Efficient flood management requires accurate real-time forecasts to allow early warnings, real-time control of hydraulics structures, or other actions. Commercially available computing tools typically use hydraulic models derived from the numerical approximation of Saint-Venant equations. These tools need powerful computers, accurate knowledge of the riverbed topography, and skilled operators with a not insignificant hydraulic background. This paper presents an alternative approach in which the river basin is modeled as a network of cascade interconnected input–output systems. Each system is modeled by an adaptive predictive expert model, which provides real-time fast and accurate forecasts over a moving prediction horizon. The approach is evaluated using real data from the Ebro river basin in Spain. The main concluded advantages of the new approach are: (1) the formulation is simple with low computational burden; (2) it does not require topographic information on the river waterbeds; (3) the forecast may be performed autonomously.
An adaptive predictive approach for river level forecasting
José V. Aguilar, Pedro Langarita, Lorenzo Linares, Manuel Gómez, José Rodellar; An adaptive predictive approach for river level forecasting. Journal of Hydroinformatics 1 April 2013; 15 (2): 232–245. doi: https://doi.org/10.2166/hydro.2012.172
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