The genetic algorithm approach for identifying the optimal operation of a multi-reservoirs on-demand irrigation system

A stochastic methodology, based on real-coded genetic algorithms for optimising the operation of reservoirs in an on-demand irrigation system, is presented. The methodology analyzes the adequacy of the difference between supply and demand taking into account the storage capacity of the reservoirs. It determines adequate inflow hydrographs to ensure the optimal regulation of reservoirs during the peak demand period. To take into account the variability of farmersʹ requirements, demand hydrographs were randomly generated within a pre-determined confidence interval. A weighted objective function, including violations of the admissible reservoir water levels (maximum, minimum and target water levels), is proposed. To solve the optimisation problem, a computer program was developed. The model was applied and tested on the Sinistra Ofanto irrigation scheme (Foggia, Italy), comprising five reservoirs fed with water from an upstream dam, each of them serving different irrigation districts. Results show that the model is efficient and robust.