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Titel |
Groundwater flow inverse modeling in non-MultiGaussian media: performance assessment of the normal-score Ensemble Kalman Filter |
VerfasserIn |
L. Li, H. Zhou, H. J. Hendricks Franssen, J. J. Gómez-Hernández |
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 ; 16, no. 2 ; Nr. 16, no. 2 (2012-02-27), S.573-590 |
Datensatznummer |
250013184
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Publikation (Nr.) |
copernicus.org/hess-16-573-2012.pdf |
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Zusammenfassung |
The normal-score ensemble Kalman filter (NS-EnKF) is tested on a synthetic
aquifer characterized by the presence of channels with a bimodal distribution
of its hydraulic conductivities. This is a clear example of an aquifer that
cannot be characterized by a multiGaussian distribution. Fourteen scenarios
are analyzed which differ among them in one or various of the following
aspects: the prior random function model, the boundary conditions of the flow
problem, the number of piezometers used in the assimilation process, or the
use of covariance localization in the implementation of the Kalman filter.
The performance of the NS-EnKF is evaluated through the ensemble mean and
variance maps, the connectivity patterns of the individual conductivity
realizations and the degree of reproduction of the piezometric heads. The
results show that (i) the localized NS-EnKF can characterize the
non-multiGaussian underlying hydraulic distribution even when an erroneous
prior random function model is used, (ii) localization plays an important
role to prevent filter inbreeding and results in a better logconductivity
characterization, and (iii) the NS-EnKF works equally well under very
different flow configurations. |
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