A multi-objective synergistic optimization model considering the water-energy-food-carbon nexus and bioenergy

As global climate change continues to pose significant challenges, it is increasingly essential to explore sustainable agricultural development strategies. This study aims to develop a multi-objective collaborative optimization model, using the Fen River Irrigation District as a case study. It examines strategies based on the water-energy-food-carbon nexus and seeks to maximize bioenergy production. The research methodology integrates multi-objective optimization theory with the ideal point method to obtain optimization solutions. This approach ensures the maximization of bioenergy output while minimizing carbon emissions and economic costs. The findings reveal that optimized bioenergy production in the study area can reach 1.17 × 1012 J, with contributions of 29.50 % from agriculture and 70.50 % from animal husbandry. Notably, animal husbandry emerges as the primary source of bioenergy production, generating 8.27 × 1011 J, predominantly from pigs, followed by sheep and cattle. The total optimized agricultural cultivation area is determined to be 6.76 × 104 ha, with corn taking the largest share at 73.86 % of the total cultivated area, which improves the economic benefits of agriculture while increasing the production of bioenergy. Fruits and vegetables account for 8.69 %, wheat for 3.45 %, and legumes for 13.99 %. In terms of the economic and environmental implications of bioenergy production, agriculture contributes more significantly to the agricultural economy compared to animal husbandry. Carbon dioxide (CO2) emissions are the major contributor to overall carbon emissions, followed by methane (CH4). The optimized allocation of water resources results in a more reasonable ratio between surface water and groundwater supply, with 0.41 × 108 m3 coming from groundwater and 1.93 × 108 m3 from surface water, effectively alleviating the problem of regional water resources tension and guaranteeing the long-term stability of agricultural production. The optimization model focuses on generating solutions that conserve resources and reduce costs while simultaneously protecting the environment. This ultimately provides decision-makers with improved alternatives for managing agricultural resources.