Journal cover Journal topic
Hydrology and Earth System Sciences An interactive open-access journal of the European Geosciences Union
doi:10.5194/hess-2017-152
© Author(s) 2017. This work is distributed
under the Creative Commons Attribution 3.0 License.
Research article
22 Mar 2017
Review status
This discussion paper is under review for the journal Hydrology and Earth System Sciences (HESS).
Use of GNSS SNR data to retrieve soil moisture and vegetation variables over a wheat crop
Sibo Zhang1,2, Nicolas Roussel3, Karen Boniface2,3,4,a, Minh Cuong Ha3, Frédéric Frappart5, José Darrozes3, Frédéric Baup4, and Jean-Christophe Calvet1 1CNRM – UMR3589 (Météo-France, CNRS), Toulouse, France
2Fondation STAE, Toulouse, France
3GET (UMR5563 CNRS/Université Paul Sabatier, UR254 IRD), Toulouse, France
4CESBIO, Université de Toulouse, CNES/CNRS/IRD/UPS, Toulouse, France
5LEGOS – UMR566 (CNES, CNRS, IRD, UPS), Toulouse, France
anow at: Joint Research Centre / European Commission, Ispra, Italy
Abstract. This work aims to estimate soil moisture and vegetation characteristics from Global Navigation Satellite System (GNSS) Signal to Noise Ratio (SNR) data using direct and reflected signals by the land surface surrounding a ground-based antenna. Observations are collected over a rainfed wheat field in southwestern France. The retrievals are compared with two independent reference datasets: in situ observations of soil moisture and vegetation height, and numerical simulations from the ISBA (Interactions between Soil, Biosphere and Atmosphere) land surface model. Results show that changes in soil moisture mainly affect the multipath phase of the SNR data (assuming the relative antenna height is constant) with little change in the dominant period of the SNR data. Changes in vegetation height are more likely to modulate the SNR dominant period derived from a wavelet analysis. Surface volumetric soil moisture can be estimated (R2 = 0.73, RMSE = 0.014 m3 m−3) when the wheat is smaller than 20 cm. The quality of the estimates markedly decreases when the vegetation height increases. This is because the GNSS signal is less affected by the soil contribution. A wavelet analysis provides an accurate estimation of the wheat crop height (R2 = 0.98, RMSE = 6.2 cm). The latter correlates with modeled above-ground biomass of the wheat from stem elongation to ripening. It is found that the vegetation retrievals are sensitive to changes in plant height of at least one wavelength. A simple smoothing of the retrieved plant height allows an excellent matching to in situ observations, and to modeled above-ground biomass.

Citation: Zhang, S., Roussel, N., Boniface, K., Ha, M. C., Frappart, F., Darrozes, J., Baup, F., and Calvet, J.-C.: Use of GNSS SNR data to retrieve soil moisture and vegetation variables over a wheat crop, Hydrol. Earth Syst. Sci. Discuss., doi:10.5194/hess-2017-152, in review, 2017.
Sibo Zhang et al.
Sibo Zhang et al.
Sibo Zhang et al.

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Short summary
GNSS SNR data were obtained over an intensively cultivated wheat field in southwestern France. The data were used to retrieve soil moisture and vegetation characteristics during the growing period of wheat. Soil moisture could not be retrieved after wheat tillering. A new algorithm based on a wavelet analysis was implemented and used to retrieve vegetation height.
GNSS SNR data were obtained over an intensively cultivated wheat field in southwestern France....
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