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Real-time flood forecasting of the Tiber river in Rome

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  • Benedetto Calvo
  • Fabrizio Savi

Abstract

An adaptive, conceptual model for real-time flood forecasting of the Tiber river in Rome is proposed. This model simulates both rainfall-runoff transformations, to reproduce the contributions of 37 ungauged sub-basins that covered about 30% of the catchment area, and flood routing processes in the hydrographic network. The adaptive component of the model concerns the rainfall-runoff analysis: at any time step the whole set of the model parameters is recalibrated by minimizing the objective function constituted by the sum of the squares of the differences between observed and computed water surface elevations (or discharges). The proposed model was tested through application under real-time forecasting conditions for three historical flood events. To assess the forecasting accuracy, to support the decision maker and to reduce the possibility of false or missed warnings, confidence intervals of the forecasted water surface elevations (or discharges), computed according to a Monte Carlo procedure, are provided. The evaluation of errors in the prediction of peak values, of coefficients of persistence and of the amplitude of confidence intervals of prediction shows the possibility to develop a flood forecast model with a lead time of 12 h, which is useful for civil protection actions. Copyright Springer Science+Business Media B.V. 2009

Suggested Citation

  • Benedetto Calvo & Fabrizio Savi, 2009. "Real-time flood forecasting of the Tiber river in Rome," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 50(3), pages 461-477, September.
  • Handle: RePEc:spr:nathaz:v:50:y:2009:i:3:p:461-477
    DOI: 10.1007/s11069-008-9312-9
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    References listed on IDEAS

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    1. C. Cin & L. Moens & PH. Dierickx & G. Bastin & Y. Zech, 2005. "An Integrated Approach for Realtime Floodmap Forecasting on the Belgian Meuse River," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 36(1), pages 237-256, September.
    2. Pao-Shan Yu & Tao-Chang Yang, 1997. "A Probability-Based Renewal Rainfall Model for Flow Forecasting," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 15(1), pages 51-70, January.
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    Cited by:

    1. Zhangjun Liu & Shenglian Guo & Honggang Zhang & Dedi Liu & Guang Yang, 2016. "Comparative Study of Three Updating Procedures for Real-Time Flood Forecasting," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(7), pages 2111-2126, May.
    2. Phuoc Nguyen & Lloyd Chua & Lam Son, 2014. "Flood forecasting in large rivers with data-driven models," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 71(1), pages 767-784, March.
    3. Wen-Cheng Liu & Chung-Yi Wu, 2011. "Flash flood routing modeling for levee-breaks and overbank flows due to typhoon events in a complicated river system," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 58(3), pages 1057-1076, September.

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