Journal cover Journal topic
Hydrology and Earth System Sciences An interactive open-access journal of the European Geosciences Union
doi:10.5194/hess-2016-584
© Author(s) 2016. This work is distributed
under the Creative Commons Attribution 3.0 License.
Research article
17 Nov 2016
Review status
This discussion paper is under review for the journal Hydrology and Earth System Sciences (HESS).
Performance of ensemble streamflow forecasts under varied hydrometeorological conditions
Harm-Jan F. Benninga1,a, Martijn J. Booij1, Renata J. Romanowicz2, and Tom H. M. Rientjes3 1Water Engineering and Management, Faculty of Engineering Technology, University of Twente, 7500 AE Enschede, The Netherlands
2Institute of Geophysics, Polish Academy of Sciences, 01-452 Warsaw, Poland
3Water Resources, Faculty of Geo-Information Science and Earth Observation, University of Twente, 7500 AE Enschede, The Netherlands
apresent address: Water Resources, Faculty of Geo-Information Science and Earth Observation, University of Twente
Abstract. The paper presents a methodology to give insight in the performance of ensemble streamflow forecasting systems. We developed an ensemble forecasting system for the Biała Tarnowska, a mountainous river catchment in southern Poland, and analysed the performance for lead times from 1 day to 10 days for low, medium and high streamflow and related runoff generating processes. Precipitation and temperature forecasts from the European Centre for Medium-Range Weather Forecasts serve as input to a deterministic lumped hydrological (HBV) model. Due to inconsistent bias, the best streamflow forecasts were obtained without pre- and post-processing of the meteorological and streamflow forecasts. Best forecast skill, relative to alternative forecasts based on historical measurements of precipitation and temperature, is shown for high streamflow and for snow accumulation low streamflow events. Forecasts of medium streamflow events and low streamflow events generated by precipitation deficit show less skill. To improve the performance of the forecasting system for high streamflow events, in particular the meteorological forecasts require improvement. For low streamflow forecasts, the hydrological model should be improved. The study recommends improving the reliability of the ensemble streamflow forecasts by including the uncertainties in hydrological model parameters and initial conditions, and by improving the dispersion of the meteorological input forecasts.

Citation: Benninga, H.-J. F., Booij, M. J., Romanowicz, R. J., and Rientjes, T. H. M.: Performance of ensemble streamflow forecasts under varied hydrometeorological conditions, Hydrol. Earth Syst. Sci. Discuss., doi:10.5194/hess-2016-584, in review, 2016.
Harm-Jan F. Benninga et al.
Harm-Jan F. Benninga et al.
Harm-Jan F. Benninga et al.

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The study develops a methodology to evaluate the performance of an ensemble streamflow forecasting system for different lead times, low, medium and high streamflow, and related runoff generating processes. It includes an investigation of the dominant error contributors to the forecasts. We applied the methodology to a study forecasting system. The results provide information about the forecasting system, in which situations it can be used, and how the system can be improved effectively.
The study develops a methodology to evaluate the performance of an ensemble streamflow...
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