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@ARTICLE{Rao:865999,
author = {Rao, Sathyanarayan and Meunier, Félicien and Ehosioke,
Solomon and Lesparre, Nolwenn and Kemna, Andreas and Nguyen,
Frédéric and Garré, Sarah and Javaux, Mathieu},
title = {{I}mpact of {M}aize {R}oots on {S}oil–{R}oot {E}lectrical
{C}onductivity: {A} {S}imulation {S}tudy},
journal = {Vadose zone journal},
volume = {18},
number = {1},
issn = {1539-1663},
address = {Alexandria, Va.},
publisher = {GeoScienceWorld},
reportid = {FZJ-2019-05259},
pages = {},
year = {2019},
abstract = {Electrical resistivity tomography (ERT) has become an
important tool for studying root-zone soil water fluxes
under field conditions. The results of ERT translate to
water content via empirical pedophysical relations, usually
ignoring the impact of roots; however, studies in the
literature have shown that roots in soils may actually play
a non-negligible role in the bulk electrical conductivity
(σ) of the soil–root continuum, but we do not completely
understand the impact of root segments on ERT measurements.
In this numerical study, we coupled an electrical model with
a plant–soil water flow model to investigate the impact of
roots on virtual ERT measurements. The coupled model can
produce three-dimensional simulations of root growth and
development, water flow in soil and root systems, and
electrical transfer in the soil–root continuum. Our
electrical simulation illustrates that in rooted soils, for
every $1\%$ increase in the root/sand volume ratio, there
can be a 4 to $18\%$ increase in the uncertainty of σ
computed via the model, caused by the presence of root
segments; the uncertainty in a loam medium is 0.2 to
$1.5\%.$ The influence of root segments on ERT measurements
depends on the root surface area (r = ∼0.6) and the σ
contrast between roots and the soil (r = ∼0.9), as
revealed by correlation analysis. This study is important in
the context of accurate water content predictions for
automated irrigation systems in sandy soil},
cin = {IBG-3},
ddc = {550},
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:000491269700001},
doi = {10.2136/vzj2019.04.0037},
url = {https://juser.fz-juelich.de/record/865999},
}