IDEAS home Printed from https://ideas.repec.org/a/spr/nathaz/v60y2012i3p1157-1165.html
   My bibliography  Save this article

Parameter estimations of a storm surge model using a genetic algorithm

Author

Listed:
  • Sung You
  • Yong Lee
  • Woo Lee

Abstract

A genetic algorithm was used to optimize the parameters of the two-dimensional Storm Surge/Tide Operational Model (STORM) to improve sea level predictions of storm surges. The model was then tested using data from Typhoon Maemi, which landed on the Korean Peninsula in 2003. The following model parameters were used: the coefficients for bottom drag, background horizontal diffusivity, Smagorinsky’s horizontal viscosity, and sea level pressure scaling. The simulation results using the optimized parameters improved sea level predictions. This study demonstrates that parameter optimizations and their adequate applications are essential for improving model performance. Copyright Springer Science+Business Media B.V. 2012

Suggested Citation

  • Sung You & Yong Lee & Woo Lee, 2012. "Parameter estimations of a storm surge model using a genetic algorithm," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 60(3), pages 1157-1165, February.
    • Handle: RePEc:spr:nathaz:v:60:y:2012:i:3:p:1157-1165
    DOI: 10.1007/s11069-011-9900-y
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s11069-011-9900-y
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s11069-011-9900-y?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    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:spr:nathaz:v:60:y:2012:i:3:p:1157-1165. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.