Technology-oriented approaches to reduce chemical fertilization in agroecosystems without influencing the vegetable yield is a proficient method for sustainable agriculture and environmental safety. However, short-term studies are not capable to indicate the effects of various inputs in a long run; therefore, a six-year experiment was conducted in Ningxia, China. The experimental units were: no fertilizer control (CK: 0 kg N ha⁻¹), chicken manure (M: organic N 362 kg ha⁻¹), reduced chemical fertilizer (RCF: chemical N 992 kg ha⁻¹ + organic N 362 kg ha⁻¹), and conventional fertilizer (CF: chemical N 1515 kg ha⁻¹ + organic N 362 kg ha⁻¹). The study aimed to assess the effects of reduced fertilization on yield, nitrogen (N) use efficiency (NUE), N leaching, and the economic benefits. The results achieved herein indicate that RCF has significantly improved the NUE, reduced N leaching (23.7%), and improved the N economic benefit (NEB, 41.8%) as compared to the CF. Based on yield, net benefit, and NUE conditions, the optimum N application range was 634–821 kg N ha⁻¹ for tomato and 556–778 kg N ha⁻¹ for cucumber. The study concluded that reduced chemical application of N is an important factor to control environmental pollution and improve fertilizer use efficiency. Further experiments are suggested to examine the optimum N rate provision from chemical fertilizer and its ratio with organic fertilization.

Under the influence of water resource conservation policies, the annual water diversion volumes in irrigation areas have been steadily decreasing, leading to substantial changes in regional cropping systems. These shifts have profoundly impacted agricultural reactive nitrogen (Nr) emissions and surface water quality. This study focuses on the Yellow River Irrigation area of Ningxia, China, and employs a life cycle assessment method to quantitatively analyze fluctuations in the nitrogen footprint (NF) and gray water footprint (GWF) across three cropping systems—rice-maize intercropping, rice monoculture, and maize monoculture—during 2021–2023. The results indicate that rice monoculture exhibited significant variability in NF values (197.89–497.57 kg Neq·ha⁻¹), with NO₃⁻ leaching identified as the primary loss pathway (102.33–269.48 kg Neq·ha⁻¹). The GWF analysis revealed that in 2021, the region’s GWF peaked at 23.18 × 10⁴ m³·ha⁻¹, with water pollution predominantly concentrated in Pingluo County (8 × 10⁴ m³·ha⁻¹). LMDI analysis identified nitrogen fertilizer application as the main contributor to variations in NF, while surface water pollution was indirectly influenced by crop yield. Furthermore, gray correlation analysis highlighted a significant coupling relationship between NF and GWF, with nitrogen fertilizer application having the most pronounced impact on GWF. Therefore, in the face of the gradual tightening of water resources in the irrigation areas, the current situation of reduced water diversion should be adopted as early as possible, and initiatives such as the reduction of nitrogen fertilizer application and the adjustment of the planting area of dryland crops should be accelerated to cope with the problem of nitrogen pollution brought about by changes in the cropping system.

This study employed the Net Anthropogenic Phosphorus Inputs (NAPI) model to assess the impact of human activities on phosphorus input in a watershed, analyzing county-level statistical data and NAPI model parameters from 1991 to 2020. The Monte Carlo method was used for a quantitative analysis of the model parameters’ effects on each NAPI component and the overall simulation results. The sensitivity index method identified each component’s sensitive parameters. The study found that the lowest NAPI value was 454 kg/(km²·a) in 1991 and the highest was 1336 kg/(km²·a) in 2003. NAPI in Ningxia showed an overall upward trend from 1991 to 1999, a slight decrease from 1999 to 2003, and a slight increase from 2003 to 2020, with fertilizer being the main contributing factor, accounting for 77.4% of the total input. On a spatial scale, NAPI in Ningxia was significantly correlated with land use patterns, showing higher values in the northern and southern regions compared to the central part. The NAPI values derived from Monte Carlo simulations with appropriate parameters ranged from −24.83% to 31.49%. The study highlighted the net food and feed imports component as having the highest uncertainty, impacting simulation results within a range of −23.89% to 53.98%. It was observed that the larger a component’s proportion in the NAPI model, the more sensitive its parameters, with the phosphorus fertilizer (P_fer) component’s parameters being notably more sensitive than those of the food/feed phosphorus input and the non-food phosphorus input (P_nf) components. These findings can inform phosphorus pollution control policies in Northwest China, while the selection of sensitive parameters provides a useful reference for future NAPI research in other regions.