Geoscientific Model Development
Geoscientific Model Development
GMD
Articles | Volume 15, issue 7
Articles | Volume 15, issue 7
https://doi.org/10.5194/gmd-15-3021-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-15-3021-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 15, issue 7
Development and technical paper
 | 
08 Apr 2022
Development and technical paper |  | 08 Apr 2022

AI4Water v1.0: an open-source python package for modeling hydrological time series using data-driven methods

Ather Abbas, Laurie Boithias, Yakov Pachepsky, Kyunghyun Kim, Jong Ahn Chun, and Kyung Hwa Cho

Supplement

https://doi.org/10.5194/gmd-15-3021-2022-supplement

Data sets

AI4Water: a framework for building and testing machine learning models for hydrological simulations Ather Abbas https://doi.org/10.5281/zenodo.5595680

Model code and software

Al4Water: a framework for building and testing machine learning models for hydrological simulations Ather Abbas https://doi.org/10.5281/zenodo.5595680

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Short summary
The field of artificial intelligence has shown promising results in a wide variety of fields including hydrological modeling. However, developing and testing hydrological models with artificial intelligence techniques require expertise from diverse fields. In this study, we developed an open-source framework based upon the python programming language to simplify the process of the development of hydrological models of time series data using machine learning.
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