Staff Publications

Staff Publications

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    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

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Record number 456095
Title Skill of a global seasonal streamflow forecasting system, relative roles of initial conditions and meteorological forcing
Author(s) Yossef, N.C.; Winsemius, H.; Weerts, A.H.; Beek, R. van; Bierkens, M.F.P.
Source Water Resources Research 49 (2013)8. - ISSN 0043-1397 - p. 4687 - 4699.
DOI https://doi.org/10.1002/wrcr.20350
Department(s) Hydrology and Quantitative Water Management
Publication type Refereed Article in a scientific journal
Publication year 2013
Keyword(s) united-states - hydrological model - water-resources - climate-change - discharge - predictability - availability - prediction - validation - balances
Abstract We investigate the relative contributions of initial conditions (ICs) and meteorological forcing (MF) to the skill of the global seasonal streamflow forecasting system FEWS-World, using the global hydrological model PCRaster Global Water Balance. Potential improvement in forecasting skill through better climate prediction or by better estimation of ICs through data assimilation depends on the relative importance of these sources of uncertainty. We use the Ensemble Streamflow Prediction (ESP) and reverse ESP (revESP) procedure to explore the impact of both sources of uncertainty at 78 stations on large global basins for lead times upto 6 months. We compare the ESP and revESP forecast ensembles with retrospective model simulations driven by meteorological observations. For each location, we determine the critical lead time after which the importance of ICs is surpassed by that of MF. We analyze these results in the context of prevailing hydroclimatic conditions for larger basins. This analysis suggests that in some basins forecast skill may be improved by better estimation of initial hydrologic states through data assimilation; whereas in others skill improvement depends on better climate prediction. For arctic and snowfed rivers, forecasts of high flows may benefit from assimilation of snow and ice data. In some snowfed basins where the onset of melting is highly sensitive to temperature changes, forecast skill depends on better climate prediction. In monsoonal basins, the variability of the monsoon dominates forecasting skill, except for those where snow and ice contribute to streamflow. In large basins, initial surface water and groundwater states are important sources of skill.
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