Articles | Volume 26, issue 9
https://doi.org/10.5194/hess-26-2481-2022
https://doi.org/10.5194/hess-26-2481-2022
Research article
 | 
12 May 2022
Research article |  | 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, Luca Brocca, Raphael Quast, Luca Ciabatta, Carla Saltalippi, Wolfgang Wagner, and Angelica Tarpanelli

Related authors

The development of an operational system for estimating irrigation water use reveals socio-political dynamics in Ukraine
Jacopo Dari, Paolo Filippucci, and Luca Brocca
EGUsphere, https://doi.org/10.5194/egusphere-2023-2479,https://doi.org/10.5194/egusphere-2023-2479, 2023
Short summary
A daily 25 km short-latency rainfall product for data-scarce regions based on the integration of the Global Precipitation Measurement mission rainfall and multiple-satellite soil moisture products
Christian Massari, Luca Brocca, Thierry Pellarin, Gab Abramowitz, Paolo Filippucci, Luca Ciabatta, Viviana Maggioni, Yann Kerr, and Diego Fernandez Prieto
Hydrol. Earth Syst. Sci., 24, 2687–2710, https://doi.org/10.5194/hess-24-2687-2020,https://doi.org/10.5194/hess-24-2687-2020, 2020
Short summary
SM2RAIN–ASCAT (2007–2018): global daily satellite rainfall data from ASCAT soil moisture observations
Luca Brocca, Paolo Filippucci, Sebastian Hahn, Luca Ciabatta, Christian Massari, Stefania Camici, Lothar Schüller, Bojan Bojkov, and Wolfgang Wagner
Earth Syst. Sci. Data, 11, 1583–1601, https://doi.org/10.5194/essd-11-1583-2019,https://doi.org/10.5194/essd-11-1583-2019, 2019
Short summary
Estimating irrigation water use over the contiguous United States by combining satellite and reanalysis soil moisture data
Felix Zaussinger, Wouter Dorigo, Alexander Gruber, Angelica Tarpanelli, Paolo Filippucci, and Luca Brocca
Hydrol. Earth Syst. Sci., 23, 897–923, https://doi.org/10.5194/hess-23-897-2019,https://doi.org/10.5194/hess-23-897-2019, 2019
Short summary

Related subject area

Subject: Global hydrology | Techniques and Approaches: Remote Sensing and GIS
Benchmarking multimodel terrestrial water storage seasonal cycle against Gravity Recovery and Climate Experiment (GRACE) observations over major global river basins
Sadia Bibi, Tingju Zhu, Ashraf Rateb, Bridget R. Scanlon, Muhammad Aqeel Kamran, Abdelrazek Elnashar, Ali Bennour, and Ci Li
Hydrol. Earth Syst. Sci., 28, 1725–1750, https://doi.org/10.5194/hess-28-1725-2024,https://doi.org/10.5194/hess-28-1725-2024, 2024
Short summary
Increasing seasonal variation in the extent of rivers and lakes from 1984 to 2022
Björn Nyberg, Roger Sayre, and Elco Luijendijk
Hydrol. Earth Syst. Sci., 28, 1653–1663, https://doi.org/10.5194/hess-28-1653-2024,https://doi.org/10.5194/hess-28-1653-2024, 2024
Short summary
Investigating sources of variability in closing the terrestrial water balance with remote sensing
Claire I. Michailovsky, Bert Coerver, Marloes Mul, and Graham Jewitt
Hydrol. Earth Syst. Sci., 27, 4335–4354, https://doi.org/10.5194/hess-27-4335-2023,https://doi.org/10.5194/hess-27-4335-2023, 2023
Short summary
Dynamic rainfall erosivity estimates derived from IMERG data
Robert A. Emberson
Hydrol. Earth Syst. Sci., 27, 3547–3563, https://doi.org/10.5194/hess-27-3547-2023,https://doi.org/10.5194/hess-27-3547-2023, 2023
Short summary
Technical note: Surface fields for global environmental modelling
Margarita Choulga, Francesca Moschini, Cinzia Mazzetti, Stefania Grimaldi, Juliana Disperati, Hylke Beck, Peter Salamon, and Christel Prudhomme
EGUsphere, https://doi.org/10.5194/egusphere-2023-1306,https://doi.org/10.5194/egusphere-2023-1306, 2023
Short summary

Cited articles

Albergel, C., Rüdiger, C., Pellarin, T., Calvet, J.-C., Fritz, N., Froissard, F., Suquia, D., Petitpa, A., Piguet, B., and Martin, E.: From near-surface to root-zone soil moisture using an exponential filter: an assessment of the method based on in-situ observations and model simulations, Hydrol. Earth Syst. Sci., 12, 1323–1337, https://doi.org/10.5194/hess-12-1323-2008, 2008. 
Barrett, E. C. and Beaumont, M. J.: Satellite rainfall monitoring: An overview, Remote Sensing Reviews, 11, 23–48, https://doi.org/10.1080/02757259409532257, 1994. 
Bauer-Marschallinger, B., Paulik, C., Hochstöger, S., Mistelbaue, T., Modanesi, S., Ciabatta, L., Massari, C., Brocca, L., and Wagner, W.: Soil Moisture from Fusion of Scatterometer and SAR: Closing the Scale Gap with Temporal Filtering, Remote Sens., 10, 1030, https://doi.org/10.3390/rs10071030, 2018. 
Bauer-Marschallinger, B., Cao, S., Navacchi, C., Freeman, V., Reuß, F., Geudtner, D., Rommen, B., Vega, F. C., Snoeij, P., Attema, P., Reimer, C., and Wagner W.: The normalised Sentinel-1 Global Backscatter Model, mapping Earth’s land surface with C-band microwaves, Scientific Data, 8, 277, https://doi.org/10.1038/s41597-021-01059-7, 2021. 
Black, E., Tarnavsky, E., Maidment, R., Greatrex, H., Mookerjee, A., Quaife, T., and Brown, M.: The Use of Remotely Sensed Rainfall for Managing Drought Risk: A Case Study of Weather Index Insurance in Zambia, Remote Sens., 8, 342, https://doi.org/10.3390/rs8040342, 2016. 
Download
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.