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| Titel |
Ensemble Kalman filter versus ensemble smoother for assessing hydraulic conductivity via tracer test data assimilation |
| VerfasserIn |
E. Crestani, M. Camporese, D. Baù, P. Salandin |
| 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. 4 ; Nr. 17, no. 4 (2013-04-19), S.1517-1531 |
| Datensatznummer |
250018854
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| Publikation (Nr.) |
 copernicus.org/hess-17-1517-2013.pdf |
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| Zusammenfassung |
| Estimating the spatial variability of hydraulic conductivity K in natural
aquifers is important for predicting the transport of dissolved compounds.
Especially in the nonreactive case, the plume evolution is mainly controlled
by the heterogeneity of K. At the local scale, the spatial distribution of
K can be inferred by combining the Lagrangian formulation of the transport
with a Kalman-filter-based technique and assimilating a sequence of
time-lapse concentration C measurements, which, for example, can be
evaluated on site through the application of a geophysical method. The
objective of this work is to compare the ensemble Kalman filter (EnKF) and
the ensemble smoother (ES) capabilities to retrieve the hydraulic
conductivity spatial distribution in a groundwater flow and transport
modeling framework. The application refers to a two-dimensional synthetic
aquifer in which a tracer test is simulated. Moreover, since Kalman-filter-based methods are optimal only if each of the involved variables fit
to a Gaussian probability density function (pdf) and since this condition may
not be met by some of the flow and transport state variables, issues related
to the non-Gaussianity of the variables are analyzed and different
transformation of the pdfs are considered in order to evaluate their
influence on the performance of the methods. The results show that the EnKF
reproduces with good accuracy the hydraulic conductivity field, outperforming
the ES regardless of the pdf of the concentrations. |
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