Articles | Volume 14, issue 2
https://doi.org/10.5194/gmd-14-821-2021
https://doi.org/10.5194/gmd-14-821-2021
Model description paper
 | 
05 Feb 2021
Model description paper |  | 05 Feb 2021

Shyft v4.8: a framework for uncertainty assessment and distributed hydrologic modeling for operational hydrology

John F. Burkhart, Felix N. Matt, Sigbjørn Helset, Yisak Sultan Abdella, Ola Skavhaug, and Olga Silantyeva

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AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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AR: Author's response | RR: Referee report | ED: Editor decision
AR by John F. Burkhart on behalf of the Authors (14 Oct 2020)  Manuscript 
ED: Publish subject to technical corrections (16 Oct 2020) by Bethanna Jackson
AR by John F. Burkhart on behalf of the Authors (16 Oct 2020)  Manuscript 
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Short summary
We present a new hydrologic modeling framework for interactive development of inflow forecasts for hydropower production planning and other operational environments (e.g., flood forecasting). The software provides a Python user interface with an application programming interface (API) for a computationally optimized C++ model engine, giving end users extensive control over the model configuration in real time during a simulation. This provides for extensive experimentation with configuration.