Water is a limiting factor for the ecological protection and high-quality development of the Yellow River Delta. At present, the classification system for wetland hydrological connectivity patterns is imperfect and cannot meet practical management needs. Therefore, this paper constructs a hydrological connectivity classification index system based on three aspects—the pressure index, state index, and response index based on the “Pressure-State-Response” model and the analytic hierarchy process (AHP)—and then uses the network connectivity index to describe the dynamics of hydrological connectivity in the Yellow River Delta wetland under different connectivity patterns. The results show that (1) the hydrological connectivity patterns in the Yellow River Delta can be divided into five types as follows: artificial freshwater connectivity, artificial saltwater connectivity, natural–artificial freshwater connectivity, artificial–natural saltwater connectivity, and natural freshwater–saltwater connectivity. Among these types, the artificial freshwater connectivity is the most widely distributed, accounting for approximately 55.14% of the study area, followed by the artificial saltwater connectivity (24.68%), natural saltwater connectivity (9.45%), natural–artificial freshwater connectivity (8.1%), and natural freshwater–saltwater connectivity (2.63%). (2) From 1990 to 2020, the network closure (α), line point rate (β), and network connectivity (γ) indices of the Yellow River Delta wetland decreased from 0.95, 2.85, and 0.96 to 0.75, 2.51, and 0.83, respectively, and the overall connectivity level remained at a high level. The α, β, and γ values of the artificial freshwater connectivity pattern decreased from 0.93, 2.86, and 0.95 to 0.68, 2.36, and 0.79 and became the type with the lowest connectivity. The α, β, and γ indices of the natural–artificial freshwater, artificial saltwater, natural saltwater, and natural freshwater–saltwater connectivity patterns increased. Among these patterns, the artificial saltwater connectivity increased from 0.74, 2.37, and 0.83 to 0.93, 2.80, and 0.95 and had the highest connectivity. This paper has certain value and significance for wetland hydrology management.

Within the framework of the dual carbon strategy, investigating the spatiotemporal characteristics and driving factors of carbon sequestration in metropolitan areas through land use analysis is important for mitigating climate change and promoting regional ecological protection and sustainable development. On the basis of land use time points for five phases from the Jinan metropolitan area (JMA) covering the period from 2000 to 2024, the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model was coupled with the extreme gradient boosting (XGBoost)–Shapley Additive exPlanations (SHAP) and multiscale geographically weighted regression (MGWR) models to explore the spatiotemporal variations in carbon storage and its driving factors. In the last 24 years, cropland has been the predominant land use category in the JMA, representing almost 62% of the overall area. Throughout the five periods, the transition from cropland to construction land predominated, resulting in an 11.78% reduction in farmland and a 49.73% expansion in construction land. Between 2000 and 2024, carbon storage in the JMA decreased overall, with a total reduction of 3.70 Tg. The occupation of farmland for construction purposes was the primary cause of the decrease in carbon storage. The spatial pattern of carbon storage was similar to that of land use in the JMA, characterized by a distribution pattern with elevated values in the southeast and reduced values in the northwest. The SHAP analysis results demonstrated that the contributions of driving factors such as elevation, vegetation coverage, human footprint, and population density were generally high, making them the main drivers affecting carbon storage, with a significantly greater contribution of natural factors than human activity factors. The MGWR model results revealed that the digital elevation model and fractional vegetation cover positively influenced carbon storage in the JMA, whereas the population density imposed a negative effect. These results could guide the judicious allocation and utilisation of resources in urban regions, the establishment of ecological conservation areas, and the advancement of regional sustainability.

The co-evolution of urban–rural spatial transformation and ecosystem services represents a key scientific issue for high-quality basin development and metropolitan ecological governance. As a core growth pole in the lower Yellow River Basin, the Jinan Metropolitan Area (JMA) faces the overlapping pressures of rapid urbanization and ecological constraints, making it an appropriate case for exploring the interactions between the urban–rural gradient and ecosystem service value (ESV). Based on multisource spatiotemporal datasets for 2000–2024, this study deploys a modified equivalent-factor method, a multidimensional urban–rural gradient model, and a geographic detector to investigate ESV dynamics, the evolution of the urban–rural gradient, and their coupling relationship at a 1 km × 1 km grid scale. The results show that: (1) Total ESV in the JMA increased slightly from 2000 to 2024, with pronounced spatial heterogeneity. High-ESV areas were distributed in the southern mountainous region and along the Yellow River, whereas low-ESV areas were mainly distributed across the northern plains and urban built-up areas. Forestland and water bodies provided the primary foundation for regional ESV stability. (2) Inner-suburban areas expanded rapidly and became the dominant urban–rural transition zone, while rural areas continued to contract. Urban areas exhibited both polarization and sprawl along transportation corridors. (3) The coupling coordination between ESV and the urban–rural gradient exhibited a “high-periphery, low-middle” spatial pattern and declined slightly over time. Land-use change, population density and normalized difference vegetation index (NDVI) serve as core driving factors, with nonlinear threshold effects; pairwise factor interactions exert stronger explanatory power than individual factors. This study advances the analytical framework for examining ESV in basin-metropolitan areas and provides a reference for integrated urban–rural development and ecological protection in similar regions.