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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 3
Hydrol. Earth Syst. Sci., 12, 751–767, 2008
https://doi.org/10.5194/hess-12-751-2008
© Author(s) 2008. This work is distributed under
the Creative Commons Attribution 3.0 License.
Hydrol. Earth Syst. Sci., 12, 751–767, 2008
https://doi.org/10.5194/hess-12-751-2008
© Author(s) 2008. This work is distributed under
the Creative Commons Attribution 3.0 License.

  23 May 2008

23 May 2008

Comparison of soil moisture fields estimated by catchment modelling and remote sensing: a case study in South Africa

T. Vischel1,*, G. G. S. Pegram1, S. Sinclair1, W. Wagner2, and A. Bartsch2 T. Vischel et al.
  • 1Civil Engineering Programme, University of KwaZulu-Natal, Durban 4041, South Africa
  • 2Institute of Photogrammetry and Remote Sensing, Vienna University of Technology, Austria
  • *now at: Laboratoire d'étude des Transferts en Hydrologie et Environnement (UMR 5564), 38000 Grenoble, France

Abstract. The paper compares two independent approaches to estimate soil moisture at the regional scale over a 4625 km2 catchment (Liebenbergsvlei, South Africa). The first estimate is derived from a physically-based hydrological model (TOPKAPI). The second estimate is derived from the scatterometer on board the European Remote Sensing satellite (ERS). Results show a good correspondence between the modelled and remotely sensed soil moisture, particularly with respect to the soil moisture dynamic, illustrated over two selected seasons of 8 months, yielding regression R2 coefficients lying between 0.68 and 0.92. Such a close similarity between these two different, independent approaches is very promising for (i) remote sensing in general (ii) the use of hydrological models to back-calculate and disaggregate the satellite soil moisture estimate and (iii) for hydrological models to assimilate the remotely sensed soil moisture.

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