Optimisation of Irrigation Water Utilisation of Reservoir by Using Meta-heuristic Approach

The objective of irrigation reservoirs is to maximise crop productivity by efficient use of water supply. To tackle optimisation problems, conventional and meta-heuristic optimisation approaches are frequently used. In the current study, a meta-heuristic evolutionary algorithm called the genetic algorithm is used to solve the problem of reservoir operation for irrigation. In a situation with several crops, the main goal is to optimise crop output. The additive function for one formulation and the product function for another are solved. The study area chosen for the model’s application is a reservoir in Madhya Pradesh which is a central state of India. The reservoir is filled in Monsoon season (June–September) and the storage water is used for irrigating crops in Rabi Season. The reservoir gets filled up to different levels of storage each year. For six separate storage levels, the optimization problem has been solved. On the MATLAB Platform’s GA Solver, the issue is resolved. There are no deficits encountered until the fifth level of storage; however, a deficit is found at the sixth level. While the multiplicative model maximises the relative yield of other crops, the additive formulation maximises the relative yield of wheat. The result shows that the multiplicative model produces higher relative yield values.