Characterizing Curvilinear Features Using the Localized Normal-Score Ensemble Kalman Filter
The localized normal-score ensemble Kalman filter is shown to work for the characterization of non-multi-Gaussian distributed hydraulic conductivities by assimilating state observation data. The influence of type of flow regime, number of observation piezometers, and the prior model structure are ev...
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| Format: | Article |
| Language: | English |
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Wiley
2012-01-01
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| Series: | Abstract and Applied Analysis |
| Online Access: | http://dx.doi.org/10.1155/2012/805707 |
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| author | Haiyan Zhou Liangping Li J. Jaime Gómez-Hernández |
| author_facet | Haiyan Zhou Liangping Li J. Jaime Gómez-Hernández |
| author_sort | Haiyan Zhou |
| collection | DOAJ |
| description | The localized normal-score ensemble Kalman filter is shown to work for the characterization of non-multi-Gaussian distributed hydraulic conductivities by assimilating state observation data. The influence of type of flow regime, number of observation piezometers, and the prior model structure are evaluated in a synthetic aquifer. Steady-state observation data are not sufficient to identify the conductivity channels. Transient-state data are necessary for a good characterization of the hydraulic conductivity curvilinear patterns. Such characterization is very good with a dense network of observation data, and it deteriorates as the number of observation piezometers decreases. It is also remarkable that, even when the prior model structure is wrong, the localized normal-score ensemble Kalman filter can produce acceptable results for a sufficiently dense observation network. |
| format | Article |
| id | doaj-art-d3514d103103433f8908cc4a27e279f5 |
| institution | Kabale University |
| issn | 1085-3375 1687-0409 |
| language | English |
| publishDate | 2012-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Abstract and Applied Analysis |
| spelling | doaj-art-d3514d103103433f8908cc4a27e279f52025-02-03T06:44:19ZengWileyAbstract and Applied Analysis1085-33751687-04092012-01-01201210.1155/2012/805707805707Characterizing Curvilinear Features Using the Localized Normal-Score Ensemble Kalman FilterHaiyan Zhou0Liangping Li1J. Jaime Gómez-Hernández2Grupo de Hidrogeologia, Departamento de Ingeniería Hidráulica y Medio Ambiente, Universitat Politècnica de València, Camino de Vera, s/n, 46022 Valencia, SpainGrupo de Hidrogeologia, Departamento de Ingeniería Hidráulica y Medio Ambiente, Universitat Politècnica de València, Camino de Vera, s/n, 46022 Valencia, SpainGrupo de Hidrogeologia, Departamento de Ingeniería Hidráulica y Medio Ambiente, Universitat Politècnica de València, Camino de Vera, s/n, 46022 Valencia, SpainThe localized normal-score ensemble Kalman filter is shown to work for the characterization of non-multi-Gaussian distributed hydraulic conductivities by assimilating state observation data. The influence of type of flow regime, number of observation piezometers, and the prior model structure are evaluated in a synthetic aquifer. Steady-state observation data are not sufficient to identify the conductivity channels. Transient-state data are necessary for a good characterization of the hydraulic conductivity curvilinear patterns. Such characterization is very good with a dense network of observation data, and it deteriorates as the number of observation piezometers decreases. It is also remarkable that, even when the prior model structure is wrong, the localized normal-score ensemble Kalman filter can produce acceptable results for a sufficiently dense observation network.http://dx.doi.org/10.1155/2012/805707 |
| spellingShingle | Haiyan Zhou Liangping Li J. Jaime Gómez-Hernández Characterizing Curvilinear Features Using the Localized Normal-Score Ensemble Kalman Filter Abstract and Applied Analysis |
| title | Characterizing Curvilinear Features Using the Localized Normal-Score Ensemble Kalman Filter |
| title_full | Characterizing Curvilinear Features Using the Localized Normal-Score Ensemble Kalman Filter |
| title_fullStr | Characterizing Curvilinear Features Using the Localized Normal-Score Ensemble Kalman Filter |
| title_full_unstemmed | Characterizing Curvilinear Features Using the Localized Normal-Score Ensemble Kalman Filter |
| title_short | Characterizing Curvilinear Features Using the Localized Normal-Score Ensemble Kalman Filter |
| title_sort | characterizing curvilinear features using the localized normal score ensemble kalman filter |
| url | http://dx.doi.org/10.1155/2012/805707 |
| work_keys_str_mv | AT haiyanzhou characterizingcurvilinearfeaturesusingthelocalizednormalscoreensemblekalmanfilter AT liangpingli characterizingcurvilinearfeaturesusingthelocalizednormalscoreensemblekalmanfilter AT jjaimegomezhernandez characterizingcurvilinearfeaturesusingthelocalizednormalscoreensemblekalmanfilter |