Articles | Volume 386
https://doi.org/10.5194/piahs-386-181-2024
https://doi.org/10.5194/piahs-386-181-2024
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

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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.