Drawing heavily upon the Sustainable Development Goals (SDGs), an SDG–pressure–state–response (PSR)–ecological–economic–social (EES) model and an index system for wetland ecosystem health assessment were constructed from the three dimensions of environment, economy, and society. By using the Yinchuan Plain urban wetlands in the Yellow River Basin of China as a case study, their ecological health status from 2000 to 2020 was systematically evaluated by integrating information from remote sensing technology, geographic information technology, field sampling, information entropy (IE), a landscape index, and a Comprehensive Evaluation Index. The results show that the restoration and protection of wetland ecosystems have achieved remarkable results in the Yinchuan Plain. The wetland ecological health index has significantly increased from 0.26 to 0.67, which is an increase of 157.7%, and the health level increased from poor (II) to sub-healthy (IV). Factors restricting the healthy development of wetland ecology in the Yinchuan Plain include wetland construction, investment, population density, the number of tourists, and fertilizer use. The research results show that the wetland restoration and protection have achieved specific environmental, economic, and social results in the Yinchuan Plain. However, we also need to pay attention to increasing the investment in wetland environmental governance, strictly controlling the intensity of land use and the total amount of chemical fertilizer applied in various regions, scientifically carrying out wetland restoration and protection, reasonably coordinating the relationship between environment and society, and providing technical and decision-making support for wetland management and protection. This study provides a reference for the ecological governance and sustainable development of wetlands in large river basins worldwide.

The long-term use of wetlands stresses wetland ecosystems and leads to degradation and C loss. This study explored an optimal remote sensing-multivariate linear regression model (RS-MLRM) for estimating wetland soil organic carbon (SOC) by using a combination of the measured SOC and above ground biomass (AGB) from 273 samples, textural features, spectral information, and a vegetation index calculated from Landsat-8 images using the Ningxia Basin of the Yellow River as the study area. To derive the optimal predictor model for SOC, these variables were regressed against the measured SOC. These were used to predict SOC and evaluate the contribution of wetland restoration and conservation projects to soil carbon sequestration and sinks on the Ningxia Basin of the Yellow River in early (2000 and 2005), intermediate (2010), and recent (2015) years. The results show that from 2000 to 2015, the project-induced contribution to C sequestration was 20.49 TC, with an annual sink of 1.37 TC. This accounted for 54.06% of the total wetland ecosystem C sequestration on the Ningxia Basin of the Yellow River. Moreover, there was a significant success of restoration and conservation projects regarding C sequestration. These restoration and conservation projects have substantially contributed to CO₂ mitigation in the arid area.

The Yellow River Basin is an essential ecological barrier in China, but it is relatively underdeveloped. The human–land relationship needs to be coordinated, and the ecological environment is fragile, which seriously restricts the sustainable development of the urban agglomeration in the Yellow River Basin. In this study, a “five-dimensional integrated” comprehensive carrying capacity evaluation model is constructed using the five dimensions of water, land, ecology, monitoring, and early warning to evaluate its resource carrying capacity quantitatively. It constructs an early warning system of the resource carrying capacity based on the quantitative evaluation results and monitors the state of the resource carrying capacity. The results show that (1) seven major urban agglomerations’ populations, grain productions, and land are surplus, and 50.85% of prefecture-level cities have food surpluses regarding human–food relationships. (2) There are shortages in the urban agglomeration’s water resources and a deficit in the water resource carrying capacity. (3) The average ecological carrying capacity index is 0.519, indicating a state of ecological affluence. (4) The comprehensive resource carrying capacity is defined as level-three heavy-load conditions, while 67%, 22%, and 14% of cities have level-one, -two, and -three heavy-load conditions, respectively. This study can aid in the monitoring of the resource carrying status of the Yellow River Basin. These results provide a scientific basis for effectively restraining the utilization and development of natural resources in the Yellow River Basin. It can also provide a research paradigm for the world’s river basins, as well as the sustainable development of man and nature in the world.

The China–Mongolia–Russia Economic Corridor (CMREC) region is part of the Silk Road Economic Belt and is critical to world food grain safety, and thus, developing its potential grain production will help counter any global food crisis. In this study, a grain production potential measurement system for the CMREC was designed and developed using spatial data to progressively correct environmental factor functions. The potential yield per unit area and potential area of four grain crops in 48 provinces were scientifically and systematically evaluated, and the grain production potential, development potential, and development potential range were calculated. The results show that the grain production potential and development potential of the corridor are significant. The yield of wheat and maize is mainly distributed in Siberia and the south of the Russian Far East. The development potential of soybean is very large and is mainly concentrated in the Russian Far East and northeast region of Mongolia. However, there is little room for paddy yield improvement, and its potential is mainly concentrated in northeast China. The grain production potential forms a high-value region with a low value from north to south, high value in the middle, extending from northwest to southeast. Grain and cereals in the whole region amounted to 8.45 × 10⁸ t (4.25 × 10⁸ t in Russia, 4.03 × 10⁸ t in China, and 0.12 × 10⁸ t in Mongolia). In terms of grain type, maize has the highest productivity potential with 1.96 × 10⁸ t, followed by wheat at 1.45 × 10⁸ t. The potential for paddy is 0.58 × 10⁴ t, whereas soybean has the lowest potential of 0.40 × 10⁸ t. The results of this study provide evidential support in the form of data for the development of the complementary advantages of agricultural resources, construction of the CMREC, and joint development of a food resource free trade zone. The CMREC will strengthen the development of modern, green, high-yield, high-quality, and efficient grain production zones for soybean and maize, and promote the diversification of grain resource cooperation.