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| Titel |
Kalman filters for assimilating near-surface observations into the Richards equation – Part 2: A dual filter approach for simultaneous retrieval of states and parameters |
| VerfasserIn |
H. Medina, N. Romano, G. B. Chirico |
| 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 ; 18, no. 7 ; Nr. 18, no. 7 (2014-07-04), S.2521-2541 |
| Datensatznummer |
250120405
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| Publikation (Nr.) |
 copernicus.org/hess-18-2521-2014.pdf |
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| Zusammenfassung |
| This study presents a dual Kalman filter (DSUKF – dual standard-unscented Kalman filter) for retrieving states and
parameters controlling the soil water dynamics in a homogeneous soil column,
by assimilating near-surface state observations. The DSUKF couples a
standard Kalman filter for retrieving the states of a linear solver of the
Richards equation, and an unscented Kalman filter for retrieving the
parameters of the soil hydraulic functions, which are defined according to
the van Genuchten–Mualem closed-form model. The accuracy and the
computational expense of the DSUKF are compared with those of the dual
ensemble Kalman filter (DEnKF) implemented with a nonlinear solver of the
Richards equation. Both the DSUKF and the DEnKF are applied with two
alternative state-space formulations of the Richards equation, respectively
differentiated by the type of variable employed for representing the states:
either the soil water content (θ) or the soil water matric pressure
head (h). The comparison analyses are conducted with reference to synthetic
time series of the true states, noise corrupted observations, and synthetic
time series of the meteorological forcing. The performance of the retrieval
algorithms are examined accounting for the effects exerted on the output by
the input parameters, the observation depth and assimilation frequency, as
well as by the relationship between retrieved states and assimilated
variables. The uncertainty of the states retrieved with DSUKF is
considerably reduced, for any initial wrong parameterization, with similar
accuracy but less computational effort than the DEnKF, when this is
implemented with ensembles of 25 members. For ensemble sizes of the same
order of those involved in the DSUKF, the DEnKF fails to provide reliable
posterior estimates of states and parameters. The retrieval performance of
the soil hydraulic parameters is strongly affected by several factors, such
as the initial guess of the unknown parameters, the wet or dry range of the
retrieved states, the boundary conditions, as well as the form
(h-based or
θ-based) of the state-space formulation. Several analyses are
reported to show that the identifiability of the saturated hydraulic
conductivity is hindered by the strong correlation with other parameters of
the soil hydraulic functions defined according to the van Genuchten–Mualem
closed-form model. |
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