Articles | Volume 26, issue 9
https://doi.org/10.5194/hess-26-2481-2022
© 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-26-2481-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
12 May 2022
Research article |
| 12 May 2022
| 12 May 2022
High-resolution (1 km) satellite rainfall estimation from SM2RAIN applied to Sentinel-1: Po River basin as a case study
Paolo Filippucci
CORRESPONDING AUTHOR
National Research Council, Research Institute for Geo-Hydrological
Protection, Perugia, Italy
TUWien (Technische Universität Wien), Department of Geodesy and
Geoinformation, Vienna, Austria
Università degli Studi di Perugia, Department of Civil and
Environmental Engineering, Perugia, Italy
Luca Brocca
National Research Council, Research Institute for Geo-Hydrological
Protection, Perugia, Italy
Raphael Quast
TUWien (Technische Universität Wien), Department of Geodesy and
Geoinformation, Vienna, Austria
Luca Ciabatta
National Research Council, Research Institute for Geo-Hydrological
Protection, Perugia, Italy
Carla Saltalippi
Università degli Studi di Perugia, Department of Civil and
Environmental Engineering, Perugia, Italy
Wolfgang Wagner
TUWien (Technische Universität Wien), Department of Geodesy and
Geoinformation, Vienna, Austria
Angelica Tarpanelli
National Research Council, Research Institute for Geo-Hydrological
Protection, Perugia, Italy
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14 citations as recorded by crossref.
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- 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
- 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
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- Soil Moisture Inversion Using Multi-Sensor Remote Sensing Data Based on Feature Selection Method and Adaptive Stacking Algorithm L. Wang & Y. Gao 10.3390/rs17091569
- SM2RAIN-Climate, a monthly global long-term rainfall dataset for climatological studies H. Mosaffa et al. 10.1038/s41597-023-02654-6
- Towards a novel high-spatial-resolution satellite rainfall product from C-band SAR Sentinel-1 over Central South Korea based on a bottom-up approach H. Nguyen et al. 10.1080/01431161.2022.2122894
- Benefits and pitfalls of irrigation timing and water amounts derived from satellite soil moisture L. Zappa et al. 10.1016/j.agwat.2024.108773
- Comprehensive performance evaluation of satellite-based and reanalysis rainfall estimate products in Ethiopia: For drought, flood, and water resources applications. D. Wodebo et al. 10.1016/j.ejrh.2024.102150
- HR-PrecipNet: A machine learning framework for 1-km high-resolution satellite precipitation estimation H. Mosaffa et al. 10.1016/j.jhydrol.2025.133217
- A novel validation of satellite soil moisture using SM2RAIN-derived rainfall estimates S. Do et al. 10.3389/frsen.2024.1474088
- Review on spatial downscaling of satellite derived precipitation estimates M. Kofidou et al. 10.1007/s12665-023-11115-7
- Playing the Water Cycle “Game”: Data From Space for A Safer Planet L. Brocca 10.3389/frym.2023.1201606
2 citations as recorded by crossref.
Latest update: 11 May 2025
Short summary
A high-resolution (1 km) rainfall product with 10–30 d temporal resolution was obtained starting from SM data from Sentinel-1. Good performances are achieved using observed data (gauge and radar) over the Po River Valley, Italy, as a benchmark. The comparison with a product characterized by lower spatial resolution (25 km) highlights areas where the high spatial resolution of Sentinel-1 has great benefits. Possible applications include water management, agriculture and index-based insurances.
A high-resolution (1 km) rainfall product with 10–30 d temporal resolution was obtained starting...
