Optimal operation of reservoir systems is the most important issue in water resources management. It presents a large variety of multi-objective problems that require powerful optimization tools in order to fully characterize the existing trade-offs. Many optimization methods have been applied based on mathematical programming and evolutionary computation (especially heuristic methods) with various degrees of success more recently. This paper presents an implementation and comparison of multi-objective particle swarm optimization (MOPSO) and non-dominated sorting genetic algorithm II (NSGA-II) for the optimal operation of two reservoirs constructed on Ozan River catchment in order to maximize income from power generation and flood control capacity using MATLAB software. The alternative solutions were based on Pareto dominance. The results demonstrated superior capacity of the NSGA-II to optimize the operation of the reservoir system, and it provides better coverage of the true Pareto front than MOPSO.

The fall velocity of sediment particles plays a key role in sediment transport studies. Researchers have attempted to determine the terminal fall velocity, and most of the studies in this regard have been based on experimental, quasi-experimental, and in-situ measurements. The present study aimed to use a numerical model to estimate the fall velocity of a single sediment particle in distilled and motionless water. We used spherical quartz particles with the diameters of 0.77, 1.09, 2.18, and 4.36 millimeters and density of 2,650 kg/m3. The Flow-3D software was applied to estimate the fall velocity based on the environment of experiment by Ferguson and Church (2004) using the void of flow method. The main objective of this research was to demonstrate the power of the numerical model to simulate the fall velocity of sediment particles. To validate the results of the model, they were compared with the experimental results and 26 well-known publications during 1933-2016 using the root-square-mean and mean-absolute-percentage errors. The results showed good agreement between the experimental and numerical data. Therefore, the proposed numerical model could be used to determine the fall velocity of sediment particles with a wide range of diameters in the proposed environment and particle types.