Water Resources Research

Flood forecast errors and ensemble spread—A case study

Authors

  • T. Nester,

    Corresponding author
    1. Institute of Hydraulic Engineering and Water Resources Management, Vienna University of Technology,Vienna,Austria
      Corresponding author: T. Nester, Institute for Hydraulic and Water Resources Engineering, Vienna University of Technology, Austria, Karlsplatz 13/222, 1040 Vienna. (nester@hydro.tuwien.ac.at)
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  • J. Komma,

    1. Institute of Hydraulic Engineering and Water Resources Management, Vienna University of Technology,Vienna,Austria
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  • A. Viglione,

    1. Institute of Hydraulic Engineering and Water Resources Management, Vienna University of Technology,Vienna,Austria
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  • G. Blöschl

    1. Institute of Hydraulic Engineering and Water Resources Management, Vienna University of Technology,Vienna,Austria
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Corresponding author: T. Nester, Institute for Hydraulic and Water Resources Engineering, Vienna University of Technology, Austria, Karlsplatz 13/222, 1040 Vienna. (nester@hydro.tuwien.ac.at)

Abstract

[1] Flood forecasts are generally associated with errors, which can be attributed to uncertainties in the meteorological forecasts and the hydrologic simulations, and ensemble spreads are usually considered capable of representing them. To quantify these two components of the total forecast errors and to compare these to ensemble spreads, an extended data set is used. Four years of operational flood forecasts at hourly time step with lead times up to 48 h are evaluated for 43 catchments in Austria and Germany. Catchment sizes range from 70 to 25,600 km2, elevations from 200 to 3800 m, and mean annual precipitation from 700 to 2000 mm. A combination of ECMWF and ALADIN ensemble forecasts are used as input in a semidistributed conceptual water balance model on an hourly time step. The results indicate that, for short lead times, the ratio of hydrological simulation error to precipitation forecast error is 1.2 to 2.7 with increasing catchment size from 100 to 10,000 km2. For long lead times the ratio of hydrological simulation error to precipitation forecast error decreases from 1.1 to 0.9 with increasing catchment size. Clear scaling relationships of the forecast error components with catchment area are found. A similar scaling is also found for ensemble spreads, which are shown to represent quantitatively the total forecast error when forecasting floods.

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