Multi-Objective Optimization of Land Use Based on Ecological Functional Zoning in Ecologically Fragile Watersheds

Land use change profoundly impacts the trade-offs and synergies among ecosystem services in ecologically fragile watersheds. Optimizing land use patterns based on ecological function zoning is an important approach to coordinate multiple ecosystem services and promote sustainable watershed management. This study focuses on the Wuding River Basin within the Chinese Loess Plateau, using Self-Organizing Map, multi-objective genetic algorithms, and the Future Land-Use Simulation model to explore land use optimization schemes. The results show that the windbreak and sand fixation service in the Wuding River Basin presents a spatial pattern of higher values in the northwest and lower values in the southeast, while the other six services exhibit a pattern of higher values in the east and lower values in the west. Based on the ecosystem service cluster characteristics, the basin can be divided into soil and water conservation zones, habitat conservation zones, and ecologically fragile zones. The trade-offs and synergies between ecosystem services within different zones differ significantly, with the trade-off between food supply, soil conservation, and habitat quality being particularly prominent. After optimization, the food supply and soil conservation in the soil and water conservation zones increased by an average of 0.63 × 104 t and 1.94 × 105 t, respectively. The food supply in the habitat conservation zones increased by 0.11 × 104 t, while habitat quality remained stable. In the ecologically fragile area, water production and carbon sequestration services increased by an average of 0.26 × 104 t and 0.58 × 105 t, respectively. During the optimization process, the reasonable allocation of grassland and unused land played a key role in balancing service conflicts. This study provides a scientific basis for coordinating trade-offs in watershed ecosystem services and achieving land use optimization management through the framework of service clusters, functional zones, and multi-objective optimization.