Articles | Volume 14, issue 2
Geosci. Model Dev., 14, 821–842, 2021
Geosci. Model Dev., 14, 821–842, 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 et al.

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Cited articles

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Anghileri, D., Monhart, S., Zhou, C., Bogner, K., Castelletti, A., Burlando, P., and Zappa, M.: The Value of Subseasonal Hydrometeorological Forecasts to Hydropower Operations: How Much Does Preprocessing Matter?, Water Resour. Res., 55, 10,, 2019. a, b, c
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.