Articles | Volume 17, issue 6
https://doi.org/10.5194/tc-17-2387-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/tc-17-2387-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Exploring the use of multi-source high-resolution satellite data for snow water equivalent reconstruction over mountainous catchments
Valentina Premier
CORRESPONDING AUTHOR
Institute for Earth Observation, Eurac Research, Viale Druso, 1, 39100 Bolzano, Italy
Department of Information Engineering and Computer Science, University of Trento, Via Sommarive, 9 I, 38123 Povo, Italy
Carlo Marin
Institute for Earth Observation, Eurac Research, Viale Druso, 1, 39100 Bolzano, Italy
Giacomo Bertoldi
Institute for Alpine Environment, Eurac Research, Viale Druso, 1, 39100 Bolzano, Italy
Riccardo Barella
Institute for Earth Observation, Eurac Research, Viale Druso, 1, 39100 Bolzano, Italy
Claudia Notarnicola
Institute for Earth Observation, Eurac Research, Viale Druso, 1, 39100 Bolzano, Italy
Lorenzo Bruzzone
Department of Information Engineering and Computer Science, University of Trento, Via Sommarive, 9 I, 38123 Povo, Italy
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Cited
14 citations as recorded by crossref.
- Fusing daily snow water equivalent from 1980 to 2020 in China using a spatiotemporal XGBoost model L. Sun et al. https://doi.org/10.1016/j.jhydrol.2024.130876
- Snow droughts over 1951–2021 show a decreasing and then increasing trend G. Ari et al. https://doi.org/10.1016/j.atmosres.2025.108237
- Improvement on the Effective Snow Cover Extraction Using Fusion Satellite Images Approach R. Esmaeelzadeh et al. https://doi.org/10.1007/s12524-024-01828-y
- Can streamflow observations constrain snow mass reconstructions? Lessons from two synthetic numerical experiments P. Wiersma et al. https://doi.org/10.5194/hess-30-3331-2026
- Evaluating precipitation corrections to enhance high-alpine hydrological modeling T. Pulka et al. https://doi.org/10.1016/j.jhydrol.2024.132202
- Combining Causal Inference with Machine Learning for Reconstructing Mountain Snow Water Equivalent Data Z. Ouyang et al. https://doi.org/10.3390/w18101243
- Morphological indexes to describe snow-cover patterns in a high-alpine area L. Ferrarin et al. https://doi.org/10.1017/aog.2023.62
- 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
- Capturing Snowmelt Runoff Onset Date under Different Land Cover Types Using Synthetic Aperture Radar: Case Study of Sierra Nevada Mountains, USA B. Gao & W. Ma https://doi.org/10.3390/app14156844
- Snow Water Equivalent Monitoring—A Review of Large-Scale Remote Sensing Applications S. Schilling et al. https://doi.org/10.3390/rs16061085
- 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
- Enhancing snow depth estimation with snow cover geometrical descriptors L. Ferrarin et al. https://doi.org/10.3389/feart.2025.1672558
- Retrieval of snow depth using synthetic aperture radar: past, current, and future Z. Li et al. https://doi.org/10.1016/j.jhydrol.2026.135103
- Recent Patterns and Trends of Snow Cover (2000–2023) in the Cantabrian Mountains (Spain) from Satellite Imagery Using Google Earth Engine A. Melón-Nava https://doi.org/10.3390/rs16193592
14 citations as recorded by crossref.
- Fusing daily snow water equivalent from 1980 to 2020 in China using a spatiotemporal XGBoost model L. Sun et al. https://doi.org/10.1016/j.jhydrol.2024.130876
- Snow droughts over 1951–2021 show a decreasing and then increasing trend G. Ari et al. https://doi.org/10.1016/j.atmosres.2025.108237
- Improvement on the Effective Snow Cover Extraction Using Fusion Satellite Images Approach R. Esmaeelzadeh et al. https://doi.org/10.1007/s12524-024-01828-y
- Can streamflow observations constrain snow mass reconstructions? Lessons from two synthetic numerical experiments P. Wiersma et al. https://doi.org/10.5194/hess-30-3331-2026
- Evaluating precipitation corrections to enhance high-alpine hydrological modeling T. Pulka et al. https://doi.org/10.1016/j.jhydrol.2024.132202
- Combining Causal Inference with Machine Learning for Reconstructing Mountain Snow Water Equivalent Data Z. Ouyang et al. https://doi.org/10.3390/w18101243
- Morphological indexes to describe snow-cover patterns in a high-alpine area L. Ferrarin et al. https://doi.org/10.1017/aog.2023.62
- 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
- Capturing Snowmelt Runoff Onset Date under Different Land Cover Types Using Synthetic Aperture Radar: Case Study of Sierra Nevada Mountains, USA B. Gao & W. Ma https://doi.org/10.3390/app14156844
- Snow Water Equivalent Monitoring—A Review of Large-Scale Remote Sensing Applications S. Schilling et al. https://doi.org/10.3390/rs16061085
- 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
- Enhancing snow depth estimation with snow cover geometrical descriptors L. Ferrarin et al. https://doi.org/10.3389/feart.2025.1672558
- Retrieval of snow depth using synthetic aperture radar: past, current, and future Z. Li et al. https://doi.org/10.1016/j.jhydrol.2026.135103
- Recent Patterns and Trends of Snow Cover (2000–2023) in the Cantabrian Mountains (Spain) from Satellite Imagery Using Google Earth Engine A. Melón-Nava https://doi.org/10.3390/rs16193592
Saved (final revised paper)
Latest update: 07 Jun 2026
Short summary
The large amount of information regularly acquired by satellites can provide important information about SWE. We explore the use of multi-source satellite data, in situ observations, and a degree-day model to reconstruct daily SWE at 25 m. The results show spatial patterns that are consistent with the topographical features as well as with a reference product. Being able to also reproduce interannual variability, the method has great potential for hydrological and ecological applications.
The large amount of information regularly acquired by satellites can provide important...