Hydrology and Earth System Sciences
Hydrology and Earth System Sciences
HESS
Articles | Volume 25, issue 11
Articles | Volume 25, issue 11
https://doi.org/10.5194/hess-25-5917-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-25-5917-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 25, issue 11
Research article
 | 
15 Nov 2021
Research article |  | 15 Nov 2021

Evaluating different machine learning methods to simulate runoff from extensive green roofs

Elhadi Mohsen Hassan Abdalla, Vincent Pons, Virginia Stovin, Simon De-Ville, Elizabeth Fassman-Beck, Knut Alfredsen, and Tone Merete Muthanna

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Short summary
This study investigated the potential of using machine learning algorithms as hydrological models of green roofs across different climatic condition. The study provides comparison between conceptual and machine learning algorithms. Machine learning models were found to be accurate in simulating runoff from extensive green roofs.
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