Articles | Volume 20, issue 4
Nat. Hazards Earth Syst. Sci., 20, 1149–1161, 2020
https://doi.org/10.5194/nhess-20-1149-2020
Nat. Hazards Earth Syst. Sci., 20, 1149–1161, 2020
https://doi.org/10.5194/nhess-20-1149-2020

Invited perspectives 29 Apr 2020

Invited perspectives | 29 Apr 2020

Invited perspectives: How machine learning will change flood risk and impact assessment

Dennis Wagenaar et al.

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Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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AR: Author's response | RR: Referee report | ED: Editor decision
ED: Reconsider after major revisions (further review by editor and referees) (15 Feb 2020) by Heidi Kreibich
AR by Dennis Wagenaar on behalf of the Authors (17 Feb 2020)  Author's response    Manuscript
ED: Referee Nomination & Report Request started (23 Feb 2020) by Heidi Kreibich
RR by Anonymous Referee #1 (09 Mar 2020)
RR by Fernando Nardi (15 Mar 2020)
ED: Publish subject to technical corrections (15 Mar 2020) by Heidi Kreibich
AR by Dennis Wagenaar on behalf of the Authors (30 Mar 2020)  Author's response    Manuscript
Short summary
This invited perspective paper addresses how machine learning may change flood risk and impact assessments. It goes through different modelling components and provides an analysis of how current assessments are done without machine learning, current applications of machine learning and potential future improvements. It is based on a 2-week-long intensive collaboration among experts from around the world during the Understanding Risk Field lab on urban flooding in June 2019.
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