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Assessment of the Long-Term Hydrological Forecast Skill Evolution across Lead-Times within the Ensemble Streamflow Prediction Framework
Authors:Moreido  V M
Institution:1.Water Problems Institute,Russian Academy of Sciences,Moscow,Russia
Abstract:Long-term or seasonal forecasting is crucial for the management of large water systems. Advances in catchment hydrology, such as mathematical models of catchment processes, are proven to be capable of creating reliable streamflow forecasting systems. In this study, the limits of predictability of streamflow in a snowmelt-dominated river basin are examined and a new illustration of the forecast efficiency across different issue dates and lead times—the so-called “forecastability map”—is demonstrated.
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