Land use spatial optimization for city clusters under changing climate and socioeconomic conditions: A perspective on the land-water-energy-carbon nexus.

Unbalanced land use development has resulted in water scarcity, high energy consumption, and a significant increase in carbon emissions. Complex and changing environments make it more difficult to manage land use sustainably. This study constructed a variety of future change scenarios coupling climate and socioeconomic development and developed a multidimensional land use spatial optimization (LUSO) model linked with water-energy-carbon. The model is solved using a nondominated sorting genetic algorithm-III (NSGA-Ⅲ) coupled with the information feedback model (IFM). The advantages of this framework include: (1) LUSO based on the clarification of the interactions between different land use types and water-energy-carbon; (2) trade-offs between dimensions are considered to achieve coordinated multidimensional development of the economy, resources, environment, and spatial conversion; and (3) a spatial optimization pattern of land use in response to climate change and socioeconomic development changes can be obtained. The model framework is applied to the Mid-Yangtze River City Cluster for empirical analysis. The results show that socioeconomic development can lead to rapid changes in land use patterns, especially in cultivated and construction land. By 2030, the optimized land use pattern under the intermediate route model is the most suitable land use scenario for the region to achieve sustainable development. Under this scenario, the area of construction land increased by 22.09%, the area of cultivated land decreased by 2.2%, the economic output increased by 76,678.31 (10 yuan), and the carbon emissions increased by only 5677.79 (10 kg), with an overall sustainability level of 0.85. This study can provide decision-makers with sustainable land resource management options that can respond to changing environments and achieve multidimensional synergistic development.