Multi-objective cropping pattern in the Vaalharts irrigation scheme

Abstract

This study presents the multi-objective cropping pattern modeling of a farm in the Vaalharts irrigation scheme (VIS) in South Africa. The cropping pattern model presents three objectives and three constraints. The objectives are to maximize the total net benefit (NB) in monetary terms (South African Rand, ZAR) generated by planting four different crops, maximize total agricultural output (tons) and minimize the irrigation water use (m3). The total farm size is 77.1 ha while the total available water for irrigation is 9,140 m3 per ha/annum. Multi-objective differential evolution algorithm (MDEA) which is a stochastic multi-objective evolutionary algorithm recently developed was used to solve the multi-objective model in this study. The model produced non-dominated solutions that converge to Pareto optimal front. The averages of total net benefit, total agricultural output, total irrigation water and total area planted are ZAR 882 890.63, 3 439 518.75 tons, 702 522.50 m3 and 661 444.06 m2 respectively with corresponding average planting areas of 416 680, 53 030, 87 620 and 212 410 m2 for maize, groundnut, Lucerne and Pecan nuts respectively. It is concluded that MDEA is a good optimizer for multi-objective cropping pattern model for generating maximum agricultural output for the farmers in the area with the constraints of land and water availabilities. Key words: Cropping pattern, irrigation, agricultural output, differential evolution, non-dominated solutions.