Hydrology and Earth System Sciences
Hydrology and Earth System Sciences
HESS
Articles | Volume 30, issue 11
Articles | Volume 30, issue 11
https://doi.org/10.5194/hess-30-3497-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-30-3497-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 30, issue 11
Research article
 | 
11 Jun 2026
Research article |  | 11 Jun 2026

Testing discharge assimilation strategies to enhance short-range AI-based operational rainfall–runoff forecasts

Bob E. Saint-Fleur, Eric Gaume, Florian Surmont, Nicolas Akil, and Dominique Theriez

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Short summary
This paper highlights the importance of discharge assimilation (DA) for artificial intelligence (AI)-based operational discharge forecasting. Using two public datasets from France and the USA, simulated discharge from two rainfall-runoff models, and a multilayer perceptron for implementation, we evaluate three DA strategies under both deterministic and probabilistic forecasting approaches. Results show that DA is crucial and that model performance may decrease between the two forecasting cases.
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