As a vital method to resolve conflicts between water use in upstream and downstream areas and solve the problem of transboundary water pollution, watershed ecological compensation is widely used worldwide. It is necessary to analyze the influencing factors of watershed ecological compensation from the perspective of how different governments interact with each other. However, the previous literature has paid less attention to the special situation of cross-regional water diversion projects, the changing processes of governmental behavior, and the interventions by the central government. Therefore, when taking the upstream and downstream governments and the central government in the basin of a cross-regional water diversion project as research objects, it is important to study their behavior and influencing factors to improve the ecological compensation system in the basin. This paper first analyzes the interactions among upstream, downstream, and central governments in the basin, based on evolutionary game theory. Second, the evolutionary game models before and after the interventions by the central government were developed separately, and the effects of different contexts on the dynamic evolutionary process were analyzed. Finally, taking the Hanjiang River Basin as an example, which is where the water source area of China’s South-to-North Water Diversion Middle Project is located, the opportunity cost of protecting the water environment in the upstream areas of this basin was estimated by establishing an econometric regression model using data on water quality and gross domestic product. The results show that (1) the initial probabilities of governments affect their final behaviors; (2) even without the supervision of the central government, it is still possible for upstream and downstream governments to reach the desired state spontaneously; (3) the supervision of the central government can promote upstream and downstream governments to reach a stable state faster; and (4) the current level of compensation from the central government is significantly lower than the opportunity cost of protecting the water environment for upstream governments in the Hanjiang River Basin. This paper can provide helpful insights for improving the ecological compensation system in the basin, which helps promote cooperation in water environment protection.

China is the largest carbon emitter in the world; thus, reducing carbon emissions while maintaining economic growth has become an important issue. Within the context of carbon neutrality strategies, calculation of the carbon footprint and embodied carbon transfer can help policymakers formulate reasonable carbon reduction plans. The multi–regional input–output (MRIO) model can clarify carbon flow pathways between regions, and social network analysis (SNA) can comprehensively evaluate the different positions of individual sectors. Combining these two approaches, the specific characteristics of carbon emissions in complex production and trade relationships can be analyzed. China has become the world’s top total carbon emitter, and the Hanjiang River basin (HJRB) constitutes an important economic link between the developed and less developed regions of China. Studying carbon emissions in the HJRB can provide a reference for other, similar regions and is vital for the realization of China’s carbon emission reduction targets. This paper examines the carbon footprint and embodied carbon emission transfer among three provinces and 12 sectors in the HJRB during different periods and identifies the key industries in the carbon transfer process. The results indicate that (1) the total carbon footprint in the HJRB exhibits an increasing trend. Energy-based Shaanxi Province exhibits the highest growth rate of the carbon footprint, agriculture-based Henan Province shows a decreasing trend, and consumption-based Hubei Province displays the lowest carbon footprint intensity. (2) There are differences in the carbon emission coefficient and final consumption rate among various sectors; construction, metal processing and metal and non-metallic products, processing and manufacturing of petroleum, coking, nuclear fuel, chemical products, and other services are the sectors accounting for a high proportion of emissions. (3) The more obvious the supply relationship is, the higher the flow of embodied carbon emission transfer between sectors. (4) Energy-based regions transfer large amounts of fossil energy, electricity, steel and coal resources to developed regions and simultaneously assume more of the carbon reduction pressure imposed on developed regions. (5) The key industries within the embodied carbon emission transfer network notably control the carbon emissions of other industries and can provide breakthroughs to achieve challenging carbon emission reduction targets.

China’s rural revitalization strategy has entered a new stage of development, in which optimizing the layout of rural settlements constitutes both a critical component and an urgent task for promoting integrated urban–rural development. Important ecological function areas play a vital role in maintaining ecological security; however, research focusing on the evaluation and optimization of rural settlement suitability within these regions remains limited, thereby constraining their sustainable development. Accordingly, this paper selects Shiyan City, situated within the core water source area of China’s South-to-North Water Diversion Project, as a case study. From an ecological perspective, a suitability evaluation system for rural settlements is developed, specifically tailored to important ecological function areas. This system integrates ecological factors including geological hazards, vegetation coverage, soil and water conservation, and soil erosion. Utilizing GIS spatial analysis and the minimum cumulative resistance model, the study assesses the suitability of rural settlements within these important ecological function areas. Furthermore, it proposes corresponding optimization types and strategies for rural settlements in such areas. The findings indicate the following: (1) The rural settlements in the study area demonstrate a “large dispersed settlements and small clustered settlements” distribution pattern, exhibiting an overall high-density agglomeration, though their internal layout remains fragmented and disordered due to geographical and ecological constraints. (2) The spatial comprehensive resistance values in the study area exhibit significant heterogeneity, with a general pattern of lower values in the north and higher values in the south. The region was categorized into five suitability levels: high yield, highly suitable, generally suitable, less suitable and unsuitable. The highly suitable areas, despite their limited spatial extent, support the highest density of rural settlements. In contrast, unsuitable areas occupy a substantially larger proportion of the territory, reaching 46.83%. These areas are strongly constrained by topographic and ecological factors, limiting their potential for development, and the spatial layout of villages requires further optimization, with emphasis placed on ecological conservation and adaptive sustainability. (3) Rural settlements are categorized into four optimized types: Urban–rural integration settlements, primarily located in high yield areas, are incorporated into urban development plans after optimization. Adjusted and improved settlements, mainly in highly suitable areas, enhance service quality and stimulate economic vitality post-optimization. Relocation and renovation settlements, including those in generally suitable and less suitable areas, achieve concentrated living and improved ecological livability after optimization. Restricted development settlements, predominantly in unsuitable areas, focus on ecological conservation and regional ecological security post-optimization. This study integrates ecological function protection factors with spatial optimization zoning for rural settlements in the study area, providing scientific reference for enhancing residential safety and ecological security for rural residents in important ecological function areas.

Lake eutrophication exhibits pronounced spatial heterogeneity at the watershed scale, yet a systematic and quantitative understanding of how landscape characteristics drive these variations remains limited. In this study, a long-term and internally consistent trophic state dataset for the Liangzi Lake Basin was constructed by integrating Landsat imagery from 1990 to 2022 with a semi-analytical water color inversion method. A multi-scale landscape feature system incorporating both land use composition and landscape pattern metrics was developed at the sub-basin level to elucidate the mechanisms by which landscape characteristics influence eutrophication dynamics. The XGBoost model was employed to characterize the nonlinear relationships between landscape attributes and trophic conditions, while the SHAP interpretability approach was applied to quantify the relative contribution of individual landscape components and their interaction pathways. The analytical framework demonstrates that landscape pattern attributes—such as fragmentation, diversity, and connectivity—play essential roles in shaping the spatial variability of eutrophication by modulating hydrological processes, nutrient transport, and ecological buffering capacity. By integrating remote sensing observations with interpretable machine learning, the study reveals the complexity and scale dependence of landscape–water interactions, providing a methodological foundation for advancing the understanding of eutrophication drivers. The findings offer theoretical guidance and practical references for optimizing watershed landscape planning, controlling non-point source pollution, and supporting ecological restoration efforts in lake basins.

Introduction: Gross primary productivity (GPP) is a key component of the global carbon cycle, and its dynamics are influenced by climate conditions and human activities. However, the nonlinear response of GPP to climate change and human activities remains unclear. The Hanjiang River Basin (HJRB), a crucial water-source region of the South-to-North Water Diversion Project in China, is vital to China's ecological security. Changes in vegetation productivity in this water-source basin may affect water conservation, soil erosion control, drought and flood regulation, and the environmental conditions to which downstream populations are exposed. In recent decades, the region has experienced significant climate change, intensified human activities, and notable increases in vegetation greenness. However, previous literature relying on the assumption of stationarity and traditional linear methods has limited capability in detecting nonlinear and gradual vegetation changes. Methods: The long-term nonlinear trend in GPP in the HJRB was analyzed using ensemble empirical mode decomposition (EEMD), and the nonlinear response relationships among climatic factors, human activities, and GPP were further quantified using the LightGBM machine-learning method. Results: From 2000 to 2020, the annual growth rate of vegetation productivity in the HJRB was 12.27 g C m ⁻² yr ⁻¹ ( P < 0.01). Most vegetated areas exhibited an upward trend in GPP. However, 28.25% and 4.41% of the region experienced transitions from growth to decline and from decline to growth, respectively, primarily in the southern upstream and eastern downstream areas. Drought (25.28%), precipitation (10.75%), and relative humidity (10.69%) were identified as significant factors influencing vegetation productivity trends. Annual precipitation above approximately 1,000 mm was associated with lower SHAP values for the continuous-increase trend, which may reflect combined hydrothermal, radiation, and topographic constraints rather than a direct inhibitory effect of precipitation. Additionally, an increase in SPEI12 was associated with higher SHAP values for the continuous-increase trend. Discussion: This study elucidates trends and underlying response patterns in vegetation productivity in the HJRB, reveals the driving factors behind regional vegetation productivity changes, and provides environmental evidence for vegetation monitoring, water-source ecosystem management, and climate-related health-risk prevention in the HJRB and similar water-source regions.