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@ARTICLE{Herbst:889718,
author = {Herbst, Michael and Pohlig, Philipp and Graf, Alexander and
Weihermüller, Lutz and Schmidt, M. and Vanderborght, Jan
and Vereecken, H.},
title = {{Q}uantification of water stress induced within-field
variability of carbon dioxide fluxes in a sugar beet stand},
journal = {Agricultural and forest meteorology},
volume = {297},
issn = {0168-1923},
address = {Amsterdam [u.a.]},
publisher = {Elsevier},
reportid = {FZJ-2021-00340},
pages = {108242 -},
year = {2021},
abstract = {Net ecosystem exchange of carbon dioxide (NEE) and soil
respiration at field scale can exhibit considerable spatial
variability linked to the heterogeneity of soil properties
and state variables. In this study, we measured NEE with the
eddy covariance (EC) method in a sugar beet field
characterized by high spatial variability in soil physical
properties. We further measured NEE and soil respiration by
chambers as well as soil water content and temperature at 18
locations within the field.Spatially averaged
chamber-measured NEE showed good agreement to the EC-based
data. During a dry period high spatial variation of
within-field NEE was detected with the chamber method. The
coefficient of variation was on average 0.57 during the dry
period, with a maximum of 0.72. Based on the depth-specific
soil water content measurements the AgroC ecosystem model
was inverted for soil hydraulic properties at each of the 18
locations, where soil water content was measured. Analyzing
the model results revealed that root water uptake stress was
the main driver of spatial and temporal variability in crop
development and NEE, whereby the soil coarse material
fraction (gravel content) and thickness of the layer above a
gravel dominated soil layer were identified as the main
influencing soil properties.The chamber-measured NEE and the
flux footprint analysis showed that particularly during
periods of severe root water uptake stress EC-based
measurements would be prone to biases. A combination of the
footprint model with the AgroC ecosystem model estimated a
bias of 14 $\%$ for the dry period and a vegetation period
bias of 6 $\%$ in relation to the average CO2 flux.},
cin = {IBG-3},
ddc = {550},
cid = {I:(DE-Juel1)IBG-3-20101118},
pnm = {2173 - Agro-biogeosystems: controls, feedbacks and impact
(POF4-217)},
pid = {G:(DE-HGF)POF4-2173},
typ = {PUB:(DE-HGF)16},
UT = {WOS:000608676000008},
doi = {10.1016/j.agrformet.2020.108242},
url = {https://juser.fz-juelich.de/record/889718},
}