Articles | Volume 373
https://doi.org/10.5194/piahs-373-167-2016
https://doi.org/10.5194/piahs-373-167-2016
12 May 2016
 | 12 May 2016

Improvement of operational flood forecasting through the assimilation of satellite observations and multiple river flow data

Fabio Castelli and Giulia Ercolani

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Cited articles

Brocca, L., Melone, F., Moramarco, T., Wagner, W., Naeimi, V., Bartalis, Z., and Hasenauer, S.: Improving runoff prediction through the assimilation of the ASCAT soil moisture product, Hydrol. Earth Syst. Sci., 14, 1881–1893, https://doi.org/10.5194/hess-14-1881-2010, 2010.
Campo, L., Caparrini, F., and Castelli, F.: Use of multi-platform, multi-temporal remote-sensing data for calibration of a distributed hydrological model: an application in the Arno basin, Italy, Hydrol. Process., 20, 2693–2712, https://doi.org/10.1002/hyp.6061, 2006.
Campo, L., Castelli, F., Caparrini, F., and Entekhabi, D.: An assimilation algorithm of satellite-derived LST observations for the operational production of soil moisture maps, in: Geoscience and Remote Sensing Symposium (IGARSS), 2012 IEEE International, Munich, Germany, 22–27 July 2012, IEEE, 1314–1317, 2012.
Caparrini, F., Castelli, F., and Entekhabi, D.: Estimation of surface turbulent fluxes through assimilation of radiometric surface temperature sequences, J. Hydrometeorol., 5, 145–159, https://doi.org/10.1175/1525-7541(2004)005<0145:EOSTFT>2.0.CO;2, 2004.
Castelli, F.: A simplified stochastic model for infiltration into a heterogeneous soil forced by random precipitation, Adv. Water Resour., 19, 133–144, https://doi.org/10.1016/0309-1708(95)00041-0, 1996.
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Short summary
Improving flood forecasting can strengthen the reduction of floods impacts through early warning systems. Our study presents improvements obtained with the integration of a data assimilation system into a hydrological model that is part of the operational forecasting chain for Arno river (central Italy). The system effectively combines the model with observations of river flow at multiple locations and satellite data, leading to more accurate predictions of flood peak flow.