13 citations as recorded by crossref.

1. Ensemble machine learning and deep learning framework for flood susceptibility mapping in the transboundary Rapti River Basin A. Kumar et al. https://doi.org/10.1007/s12665-026-12912-6
2. High-resolution satellite observations for developing advanced decision support systems for water resources management in the Po River S. Camici et al. https://doi.org/10.1016/j.jhydrol.2025.134047
3. Winter snow deficit was a harbinger of summer 2022 socio-hydrologic drought in the Po Basin, Italy F. Avanzi et al. https://doi.org/10.1038/s43247-024-01222-z
4. Mapping snow cover frequency at 30 m for studying seasonal variations and topographic controls on the Tibetan Plateau G. Wang et al. https://doi.org/10.1016/j.jhydrol.2025.133303
5. A Digital Twin of the terrestrial water cycle: a glimpse into the future through high-resolution Earth observations L. Brocca et al. https://doi.org/10.3389/fsci.2023.1190191
6. MODELLING THE HUMAN IMPACT ON HYDROLOGICAL CYCLE: THE MISDc v3.1 MODEL S. Kalimisetty et al. https://doi.org/10.1016/j.envsoft.2026.107056
7. Effect of Image-Processing Routines on Geographic Object-Based Image Analysis for Mapping Glacier Surface Facies from Svalbard and the Himalayas S. Jawak et al. https://doi.org/10.3390/rs14174403
8. Enhancing the Representation of Glaciers and Ice Sheets in the ecLand Land-Surface Model: Impacts on Surface Energy Balance and Hydrology Across Scales G. Arduini et al. https://doi.org/10.5194/tc-20-1119-2026
9. Estimating robust melt factors and temperature thresholds for snow modelling across the Northern Hemisphere A. Fontrodona-Bach et al. https://doi.org/10.5194/hess-30-2613-2026
10. IT-SNOW: a snow reanalysis for Italy blending modeling, in situ data, and satellite observations (2010–2021) F. Avanzi et al. https://doi.org/10.5194/essd-15-639-2023
11. High-resolution satellite products improve hydrological modeling in northern Italy L. Alfieri et al. https://doi.org/10.5194/hess-26-3921-2022
12. Estimating the Ebro river discharge at 1 km/daily resolution using indirect satellite observations V. Pellet et al. https://doi.org/10.1088/2515-7620/ad7adb
13. Learning to filter: snow data assimilation using a Long Short-Term Memory network G. Blandini et al. https://doi.org/10.5194/tc-19-4759-2025