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Soil Science Society of America, Vadose Zone Journal, 4(11), p. 0

DOI: 10.2136/vzj2011.0177

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Estimation of soil hydraulic parameters in the field by integrated hydrogeophysical inversion of time-lapse ground-penetrating radar data

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This paper is available in a repository.

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Abstract

An integrated hydrogeophysical inversion approach was used to remotely infer the unsaturated soil hydraulic parameters from time-lapse ground-penetrating radar (GPR) data collected at a fixed location over a bare agricultural field. The GPR model combines a full-waveform solution of Maxwell's equations for three-dimensional wave propaga- tion in planar layered media together with global reflection and transmission functions to account for the antenna and its interactions with the medium. The hydrological simu- lator HYDRUS-1D was used with a two layer single- and dual-porosity model. The radar model was coupled to the hydrodynamic model, such that the soil electrical properties (permitivity and conductivity) that serve as input to the GPR model become a function of the hydrodynamic model output (water content), thereby permiting estimation of the soil hydraulic parameters from the GPR data in an inversion loop. To monitor the soil water con- tent dynamics, time-lapse GPR and time domain reflectometry (TDR) measurements were performed, whereby only GPR data was used in the inversion. Significant effects of water dynamics were observed in the time-lapse GPR data and in particular precipitation and evaporation events were clearly visible. The dual porosity model provided betier results compared to the single porosity model for describing the soil water dynamics, which is sup- ported by field observations of macropores. Furthermore, the GPR-derived water content profiles reconstructed from the integrated hydrogeophysical inversion were in good agree- ment with TDR observations. These results suggest that the proposed method is promising for non-invasive characterization of the shallow subsurface hydraulic properties and moni- toring water dynamics at the field scale. © Soil Science Society of America.