Title: Evaluation of whale and particle swarm optimisation algorithms in optimal allocation of water resources of irrigation network to maximise net benefit case study: Salman Farsi
Authors: Seyed Zaman Mousavi; Ali Mohammad Akhondali; Abdali Naseri; Saeid Eslamian; Sara Saadati
Addresses: Hydrology and Water Resource Engineering Department, Shahid Chamran University, Ahvaz, Iran ' Irrigation and Drainage Department, Faculty of Water Science Engineering, Shahid Chamran University of Ahvaz, Iran ' Irrigation and Drainage Department, Faculty of Water Science Engineering, Shahid Chamran University of Ahvaz, Iran ' Department of Water Engineering, College of Agriculture, Isfahan University of Technology, Isfahan, Iran ' Natural Resources Engineering, Isfahan University of Technology, Isfahan, Iran
Abstract: In this study, an optimisation model was developed to optimally allocate water to Salman Farsi irrigation network using the whale algorithms optimisation method. In this method, the amount of irrigation water depth of the crops and their cropping area were the decision-making variables of the model. The results showed the cropping pattern of all crops were increased and total cultivated area of the network was raised by 981 hectares that means 17% of the abandoned area of the network is recultivated. So, the crops were exposed to insignificant amount of water stress and the yield is not significantly reduced, however, the amount of total water use is not reduced compared to the current irrigation water allocation situation because the network total cropping area increased. The water resources allocation optimisation leads to increase in total net benefit by 62 million rials. Results proved the efficiency of whale algorithm in this model by increasing the total cropping area and the network total net benefit.
Keywords: Salman Farsi; whale algorithm; particle swarm; optimisation; water stress.
International Journal of Hydrology Science and Technology, 2021 Vol.12 No.3, pp.333 - 345
Received: 16 Mar 2020
Accepted: 13 Sep 2020
Published online: 13 Sep 2021 *