GloFAS-global ensemble streamflow forecasting and flood early warning

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Abstract

Anticipation and preparedness for large-scale flood events have a key role in mitigating their impact and optimizing the strategic planning of water resources. Although several developed countries have well-established systems for river monitoring and flood early warning, figures of populations affected every year by floods in developing countries are unsettling. This paper presents the Global Flood Awareness System (GloFAS), which has been set up to provide an overview on upcoming floods in large world river basins. GloFAS is based on distributed hydrological simulation of numerical ensemble weather predictions with global coverage. Streamflow forecasts are compared statistically to climatological simulations to detect probabilistic exceedance of warning thresholds. In this article, the system setup is described, together with an evaluation of its performance over a two-year test period and a qualitative analysis of a case study for the Pakistan flood, in summer 2010. It is shown that hazardous events in large river basins can be skilfully detected with a forecast horizon of up to 1 month. In addition, results suggest that an accurate simulation of initial model conditions and an improved parameterization of the hydrological model are key components to reproduce accurately the streamflow variability in the many different runoff regimes of the earth. © 2013 Author(s).

Figures

  • Fig. 1. Overview of the GloFAS structure.
  • Fig. 2. Coefficient of variation of the estimation residuals for the 620 stations considered. Circle size is proportional to the upstream area of the river station.
  • Fig. 3. Comparison between observed and simulated daily average discharge in the Amazon River at Óbidos, linigrafo, Brazil.
  • Fig. 4. Scatter plot of observed and simulated daily average discharge (1990–2007) in the Amazon River at Óbidos, linigrafo, Brazil. 90th percentiles used for threshold exceedance analysis are shown with dashed lines while skill scores are shown on the left side.
  • Fig. 5. Pearson correlation coefficient of simulated versus observed discharge for the 620 stations considered plotted against the corresponding upstream area. Circle color depends on the latitude of each river station.
  • Fig. 6. Peirce’s skill score of simulated versus observed discharge for the 620 stations considered. Circle size is proportional to the upstream area of the river station. The black-contoured rectangle indicates the area shown in Fig. 10.
  • Fig. 7. CRPSS maps of ESPs for 2009–2010 against simulated corrected discharge climatology. Panels refer to lead time of 5, 15, and 25 days (top to bottom).
  • Fig. 8. Forecast lead time, in days, for which ESPs are skillful (AROC > 0.7).

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CITATION STYLE

APA

Alfieri, L., Burek, P., Dutra, E., Krzeminski, B., Muraro, D., Thielen, J., & Pappenberger, F. (2013). GloFAS-global ensemble streamflow forecasting and flood early warning. Hydrology and Earth System Sciences, 17(3), 1161–1175. https://doi.org/10.5194/hess-17-1161-2013

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