| Summary: | In our changing world, humans experience increasingly the negative consequences of floods and droughts. Seasonal forecasts with lead times of several months, and covering larger areas are necessary to increase global preparedness. This thesis explores the potential of global hydrological models in operational seasonal forecasting applications, assesses the skill and value of global seasonal streamflow forecasts and investigates possible ways to improve the current skill and value. To assess the prospect of applying a global hydrological model for seasonal forecasting, global terrestrial hydrology is simulated with the model PCR-GLOBWB. The model is forced with a meteorological dataset based on historical observations and model skill is assessed based on monthly discharges for twenty large rivers across the world. PCR-GLOBWB cannot forecast the historical hydrographs adequately for all basins but higher skills can be attained in forecasting the occurrence of monthly anomalies. The prospects for seasonal forecasting with PCR-GLOBWB or other comparable models are assessed to be positive. The simulated hydrological response depends on both the initial hydrological conditions and the meteorological forcing. Uncertainty in both inputs is evaluated by comparing ESP/revESP forecast ensembles with retrospective model simulations driven by meteorological observations. The results are analysed in the context of prevailing hydroclimatic conditions for larger rivers across the globe. The influence of the initial conditions and meteorological forcing on forecasting skill is found to vary considerably according to location, season and lead time. For arctic and snow fed rivers, forecasts of high flows may benefit from assimilation of snow and ice data. In some snow fed basins where the onset of melting is highly sensitive to temperature changes, forecast skill depends on better climate prediction. Groundwater and surface water states also strongly influence the skill in very large rivers. In monsoonal basins, the variability of ...
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