Articles | Volume 25, issue 8
https://doi.org/10.5194/hess-25-4611-2021
https://doi.org/10.5194/hess-25-4611-2021
Research article
 | 
30 Aug 2021
Research article |  | 30 Aug 2021

Combining split-sample testing and hidden Markov modelling to assess the robustness of hydrological models

Etienne Guilpart, Vahid Espanmanesh, Amaury Tilmant, and François Anctil

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Latest update: 13 Dec 2024
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Short summary
The stationary assumption in hydrology has become obsolete because of climate changes. In that context, it is crucial to assess the performance of a hydrologic model over a wide range of climates and their corresponding hydrologic conditions. In this paper, numerous, contrasted, climate sequences identified by a hidden Markov model (HMM) are used in a differential split-sample testing framework to assess the robustness of a hydrologic model. We illustrate the method on the Senegal River.