With the constant advancement of irrigation technology and the continuous expansion of irrigation areas, non-point source pollution (NPS) caused by agricultural activities has posed a persistent threat to ecosystems and biological safety. Against this backdrop, it is imperative to lay scientific foundations for green, sustainable, and high-quality agricultural development through a thorough review of the relevant research progress. In this study, bibliometric methods are adopted to comprehensively analyze and visualize the current state and key literature on agricultural irrigation and NPS pollution from 2010 to July 2024. The focus of this study is specifically on summarizing the research hotspots and development trends of different irrigation methods and the mechanisms behind their impacts on NPS pollution. The results indicate that publications from the United States and China account for 63.8% of the total, but the fragmentation of research efforts remains, suggesting a necessity to strengthen international and regional collaboration. There are three institutions with the highest publication output, namely Northwest A&F University, Hohai University, and the Chinese Academy of Sciences. The subjects identified as the key areas of research on irrigation-related NPS pollution (IRR-NPS) include precision irrigation, rapid water pollution response, spatiotemporal management, interdisciplinary integration, wastewater treatment, and crop models. Regarding future research, it is necessary to focus attention on real-time precision irrigation, standardized crop models, data accuracy, spatiotemporal pollution coordination, pollution purification technology development, interdisciplinary integrated governance, and the innovative applications of soil improvement technologies. In addition to offering theoretical support and practical guidance for the management of agricultural NPS pollution, this study also provides management and technical support for policymakers, which is beneficial for advancing agricultural irrigation technology and environmental preservation.

To investigate the mechanism and influence of applying gamma-polyglutamic acid (γ-PGA) on soil water infiltration, laboratory experiments and numerical simulations were conducted using Hydrus-1D. These studies assessed the impact of various application rates of γ-PGA on soil water characteristic parameters. Orthogonal simulation experiments on soil bulk density, γ-PGA application rates, and burial depths were performed utilizing predefined soil water characteristic values (twelve groups: nine groups of numerical simulation experiments and three groups of laboratory verification tests), and the soil infiltration characteristics were analyzed. Concurrently, an empirical model was developed to elucidate the relationships between the empirical model parameters and influencing factors, as well as to examine the sensitivity of these factors to changes in soil infiltration rate. The relationship between cumulative infiltration and the distance of wetting front movement, based on the water balance equation, was refined. The results indicated that γ-PGA significantly affected soil water characteristic parameters, where the saturated water content and the reciprocal of soil intake suction increased with rising γ-PGA applications (p < 0.01), while the saturated hydraulic conductivity and the parameter n decreased (p < 0.01), with no notable changes in the retained water content (p > 0.05). The trend in cumulative infiltration influenced by various factors could be modeled by a capacitive charging model function, which yielded a superior fit. A negative correlation existed between the sensitivity index and all the influencing factors (p < 0.05), with the order of influence being soil bulk density, γ-PGA application rate, and γ-PGA burial depth, respectively. Utilizing the modified water balance equation, the ratio of cumulative infiltration to wetting front migration distance corresponded more closely with a power function. These findings provide a theoretical foundation for further studies on the effects of γ-PGA on crop growth characteristics in fields and the optimization of γ-PGA technical element combinations.

The North China Plain is a major wheat-producing region in China where appropriate irrigation and nitrogen management are essential for coordinating grain yield, grain nutritional quality, and resource-use efficiency. We hypothesized that moderate water and nitrogen inputs would achieve a better balance among these objectives than excessive or insufficient inputs. The objective of this study was to quantify the effects of irrigation and nitrogen application on wheat growth, grain yield, selected grain nutritional quality indicators, and water–nitrogen-use efficiency, and to identify a management regime that balances these objectives using the entropy-weighted TOPSIS method. To test this hypothesis, a two-year field experiment was conducted with three irrigation levels (350, 275, and 200 mm) and four nitrogen application rates (0, 120, 240, and 360 kg ha⁻¹). Wheat growth, photosynthetic traits, dry-matter accumulation, grain yield, selected grain nutritional quality indicators, irrigation water-use efficiency (IWUE), and nitrogen partial factor productivity (NPFP) were evaluated. The results showed that high irrigation combined with high nitrogen application promoted plant height, chlorophyll content, photosynthetic activity, and dry-matter accumulation. However, grain yield and resource-use efficiency did not increase continuously with increasing water or nitrogen inputs. The moderate-irrigation and moderate-nitrogen treatment (IMNW) produced the highest grain yield in both growing seasons and achieved the highest comprehensive evaluation score in the entropy-weighted TOPSIS assessment. Regression analysis identified overlapping suitable input ranges of 295–316 mm for annual irrigation and 210–278 kg ha⁻¹ for nitrogen application. Therefore, under the experimental conditions of the North China Plain, moderate water and nitrogen inputs provided a better balance among grain yield, selected grain nutritional quality indicators, and resource-use efficiency.