Regional Low-Carbon Agricultural Resource Optimization and Management Model Based on the Coupling Relationship of Water, Land, and Carbon: A Case Study of Sichuan Province

With the acceleration of global warming and the onset of the resource shortage crisis, agricultural development faces unprecedented challenges. In this paper, the uncertainty of water resources is fully considered, and a multiobjective optimization model based on the coupled relationship of water, land, and carbon is proposed for the integrated management of regional agricultural water and land resources with the objectives of minimizing agricultural carbon emissions, maximizing the economic benefits of irrigation water use, and maximizing the equity of water resource allocation. An empirical study was conducted in Sichuan Province, China, to verify the validity of the proposed model, and scenarios with total water resource uncertainty coefficients of 0.2 and 0.6 were selected for the analysis of land and water resource allocation schemes. The results reveal that (1) the different distributions of Pareto noninferior solution sets and Pareto optimal solutions for different scenarios indicate that the settings of the model uncertainty parameters are valid. (2) After optimization, the allocation of water resources is reduced by 0.11% and 1.67%, and the allocation of land resources is reduced by 0.91% and 1.52%, respectively. (3) The direction of change in planting structure is consistent across both scenarios, with an increase in the area planted with wheat, a decrease in the area planted with corn and rapeseed, and an insignificant change in the area planted with rice. (4) The optimized carbon emissions from agriculture were 4,058,400 and 23,951,200 t, respectively, representing reductions of 0.91% and 1.36% compared with the preoptimization period. The results show that the multiobjective optimization model established in this study can effectively improve the resource utilization rate and achieve a balance between economic benefits, social benefits, and carbon emissions.