Proceedings of IAHS
Proceedings of IAHS
PIAHS
Articles | Volume 386
Articles | Volume 386
https://doi.org/10.5194/piahs-386-181-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/piahs-386-181-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 386
Post-conference publication
 | 
19 Apr 2024
Post-conference publication |  | 19 Apr 2024

Flood damage model bias caused by aggregation

Seth Bryant, Heidi Kreibich, and Bruno Merz

Viewed

Total article views: 258 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
168 74 16 258 12 11
  • HTML: 168
  • PDF: 74
  • XML: 16
  • Total: 258
  • BibTeX: 12
  • EndNote: 11
Views and downloads (calculated since 19 Apr 2024)
Cumulative views and downloads (calculated since 19 Apr 2024)

Viewed (geographical distribution)

Total article views: 244 (including HTML, PDF, and XML) Thereof 244 with geography defined and 0 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 13 Dec 2024
Download
Short summary
Our study found that simplifying data in flood risk models can introduce errors. We tested 344 damage functions and found errors up to 40 % of the total asset value. This means large-scale flood risk assessments may have significant errors due to the modelling approach. Our research highlights the need for more attention to data aggregation in flood risk models.
Read more