OPTIMAL RESERVOIR OPERATION FOR IRRIGATION OF CROPS USING GENETIC ALGORITHM: A CASE STUDY OF SUKHI RESERVOIR PROJECT

Genetic Algorithm is one of the global optimization schemes that have gained popularity as a means to attain water resources optimization. It is an optimization technique, based on the principle of natural selection, derived from the theory of evolution, is used for solving optimization problems. In the present study Genetic Algorithm (GA) has been used to develop a policy for optimizing the release of water for the purpose of irrigation. The study area is Sukhi Reservoir project in Gujarat, India. The months taken for the case study are June, July, August and September for three years from year 2004 to 2006. The fitness function used is to minimize the squared difference between the monthly reservoir release and irrigation demand along with squared deviation in mass balance equation. The decision variables are monthly reservoir releases for irrigation and initial storages in reservoir at beginning of the month. The constraints considered for this optimization are the bounds for the reservoir releases and reservoir storage capacity. The results derived by using GA shows that the downstream irrigation demands are completely satisfied and also considerable amount of water is saved.