Developing an alternative data-driven model to resemble geomorphologic rainfall-runoff models
The primary merit of data-driven-based runoff models is their capability to handle various inputs, including hydrological, land use, and geographical data, allowing for flexibility regarding different environmental conditions and landscapes. Physics-based models provide a comprehensive framework for...
Saved in:
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2025-12-01
|
| Series: | Geomatics, Natural Hazards & Risk |
| Subjects: | |
| Online Access: | https://www.tandfonline.com/doi/10.1080/19475705.2025.2516725 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
