Optimizing food crop layout considering precipitation uncertainty: Balancing regional water, carbon, and economic pressures with food security

Abstract

As the global food supply chain becomes increasingly unstable, food security is gaining importance in China. Nevertheless, factors such as water scarcity, limited land resources, and global climate change pose great challenges to increasing food production. Therefore, it is crucial to explore sustainable development models for food systems. In this paper, a multi-objective crop layout model considering crop rotation is constructed and solved using the INSGA2-DS algorithm. Various precipitation scenarios were established for climate change. Data analysis and optimization were conducted under different precipitation scenarios. Applied in the plain area of southwestern Shandong Province, the model can increase soybean yield by 6.78%, net carbon sequestration intensity by 0.04%, net benefit by 2.09%, and crop water productivity by 3.91% during a median flow year. Optimization tends to increase the total area planted with food crops during wet years and decrease it during dry years. The optimization model can enhance water productivity and carbon sequestration intensity of crops, as well as prevent unreasonable fluctuations in the area planted with food crops. This enables the benefits of water conservation and yield increase to be fully utilized, and reduces yield and economic losses due to dry years. The models help to rationally allocate soil and water resources, effectively respond to climate change risks, and provide robust decision support for regional food crop planning.