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@ARTICLE{Mangel:203156,
author = {Mangel, Adam R. and Moysey, Stephen M. J. and van der Kruk,
Jan},
title = {{R}esolving precipitation induced water content profiles by
inversion of dispersive {GPR} data: {A} numerical study},
journal = {Journal of hydrology},
volume = {525},
issn = {0022-1694},
address = {Amsterdam [u.a.]},
publisher = {Elsevier},
reportid = {FZJ-2015-05161},
pages = {496 - 505},
year = {2015},
abstract = {Surface-based ground-penetrating radar (GPR) measurements
have significant potential for monitoring dynamic hydrologic
processes at multiple scales in time and space. At early
times during infiltration into a soil, the zone above the
wetting front may act as a low-velocity waveguide that traps
GPR waves, thereby causing dispersion and making
interpretation of the data using standard methods difficult.
In this work, we show that the dispersion is dependent upon
the distribution of water within the waveguide, which is
controlled by soil hydrologic properties. Simulations of
infiltration were performed by varying the n-parameter of
the Mualem–van Genuchten equation using HYDRUS-1D; the
associated GPR data were simulated to evaluate the influence
of dispersion. We observed a notable decrease in wave
dispersion as the sharpness of the wetting front profile
decreased. Given the sensitivity of the dispersion effect to
the wetting front profile, we also evaluated whether the
water content distribution can be determined through
inversion of the dispersive GPR data. We found that a global
grid search combined with the simplex algorithm was able to
estimate the average water content when the wetted zone is
divided into 2 layers. This approach was incapable, however,
of representing the gradational nature of the water content
distribution behind the wetting front. In contrast, the
shuffled complex evolution algorithm was able to constrain a
piece-wise linear function to closely match the shallow
gradational water content profile. In both the layered and
piece-wise linear case, the sensitivity of the dispersive
data dropped sharply below the wetting front, which in this
case was around 20 cm, i.e., twice the average wavelength,
for a 900 MHz GPR survey. This study demonstrates that
dispersive GPR data has significant potential for capturing
the early-time dynamics of infiltration that cannot be
obtained with standard GPR analysis approaches.},
cin = {IBG-3},
ddc = {690},
cid = {I:(DE-Juel1)IBG-3-20101118},
pnm = {255 - Terrestrial Systems: From Observation to Prediction
(POF3-255)},
pid = {G:(DE-HGF)POF3-255},
typ = {PUB:(DE-HGF)16},
UT = {WOS:000355885600042},
doi = {10.1016/j.jhydrol.2015.04.011},
url = {https://juser.fz-juelich.de/record/203156},
}