Preprints
https://doi.org/10.5194/hess-2020-596
https://doi.org/10.5194/hess-2020-596

  22 Dec 2020

22 Dec 2020

Review status: this preprint is currently under review for the journal HESS.

A Robust calibration/validation protocol of a hydrological model using hidden Markov states

Etienne Guilpart, Vahid Espanmanesh, Amaury Tilmant, and François Anctil Etienne Guilpart et al.
  • Département de génie civil et de génie des eaux, Université Laval, Québec, Canada

Abstract. The impacts of climate and land-use changes make the stationary assumption in hydrology obsolete. Moreover, there is still considerable uncertainty regarding the future evolution of the Earth's climate and the extent of the alteration of flow regimes. 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. We propose a calibration/validation protocol based on the differential split-sample test and numerous, contrasted, climate sequences identified through a Hidden Markov Model (HMM) classification. The proposed protocol is tested on the Senegal River in West Africa. Results show that when the time series of river discharges does not exhibit a clear climate trend, or when it has multiple change points, classical rupture tests are useless and HMM classification is a viable alternative as long as the climate sub-sequences are long enough.

Etienne Guilpart et al.

 
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Status: final response (author comments only)
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Etienne Guilpart et al.

Etienne Guilpart et al.

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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. We propose a calibration/validation protocol based on the differential split-sample test and numerous, contrasted, climate sequences identified through a Hidden Markov Model (HMM) classification. The proposed protocol is tested on the Senegal River.