% 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{Weigand:828468,
author = {Weigand, Susanne and Bol, Roland and Reichert, Barbara and
Graf, Alexander and Wiekenkamp, Inge and Stockinger, Michael
and Lücke, Andreas and Tappe, Wolfgang and Bogena, Heye and
Pütz, Thomas and Amelung, Wulf and Vereecken, Harry},
title = {{S}patiotemporal {A}nalysis of {D}issolved {O}rganic
{C}arbon and {N}itrate in {W}aters of a {F}orested
{C}atchment {U}sing {W}avelet {A}nalysis},
journal = {Vadose zone journal},
volume = {16},
number = {3},
issn = {1539-1663},
address = {Madison, Wis.},
publisher = {SSSA},
reportid = {FZJ-2017-02427},
pages = {},
year = {2017},
abstract = {Understanding natural controls on N and C biogeochemical
cycles is important to estimate human impacts on these
cycles. This study examined the spatiotemporal relationships
between time series of weekly monitored stream and
groundwater N and C (assessed by NO3− and dissolved
organic C [DOC]) in the forested Wüstebach catchment
(Germany). In addition to traditional correlation analysis,
we applied wavelet transform coherence (WTC) analysis to
study variations in the correlation and lag time between the
N and C time series for different time scales. Median
transit times were used to connect hydrologic and water
chemistry data. We defined three stream-water groups: (i)
subsurface runoff dominated locations with strong seasonal
fluctuations in concentrations, short transit times, and
strong negative C/N correlations with short time lags, (ii)
groundwater dominated locations, with weaker seasonal
fluctuations, longer transit times, and weaker C/N
correlations with lags of several months, and (iii)
intermediate locations, with moderate seasonal fluctuations,
moderate transit times, and strong C/N correlations with
short time lags. Water transit times could be identified as
key drivers for the C/N relationship and we conclude that C
and N transport in stream water can be explained by mixing
of groundwater and subsurface runoff. Complemented by
transit times and the hydrochemical time series, WTC
analysis allowed us to discriminate between different water
sources (groundwater vs. subsurface runoff). In conclusion,
we found that in time series studies of hydrochemical data,
e.g., DOC and NO3−, WTC analysis can be a viable tool to
identify spatiotemporally dependent relationships in
catchments.},
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:000397092300002},
doi = {10.2136/vzj2016.09.0077},
url = {https://juser.fz-juelich.de/record/828468},
}