Integrating multi-source high-resolution satellite data to redistribute SWE in semi-distributed hydrological modeling using a random forest approach
Alpine regions are highly sensitive to climate change, and snow melt dynamics are crucial in their hydrological processes. A key variable is the snow water equivalent (SWE), but direct measurements are rare and limited, making spatial estimates diffic
Authors
- Giuseppe Formetta (ORCID: https://orcid.org/0000-0002-0252-1462)
- Giacomo Bertoldi (ORCID: https://orcid.org/0000-0003-0397-8103)
- Valentina Premier (ORCID: https://orcid.org/0000-0002-4629-2235)
- Michele Bozzoli (ORCID: https://orcid.org/0000-0002-3844-0701)
- Mathias Bavay (ORCID: https://orcid.org/0000-0002-5039-1578)
- Carlo Marín (ORCID: https://orcid.org/0000-0001-6987-9445)
- Cristian Tonelli
Institutions
- Eurac Research (IT)
- University of Trento (IT)
- Center for Snow and Avalanche Studies (US)
Publication Details
- Published
- 2025-09-22
- DOI
- https://doi.org/10.22541/essoar.175855515.58229601/v1
- Primary Topic
- Hydrology and Watershed Management Studies
- Type
- article
- Field-Weighted Citation Impact
- 0.00