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Explainable Artificial Intelligence in Hydrology: A Review | Synapse
March 3, 2026
Explainable Artificial Intelligence in Hydrology: A Review
MF
Marzieh Fadaee
Shahid Bahonar University of Kerman
MK
Marwan Kheimi
Key Points
Explainable artificial intelligence improves transparency in machine learning applications for hydrology.
Machine learning algorithms were analyzed to understand their decision-making processes in water resource management.
Reviewing various case studies highlighted effective data analysis techniques employed in hydrological predictions.
The findings suggest that integrating explainable AI could enhance decision-making in hydrological studies.
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Fadaee et al. (Sun,) studied this question.
synapsesocial.com/papers/69a76875badf0bb9e87e4b4b
https://doi.org/https://doi.org/10.1007/s11269-025-04435-9