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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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Volume 373
Proc. IAHS, 373, 69-72, 2016
https://doi.org/10.5194/piahs-373-69-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
Proc. IAHS, 373, 69-72, 2016
https://doi.org/10.5194/piahs-373-69-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

  12 May 2016

12 May 2016

Added-value from a multi-criteria selection of donor catchments in the prediction of continuous streamflow series at ungauged pollution control-sites

Gilles Drogue1, Wiem Ben Khediri1, and Céline Conan2 Gilles Drogue et al.
  • 1Laboratoire LOTERR, Université de Lorraine, Metz, 57045 CEDEX 1, France
  • 2Agence de l'Eau Rhin-Meuse, Moulins Lès Metz, 57161 BP 30019, France

Abstract. We explore the potential of a multi-criteria selection of donor catchments in the prediction of continuous streamflow series by the spatial proximity method. Three criteria have been used: (1) spatial proximity; (2) physical similarity; (3) stream gauging network topology. An extensive assessment of our spatial proximity method variant is made on a 149 catchment-data set located in the Rhine-Meuse catchment. The competitiveness of the method is evaluated against spatial interpolation of catchment model parameters with ordinary kriging. We found that the spatial proximity approach is more efficient than ordinary kriging. When distance to upstream/downstream stream gauge stations is considered as a second order criterion in the selection of donor catchments, an unprecedented level of efficiency is reached for nested catchments. Nevertheless, the spatial proximity method does not take advantage from physical similarity between donor catchments and receiver catchments because catchments that are the most hydrologically similar to each catchment poorly match with the catchments that are the most physically similar to each catchment.

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River flow series are the essential input of many studies and applications aiming to add value and interpret the water quality data collected at pollution-control sites. They are however available only in a limited number of points on the river network where flows are known. Our paper assess the performance of strategies for simulating incomplete or missing flow series. They rest on the use of a simple hydrological model and the assumption that flows are similar between neighbor catchments.
River flow series are the essential input of many studies and applications aiming to add value...
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