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Neural networks and non-parametric methods for improving real-time flood forecasting through conceptual hydrological models
2002
Hydrology and Earth System Sciences
Time-series analysis techniques for improving the real-time flood forecasts issued by a deterministic lumped rainfall-runoff model are presented. Such techniques are applied for forecasting the short-term future rainfall to be used as real-time input in a rainfall-runoff model and for updating the discharge predictions provided by the model. Along with traditional linear stochastic models, both stationary (ARMA) and nonstationary (ARIMA), the application of non-linear time-series models is
doi:10.5194/hess-6-627-2002
fatcat:onhxexqi5zcqdglmkmfezikzqa