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The implementation of water diversion projects will exert different influences on upstream water offering areas and the downstream water receiving areas. In order to effectively promote the coordinated development of the two regions, a comprehensive evaluation system for the coordinated development of water transfer projects has been proposed with the Middle Route of the South-to-North Water Transfer Project as the research object. The system conducts a multidimensional evaluation of social development, economic development, and ecological environmental impact, and builds a comprehensive evaluation index system with fifteen evaluation indexes at three levels, with the indexes weighted through the comprehensive weighting method based on the combination of the G1 method and the entropy weight method. Based on the degree of coordinated development among various systems, the coordinated development of the Middle Route of the South–North Water Transfer Project is graded through a comprehensive evaluation. This method is tested in the decision support system of the Middle Route Construction and Administration Bureau, China. The results show that: (1) The coupling coordination degree value of the middle route of the South-to-North Water Diversion Project is 0.8912, which shows that the regional development of the water transfer project is high coupled coordination. (2) The coordination between the economic system and the ecological environment system is weaker than the coordination between the economic system and the social service system, and the coordination between the ecological and social services is the best. Finally, based on an advanced SWOT analysis of the future development of the middle route of the South-to-North Water Diversion Project, effective suggestions for regional development are provided. It provides reference or guidance for the competent authority to manage the water diversion project and the central government to comprehensively evaluate the effectiveness of the water diversion project.

Since the reform and opening-up, under the new economic situation and policy, the rapid growth of power demand in Beijing is threatening the sustainable development of China’s economy and environment. To recognize the driving factors of electricity consumption growth and offer policy implications, based on the data of electricity consumption, the Gross Domestic Product (GDP) and the resident population in Beijing from 1990 to 2021, this research used the Kaya-equation and logarithmic mean divisia index (LMDI) model to decompose the growth of power demand in Beijing into the quantitative contribution of each driving factor from the perspective of industrial electricity consumption and residential electricity consumption. The results of the decomposition analysis show that, as far as industrial electricity consumption is concerned, the contribution rates of economic growth, electricity consumption intensity and output value structure to industrial electricity growth are 234.26%, −109.01% and −25.25%, respectively, which shows that economic growth is the primary driving force promoting the growth of industrial electricity demand. Power consumption intensity is the main reason for restraining the growth of industrial power demand, the growth rate is sliding and the contribution of the industrial structure is relatively small; as far as residential power consumption is concerned, the contribution rates of per capita power consumption and population size to residential power growth are 68.13% and 31.87%, respectively, which indicates that per capita power consumption is the main factor promoting the growth of residential power demand, followed by the total population. The study results show that the consumption of electric power would increase if Beijing’s economy and urbanization keep developing, and optimizing the industry structure, improving the efficiency of electric energy utilization and adopting clean power energy are the main approaches to making Beijing’s consumption of electric power decrease.

Based on the NDVI data of vegetation in Inner Mongolia from 1982 to 2015, the variational mode decomposition (VMD) method, which has been well applied in the field of signal decomposition, is introduced to study the periodicity of vegetation index in Inner Mongolia. The VMD method is used to extract the monthly and annual NDVI and the long time series cycle characteristics of temperature and precipitation in the same period from April 1982 to October 2015 in Inner Mongolia. The results show that temperature and precipitation are important factors affecting the growth of vegetation, and there are 6.99 and 3.49 months of the same oscillation cycle for monthly NDVI and temperature and precipitation time series; when the central frequency is the same, the amplitude of the monthly temperature and precipitation time series increases with the increase of the lag period. The annual scale NDVI has the same period of 16.95, 6.8a, and 4.85a with precipitation, and the same period of 6.8a and 4.85a with temperature. The Residue component shows that the overall NDVI and temperature in Inner Mongolia have shown a significant slow growth trend in the past 30 years. Although the precipitation has shown a significant slow decline trend in the same time period (p = 0.000), the grassland is still in the process of continuous improvement.