Articles | Volume 19, issue 11
https://doi.org/10.5194/nhess-19-2513-2019
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, Mohammad E. Banihabib, Abbas Roozbahani, and Jörg Dietrich

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Latest update: 23 Nov 2024
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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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