% 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{Altdorff:134440,
author = {Altdorff, Daniel and Epting, J. and van der Kruk, Jan and
Dietrich, P. and Huggenberger, P.},
title = {{D}elineation of fluvial sediment architecture of subalpine
riverinesystems using noninvasive hydrogeophysical methods},
journal = {Environmental earth sciences},
volume = {69},
number = {2},
issn = {1866-6280},
address = {Berlin},
publisher = {Springer},
reportid = {FZJ-2013-02639},
pages = {633-644},
year = {2013},
abstract = {River management and restoration measures are of increasing
importance for integrated water resources management (IWRM)
as well as for ecosystem services. However, often river
management mainly considers engineering and construction
aspects only and the hydrogeological settings as the
properties and functions of ancient fluvial systems are
neglected which often do not lead to the desired outcome.
Knowledge of the distribution of sediment units could
contribute to a more efficient restoration. In this study,
we present two noninvasive approaches for delineation of
fluvial sediment architecture that can form a basis for the
restoration, particularly in areas where site disturbance is
not permitted. We investigate the floodplain of a heavily
modified low-mountain river in Switzerland using different
hydrogeophysical methods. In the first approach, we use data
from electromagnetic induction (EMI) with four different
integral depths (0.75–6 m) and gamma-spectrometry as well
as the elevation data as input for a K-means cluster
algorithm. The generated cluster map of the surface combines
the main characteristics from multilayered input data and
delineates areas of varying soil properties. The resulting
map provides an indication of areas with different
sedimentary units. In the second approach, we develop a new
iterative method for the generation of a geological
structure model (GSM) by means of various EMI forward
models. We vary the geological input parameters based on the
measured data until the predicted EMI maps match the
measured EMI values. Subsequently, we use the best matched
input data for the GSM generation. The derived GSM provides
a 3D delineation of possible ancient stream courses. A
comparison with an independent ground penetrating radar
(GPR) profile confirmed the delineations on the cluster map
as well as the vertical changes of the GSM qualitatively.
Thus, each of the approaches had the capacity for detecting
sedimentary units with distinct hydraulic properties as an
indication of former stream courses. The developed
methodology presents a promising tool for the
characterization of test sites with no additional subsurface
information.},
cin = {IBG-3},
ddc = {550},
cid = {I:(DE-Juel1)IBG-3-20101118},
pnm = {246 - Modelling and Monitoring Terrestrial Systems: Methods
and Technologies (POF2-246)},
pid = {G:(DE-HGF)POF2-246},
typ = {PUB:(DE-HGF)16},
UT = {WOS:000318280400024},
doi = {10.1007/s12665-013-2304-4},
url = {https://juser.fz-juelich.de/record/134440},
}