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@ARTICLE{Dimitrov:150362,
author = {Dimitrov, M. and Vanderborght, J. and Kostov, K. G. and
Jadoon, K. Z. and Weihermüller, L. and Jackson, T. J. and
Bindlish, R. and Pachepsky, Y. and Schwank, M. and
Vereecken, H.},
title = {{S}oil {H}ydraulic {P}arameters and {S}urface {S}oil
{M}oisture of a {T}illed {B}are {S}oil {P}lot {I}nversely
{D}erived from {L}-{B}and {B}rightness {T}emperatures},
journal = {Vadose zone journal},
volume = {13},
number = {1},
issn = {1539-1663},
address = {Madison, Wis.},
publisher = {SSSA},
reportid = {FZJ-2014-00432},
pages = {1-18},
year = {2014},
abstract = {L-band radiometers can be used to remotely monitor the
microwave brightness temperature of land surfaces. We
investigated how soil hydraulic properties and soil moisture
contents of a bare soil plot can be inferred from L-band
brightness temperatures using a coupled inversion
approach.We coupled a radiative transfer model and a soil
hydrologic model (HYDRUS 1D) with an optimization routine to
derive soil hydraulic parameters, surface roughness, and
soil moisture of a tilled bare soil plot using measured
brightness temperatures at 1.4 GHz (L-band), rainfall, and
potential soil evaporation. The robustness of the approach
was evaluated using five 28-d data sets representing
different meteorological conditions. We considered two soil
hydraulic property models: the unimodal Mualem–van
Genuchten and the bimodal model of Durner. Microwave
radiative transfer was modeled by three different
approaches: the Fresnel equation with depth-averaged
dielectric permittivity of either 2- or 5-cm-thick surface
layers and a coherent radiative transfer model (CRTM) that
accounts for vertical gradients in dielectric permittivity.
Brightness temperatures simulated by the CRTM and the
2-cm-layer Fresnel model fitted well to the measured ones.
L-band brightness temperatures are therefore related to the
dielectric permittivity and soil moisture in a 2-cm-thick
surface layer. The surface roughness parameter that was
derived from brightness temperatures using inverse modeling
was similar to direct estimates from laser profiler
measurements. The laboratory-derived water retention curve
was bimodal and could be retrieved consistently for the
different periods from brightness temperatures using inverse
modeling. A unimodal soil hydraulic property function
underestimated the hydraulic conductivity near saturation.
Surface soil moisture contents simulated using retrieved
soil hydraulic parameters were compared with in situ
measurements. Depth-specific calibration relations were
essential to derive soil moisture from near-surface
installed sensors.},
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:000330971700007},
doi = {10.2136/vzj2013.04.0075},
url = {https://juser.fz-juelich.de/record/150362},
}