Articles | Volume 17, issue 8
https://doi.org/10.5194/hess-17-3159-2013
https://doi.org/10.5194/hess-17-3159-2013
Research article
 | 
06 Aug 2013
Research article |  | 06 Aug 2013

Application of a model-based rainfall-runoff database as efficient tool for flood risk management

L. Brocca, S. Liersch, F. Melone, T. Moramarco, and M. Volk

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Cited articles

Asquith, W. H., Thompson, D. B., Cleveland, T. G., and Fang, X.: Synthesis of Rainfall and Runoff Data used for Texas Department of Transportation Research Projects 0-4193 and 0-4194, US Geological Survey, Open File Report 2004-103, p. 50, 2004.
Bae, D. H., Georgakakos, K. P., and Nanda, S. K.: Operational forecasting with real-time databases, J. Hydraul. Div.-ASCE, 121, 49–60, 1995.
Barbetta, S., Moramarco, T., Brocca, L., Franchini, M., and Melone, F.: Confidence interval of real-time forecast stages provided by the STAFOM-RCM model: the case study of the Tiber River (Italy), Hydrol. Process., online first, https://doi.org/10.1002/hyp.9613, 2012.
Berni, N., Brocca, L., Giustarini, L., Pandolfo, C., Stelluti, M., Melone, F., Moramarco, T.: Coupling hydrological and hydraulic modeling for a reliable flood risk mitigation activities in the Upper-Medium Tiber River basin, Geophys. Res. Abstr., EGU2009-9498-3, EGU General Assembly 2009, Vienna, Austria, 2009a.
Berni, N., Pandolfo, C., Ponziani, F., Stelluti, M., and Viterbo, A.: Umbria Region Forecasting/Decision Support fr Hydraulic Risk Mitigation Purposes, in: Proceedings of the Tenth International Conference on Computing and Control in the Water Industry, CRC Press, Sheffield (UK), 6 pp., 2009b.
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