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Stochastic Techniques for Improving Real-Time Flood Predictions

Author(s): Armando Brath; Alberto Montanari; Elena Toth

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Keywords: Real-time flood forecasting; ARIMA models; Stochastic processes

Abstract: Stochastic modelling of the simulation errors resulting from the off-line application of conceptual rainfall-runoff models is often performed in the context of real-time flood forecasting. Although widely applied in the operational practice, such approach has not been yet extensively investigated in the scientific literature. The paper is aimed at evaluating the benefits in discharge forecast accuracy achievable by this kind of approach and to provide some insights into the identification and estimation procedures of the optimal stochastic model to be applied. Application of univariate linear ARIMA models, even in the fractionally differenced form, has been considered for a case studies referred to the Sieve River basin, located in Central Italy. The results highlight the dependence of the benefits retrievable from the stochastic updating procedure on the lead time of the flood forecasting.

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Year: 1999

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