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• W3021324401 abstract "Abstract Recent technological advances in representation of processes in numerical climate models have led to skillful predictions, which can consequently increase the confidence of hydrological predictions and usability of hydroclimatic services. Given that many water‐related stakeholders are affected by seasonal hydrological variations, there is a need to manage such variations to their advantage through better understanding of the drivers that influence hydrological predictability. Here we analyze the seasonal forecasts of streamflow volumes across about 35,400 basins in Europe, which lie along a strong gradient in terms of climatology, scale, and hydrological regime. We then link the seasonal volumetric errors to various physiographic‐hydroclimatic descriptors and meteorological biases in order to identify the key drivers controlling predictability. Streamflow volumes over Europe are well predicted, yet with some geographic and seasonal variability; however, the predictability deteriorates with increasing lead time particularly in the winter months. Nevertheless, we show that the forecast quality is well correlated to a set of descriptors, which vary depending on the initialization month. The forecast quality of seasonal streamflow volumes is strongly dependent on the basin's hydrological regime, with limited predictability in relatively flashy basins. On the contrary, snow and/or baseflow dominated regions with long recessions show high streamflow predictability. Finally, climatology and precipitation forecast biases are also related to streamflow predictability, highlighting the importance of developing robust bias adjustment methods. Overall, this investigation shows that the seasonal streamflow predictability can be clustered, and hence regionalized, based on a priori knowledge of local hydroclimatic conditions." @default.
• W3021324401 created "2020-05-13" @default.
• W3021324401 creator A5061277365 @default.
• W3021324401 creator A5066470371 @default.
• W3021324401 creator A5073465579 @default.
• W3021324401 creator A5079850602 @default.
• W3021324401 date "2020-06-01" @default.
• W3021324401 modified "2023-10-09" @default.
• W3021324401 title "What Are the Key Drivers Controlling the Quality of Seasonal Streamflow Forecasts?" @default.
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• W3021324401 doi "https://doi.org/10.1029/2019wr026987" @default.
• W3021324401 hasPublicationYear "2020" @default.
• W3021324401 type Work @default.
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• W3021324401 hasAuthorship W3021324401A5061277365 @default.
• W3021324401 hasAuthorship W3021324401A5066470371 @default.
• W3021324401 hasAuthorship W3021324401A5073465579 @default.

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