Journal cover Journal topic
Natural Hazards and Earth System Sciences An interactive open-access journal of the European Geosciences Union
Journal topic

Journal metrics

Journal metrics

  • IF value: 2.281 IF 2.281
  • IF 5-year value: 2.693 IF 5-year 2.693
  • CiteScore value: 2.43 CiteScore 2.43
  • SNIP value: 1.193 SNIP 1.193
  • SJR value: 0.965 SJR 0.965
  • IPP value: 2.31 IPP 2.31
  • h5-index value: 40 h5-index 40
  • Scimago H index value: 73 Scimago H index 73
Volume 14, issue 6 | Copyright
Nat. Hazards Earth Syst. Sci., 14, 1505-1515, 2014
https://doi.org/10.5194/nhess-14-1505-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 17 Jun 2014

Research article | 17 Jun 2014

The extreme runoff index for flood early warning in Europe

L. Alfieri1,2, F. Pappenberger1, and F. Wetterhall1 L. Alfieri et al.
  • 1European Centre for Medium-Range Weather Forecasts, Reading, UK
  • 2European Commission – Joint Research Centre, Ispra, Italy

Abstract. Systems for the early detection of floods over continental and global domains have a key role in providing a quick overview of areas at risk, raise the awareness and prompt higher detail analyses as the events approach. However, the reliability of these systems is prone to spatial inhomogeneity, depending on the quality of the underlying input data and local calibration.

This work proposes a simple approach for flood early warning based on ensemble numerical predictions of surface runoff provided by weather forecasting centers. The system is based on a novel indicator, referred to as an extreme runoff index (ERI), which is calculated from the input data through a statistical analysis. It is designed for use in large or poorly gauged domains, as no local knowledge or in situ observations are needed for its setup. Daily runs over 32 months are evaluated against calibrated hydrological simulations for all of Europe. Results show skillful flood early warning capabilities up to a 10-day lead time. A dedicated analysis is performed to investigate the optimal timing of forecasts to maximize the detection of extreme events. A case study for the central European floods of June 2013 is presented and forecasts are compared to the output of a hydro-meteorological ensemble model.

Publications Copernicus
Download
Citation
Share