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| Titel |
Is high-resolution inverse characterization of heterogeneous river bed hydraulic conductivities needed and possible? |
| VerfasserIn |
W. Kurtz, H.-J. Hendricks Franssen, P. Brunner, H. Vereecken |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1027-5606
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| Digitales Dokument |
URL |
| Erschienen |
In: Hydrology and Earth System Sciences ; 17, no. 10 ; Nr. 17, no. 10 (2013-10-07), S.3795-3813 |
| Datensatznummer |
250085946
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| Publikation (Nr.) |
 copernicus.org/hess-17-3795-2013.pdf |
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| Zusammenfassung |
| River–aquifer exchange fluxes influence local and regional water
balances and affect groundwater and river water quality and
quantity. Unfortunately, river–aquifer exchange fluxes tend to be
strongly spatially variable, and it is an open research question to
which degree river bed heterogeneity has to be represented in
a model in order to achieve reliable estimates of river–aquifer
exchange fluxes. This research question is addressed in this paper
with the help of synthetic simulation experiments, which mimic the
Limmat aquifer in Zurich (Switzerland), where river–aquifer exchange
fluxes and groundwater management activities play an important role.
The solution of the unsaturated–saturated subsurface hydrological
flow problem including river–aquifer interaction is calculated for
ten different synthetic realities where the strongly heterogeneous
river bed hydraulic conductivities (L) are perfectly
known. Hydraulic head data (100 in the default scenario) are sampled
from the synthetic realities. In subsequent data assimilation
experiments, where L is unknown now, the hydraulic head data are
used as conditioning information, with the help of the ensemble Kalman
filter (EnKF). For each of the ten synthetic realities, four
different ensembles of L are tested in the experiments with EnKF;
one ensemble estimates high-resolution L fields with different L
values for each element, and the other three ensembles estimate
effective L values for 5, 3 or 2 zones. The calibration of higher-resolution
L fields (i.e. fully heterogeneous or 5 zones) gives
better results than the calibration of L for only 3 or 2 zones in
terms of reproduction of states, stream–aquifer exchange fluxes and
parameters. Effective L for a limited number of zones cannot
always reproduce the true states and fluxes well and results in
biased estimates of net exchange fluxes between aquifer and
stream.
Also in case only 10 head data are used for conditioning, the high-resolution
characterization of L fields with EnKF is still feasible. For less
heterogeneous river bed hydraulic conductivities, a high-resolution
characterization of L is less important. When uncertainties in the
hydraulic parameters of the aquifer are also regarded in the assimilation,
the errors in state and flux predictions increase, but the ensemble with a
high spatial resolution for L still outperforms the ensembles with
effective L values. We conclude that for strongly heterogeneous river beds
the commonly applied simplified representation of the streambed, with
spatially homogeneous parameters or constant parameters for a few zones,
might yield significant biases in the characterization of the water balance.
For strongly heterogeneous river beds, we suggest adopting a stochastic field
approach to model the spatially heterogeneous river beds geostatistically.
The paper illustrates that EnKF is able to calibrate such heterogeneous
streambeds on the basis of hydraulic head measurements, outperforming
zonation approaches. |
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