IDEAS home Printed from https://ideas.repec.org/a/spr/nathaz/v36y2005i1p25-42.html
   My bibliography  Save this article

Flood Forecasting and Warning at the River Basin and at the European Scale

Author

Listed:
  • Micha Werner
  • Paolo Reggiani
  • Ad Roo
  • Paul Bates
  • Eric Sprokkereef

Abstract

Application of recent advances in numerical weather prediction (NWP) has the potential of allowing delivery of flood warning to extend well beyond the typical lead times of operational flood warning at the river basin scale. A prototype system, a European Flood Forecasting System ( EFFS) developed to deliver such pre-warnings, aiming at providing a pre-warning at lead times of between 5 and 10 days is described. Considerable uncertainty in the weather forecast at these lead times, however, means that resulting forecasts must be treated probabilistically, and although probabilistic forecasts may be easy to disseminate, these are difficult to understand. This paper explores the structure of operational flood warning, and shows that integration in the flood warning process is required if the pre-warning is to fulfil its potential. A simple method of summarising the information in the pre-warning is presented, and the system in hindcast mode is shown to give clear indication of an upcoming major event in the Rhine basin up to 10 days before the actual event. Finally recommendations on the use of data assimilation to embed the EFFS system within an operational environment are given. Copyright Springer 2005

Suggested Citation

  • Micha Werner & Paolo Reggiani & Ad Roo & Paul Bates & Eric Sprokkereef, 2005. "Flood Forecasting and Warning at the River Basin and at the European Scale," 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. 36(1), pages 25-42, September.
  • Handle: RePEc:spr:nathaz:v:36:y:2005:i:1:p:25-42
    DOI: 10.1007/s11069-004-4537-8
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s11069-004-4537-8
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1007/s11069-004-4537-8?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.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Muhammad Hanif & Muhammad Waqas & Amgad Muneer & Ayed Alwadain & Muhammad Atif Tahir & Muhammad Rafi, 2023. "DeepSDC: Deep Ensemble Learner for the Classification of Social-Media Flooding Events," Sustainability, MDPI, vol. 15(7), pages 1-20, March.
    2. Melanie Kunz & Adrienne Grêt-Regamey & Lorenz Hurni, 2011. "Visualization of uncertainty in natural hazards assessments using an interactive cartographic information system," 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. 59(3), pages 1735-1751, December.
    3. Saeed Golian & Bahram Saghafian & Reza Maknoon, 2010. "Derivation of Probabilistic Thresholds of Spatially Distributed Rainfall for Flood Forecasting," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 24(13), pages 3547-3559, October.
    4. A. Fernández Bou & R. Sá & M. Cataldi, 2015. "Flood forecasting in the upper Uruguay River basin," 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. 79(2), pages 1239-1256, November.

    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:36:y:2005:i:1:p:25-42. 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.