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Natural Hazards and Earth System Sciences An interactive open-access journal of the European Geosciences Union
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Volume 14, issue 6 | Copyright

Special issue: Advanced methods for flood estimation in a variable and changing...

Nat. Hazards Earth Syst. Sci., 14, 1417-1428, 2014
https://doi.org/10.5194/nhess-14-1417-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 05 Jun 2014

Research article | 05 Jun 2014

Flood design recipes vs. reality: can predictions for ungauged basins be trusted?

A. Efstratiadis1, A. D. Koussis2, D. Koutsoyiannis1, and N. Mamassis1 A. Efstratiadis et al.
  • 1Department of Water Resources and Environmental Engineering, National Technical University of Athens, Athens, Greece
  • 2Institute of Environmental Research and Sustainable Development, National Observatory of Athens, Athens, Greece

Abstract. Despite the great scientific and technological advances in flood hydrology, everyday engineering practices still follow simplistic approaches that are easy to formally implement in ungauged areas. In general, these "recipes" have been developed many decades ago, based on field data from typically few experimental catchments. However, many of them have been neither updated nor validated across all hydroclimatic and geomorphological conditions. This has an obvious impact on the quality and reliability of hydrological studies, and, consequently, on the safety and cost of the related flood protection works. Preliminary results, based on historical flood data from Cyprus and Greece, indicate that a substantial revision of many aspects of flood engineering procedures is required, including the regionalization formulas as well as the modelling concepts themselves. In order to provide a consistent design framework and to ensure realistic predictions of the flood risk (a key issue of the 2007/60/EU Directive) in ungauged basins, it is necessary to rethink the current engineering practices. In this vein, the collection of reliable hydrological data would be essential for re-evaluating the existing "recipes", taking into account local peculiarities, and for updating the modelling methodologies as needed.

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