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Volume 44 | Copyright
Adv. Geosci., 44, 89-100, 2017
https://doi.org/10.5194/adgeo-44-89-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.

  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 et al.
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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, https://doi.org/10.1016/j.rse.2011.11.017, 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, https://doi.org/10.3390/s17061455, 2017.
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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, https://doi.org/10.1016/j.envsci.2011.05.017, 2011.
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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.
This research aims at improving hydrological modelling skills of flash flood prediction by...
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