Articles | Volume 28, issue 4
https://doi.org/10.5194/hess-28-851-2024
https://doi.org/10.5194/hess-28-851-2024
Research article
 | 
23 Feb 2024
Research article |  | 23 Feb 2024

Flow intermittence prediction using a hybrid hydrological modelling approach: influence of observed intermittence data on the training of a random forest model

Louise Mimeau, Annika Künne, Flora Branger, Sven Kralisch, Alexandre Devers, and Jean-Philippe Vidal

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Cited articles

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Short summary
Modelling flow intermittence is essential for predicting the future evolution of drying in river networks and better understanding the ecological and socio-economic impacts. However, modelling flow intermittence is challenging, and observed data on temporary rivers are scarce. This study presents a new modelling approach for predicting flow intermittence in river networks and shows that combining different sources of observed data reduces the model uncertainty.
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