E3S Web Conf.
Volume 7, 20163rd European Conference on Flood Risk Management (FLOODrisk 2016)
|Number of page(s)||11|
|Section||Forecasting and warning|
|Published online||20 October 2016|
Probabilistic flood forecasting on the Rhone River: evaluation with ensemble and analogue-based precipitation forecasts
1 Université Grenoble Alpes, Laboratoire d’étude des Transferts en Hydrologie et Environnement, 70 rue de la Physique, 38400 St-Martin-d’Hères, France
2 Compagnie Nationale du Rhône, 2 rue André Bonin, 69004 Lyon, France
a Corresponding author: email@example.com
Hydrological ensemble forecasting performances are analysed over 5 basins up to 2000 km2 in the French Upper Rhone region. Streamflow forecasts are issued at an hourly time step from lumped ARX rainfall-runoff models forced by different precipitation forecasts. Ensemble meteorological forecasts from ECMWF and NCEP are considered, as well as analogue-based forecasts fed by their corresponding control forecast. Analogue forecasts are rearranged using an adaptation of the Schaake-Shuffle method in order to ensure the temporal coherence. A new evaluation approach is proposed, separating forecasting performances on peak amplitudes and peak timings for high flow events. Evaluation is conducted against both simulated and observed streamflow (so that relative meteorological and hydrological uncertainties can be assessed), by means of CRPS and rank histograms, over the 2007-2014 period. Results show a general agreement of the forecasting performances when averaged over the 5 basins. However, ensemble-based and analogue-based streamflow forecasts produce a different signature on peak events in terms of bias, spread and reliability. Strengths and weaknesses of both approaches are discussed as well as potential improvements, notably towards their merging.
© The Authors, published by EDP Sciences, 2016
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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