Preprints
https://doi.org/10.5194/hess-2018-342
https://doi.org/10.5194/hess-2018-342
29 Jun 2018
 | 29 Jun 2018
Status: this discussion paper is a preprint. It has been under review for the journal Hydrology and Earth System Sciences (HESS). The manuscript was not accepted for further review after discussion.

Tailor-made spatial patterns for hydrological model parameters combining regionalisation methods

Laura Rouhier, Federico Garavaglia, Matthieu Le Lay, Timothée Michon, William Castaings, Nicolas Le Moine, Frédéric Hendrickx, Céline Monteil, and Pierre Ribstein

Abstract. Calibration of spatially distributed models is an important issue given their over-parameterisation. Three common regionalisation methods can be distinguished: transposition, prescription and constraint. This paper proposes a strategy where the three methods are combined to provide several spatial patterns depending on the model parameters. On the one hand, insensitive and equifinal parameters are prescribed uniformly while parameters with a physical meaning are prescribed at the mesh scale. On the other hand, parameters linked with a proxy runoff signature are constrained over each sub-basin and the remaining parameters are transposed with a physio-climatic pattern constructed over the calibration sub-basins.

The above tailor-made pattern regionalisation is applied at the daily time step over two large French catchments, the Loire catchment at Gien covering 35 707 km2 and the Durance catchment at Cadarache covering 11 738 km2. It is then evaluated and compared to a single regionalisation method over dozens of validation stations, treated as ungauged during the parameter regionalisation process. For that purpose, simulated and observed streamflows are compared in light of four runoff signatures: daily runoff, seasonality, flood and low flow. The results show that the tailor-made patterns succeed in significantly enhancing almost all the signatures. The enhancement appears for the least well-modelled stations and contributes a 20 % improvement towards gauged modelling. It also tends to guarantee a minimum performance in an ungauged context since the minimum KGE is now 0.4 whatever runoff signature is used.

Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this preprint. The responsibility to include appropriate place names lies with the authors.
Laura Rouhier, Federico Garavaglia, Matthieu Le Lay, Timothée Michon, William Castaings, Nicolas Le Moine, Frédéric Hendrickx, Céline Monteil, and Pierre Ribstein
 
Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version Supplement - Supplement
Laura Rouhier, Federico Garavaglia, Matthieu Le Lay, Timothée Michon, William Castaings, Nicolas Le Moine, Frédéric Hendrickx, Céline Monteil, and Pierre Ribstein
Laura Rouhier, Federico Garavaglia, Matthieu Le Lay, Timothée Michon, William Castaings, Nicolas Le Moine, Frédéric Hendrickx, Céline Monteil, and Pierre Ribstein

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Short summary
Parameter estimation of distributed hydrological models is usually conducted with a single method. However, the main methods can be combined to consider differently the model parameters according to their characteristics. The strategy presented in the paper takes advantage of three different methods to provide four different spatial patterns. This tailor-made method then proves to be more robust and more relevant for prediction in ungauged basins while significantly reducing the number of degree.