WSEAS Transactions on Environment and Development
Print ISSN: 1790-5079, E-ISSN: 2224-3496
Volume 21, 2025
Hourly Discharge Modelling and Forecast for a Run-of-river Dam
Authors: , ,
Abstract: Water resources have become a growing concern in society. This is largely due to the scarcity of this
natural asset and the realisation that increasing demand could lead to future conflicts. Sometimes, human action
limits access to water or alters natural flows. Run-of-river hydropower schemes manage river flows on a short-term
basis, altering the natural flow of rivers according to the energy needs of consumers or the risk of flooding.
The aim of this work is to show how to model and predict the hourly flow in a run-of-river reservoir, using the
Crestuma-Lever dam on the river Douro (Portugal) as a case study. Data collected from 1998 to 2020 will be
used. The study focuses on the use of time series models capable of dealing with multiple periodicities, such as
the TBATS model. The findings show that the model can be used for 48-hour to weekly forecasting. In general,
it captures the large fluctuations in the turbine discharges and most peak discharges. However, it does not capture
most zeros and has difficulty in dealing with low flow values. The results of the time-series model are also
compared with those obtained using three machine learning algorithms: the Seasonal Naïve, the Neural Network,
and the Random Forest.
Search Articles
Pages: 137-144
DOI: 10.37394/232015.2025.21.12