Optimal Cropping Pattern Modifications with the Aim of Environmental-Economic Decision Making Under Uncertainty

Sustainability in agriculture is determined by such aspects as economic, social, and environment. The multi-objective programming (MOP) model has been a widely used tool for studying and analyzing the sustainability of agricultural systems; however, optimization models, in most applications, have to use data that are uncertain. Recently, robust optimization has been used as an optimization model that incorporates uncertainty. This paper develops a framework for environmental-economic decision-making that considers the environmental and economic sustainability criteria in determining an optimal allocation of agricultural areas that cover an irrigation network under uncertain data. The primary uncertain parameter of the robust model was the quantity of available water for each season. The application of the proposed model to the case study of the right fringe of the Nekooabad irrigation network in the province of Isfahan, Iran demonstrates the reliability and flexibility of the model. The results show that the optimal total gross margin decreases with higher robustness levels. To compensate for the loss of gross margin of farmers in the robust pattern, efficiency enhancement policies were emphasized.