title: Reservoir operation using a robust evolutionary optimization algorithm.
abstract: In this research, a significant improvement in reservoir operation was achieved using a state-of-the-art evolutionary algorithm named Borg MOEA. A real-world multipurpose dam was used to test the algorithm's performance, and the target of the reservoir operation policy was to fulfil downstream water demands in drought condition while maintaining a sustainable quantity of water in the reservoir for the next year. The reservoir's performance was improved by increasing the maximum reservoir storage by 14.83 million m3. Furthermore, sustainable water storage in the reservoir was achieved for the next year, for the simulated low flow condition considered, while the total annual imbalance between the monthly reservoir releases and water demands was reduced by 64.7%. The algorithm converged quickly and reliably, and consistently good results were obtained. The methodology and results will be useful to decision makers and water managers for setting the policy to manage the reservoir efficiently and sustainably.
authors.affiliation: Department of Civil and Environmental Engineering, University of Strathclyde Glasgow, 75 Montrose St, Glasgow G1 1XJ, UK. Electronic address: jafar.al-jawad@strath.ac.uk.
authors.forename: Jafar Y
authors.initials: JY
authors.lastname: Al-Jawad
authors.affiliation: Department of Civil and Environmental Engineering, University of Strathclyde Glasgow, 75 Montrose St, Glasgow G1 1XJ, UK. Electronic address: tikutanyimboh@hotmail.co.uk.
authors.forename: Tiku T
authors.initials: TT
authors.lastname: Tanyimboh
mesh_terms: D000465:Algorithms; D055864:Droughts; D014867:Water; D014881:Water Supply
chemical_list: D014867:Water
keywords: Environmental water management; Evolutionary optimization algorithm; Multipurpose reservoir system; Reservoir drawdown limits; Reservoir operation policy; Self-adaptive recombination