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    Author(s): G. Thirel; V. Andreassian; C. Perrin; J.-N. Audouy; L. Berthet; Pamela Edwards; N. Folton; C. Furusho; A. Kuentz; J. Lerat; G. Lindstrom; E. Martin; T. Mathevet; R. Merz; J. Parajka; D. Ruelland; J. Vaze
    Date: 2015
    Source: Hydrological Sciences Journal. 60(7-8): 1184-1199.
    Publication Series: Scientific Journal (JRNL)
    Station: Northern Research Station
    PDF: Download Publication  (1.0 MB)


    Testing hydrological models under changing conditions is essential to evaluate their ability to cope with changing catchments and their suitability for impact studies. With this perspective in mind, a workshop dedicated to this issue was held at the 2013 General Assembly of the International Association of Hydrological Sciences (IAHS) in Göteborg, Sweden, in July 2013, during which the results of a common testing experiment were presented. Prior to the workshop, the participants had been invited to test their own models on a common set of basins showing varying conditions specifically set up for the workshop. All these basins experienced changes, either in physical characteristics (e.g. changes in land cover) or climate conditions (e.g. gradual temperature increase). This article presents the motivations and organization of this experiment--that is--the testing (calibration and evaluation) protocol and the common framework of statistical procedures and graphical tools used to assess the model performances. The basins datasets are also briefly introduced (a detailed description is provided in the associated Supplementary material).

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    Thirel, G.; Andréassian, V.; Perrin, C.; Audouy, J.-N.; Berthet, L.; Edwards, P.; Folton, N.; Furusho, C.; Kuentz, A.; Lerat, J.; Lindström, G.; Martin, E.; Mathevet, T.; Merz, R.; Parajka, J.; Ruelland, D.; Vaze, J. 2015. Hydrology under change: an evaluation protocol to investigate how hydrological models deal with changing catchments. Hydrological Sciences Journal. 60(7-8): 1184-1199.


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    non-stationarity, IAHS workshop, calibration, evaluation, protocol, split-sample test, changing catchments dataset

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