Open AccessElectromagnetic Inversion of GPR Signals and Subsequent Hydrodynamic Inversion to Estimate Effective Vadose Zone Hydraulic Properties
Author(s) -
Lambot S.,
Antoine M.,
Bosch I.,
Slob E. C.,
Vanclooster M.
Publication year - 2004
Publication title -
vadose zone journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.036
H-Index - 81
ISSN - 1539-1663
DOI - 10.2136/vzj2004.1072
Subject(s) - ground penetrating radar , reflectometry , vadose zone , richards equation , radar , inversion (geology) , time domain , inverse problem , geology , remote sensing , finite difference time domain method , soil science , groundwater , water content , geotechnical engineering , optics , computer science , geomorphology , physics , mathematics , telecommunications , mathematical analysis , structural basin , computer vision
We combine electromagnetic inversion of ground penetrating radar (GPR) signals with hydrodynamic inverse modeling to identify the effective soil hydraulic properties of a sand in laboratory conditions. Ground penetrating radar provides soil moisture time series that are subsequently used as input in the hydrodynamic inverse procedure. The technique relies on an ultrawide band (UWB) stepped frequency continuous wave (SFCW) radar combined with an off‐ground monostatic transverse electromagnetic (TEM) horn antenna. Ground penetrating radar signal forward modeling is based on the exact solution of the three‐dimensional Maxwell equations for describing free wave propagation and on linear systems in series and parallel for describing wave propagation in the antenna. Water flow in the sand is described by the one‐dimensional Richards equation using the Mualem–van Genuchten parameterization. Both model inversions are formulated by the classical least‐squares problem and are performed iteratively using advanced global optimization techniques. Compared with time domain reflectometry (TDR), results demonstrated the appropriateness of the GPR integrated approach to measure soil moisture remotely. In particular, the approach was found to be less sensitive to the inherent small‐scale heterogeneities. Hydrodynamic inversion of soil moisture data led to hydraulic parameters agreeing reasonably well with direct measurements. The observed discrepancies were attributed to the different characterization scales and samples. The overall integrated approach offers great promise to map the effective hydraulic properties of the shallow subsurface at a high spatial resolution.