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Hydrology and Earth System Sciences An interactive open-access journal of the European Geosciences Union
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Volume 12, issue 6
Hydrol. Earth Syst. Sci., 12, 1323–1337, 2008
https://doi.org/10.5194/hess-12-1323-2008
© Author(s) 2008. This work is distributed under
the Creative Commons Attribution 3.0 License.

Special issue: Remote sensing in hydrological sciences

Hydrol. Earth Syst. Sci., 12, 1323–1337, 2008
https://doi.org/10.5194/hess-12-1323-2008
© Author(s) 2008. This work is distributed under
the Creative Commons Attribution 3.0 License.

  10 Dec 2008

10 Dec 2008

From near-surface to root-zone soil moisture using an exponential filter: an assessment of the method based on in-situ observations and model simulations

C. Albergel1, C. Rüdiger*,1, T. Pellarin2, J.-C. Calvet1, N. Fritz1, F. Froissard1, D. Suquia1, A. Petitpa1, B. Piguet1, and E. Martin1 C. Albergel et al.
  • 1CNRM/GAME (Météo-France, CNRS), Toulouse, France
  • 2LTHE (UMR 5564), Grenoble, France
  • *now with: Department of Civil and Environmental Engineering, The University of Melbourne, Melbourne, Australia

Abstract. A long term data acquisition effort of profile soil moisture is under way in southwestern France at 13 automated weather stations. This ground network was developed in order to validate remote sensing and model soil moisture estimates. In this paper, both those in situ observations and a synthetic data set covering continental France are used to test a simple method to retrieve root zone soil moisture from a time series of surface soil moisture information. A recursive exponential filter equation using a time constant, T, is used to compute a soil water index. The Nash and Sutcliff coefficient is used as a criterion to optimise the T parameter for each ground station and for each model pixel of the synthetic data set. In general, the soil water indices derived from the surface soil moisture observations and simulations agree well with the reference root-zone soil moisture. Overall, the results show the potential of the exponential filter equation and of its recursive formulation to derive a soil water index from surface soil moisture estimates. This paper further investigates the correlation of the time scale parameter T with soil properties and climate conditions. While no significant relationship could be determined between T and the main soil properties (clay and sand fractions, bulk density and organic matter content), the modelled spatial variability and the observed inter-annual variability of T suggest that a weak climate effect may exist.

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