Fuzzy multi-objective optimization for sustainable agricultural water management of irrigation networks

Sustainable water resource management in arid and water deficit regions requires optimal use of water resources due to competition among different water sectors. The purpose of this study is to model uncertainties in economic and hydro-climatic variables and parameters to optimize agricultural water management in irrigation system networks to have sustainable water use. The study focuses on mitigating water shortages in Iran's Varamin irrigation network through improved agricultural patterns and efficient water consumption. The impact of employing reclaimed wastewater containing nitrates instead of nitrogen fertilizers is also evaluated. A Fuzzy Multi-Objective Particle Swarm Optimization (F-MOPSO) is applied to maximize the net benefit, restore groundwater, and minimize nitrate leaching into the aquifer. The results demonstrate that replacing groundwater with reclaimed wastewater boosted net benefits by 21% while improving groundwater restoration by 82%. These results indicate that the developed fuzzy model can handle uncertainties in irrigation system networks with a sustainable water use perspective. This research can assist decision-makers within the water, agriculture, and the environment in finding sustainable water solutions and improving the current water consumption practices, considering environmental aspects of nitrogen leaching in other regions and highlighting the potential of the developed fuzzy model.