Optimizing Selective Withdrawal System in Reservoir to Manage Downstream Water Quality and Hydropower Energy Generation

The integrated water quality and quantity management in reservoir design and operation is the key to meet sustainable development goals while maintain ecological services and economic benefits. Selective withdrawal systems (SWS) can help adapt reservoir operation to manage and enhance downstream water quality. This research develops a surrogate based simulation-optimization approach (SBSOA) to release water from different intakes in reservoir to minimize deviations from standard dissolved oxygen (DO) concentration and maximize annual hydro power peak energy generation. ANN is developed to act as surrogate of time consuming CE-QUAL-W2 model in approximation reservoir outflow DO concentration. The developed surrogate model is coupled with multi-objective particle swarm optimization (MOPSO) to derive optimal SWS (locations and withdrawal ratio) in Karkheh reservoir. Optimization results for water quality and quantity management with SWS are compared to historical release model. The results show optimal SWS can help enhance release water quality compared with historical scenario.