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@ARTICLE{Groh:845880,
author = {Groh, Jannis and Stumpp, Christine and Lücke, Andreas and
Pütz, Thomas and Vanderborght, Jan and Vereecken, Harry},
title = {{I}nverse {E}stimation of {S}oil {H}ydraulic and
{T}ransport {P}arameters of {L}ayered {S}oils from {W}ater
{S}table {I}sotope and {L}ysimeter {D}ata},
journal = {Vadose zone journal},
volume = {17},
number = {1},
issn = {1539-1663},
address = {Madison, Wis.},
publisher = {SSSA},
reportid = {FZJ-2018-03079},
pages = {1 -19},
year = {2018},
abstract = {Accurate estimates of soil hydraulic parameters and
dispersivities are crucial to simulate water flow and solute
transport in terrestrial systems, particularly in the vadose
zone. However, parameters obtained from inverse modeling can
be ambiguous when identifying multiple parameters
simultaneously and when boundary conditions are not well
known. Here, we performed an inverse modeling study in which
we estimated soil hydraulic parameters and dispersivities of
layered soils from soil water content, matric potential, and
stable water isotope ( d 18O) measurements in weighable
lysimeter systems. We used different optimization strategies
to investigate which observation types are necessary for
simultaneously estimating soil hydraulic and solute
transport parameters. Combining water content, matric
potential, and tracer (e.g., d 18O) data in one objective
function (OF) was found to be the best strategy for
estimating parameters that can simulate all observed water
flow and solute transport variables. A sequential
optimization, in which first an OF with only water flow
variables and subsequently an OF with transport variables
was optimized, performed slightly worse indicating that
transport variables contained additional information for
estimating soil hydraulic parameters. Hydraulic parameters
that were obtained from optimizing OFs that used either
water contents or matric potential could not predict
non-measured water flow variables. When a bromide (Br−)
tracer experiment was simulated using the optimized
parameters, the arrival time of the bromide pulse was
underestimated. This suggested that Br− sorbed onto clay
minerals and amorphous oxides under the prevailing
geochemical conditions with low pH values. When accounting
for anion adsorption in the simulation, Br− concentrations
were well predicted, which validated the dispersivity
parameterization.},
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:000437536200001},
doi = {10.2136/vzj2017.09.0168},
url = {https://juser.fz-juelich.de/record/845880},
}