Objective Under the dual pressures of rapid global climate change and the high-density urbanization strategy involving cross-river expansion, the Xi’an section of the Wei River Basin constitutes a critical ecological barrier in Northwest China. However, this region currently faces unprecedented challenges characterized by the superimposition of ecological degradation and intensifying climate risks. The increasing concentration of high-intensity construction activities along the riverfront has triggered a cascade of ecological issues, most notably the fragmentation of riverine floodplains, the shrinkage of natural wetlands, and a significant reduction in hydrological connectivity. These disruptions have severely threatened the stability of the regional ecosystem and undermined its service capacity. More critically, the rapid conversion of land use has heightened the region’s exposure to compound climate risks, specifically the coupling effects of the urban heat island (UHI), Urban Waterlogging, and the urban dry island (UDI). There is a growing spatial mismatch between the rigid expansion of urban boundaries and the dynamic demands of ecological security, leading to a “supply-demand dislocation” in climate resilience. Traditional static planning methods often fail to address these dynamic uncertainties. Consequently, there is an urgent need to construct a scientifically grounded ecological protection and restoration framework that shifts from “passive defense” to “active adaptation”. The primary objective of this study is to clarify the ecological baseline and vulnerability of blue-green spaces in the study area and to propose a “hierarchical and categorical” resilience planning strategy. This strategy aims to delineate precise control units and formulate differentiated restoration measures, thereby guiding the implementation of ecological spaces within detailed planning units and coordinating high-quality urban development with long-term regional ecological security. Methods Focusing on the Xi’an section of the Wei River Basin, this study introduces the systematic conservation planning (SCP) theory to establish a comprehensive analytical framework titled “ecological status assessment−future scenario simulation−hierarchical and categorical delineation−planning strategy response”. The methodology proceeds in three rigorous steps. Firstly, the study integrates multi-source datasets—including digital elevation models, land-use data, remote sensing imagery, and administrative vector data—to conduct a systematic baseline quantification. The InVEST model is applied to assess habitat quality and ecological sensitivity, identifying the current service functions and fragility of blue-green spaces. Secondly, grounded in the Master Plan for Xi’an Territorial Spatial Development (2021−2035), the research employs the XGBoost model and scenario simulation techniques to predict the spatiotemporal patterns of compound climate risks. The study simulates the distribute on and intensity of UHI, waterlogging risk, and UDI effects under future land-use scenarios (2035), quantifying the spatial coupling relationship between ecological value and multiple risk stressors. Thirdly, by embedding SCP principles such as conservation target setting and cost-benefit analysis, the study utilizes the Zonation 5 model to overlay the baseline ecological importance with future risk gradients. This process allows for the quantitative identification of protection priorities and the formulation of spatial optimization strategies that respond to both current ecological deficits and future climate stressors. Results The integrated analysis yields three critical findings regarding the ecological pattern and risk distribution of the study area. 1) Spatial congruence between high value and high sensitivity: The ecological status assessment reveals a pronounced spatial overlap between high-value ecological patches and highly sensitive areas. Quantitative analysis indicates that areas with high habitat quality (Class I and II) account for 59.21% of the total blue-green space, closely aligns with the 47.11% coverage of highly sensitive areas (Class I and II). These categories exhibit strong spatial consistency, being primarily concentrated in riparian wetlands and riverine forests. This finding underscores that the region’s most valuable ecological assets are simultaneously its most fragile, possessing limited resilience against human interference. 2) Agglomeration of compound climate risks: The future scenario simulation demonstrates that, by 2035, the high-value areas for superimposed risks (UHI, waterlogging, and UDI) will further cluster in the built-up urban zones. These high-risk areas, representing the structural conflict zones at the urban expansion interface, account for 24.3% of the total study area. This suggests a deepening conflict between urban densification and environmental comfort. 3) Hierarchical and categorical spatial optimization: Based on these findings, the study adopts a conservation priority threshold of 0.7. By integrating the ecological baseline conditions with future risk boundaries, the research delineates a “4-Level, 8-Type” blue-green space system. The four hierarchical levels correspond to distinct ecological roles: ecological function enhancement, composite utilization, network optimization, and quality improvement within built-up areas. The eight functional units are explicitly defined as follows: Core conservation units, urban wilderness units, restoration and compensation units, cultural heritage units, urban agriculture units, public service units, ecological infrastructure units, and urban recreation units. For each unit type, specific spatial boundaries and differentiated restoration strategies are formulated to ensure precise governance. Conclusion By integrating SCP theory with multi-scenario simulations, this study develops a dynamic and quantitative methodological framework suitable for the hierarchical and categorical determination of blue-green spaces under multi-climate risks. The research moves beyond static assessment by incorporating future climate uncertainties into the conservation decision-making process. The findings confirm that establishing a prioritized, unit-based control system is essential for managing the trade-offs between conservation and development in high-density areas. The proposed “4-Level, 8-Type” system provides a transferable framework for enhancing regional ecological resilience. Furthermore, the outcomes offer strong theoretical support and actionable indicators for the integration of ecological requirements into territorial spatial detailed planning, ensuring that macro-level ecological security patterns are effectively translated into micro-level implementation measures in rapidly urbanizing river basin regions.
Liu et al. (Sun,) studied this question.