Exposure and vulnerability estimation for modelling flood losses to commercial assets in Europe.
Flood exposure
Flood risk
Flood vulnerability
Hydrodynamic models
Journal
The Science of the total environment
ISSN: 1879-1026
Titre abrégé: Sci Total Environ
Pays: Netherlands
ID NLM: 0330500
Informations de publication
Date de publication:
01 Oct 2020
01 Oct 2020
Historique:
received:
01
04
2020
revised:
25
05
2020
accepted:
04
06
2020
pubmed:
23
6
2020
medline:
23
6
2020
entrez:
23
6
2020
Statut:
ppublish
Résumé
Commercial assets comprise buildings, machinery and equipment, which are susceptible to floods. Existing damage models and exposure estimation methods for this sector have limited transferability between flood events and therefore limited potential for pan-European applications. In this study we introduce two methodologies aiming at improving commercial flood damage modelling: (1) disaggregation of economic statistics to obtain detailed building-level estimates of replacement costs of commercial assets; (2) a Bayesian Network (BN) damage model based primarily on post-disaster company surveys carried out in Germany. The BN model is probabilistic and provides probability distributions of estimated losses, and as such quantitative uncertainty information. The BN shows good accuracy of predictions of building losses, though overestimates machinery/equipment loss. To test its suitability for pan-European flood modelling, the BN was applied to three case studies, comprising a coastal flood in France (2010) and fluvial floods in Saxony (2013) and Italy (2014). Overall difference between modelled and reported average loss per company was only 2-19% depending on the case study. Additionally, the BN model achieved better results than six alternative damage models in those case studies (except for one model in the Italian case study). Further, our exposure estimates mostly resulted in better predictions of the damage models compared to previously published pan-European exposure data, which tend to overestimate exposure. All in all, the methods allow easy modelling of commercial flood losses in the whole of Europe, since they are applicable even if only publicly-available datasets are obtainable. The methods achieve a higher accuracy than alternative approaches, and inherently provide confidence intervals, which is particularly valuable for decision making under high uncertainty.
Identifiants
pubmed: 32569902
pii: S0048-9697(20)33531-2
doi: 10.1016/j.scitotenv.2020.140011
pii:
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
140011Informations de copyright
Copyright © 2018. Published by Elsevier B.V.
Déclaration de conflit d'intérêts
Declaration of competing interest The authors declare no conflict of interest.