Deep Learning, Epistemic Uncertainties and the Inexact Sciences
ABSTRACT This commentary considers the recent explosion of models based on Deep Learning/Machine Learning methods in hydrological journals and how their application might better contribute to hydrological understanding in the face of epistemic uncertainties in an inexact science.
Authors
- Keith Beven (ORCID: https://orcid.org/0000-0001-7465-3934)
Institutions
- Lancaster University (GB)
Publication Details
- Journal
- Hydrological Processes
- Published
- 2026-03-01
- DOI
- https://doi.org/10.1002/hyp.70489
- Primary Topic
- Hydrology and Watershed Management Studies
- Type
- article
- Field-Weighted Citation Impact
- 0.00