Articles | Volume 19, issue 11
Nat. Hazards Earth Syst. Sci., 19, 2513–2524, 2019
https://doi.org/10.5194/nhess-19-2513-2019

Special issue: Hydroclimatic extremes and impacts at catchment to regional...

Nat. Hazards Earth Syst. Sci., 19, 2513–2524, 2019
https://doi.org/10.5194/nhess-19-2513-2019

Research article 13 Nov 2019

Research article | 13 Nov 2019

Bayesian network model for flood forecasting based on atmospheric ensemble forecasts

Leila Goodarzi 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) (26 Aug 2019) by Fernando Domínguez-Castro
AR by Jörg Dietrich on behalf of the Authors (09 Sep 2019)  Author's response    Manuscript
ED: Referee Nomination & Report Request started (23 Sep 2019) by Fernando Domínguez-Castro
RR by Anonymous Referee #2 (27 Sep 2019)
ED: Publish subject to technical corrections (09 Oct 2019) by Fernando Domínguez-Castro
AR by Jörg Dietrich on behalf of the Authors (11 Oct 2019)  Author's response    Manuscript
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Short summary
We developed a novel approach in using Bayesian networks (BNs) for ensemble flood forecasting in a case study in Iran. This allows fast early warning without the need for hydrological modelling. We recommend to combine precipitation ensembles with hydrological initial conditions in the BN. The number of observed flood events is low by nature. Under the limited amount of data, BN outperformed artificial neural networks with good results. Future work will validate the concept further.
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