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Measuring soil surface water content in irrigated areas of southern Tunisia using full‐waveform inversion of proximal GPR data
Author(s) -
Lambot Sébastien,
Slob Evert,
Chavarro Diana,
Lubczynski Maciek,
Vereecken Harry
Publication year - 2008
Publication title -
near surface geophysics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.639
H-Index - 39
eISSN - 1873-0604
pISSN - 1569-4445
DOI - 10.3997/1873-0604.2008028
Subject(s) - ground penetrating radar , reflectometry , water content , geology , reflection coefficient , radar , remote sensing , time domain , soil science , horn antenna , geotechnical engineering , optics , antenna (radio) , telecommunications , physics , slot antenna , computer science , directional antenna , computer vision
ABSTRACT Full‐waveform inverse modelling of proximal ground‐penetrating radar was used to measure soil surface water content in irrigated areas of southern Tunisia. The ground‐penetrating radar system consisted of a hand held vector network analyser combined with an off‐ground monostatic horn antenna, thereby setting up an ultra wideband stepped‐frequency continuous‐wave radar. Inversion of the radar Green’s function was performed in the time‐domain, on a time window focused on the surface reflection only. Results were compared with volumetric and time‐domain reflectometry measurements, as well as with an improved version of the standard reflection coefficient method. Except for water contents close to saturation, good agreements were obtained between ground‐penetrating radar, time‐domain reflectometry and volumetric samples. Significant differences were observed when the soil electric conductivity was high and could not be neglected anymore in the inversion process. Accounting for electric conductivity provided better results. Remaining errors were attributed to the different scales of characterization dealt with in relation to the vertical variability of water content in the top few centimetres of the soil. The proposed method appears to be more practical and accurate than the standard reflection coefficient method and shows great promise for real‐time mapping of surface soil moisture at the field scale.