Proceedings of IAHS
Proceedings of IAHS
PIAHS
Articles | Volume 374
Articles | Volume 374
https://doi.org/10.5194/piahs-374-159-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/piahs-374-159-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
Articles | Volume 374
17 Oct 2016
 | 17 Oct 2016

Comparison of cross-validation and bootstrap aggregating for building a seasonal streamflow forecast model

Simon Schick, Ole Rössler, and Rolf Weingartner

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Latest update: 08 Nov 2024
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Short summary
In water resources management, planning at the seasonal time scale is confronted with large uncertainties. Key variables are often unknown or hard to forecast, e.g. precipitation of the next three months. In the present study, we try to highlight some aspects concerning the development of a model faced with these uncertainties. Using the example of statistical streamflow forecasts, the results of the study indicate that the forecast accuracy is improved by the combination of several models.
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