Reservoir ecological operation has become an important means of protection and restoration. The reservoirs on sediment-laden rivers with water supply, sediment transport, flood control, wetland protection, power generation as the primary objectives is a challenge in resources management. Currently, most studies reservoir models involve single objective, inadequacy corresponding constraint condi...

In this paper, a new Continuous Ant Colony Optimization (CACO) algorithm is proposed for optimal reservoir operation. The paper presents a new method of determining and setting a complete set of control parameters for any given problem, saving the user from a tedious trial and error based approach to determine them. The paper also proposes an elitist strategy for CACO algorithm where best solut...

Optimizing the operation of reservoir involving ecological and environmental (eco-environmental) objectives is challenging due to the often competing social-economic objectives. Non-dominated Sorting Genetic Algorithm-II is a popular method for solving multi-objective optimization problems. However, within a complex search space, the NSGA-II population (i.e., a group of candidate solutions) may...

For reservoir operation, maintaining a quasi-natural flow regime can benefit river ecosystems, but may sacrifice human interests. This study took the Qingshitan Reservoir in the Lijiang River as a case, and developed an optimization model to explore a trade-off solution between social-economic interests and nature flow maintenance on a monthly base. The objective function considered irrigation,...

Many water resources systems are characterized by multiple objectives. For multiobjective optimization, typically there can be no single optimal solution which can simultaneously satisfy all the goals, but rather a set of technologically efficient noninferior or Pareto optimal solutions exists. Generating those Pareto optimal solutions is a challenging task and often difficulties arise in using...

A multi-objective particle swarm optimization (MOPSO) approach is presented for generating Pareto-optimal solutions for reservoir operation problems. This method is developed by integrating Pareto dominance principles into particle swarm optimization (PSO) algorithm. In addition, a variable size external repository and an efficient elitist-mutation (EM) operator are introduced. The proposed EM-...

Reservoir is one of the emergency environments that required fast an accurate decision to reduce flood risk during heavy rainfall and contain water during less rainfall. Typically, during heavy rainfall, the water level increase very fast, thus decision of the water release is timely and crucial task. In this paper, intelligent decision support model based on neural network (NN) is proposed. Th...

This paper describes a general Bayesian methodology for reservoir operations. This methodology is applied to the operation of the two main reservoirs in the Zambezi river: Lake Kariba and Cahora Bassa.

Many Alpine rivers are affected by hydro-peaking, strong sub-daily fluctuations of discharge caused by intermittent power production from hydropower plants. Adding a retention volume at the outlet of a hydropower plant aims at attenuating hydro-peaking to a level where adverse effects on fish and invertebrates are minimal. The performance of such a retention volume needs to be assessed when ext...