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@ARTICLE{Jonard:21233,
author = {Jonard, F. and Weihermüller, L. and Vereecken, H. and
Lambot, S.},
title = {{A}ccounting for soil surface roughness in the inversion of
ultrawideband off-ground {GPR} signal for soil moisture
retrieval},
journal = {Geophysics},
volume = {77},
issn = {0016-8033},
address = {Tulsa, Okla.},
publisher = {SEG},
reportid = {PreJuSER-21233},
pages = {H1 - H7},
year = {2012},
note = {This work was supported in part by the Transregional
Collaborative Research Centre 32 funded by the DFG (Deutsche
Forschungsgemeinschaft) and in part by the FNRS (Fonds
National de la Recherche Scientifique, Belgium). The authors
are particularly grateful to Khan Zaib Jadoon of the
Agrosphere Institute, Forschungszentrum Julich, for his help
during the project. Finally, we also thank the anonymous
reviewers for their constructive comments.},
abstract = {We combined a full-waveform ground-penetrating radar (GPR)
model with a roughness model to retrieve surface soil
moisture through signal inversion. The proposed approach was
validated under laboratory conditions with measurements
performed above a sand layer subjected to seven different
water contents and four different surface roughness
conditions. The radar measurements were performed in the
frequency domain in the range of 1-3 GHz and the roughness
amplitude standard deviation was varied from 0 to 1 cm. Two
inversion strategies were investigated: (1) Full-waveform
inversion using the correct model configuration, and (2)
inversion focused on the surface reflection only. The
roughness model provided a good description of the
frequency-dependent roughness effect. For the full-waveform
analysis, accounting for roughness permitted us to
simultaneously retrieve water content and roughness
amplitude. However, in this approach, information on soil
layering was assumed to be known. For the surface reflection
analysis, which is applicable under field conditions,
accounting for roughness only enabled water content to be
reconstructed, but with a root mean square error (RMS) in
terms of water content of 0.034 m(3) m(-3) compared to an
RMS of 0.068 m(3) m(-3) for an analysis where roughness is
neglected. However, this inversion strategy required a
priori information on soil surface roughness, estimated,
e.g., from laser profiler measurements.},
keywords = {J (WoSType)},
cin = {IBG-3},
ddc = {550},
cid = {I:(DE-Juel1)IBG-3-20101118},
pnm = {Terrestrische Umwelt},
pid = {G:(DE-Juel1)FUEK407},
shelfmark = {Geochemistry $\&$ Geophysics},
typ = {PUB:(DE-HGF)16},
UT = {WOS:000300767000019},
doi = {10.1190/geo2011-0054.1},
url = {https://juser.fz-juelich.de/record/21233},
}