% IMPORTANT: The following is UTF-8 encoded. This means that in the presence
% of non-ASCII characters, it will not work with BibTeX 0.99 or older.
% Instead, you should use an up-to-date BibTeX implementation like “bibtex8” or
% “biber”.
@ARTICLE{Herbst:50874,
author = {Herbst, M. and Diekkrüger, B. and Vereecken, H.},
title = {{G}eostatistical co-regionalization of soil hydraulic
properties in a micro-scale catchment using terrain
attributes},
journal = {Geoderma},
volume = {132},
issn = {0016-7061},
address = {Amsterdam [u.a.]},
publisher = {Elsevier Science},
reportid = {PreJuSER-50874},
pages = {206 - 221},
year = {2006},
note = {Record converted from VDB: 12.11.2012},
abstract = {Any effort of distributed hydrological modeling requires
the spatially distributed input of soil hydraulic properties
and soil thickness. Most of the hydrological models are
sensitive concerning these soil properties, thus the use of
point measurements and co-variables should be optimized for
a most accurate spatial prediction. During this study, we
focus on the use of terrain attributes as co-variables. In
order to determine the dependencies between the soil
properties and topography, we derived 17 terrain attributes
for a small rural catchment (28.6 ha). Correlation
statistics between these terrain attributes and soil
hydraulic properties calculated from measured grain size
distribution and organic carbon content with pedo-transfer
functions were used to identify terrain attributes as
co-variables for the spatial prediction of the soil
properties. We detected in particular for the following
terrain attributes a high prediction potential for soil
properties: relative elevation, slope of the catchment area,
radiation angle and morphometric units such as slope
elements. We also compared the performance of multiple
regression, ordinary kriging, external drift kriging and
regression kriging model C to estimate the spatial
distribution of topsoil and subsoil hydraulic properties and
horizon thickness. The prediction errors for the spatial
structure of soil hydraulic properties according to
Mualem/Van Genuchten and horizon thickness were quantified
by a cross validation procedure. We determined the
regression kriging model C as the most appropriate method
with, on average, the smallest prediction errors and because
the resulting spatial structure corresponds to recent models
of soil properties spatial structure. Compared to ordinary
kriging without covariables, the spatial prediction of soil
properties could be improved with up to $15\%$ by using
terrain attributes as co-variables. (c) 2005 Elsevier B.V.
All rights reserved.},
keywords = {J (WoSType)},
cin = {ICG-IV / JARA-ENERGY},
ddc = {550},
cid = {I:(DE-Juel1)VDB50 / $I:(DE-82)080011_20140620$},
pnm = {Terrestrische Umwelt},
pid = {G:(DE-Juel1)FUEK407},
shelfmark = {Soil Science},
typ = {PUB:(DE-HGF)16},
UT = {WOS:000236740900017},
doi = {10.1016/j.geoderma.2005.05.008},
url = {https://juser.fz-juelich.de/record/50874},
}