Articles | Volume 28, issue 17
https://doi.org/10.5194/hess-28-4127-2024
https://doi.org/10.5194/hess-28-4127-2024
Research article
 | 
12 Sep 2024
Research article |  | 12 Sep 2024

FROSTBYTE: a reproducible data-driven workflow for probabilistic seasonal streamflow forecasting in snow-fed river basins across North America

Louise Arnal, Martyn P. Clark, Alain Pietroniro, Vincent Vionnet, David R. Casson, Paul H. Whitfield, Vincent Fortin, Andrew W. Wood, Wouter J. M. Knoben, Brandi W. Newton, and Colleen Walford

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Skilful probabilistic predictions of UK flood risk months ahead using a large-sample machine learning model trained on multimodel ensemble climate forecasts
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Canadian historical Snow Water Equivalent dataset (CanSWE, 1928–2020)
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Cited articles

Arnal, L., Cloke, H. L., Stephens, E., Wetterhall, F., Prudhomme, C., Neumann, J., Krzeminski, B., and Pappenberger, F.: Skilful seasonal forecasts of streamflow over Europe?, Hydrol. Earth Syst. Sci., 22, 2057–2072, https://doi.org/10.5194/hess-22-2057-2018, 2018. a
Arnal, L., Casson, D. R., Clark, M. P., and Thiombiano, A. N.: FROSTBYTE: Forecasting River Outlooks from Snow Timeseries: Building Yearly Targeted Ensembles, Zenodo [code], https://doi.org/10.5281/zenodo.13381746, 2024a. a, b
Arnal, L., Vionnet, V., and Clark, M.: FROSTBYTE: Forecasting River Outlooks from Snow Timeseries: Building Yearly Targeted Ensembles, Zenodo [code and data set], https://doi.org/10.5281/zenodo.12100921, 2024b. a
Baker, S. A., Wood, A. W., and Rajagopalan, B.: Application of Postprocessing to Watershed-Scale Subseasonal Climate Forecasts over the Contiguous United States, J. Hydrometeorol., 21, 971–987, https://doi.org/10.1175/JHM-D-19-0155.1, 2020. a, b
Berghuijs, W. R., Woods, R. A., and Hrachowitz, M.: A precipitation shift from snow towards rain leads to a decrease in streamflow, Nat. Clim. Change, 4, 583–586, https://doi.org/10.1038/nclimate2246, 2014. a
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Short summary
Forecasting river flow months in advance is crucial for water sectors and society. In North America, snowmelt is a key driver of flow. This study presents a statistical workflow using snow data to forecast flow months ahead in North American snow-fed rivers. Variations in the river flow predictability across the continent are evident, raising concerns about future predictability in a changing (snow) climate. The reproducible workflow hosted on GitHub supports collaborative and open science.
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