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Hydrology and Earth System Sciences An interactive open-access journal of the European Geosciences Union
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Volume 16, issue 4
Hydrol. Earth Syst. Sci., 16, 1171–1189, 2012
https://doi.org/10.5194/hess-16-1171-2012
© Author(s) 2012. This work is distributed under
the Creative Commons Attribution 3.0 License.
Hydrol. Earth Syst. Sci., 16, 1171–1189, 2012
https://doi.org/10.5194/hess-16-1171-2012
© Author(s) 2012. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 11 Apr 2012

Research article | 11 Apr 2012

Multimodel evaluation of twenty lumped hydrological models under contrasted climate conditions

G. Seiller1, F. Anctil1, and C. Perrin2 G. Seiller et al.
  • 1Chaire de recherche EDS en prévisions et actions hydrologiques, Université Laval, Département de génie civil et de génie des eaux, 1065, avenue de la Médecine, Québec, Qc, G1V 0A6, Canada
  • 2Irstea, Hydrosystems and Bioprocesses Research Unit (HBAN), 1, rue Pierre-Gilles de Gennes, 92761 Antony Cedex, France

Abstract. This paper investigates the temporal transposability of hydrological models under contrasted climate conditions and evaluates the added value of using an ensemble of model structures for flow simulation. This is achieved by applying the Differential Split Sample Test procedure to twenty lumped conceptual models on a catchment in the Province of Québec (Canada) and another one in the State of Bavaria (Germany). First, a calibration/validation procedure was applied on four historical non-continuous periods with contrasted climate conditions. Then, model efficiency was quantified individually (for each model) and collectively (for the model ensemble). The individual analysis evaluated model performance and robustness. The ensemble investigation, based on the average of simulated discharges, focused on the twenty-member ensemble and all possible model subsets. Results showed that using a single model may provide hazardous results when the model is to be applied in contrasted conditions. Overall, some models turned out as a good compromise in terms of performance and robustness, but generally not as much as the twenty-model ensemble. Model subsets offered yet improved performance over the twenty-model ensemble, but at the expanse of spatial transposability (i.e. need of site-specific analysis).

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