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Hydrology and Earth System Sciences An interactive open-access journal of the European Geosciences Union
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Volume 17, issue 4
Hydrol. Earth Syst. Sci., 17, 1319–1330, 2013
https://doi.org/10.5194/hess-17-1319-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
Hydrol. Earth Syst. Sci., 17, 1319–1330, 2013
https://doi.org/10.5194/hess-17-1319-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 08 Apr 2013

Research article | 08 Apr 2013

A method for low-flow estimation at ungauged sites: a case study in Wallonia (Belgium)

M. Grandry, S. Gailliez, C. Sohier, A. Verstraete, and A. Degré M. Grandry et al.
  • Univ. Liège – Gembloux Agro-Bio Tech., Soil–Water Systems, Passage des Déportés, 2, 5030 Gembloux, Belgium

Abstract. Well-integrated water management can notably require estimating low flows at any point of a river. Depending on the management practice, it can be needed for various return periods. This is seldom addressed in the literature. This paper shows the development of a full analysis chain including quality analysis of gauging stations, low-flow frequency analysis, and building of a global model to assess low-flow indices on the basis of catchment physical parameters.

The most common distributions that fit low-flow data in Wallonia were two-parameter lognormal and gamma. The recession coefficient and percolation were the most explanatory variables, regardless of the return period. The determination coefficients of the models ranged from 0.51 to 0.67 for calibration and from 0.61 to 0.80 for validation. The regression coefficients were found to be linked to the return period. This was used to design a complete equation that gives the low-flow index based on physical parameters and the desired return period (in a 5 to 50 yr range).

The interest of regionalisation and the development of regional models are also discussed. Four homogeneous regions are identified, but to date the global model remains more robust due to the limited number of 20-yr-long gauging stations. This should be reconsidered in the future when enough data will be available.

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