Articles | Volume 26, issue 14
https://doi.org/10.5194/hess-26-3921-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-26-3921-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
29 Jul 2022
Research article |
| 29 Jul 2022
| 29 Jul 2022
High-resolution satellite products improve hydrological modeling in northern Italy
Lorenzo Alfieri
CORRESPONDING AUTHOR
CIMA Research Foundation, University Campus of Savona, Savona, 17100, Italy
Francesco Avanzi
CIMA Research Foundation, University Campus of Savona, Savona, 17100, Italy
Fabio Delogu
CIMA Research Foundation, University Campus of Savona, Savona, 17100, Italy
Simone Gabellani
CIMA Research Foundation, University Campus of Savona, Savona, 17100, Italy
Giulia Bruno
CIMA Research Foundation, University Campus of Savona, Savona, 17100, Italy
Lorenzo Campo
CIMA Research Foundation, University Campus of Savona, Savona, 17100, Italy
Andrea Libertino
CIMA Research Foundation, University Campus of Savona, Savona, 17100, Italy
Christian Massari
National Research Council, Research Institute for Geo-Hydrological
Protection, Perugia, 06128, Italy
Angelica Tarpanelli
National Research Council, Research Institute for Geo-Hydrological
Protection, Perugia, 06128, Italy
Dominik Rains
Hydro-Climate Extremes Lab (H-CEL), Ghent University, Ghent, 9000,
Belgium
Diego G. Miralles
Hydro-Climate Extremes Lab (H-CEL), Ghent University, Ghent, 9000,
Belgium
Raphael Quast
Department of Geodesy and Geoinformation, TU Wien, Vienna, 1040,
Austria
Mariette Vreugdenhil
Department of Geodesy and Geoinformation, TU Wien, Vienna, 1040,
Austria
Huan Wu
Southern Marine Science and Engineering Laboratory (Zhuhai), School of Atmospheric Sciences, Sun Yat-sen University, Zhuhai, 519082, China
Guangdong Province Key Laboratory for Climate Change and Natural Disaster Studies, Sun Yat-sen University, Guangzhou, 510275, China
Luca Brocca
National Research Council, Research Institute for Geo-Hydrological
Protection, Perugia, 06128, Italy
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- Uncertainty Quantification of Satellite Soil Moisture Retrieved Precipitation in the Central Tibetan Plateau K. Zhang et al. 10.3390/rs15102600
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- Playing the Water Cycle “Game”: Data From Space for A Safer Planet L. Brocca 10.3389/frym.2023.1201606
- Satellite-based soil moisture enhances the reliability of agro-hydrological modeling in large transboundary river basins M. Eini et al. 10.1016/j.scitotenv.2023.162396
- Hydrologic applicability of satellite-based precipitation estimates for irrigation water management in the data-scarce region S. Bista et al. 10.1016/j.jhydrol.2024.131310
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- Impact-based flood forecasting in the Greater Horn of Africa L. Alfieri et al. 10.5194/nhess-24-199-2024
- Connecting hydrological modelling and forecasting from global to local scales: Perspectives from an international joint virtual workshop A. Dasgupta et al. 10.1111/jfr3.12880
- Exploring the actual spatial resolution of 1 km satellite soil moisture products L. Brocca et al. 10.1016/j.scitotenv.2024.174087
- Capability of satellite rainfall products in simulating streamflows in the Black Volta Basin F. Logah et al. 10.1007/s40899-023-00871-w
- Evaluation of snow depth retrievals from ICESat-2 using airborne laser-scanning data C. Deschamps-Berger et al. 10.5194/tc-17-2779-2023
- A Complete Meteo/Hydro/Hydraulic Chain Application to Support Early Warning and Monitoring Systems: The Apollo Medicane Use Case M. Lagasio et al. 10.3390/rs14246348
- High-resolution observations from space to address new applications in hydrology L. Brocca et al. 10.1016/j.xinn.2023.100437
- Hydrological model skills change with drought severity; insights from multi-variable evaluation G. Bruno et al. 10.1016/j.jhydrol.2024.131023
- A Digital Twin of the terrestrial water cycle: a glimpse into the future through high-resolution Earth observations L. Brocca et al. 10.3389/fsci.2023.1190191
- IT-SNOW: a snow reanalysis for Italy blending modeling, in situ data, and satellite observations (2010–2021) F. Avanzi et al. 10.5194/essd-15-639-2023
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Latest update: 26 Jul 2024
Short summary
This work shows advances in high-resolution satellite data for hydrology. We performed hydrological simulations for the Po River basin using various satellite products, including precipitation, evaporation, soil moisture, and snow depth. Evaporation and snow depth improved a simulation based on high-quality ground observations. Interestingly, a model calibration relying on satellite data skillfully reproduces observed discharges, paving the way to satellite-driven hydrological applications.
This work shows advances in high-resolution satellite data for hydrology. We performed...
