DOI: 10.5194/hess-21-5273-2017
Scopus记录号: 2-s2.0-85031927229
论文题名: Performance of ensemble streamflow forecasts under varied hydrometeorological conditions
作者: Benninga H ; -J ; F ; , Booij M ; J ; , Romanowicz R ; J ; , Rientjes T ; H ; M
刊名: Hydrology and Earth System Sciences
ISSN: 10275606
出版年: 2017
卷: 21, 期: 10 起始页码: 5273
结束页码: 5291
语种: 英语
Scopus关键词: Atmospheric movements
; Catchments
; Climate models
; Dispersions
; Forecasting
; Hydrology
; Stream flow
; Ensemble forecasting
; European centre for medium-range weather forecasts
; Hydrological modeling
; Hydrometeorological conditions
; Meteorological input
; Precipitation deficits
; Streamflow forecasting
; Temperature forecasts
; Weather forecasting
; catchment
; ensemble forecasting
; forecasting method
; hydrological modeling
; hydrometeorology
; model validation
; mountain stream
; performance assessment
; streamflow
; weather forecasting
; Biala River
; Poland [Central Europe]
; Slaskie
英文摘要: The paper presents a methodology that gives insight into the performance of ensemble streamflow-forecasting systems. We have developed an ensemble forecasting system for the Biała Tarnowska, a mountainous river catchment in southern Poland, and analysed the performance for lead times ranging from 1 to 10 days for low, medium and high streamflow and different hydrometeorological conditions. Precipitation and temperature forecasts from the European Centre for Medium-Range Weather Forecasts served as inputs to a deterministic lumped hydrological (HBV) model. Due to a non-homogeneous bias in time, pre- and post-processing of the meteorological and streamflow forecasts are not effective. The best forecast skill, relative to alternative forecasts based on meteorological climatology, is shown for high streamflow and snow accumulation low-streamflow events. Forecasts of medium-streamflow events and low-streamflow events under precipitation deficit conditions show less skill. To improve performance of the forecasting system for high-streamflow events, the meteorological forecasts are most important. Besides, it is recommended that the hydrological model be calibrated specifically on low-streamflow conditions and high-streamflow conditions. Further, it is recommended that the dispersion (reliability) of the ensemble streamflow forecasts is enlarged by including the uncertainties in the hydrological model parameters and the initial conditions, and by enlarging the dispersion of the meteorological input forecasts. © Author(s) 2017. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/79021
Appears in Collections: 气候变化事实与影响
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作者单位: Water Engineering and Management, Faculty of Engineering Technology, University of Twente, Enschede, Netherlands; Institute of Geophysics, Polish Academy of Sciences, Warsaw, Poland; Department of Water Resources, Faculty of Geo-Information Science and Earth Observation, University of Twente, Enschede, Netherlands
Recommended Citation:
Benninga H,-J,F,et al. Performance of ensemble streamflow forecasts under varied hydrometeorological conditions[J]. Hydrology and Earth System Sciences,2017-01-01,21(10)