China has witnessed accelerated urbanization since the reforms and open policies which began in 1978. This eventually resulted in increased residential water requirements and worsening water shortages, particularly in the current century. In the context of resource and environmental constraints, improving agricultural water use efficiency (AWUE) is a crucial issue to ensure food security, improve the ecological environment, and meet the needs of sustainable agricultural development. Based on the panel data of 30 provinces in China from 1999 to 2018, the article uses the Super-SBM model to measure the AWUE. Moreover, the study uses the entropy method to establish the urbanization evaluation index system from the dimensions of population, land, economy, measures the comprehensive level of urbanization development, and further constructs a dynamic spatial econometric model. We use the unconditional maximum likelihood estimation method to evaluate the impact of urbanization development on AWUE and its heterogeneity. The findings reveal that the AWUE considering undesired outcomes has generally shown a steady improvement, but there is ample space for resource conservation and environmental protection, and there are noticeable differences among regions. The decomposition of spatial effects shows that urbanization development in each region has a short-term positive effect on AWUE in the region and neighboring regions, and a long-term effect exists only in the western region. The impact of urbanization in different dimensions has been found that both land urbanization and economic urbanization contribute to the improvement of AWUE, while population urbanization helps to improve AWUE by improving the awareness level of the farmers.

Improving agricultural water use efficiency (AWUE) is an important way to solve the shortage of water resources in arid and semi-arid regions. This study used the Super-DEA (data envelopment analysis) to measure the AWUE of 52 cities in Northwest China from 2000 to 2018. Based on spatial and temporal perspectives, it applied Exploratory Spatial Data Analysis (ESDA) to explore the dynamic evolution and regional differences of AWUE. A spatial econometric model was then used to analyze the main factors that influence the AWUE in Northwest China. The results showed firstly that the overall AWUE in Northwest China from 2000 to 2018 presented a steady upward trend. However, only a few cities achieved effective agricultural water usage by 2018, and the differences among cities were obvious. Secondly, AWUE showed an obvious spatial autocorrelation in Northwest China and showed significant high–high and low–low agglomeration characteristics. Thirdly, economic growth, urbanization development, and effective irrigation have significant, positive effects on AWUE, while per capita water resource has a significant, negative influence. Finally, when improving the AWUE in arid and semi-arid regions, plans should be formulated according to local conditions. The results of this study can provide new ideas on the study of AWUE in arid and semi-arid regions and provide references for the formulation of regional agricultural water resource utilization policies as well.

The coordinated development of the economy, resources, and environment is a key aspect of sustainable development. China’s rapid agricultural modernization has been accompanied by the continuous growth of rural economic aggregate and carbon emissions from the planting industry. However, the quantitative relationship between these two factors and its internal mechanism are not yet fully understood. In this paper, the Intergovernmental Panel on Climate Change (IPCC) method is used to calculate the carbon emissions of the planting industry in China from 1998–2019. Based on this, the Tapio decoupling analysis model was constructed to study the decoupling relationship between economic development and carbon emissions of the planting industry in China from 1998–2019 and the associated spatial and temporal evolution patterns. The effect of the complete decomposition model (without residuals), in terms of carbon emissions from the planting industry, on the process of economic development and its transmission mechanism are introduced. The results show that: (1) The carbon emissions of the planting industry in China increased with the economic development occurring from 1998–2005, where agricultural economic development was highly dependent on resource factors and the environment. The growth trend of carbon emissions of the planting industry slowed from 2006 to 2019, while economic development has gradually realized the decoupling of carbon emissions from the planting industry. (2) From 1998–2019, in Heilongjiang, Sichuan, and Hunan, the economic development was given priority, showing strong and negative decoupling with carbon emissions from farming. The economic development in most regions were given priority, showing strong decoupling with carbon emissions from farming. Up to 2019, decoupling was observed with a significant trend of spatial agglomeration. (3) Economic scale effects had a positive influence on the carbon emissions of the planting industry, while the technology effect and population effect had an inhibiting influence on the carbon emissions of the planting industry. The key policy implication of this paper is that improvement of the quality of economic development serves as the premise for the transformation of the economic development mode. It is necessary to reasonably regulate the economic growth rate and expansion scale, reduce resource consumption and pollutant emission technology, and to make full use of resources, in order to provide a basis for the formulation of reasonable emission reduction policies. An effective way to realize the sustainable development of the agricultural economy would be to improve the technical efficiency, control the population scale appropriately, and optimize the agricultural industrial structure.

The Sloping Land Conversion Program (SLCP) is the largest ecological restoration program in the world. Evaluating the ecological effects of the SLCP not only provides a scientific basis for China to improve the SLCP but also provides a reference for other countries in the world to evaluate the ecological effects of ecological restoration programs being implemented or to be implemented. To this end, we took the Loess Plateau, the core area for the implementation of the SLCP, as an example and, based on multi-source remote sensing data and GIS technology, we conducted a comprehensive evaluation of the ecological effects of the implementation of the SLCP on the Loess Plateau. The results showed that, first, from 2000 to 2018, a total of 12,372.05 km² of cultivated land was converted into forest land and grassland on the Loess Plateau, and this contributed to an increase in vegetation cover from 45.09% in 2000 to 64.15% in 2018, and a decrease in the soil erosion modulus from 26.41 t·hm⁻²·yr⁻¹ in 2000 to 17.92 t·hm⁻²·yr⁻¹ in 2018. Second, the 6–25° slope range is the core area of the Loess Plateau for implementation of the SLCP. In this range, the area of cultivated land converted into forest land and grassland accounts for 60.16% of the total area of transferred cultivated land. As a result, the 6–25° slope range has become the most significant area for improving vegetation cover and reducing the soil erosion intensity, and it is mainly concentrated in the southwestern, central and central-eastern hilly and gully areas of the Loess Plateau. Third, from 2000 to 2018, the climate of the Loess Plateau tended to be warm and humid and was conducive to the implementation of the SLCP. Among these factors, precipitation is the dominant factor in determining the spatial distribution of vegetation on the Loess Plateau, and the increase in precipitation is also the main reason for the promotion of vegetation growth. Fourthly, from 2000 to 2018, the ecological environment of the Loess Plateau was significantly improved as a result of the combined effects of the implementation of the SLCP and climate warming and humidification, but the primary reason is still the implementation of the SLCP.

The green development theory proposed by the Organization for Economic Cooperation and Development (OECD) has promoted the harmonious development of the economy, society, and environment in many countries, in particular, it has provided a good option for the coordinative development of economic growth, resource utilization, and ecological protection in rural areas of developing countries. For this reason, we used the OECD model to measure green development in arid, rural areas of China, and also subjective and objective weighting methods to measure the rural green development level of 78 county-level regions in Shaanxi province in 2018. At the same time, the least square error (LSE) method was used to determine the contribution rate of government support, environmental pressure, resource endowment, and quality of life, so as to determine the influencing factors of rural green development in Shaanxi. The results show that the levels of rural green development in Shaanxi province differed internally: the level of green development in the north was strong, moderate in the southwest and northwest, and weak in the center and south. The driving types of rural green development in Shaanxi province are divided into five types: Three Factors I, Three Factors II, Four Factors I, Four Factors II, and Five Factors; the influencing factors of rural green development are varied from county to county. In terms of different regions, different development approaches and countermeasures are proposed respectively. This research provides scientific guidance for local government to formulate green agricultural development policies and to overcome the development difficulties in rural areas.

Combining the measurement of urban and rural areas to link water and poverty provides a new insight into the fields of water resources management and poverty alleviation. Owing to rapid urban development, water resource conflicts between urban and rural areas are gettingbecoming more intensified and more complex. This study details the application of a water poverty index (WPI) using 26 indicators to evaluate urban and rural water poverty in northwest China during the period 2000–2017. This study also analyzes temporal variations of urban and rural water poverty by the kernel density estimation (KDE). We found that the level of water poverty is gradually declining over time and the improvements in urban and rural areas are not harmonious. Additionally, it applies the synergic theory to analyze the relationships between urban and rural water poverty. The correspondence analysis between urban and rural water poverty is significant because of the synergic level results. The results show that there are four primary types in northwest China: synchronous areas, urban-priority areas, rural-priority areas, and conflict areas, and their evolution stages. The results suggest the need for location-specific policy interventions. Furthermore, we put forward corresponding countermeasures. The research findings also provide a theoretical foundation for the evaluation of urban and rural water poverty, and a regional strategy to relieve conflict between urban and rural water poverty.