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Proceedings of the International Association of Hydrological Sciences An open-access publication for refereed proceedings in hydrology

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Proc. IAHS, 373, 87-94, 2016
https://doi.org/10.5194/piahs-373-87-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
 
12 May 2016
Spatial variability of the parameters of a semi-distributed hydrological model
Alban de Lavenne, Guillaume Thirel, Vazken Andréassian, Charles Perrin, and Maria-Helena Ramos Irstea, Hydrosystems and Bioprocesses Research Unit (HBAN), 1, rue Pierre-Gilles de Gennes, CS 10030, 92761 Antony Cedex, France
Abstract. Ideally, semi-distributed hydrologic models should provide better streamflow simulations than lumped models, along with spatially-relevant water resources management solutions. However, the spatial distribution of model parameters raises issues related to the calibration strategy and to the identifiability of the parameters. To analyse these issues, we propose to base the evaluation of a semi-distributed model not only on its performance at streamflow gauging stations, but also on the spatial and temporal pattern of the optimised value of its parameters. We implemented calibration over 21 rolling periods and 64 catchments, and we analysed how well each parameter is identified in time and space. Performance and parameter identifiability are analysed comparatively to the calibration of the lumped version of the same model. We show that the semi-distributed model faces more difficulties to identify stable optimal parameter sets. The main difficulty lies in the identification of the parameters responsible for the closure of the water balance (i.e. for the particular model investigated, the intercatchment groundwater flow parameter).

Citation: de Lavenne, A., Thirel, G., Andréassian, V., Perrin, C., and Ramos, M.-H.: Spatial variability of the parameters of a semi-distributed hydrological model, Proc. IAHS, 373, 87-94, https://doi.org/10.5194/piahs-373-87-2016, 2016.
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Short summary
Developing modelling tools that help to understand the spatial distribution of water resources is a key issue for better management. Ideally, hydrological models which discretise catchment space into sub-catchments should offer better streamflow simulations than lumped models, along with spatially-relevant water resources management solutions. However we demonstrate that those model raise other issues related to the calibration strategy and to the identifiability of the parameters.
Developing modelling tools that help to understand the spatial distribution of water resources...
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