Spatiotemporal evolution and driving factors of water conservation capacity in Lanzhou City.

Water conservation services serve as a pivotal ecosystem service for water regulation and storage, which is of great significance for alleviating water scarcity and addressing climate change. Taking Lanzhou City as the research area, this study adopted long-term sequential land use, meteorological and socio-economic datasets from 2000 to 2023. By integrating the PLUS model, InVEST model and the interpretable machine learning framework of XGBoost-SHAP, this paper systematically explored the spatio-temporal evolution, driving mechanisms and future scenario responses of water conservation capacity. The results showed that: (1) Water conservation capacity in Lanzhou experienced prominent interannual fluctuations from 2000 to 2023 without any statistically significant long-term trend. Spatially, it generally presented a distribution pattern with high values concentrated in the northwestern and southern mountainous areas and low values distributed in central river valleys and southeastern regions. (2) Soil saturated water content, precipitation and NDVI were the core positive driving factors, while human activity intensity was the dominant negative driving factor. Complex nonlinear synergistic and antagonistic interactions existed among multiple influencing factors, and their influencing directions varied dynamically with factor intensity. (3) By 2050, the spatial pattern of water conservation capacity under different climatic and socio-economic scenarios will remain basically consistent with that in 2020, while its total volume is highly sensitive to scenario selection. Under the SSP1-2.6 pathway, the ecological protection scenario exhibits the highest water conservation capacity (2872.82 × 10