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Sep 26, 2022

Discussion of “Comprehensive Evaluation of Machine Learning Techniques for Hydrological Drought Forecasting” by Muhammad Jehanzaib, Muhammad Bilal Idrees, Dongkyun Kim, and Tae-Woong Kim

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Publication: Journal of Irrigation and Drainage Engineering
Volume 148, Issue 12
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Data Availability Statement

No data, models, or codes were generated or used during the study.

Acknowledgments

The authors acknowledge the financial support provided by the Natural Science and Engineering Research Council of Canada (NSERC) Discovery Grant (#RGPIN-2020-04583).

References

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Go to Journal of Irrigation and Drainage Engineering
Journal of Irrigation and Drainage Engineering
Volume 148Issue 12December 2022

History

Received: Aug 12, 2021
Accepted: Sep 14, 2021
Published online: Sep 26, 2022
Published in print: Dec 1, 2022
Discussion open until: Feb 26, 2023

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Ph.D. Candidate, Dept. of Soils and Agri-Food Engineering, Université Laval, Québec, Canada G1V0A6. ORCID: https://orcid.org/0000-0002-6906-629X. Email: [email protected]
Assistant Professor, Dept. of Soils and Agri-Food Engineering, Université Laval, Québec, Canada 1V0A6; Assistant Professor, Dept. of Civil Engineering, Univ. of Ottawa, 161 Louis Pasteur Dr., Ottawa, Canada K1N6N5 (corresponding author). ORCID: https://orcid.org/0000-0001-6169-3654. Email: [email protected]; [email protected]

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