Decision support system for optimal reservoir operation modeling within sediment deposition control

Suspended sediment deals with surface runoff moving toward watershed affects reservoir sustainability due to the reduction of storage capacity. The purpose of this study is to introduce a reservoir operation model aimed at minimizing sediment deposition and maximizing energy production expected to obtain optimal decision policy for both objectives. The reservoir sediment-control operation model is formulated by using Non-Linear Programming with an iterative procedure based on a multi-objective measurement in order to achieve optimal decision policy that is established in association with the development of a relationship between stream inflow and sediment rate by utilizing the Artificial Neural Network. Trade off evaluation is introduced to generate a strategy for controlling sediment deposition at same level of target ratio while producing hydroelectric energy. The case study is carried out at the Sanmenxia Reservoir in China where redesign and reconstruction have been accomplished. However, this model deals only with the original design and focuses on a wet year operation. This study will also observe a five-year operation period to show the accumulation of sediment due to the impact of reservoir storage capacity.