Real time operation model for optimum operation of bukan reservoir in lake urmia basin

This paper presents an adaptive forecast-based mathematical model for real-time operation of Bukan reservoir located in Lake Urmia (LU) Basin. The model consists of three modules: 1) a forecasting module that predicts future inflows to the reservoir up to the end of a year, 2) a reservoir operation optimization module determining optimum reservoir releases and 3) an updating module that updates inflow forecasts and optimal releases at the beginning of every time step. As the forecasting module, an adaptive neural- based fuzzy inference system (ANFIS) is trained and used to forecast future inflows. Having these future inflows, a linear optimization model is formulated and solved to iind optimal reservoir releases in future time steps of the year. The objective function of the model is to maximize total volume of water received by the lake while supplying water for irrigation demands and instrearn flow. The model is tested for 2015- 2016 water year and its performance is assessed. Results obtained are promising in terms of volumes of water allocated to different demand sectors and preventing downstream areas from flooding caused by uncontrolled spillage. This is important as the system has experienced a severe flood in this particular year resulting in significant damages.

Keywords:

Lake Urmia , Bukan Reservoir , Real Time Operation , Optimization