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.
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.
the Creative Commons Attribution 4.0 License.
Development and technical paper
| 
08 Apr 2022
Development and technical paper |
| 08 Apr 2022
| 08 Apr 2022
AI4Water v1.0: an open-source python package for modeling hydrological time series using data-driven methods
Ather Abbas
Urban and Environmental Engineering, Ulsan National Institute of Science and Technology, Ulsan 44919, Republic of Korea
Laurie Boithias
Géosciences Environnement Toulouse, Université de Toulouse, CNRS, IRD, UPS, 31400 Toulouse, France
Yakov Pachepsky
Environmental Microbial and Food Safety Laboratory, USDA-ARS, Beltsville, MD, USA
Kyunghyun Kim
Watershed and Total Load Management Research Division, National Institute of Environmental Research, Hwangyeong-ro 42, Seogu, Incheon 22689, Republic of Korea
Climate Research Department, APEC Climate Center, Busan, Republic of Korea
Kyung Hwa Cho
CORRESPONDING AUTHOR
Urban and Environmental Engineering, Ulsan National Institute of Science and Technology, Ulsan 44919, Republic of Korea
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Latest update: 16 Aug 2025
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.
The field of artificial intelligence has shown promising results in a wide variety of fields...
