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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
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    Citations

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    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.

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