The large amount of nitrogen application on the North China Plain has caused a serious negative impact on the sustainable development of regional agriculture and ecological environmental protection. Our aim was to explore the effects of nitrogen fertilization rate and groundwater depth on growth attributes, soil-water and soil-fertilizer contents, and the winter wheat yield. Experiments were carried out in micro-lysimeters at groundwater depths of 60, 90, 120, and 150 cm on the basis of 0, 150, 240, and 300 kg/ha nitrogen fertilization rates in the growth season for winter wheat. Results showed that plant height, leaf area index, soil plant analysis development, and yield without nitrogen application increased significantly with increases in groundwater depth. The optimal groundwater depths for growth attributes and yield were 60–120 cm and tended to be shallower with added nitrogen application. Soil moisture was lowered significantly with groundwater depth, adding a nitrogen application reduced soil moisture, and excessive nitrogen input intensified soil drought. Nitrate-N accumulation at the 120–150 cm depths was significantly higher than that at the 60–90 cm depths, and a 300 kg/ha (traditional nitrogen application rate) treatment was 6.7 times greater than that of 150 kg/ha treatment and increased by 74% more than that of the 240 kg/ha treatment at 60–150 cm depth. Compared with the yield of the 300 kg/ha rate, the yield of the 240 kg/ha rate had no significant difference, but the yield increased by 3.90% and 11.09% at the 120 cm and 150 cm depths. The growth attributes and yield of winter wheat were better, and the soil nitrate-N content was lower, when the nitrogen application rate was 240 kg/ha. Therefore, it can be concluded that nitrogen application can be reduced by 20% on the North China Plain.

To reveal the relationship between agricultural water resource consumption and grain production in the Yellow River Basin, the irrigation water productivity (WPI), crop water productivity (WPC), total inflow water productivity (WPT), and eleven influencing factors were selected. The spatial and temporal distribution characteristics and driving factors of water productivity of the main crops in the Yellow River Basin were analyzed with the spatial autocorrelation analysis, grey correlation analysis, sensitivity analysis, and relative contribution rate. The results showed that the minimum mean values of WPI, WPC, and WPT were 0.22, 0.35, and 0.18 kg/m³ in Qinghai, respectively, the maximum mean value of WPI was 2.11 kg/m³ in Henan, and the maximum mean values of WPC and WPT were 0.71 and 0.61 kg/m³ in Shandong, respectively. The changing trends in WPI and WPT in Qinghai and in WPC in Shandong were insignificant, whereas the WPI, WPC, and WPT in other provinces showed a significant increasing trend. Water productivity displayed a certain spatial clustering feature in the Yellow River Basin in different years, such as a high-high (H-H) aggregation in Henan in 2005, and an H-H aggregation in Shanxi in 2015 for WPI. The water productivity had a significant positive correlation with the consumption of chemical fertilizer with a 100% effective component (CFCEC), effective irrigated area (EIA), plastic film used for agriculture (PFUA), and total power of agricultural machinery (AMTP), while it had a significant negative correlation with the persons engaged in rural areas (PERA). There was a large grey correlation degree between the water productivity and the average annual precipitation (AAP), CFCEC, PFUA, consumption of chemical pesticides (CFC), and AMTP in the Yellow River Basin, but their sensitivity was relatively small. The main driving factors were EIA (8.98%), agricultural water (AW, 15.55%), AMTP (12.64%), CFCEC (12.06%), and CPC (9.77%) for WPI; AMTP (16.46%), CFCEC (13.25%), average annual evaporation (AAE, 12.94%), EIA (10.49%), and PERA (10.19%) for WPC; and EIA (14.26%), AMTP (13.38%), AAP (12.30%), CFCEC (10.49%), and PFUA (9.69%) for WPT in the Yellow River Basin. The results can provide support for improving the utilization efficiency of agricultural water resources, optimizing the allocation of water resources, and implementing high-quality agricultural developments in the Yellow River Basin.

Improving the agricultural water resources allocation efficiency (AWRAE) and promoting the efficient and intensive utilization of agricultural water resources and high-quality development is an effective path to alleviate the water scarcity in one basin. In this study, the AWRAE and its influencing factors were measured and evaluated by constructing the evaluation system of the AWRAE in nine provinces (autonomous regions) of the Yellow River Basin, which consists of the super-efficiency slacks-based model (SBM), standard deviation ellipse (SDE), spatial autocorrelation analysis, Malmquist index and Tobit regression model. The results show that the value of AWRAE is 0.768 and it is at the medium level in the whole Yellow River Basin. The AWRAE values in the nine provinces (autonomous regions) ranking from large to small are Sichuan > Shaanxi > Ningxia > Henan > Inner Mongolia > Shanxi > Qinghai > Shandong > Gansu, and the AWRAE values show a significant increasing trend in Shanxi, Henan, Inner Mongolia and Shandong. The gravity center of the AWRAE keeps wandering along the provincial boundaries of Gansu and Shaanxi, which presents a counterclockwise rotation trend; the AWRAE of Shaanxi exhibits significant H-H aggregation in 2000, 2005, 2010, and 2015 (p < 0.05) while the agglomeration is not significant in 2020. The AWRAE has been continuously improved in which the technological progress change (Techch) and technical efficiency change (Effch) play an important positive role while the pure technical efficiency change (Pech) acts as the negative role in the Yellow River Basin. Moreover, the key influencing factors on the AWRAE in different provinces and autonomous regions are significantly different; for example, the total power of agricultural machinery (AMTP) has a significant positive effect on AWRAE in most provinces, but the annual average precipitation (AAP), agricultural water (AW), water saving irrigated area (WIA) and water saving irrigation machinery (WIM) have significant negative effects on the efficiency of AWRAE in Qinghai. The research results can provide quantitative support for agricultural water-saving and stable grain yield increase in the Yellow River Basin.