The present paper describes a hydrological model aimed at improving prediction systems for a hydropower production plant. A significant merit of the work lies in the model structure that incorporates physically based processes allowing a new calibration strategy. In fact, calibration procedure is three phases according to the simulated processes: i) parameters of snowmelt module are calibrated using the snow coverage obtained by satellite imaes, ii) baseflow is identified using a mathematical filter, iii) this allow the calibration of the parameters controlling surface runoff with the time series of surface runoff. This allows the definition of a reliable model structure able to provide good estimates of the streamflow. The runoff forecast is generally useful in water resources and flood risk management, but is also very important for the electricity market. In fact, its prediction provides information at great interest to the participants of the electricity market, selling and buying electricity for each at the 24 hours of the following day. Model is used on the Aniene river basin generating deterministic forecast obtained from COSMO—LAMI. Analyses have been used to make prediction with 1, 2 and 3 days in advance. Results show a good level of the performances of the forecast with 1 day in advance while errors increase more markedly at 2 and 3 days. Model may represent a useful tool for power production optimization in hydropower plants.
How to cite: Salvatore Manfreda e Leonardo Mancusi, Hydrological Prediction for Hydropower Production, L’ACQUA 4/2013 Luglio – Agosto, 2013. [pdf]