IDEAS home Printed from https://ideas.repec.org/a/hin/jnlaaa/805707.html
   My bibliography  Save this article

Characterizing Curvilinear Features Using the Localized Normal-Score Ensemble Kalman Filter

Author

Listed:
  • Haiyan Zhou
  • Liangping Li
  • J. Jaime Gómez-Hernández

Abstract

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.

Suggested Citation

  • Haiyan Zhou & Liangping Li & J. Jaime Gómez-Hernández, 2012. "Characterizing Curvilinear Features Using the Localized Normal-Score Ensemble Kalman Filter," Abstract and Applied Analysis, Hindawi, vol. 2012, pages 1-18, July.
    • Handle: RePEc:hin:jnlaaa:805707
    DOI: 10.1155/2012/805707
    as

    Download full text from publisher

    File URL: http://downloads.hindawi.com/journals/AAA/2012/805707.pdf
    Download Restriction: no
    File URL: http://downloads.hindawi.com/journals/AAA/2012/805707.xml
    Download Restriction: no
    File URL: https://libkey.io/10.1155/2012/805707?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:hin:jnlaaa:805707. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Mohamed Abdelhakeem (email available below). General contact details of provider: https://www.hindawi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.