Adaptive forecast-based real-time optimal reservoir operations: application to Lake Urmia

Abstract

Abstract Boukan Dam reservoir is the largest infrastructure constructed on the Zarineh-Roud River regulating streamflow for different uses including supplying water to Lake Urmia, the second largest salt lake in the world. This paper presents a forecast-based adaptive real-time optimal operation model (ARTOM) for Boukan reservoir with the aim of maximizing releases feeding the lake while meeting other needs such as irrigation, industrial, and domestic uses. Adaptive neuro-fuzzy system-based inflow-to-reservoir forecasts are used in the ARTOM to determine optimal releases from the reservoir for future months up to the end of a year, but only the current period's release is applied. At the beginning of the next period, the forecasts are updated, and the procedure is repeated until the last period of the year. Additionally, the optimal terminal end-of-year reservoir storage volume is a dynamic updating input to the ARTOM, which is estimated from the results of a long-term reservoir operation optimization model. The ARTOM performance is tested against the last nine-year monthly data not utilized for training the forecast module. Results demonstrate that the ARTOM attains an objective function value very close to the best possible value that can ever be reached by utilizing an ideal operation model, benefiting from perfect foresight on future streamflows.