Articles | Volume 44
01 Nov 2017
 | 01 Nov 2017

An evaluation of the potential of Sentinel 1 for improving flash flood predictions via soil moisture–data assimilation

Luca Cenci, Luca Pulvirenti, Giorgio Boni, Marco Chini, Patrick Matgen, Simone Gabellani, Giuseppe Squicciarino, and Nazzareno Pierdicca

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Cited articles

Albergel, C., de Rosnay, P., Gruhier, C., Muñoz-Sabater, J., Hasenauer, S., Isaksen, L., Kerr, Y., and Wagner, W.: Evaluation of remotely sensed and modelled soil moisture products using global ground-based in situ observations, Remote Sens. Environ., 118, 215–226,, 2012.
Alexakis, D. D., Mexis, F. D. K., Vozinaki, A. E. K., Daliakopoulos, I. N., and Tsanis, I. K.: Soil moisture content estimation based on Sentinel-1 and auxiliary earth observation products. A hydrological approach, Sensors, 17, 1455,, 2017.
Attema, E. P. W. and Ulaby, F. T.: Vegetation modelled as a water cloud, Radio Sci., 13, 357–364,, 1978.
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Borga, M., Anagnostou, E. N., Blöschl, G. and Creutin, J. D.: Flash flood forecasting, warning and risk management: The HYDRATE project, Environ. Sci. Policy, 14, 834–844,, 2011.
Short summary
This research aims at improving hydrological modelling skills of flash flood prediction by exploiting earth observation data. To this aim, high spatial/moderate temporal resolution soil moisture maps, derived from Sentinel 1 acquisitions, were used in a data assimilation framework. Findings revealed the potential of Sentinel 1-based soil moisture data assimilation for flash flood risk reduction and improved our understanding of the capabilities of the aforementioned satellite-derived product.