tobit estimation technique is used to deal with the issue of zero damage observations. The results show that in the ‘depth-damage’ models flood depth has a significant impact on the damage. In the ‘rainfall-damage’ models there is a significant impact of rainfall accumulation on the damage when using the gauge rainfall data as predictor, but not when using the radar rainfall data. Finally, non-hazard indicators are found to be important for explaining pluvial flood damage in both ‘depth-damage’ and ‘rainfall-damage’ models.
Original languageEnglish
JournalJournal of Flood Risk Management
Volume11
Issue number52
Pages (from-to)S916-S929
ISSN1753-318X
DOIs
Publication statusPublished - 1 Feb 2018
Externally publishedYes

Keywords

  • Depth-damage
  • flood damage models
  • non-hazard indicators
  • pluvial flood
  • rainfall-damage

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