Preprints
https://doi.org/10.5194/hess-2021-563
https://doi.org/10.5194/hess-2021-563

  16 Nov 2021

16 Nov 2021

Review status: this preprint is currently under review for the journal HESS.

High resolution (1 km) satellite rainfall estimation from SM2RAIN applied to Sentinel-1: Po River Basin as case study

Paolo Filippucci1,2,3, Luca Brocca1, Raphael Quast2, Luca Ciabatta1, Carla Saltalippi3, Wolfgang Wagner2, and Angelica Tarpanelli1 Paolo Filippucci et al.
  • 1National Research Council, Research Institute for Geo-Hydrological Protection, Perugia, Italy
  • 2TUWien (Technische Universität Wien), Department of Geodesy and Geoinformation, Wien, Austria
  • 3Università degli Studi di Perugia, Department of Civil and Environmental Engineering, Perugia, Italy

Abstract. Satellite sensors to infer rainfall measurements have become widely available in the last years, but their spatial resolution usually exceed 10 kilometres, due to technological limitation. This poses an important constraint on their use for application such as water resource management, index insurance evaluation or hydrological models, which require more and more detailed information.

In this work, the algorithm SM2RAIN (Soil Moisture to Rain) for rainfall estimation is applied to a high resolution soil moisture product derived from Sentinel-1, named S1-RT1, characterized by 1 km spatial resolution (500 m spacing), and to the 25 km ASCAT soil moisture (12.5 km spacing), resampled to the same grid of S1-RT1, to obtain rainfall products with the same spatial and temporal resolution over the Po River basin. In order to overcome the need of calibration and to allow its global application, a parameterized version of SM2RAIN algorithm was adopted along with the standard one. The capabilities in estimating rainfall of each obtained product were then compared, to assess both the parameterized SM2RAIN performances and the added value of Sentinel-1 high spatial resolution.

The results show that good estimates of rainfall are obtainable from Sentinel-1 when considering aggregation time steps greater than 1 day, since to the low temporal resolution of this sensor (from 1.5 to 4 days over Europe) prevents its application to infer daily rainfall. On average, the ASCAT derived rainfall product performs better than S1-RT1 one, even if the performances are equally good when 30 days accumulated rainfall is considered, being the mean Pearson’s correlation of the rainfall obtained from ASCAT and S1-RT1 equal to 0.74 and 0.73, respectively, using the parameterized SM2RAIN. Notwithstanding this, the products obtained from Sentinel-1 outperform those from ASCAT in specific areas, like in valleys inside mountain regions and most of the plains, confirming the added value of the high spatial resolution information in obtaining spatially detailed rainfall. Finally, the parameterized products performances are similar to those obtained with SM2RAIN calibration, confirming the reliability of the parameterized algorithm for rainfall estimation in this area and fostering the possibility to apply SM2RAIN worldwide even without the availability of a rainfall benchmark product.

Paolo Filippucci et al.

Status: open (until 11 Jan 2022)

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Paolo Filippucci et al.

Paolo Filippucci et al.

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Short summary
A high resolution (1 km) rainfall product with 10–30 days temporal resolution was obtained starting from SM data from Sentinel-1. Good performances are achieved using as benchmark observed data (gauge+radar) over the Po River Valley, in Italy. The comparison with a product characterized by lower spatial resolution (25 km) highlights areas where the high spatial resolution of Sentinel-1 allows great benefits. Possible applications include water management, agriculture and index based insurances.