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@ARTICLE{HendricksFranssen:16634,
author = {Hendricks Franssen, H.J. and Kaiser, H.P. and Kuhlmann, U.
and Bauser, G. and Stauffer, F. and Müller, R. and
Kinzelbach, W.},
title = {{O}perational real-time modeling with ensemble {K}alman
filter of variably saturated subsurface flow including
stream-aquifer interaction and parameter updating},
journal = {Water resources research},
volume = {47},
issn = {0043-1397},
address = {Washington, DC},
publisher = {AGU},
reportid = {PreJuSER-16634},
pages = {W02532},
year = {2011},
note = {The study was performed within the project "Real-Time
Control of a Well-Field Using a Groundwater Model," a
cooperation between ETH Zurich, Zurich Water Supply, and TK
Consult Zurich. This project is funded by the Swiss
Innovation Promotion Agency CTI under contract 7608.2
EPRP-IW.},
abstract = {Urban groundwater is frequently contaminated, and the exact
location of the pollution spots is often unknown.
Intelligent monitoring of the temporal variations in
groundwater flow in such an area assists in selectively
extracting groundwater of drinking water quality. Here an
example from the city of Zurich (Switzerland) is shown. The
monitoring strategy consists of using the ensemble Kalman
filter (EnKF) for optimally combining online observations
and online models for the real-time characterization of
groundwater flow. We conducted numerical simulation
experiments for the period January 2004 to December 2007
with a 3-D finite element model for variably saturated
groundwater flow. It was found that the daily assimilation
of piezometric head data with EnKF results in a better
characterization of piezometric heads than does a model
which is inversely calibrated with historical data but not
updated in real time. The positive impact of model updating
with observations can still be observed 10 days after the
update. These simulations also suggest that parameters
(hydraulic conductivity and leakage) are successfully
updated: 1 and 10 day piezometric head predictions are
better with than without updating of parameters. Additional
experiments with a synthetic model for the same site, in
which the only difference is that certain parameter values
are selected as the unknown "true" conditions, show that
EnKF also successfully updates unknown parameters. However,
this is only the case if spatially distributed hydraulic
conductivities and leakage coefficients are jointly updated
and if a damping parameter is used. The mean absolute error
of estimated log leakage coefficients decreased by up to
$63\%;$ for log hydraulic conductivity a decrease of up to
$27\%$ was observed. From January 2009 the method has been
operational at the Water Works Zurich and showed a
remarkable performance until present (October 2010).},
keywords = {J (WoSType)},
cin = {IBG-3},
ddc = {550},
cid = {I:(DE-Juel1)IBG-3-20101118},
pnm = {Terrestrische Umwelt},
pid = {G:(DE-Juel1)FUEK407},
shelfmark = {Environmental Sciences / Limnology / Water Resources},
typ = {PUB:(DE-HGF)16},
UT = {WOS:000287819100003},
doi = {10.1029/2010WR009480},
url = {https://juser.fz-juelich.de/record/16634},
}