The coupling relationship and driving mechanism between ecological environment and high-quality economic development in the Middle Yellow River Basin.

Promoting the dynamic balance between economic development and ecological environment is key to achieving the "dual carbon" goals and sustainable development. The Middle Yellow River Basin, characterized by severe soil erosion and intensive resource utilization, serve as a critical area for advancing ecological protection and high-quality development in the Yellow River Basin. This study examines the spatial-temporal differentiation and coupling coordination characteristics of the ecological environment (EE) and high-quality economic development (HQED) across 226 counties in the Middle Yellow River Basin from 2010 to 2020. Utilizing the Random Forest model and the Geographical and Temporal Weighted Regression model, the study investigates the driving mechanism of high-quality economic development on ecological environment. The zoning management strategy is proposed based on the types of coupling coordination and the dominant driving factors, with the aim of providing theoretical support for sustainable development in the river basins. The results show that: (1) During the study period, the level of ecological environment initially declined and then improved, while high-quality economic development consistently increased. The EE exhibited a spatial pattern of "southeast low, northwest high," while the distribution pattern of HQED was the reverse. (2) The coupling coordination degree considerably increased after 2015, displaying the spatial pattern characterized by higher levels in the southeast and northwest and lower levels in the central region, with the strong spatial positive correlation. (3) Forest cover rate, PM2.5 concentration, agricultural fertilizer application intensity, and market activity make high contributions to the ecological environment, making them key drivers. Forest cover rate is the strongest positive driver, while PM2.5 concentration is the strongest negative driver. There are evident spatial distribution differences among the various driving factors. Ultimately, the study area is divided into six types of zones, and corresponding development strategies is proposed.