In hydrological modelling, the challenge is to identify an optimal strategy to exploit tools and available observations in order to enhance model reliability. The increasing availability of data promotes the use of new calibration techniques able to make use of additional information on river basins. In the present study, a lumped hydrological model—designed with the aim of utilizing remotely sensed data—is introduced and calibrated, adopting four different schemes that adopt, to varying extents, available physical information. The physically consistent conceptualization of the hydrological model used allowed development of a step by step calibration based on a combination of information, such as remotely sensed data describing snow cover, recession curves obtained from streamflow measurements, and time series of surface run‐off obtained with a baseflow mathematical filter applied to the streamflow time‐series. Results suggest that the use of physical information in the calibration procedure tends to increase model reliability with respect to approaches where the parameters are calibrated using an overall statistic based, considerably or exclusively, on streamflow data.
How to cite: Manfreda, S., Mita, L., S. F. Dal Sasso, C. Samela, L. Mancusi, Exploiting the Use of Physical Information for the Calibration of a Lumped Hydrological Model, Hydrological Processes, 32(10), 1420-1433, (doi: 10.1002/hyp.11501) 2018. [pdf]
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]