Dissolved organic nitrogen (DON) plays a crucial role in biogeochemical processes of nitrogen (N) and has become a non-negligible source of increasing groundwater nitrogen contamination. Therefore, the extraction accuracy of DON in unsaturated zones is essential for sound understanding of N transport, transformation behaviour and contamination processes. However, there is no uniform extraction standard for measuring DON content in the unsaturated zone. Moreover, the influences of various extraction conditions on the DON measurement are not clear. Hereby, we are the first to address the issues associated with all the extraction indicators (extractant types and concentrations, extraction duration, frequency, and solution volume-to-soil weight ratio) for the DON extraction accuracy in unsaturated zones, and present a comprehensive influence analyses. Our results revealed that extraction conditions could significantly influence the extraction accuracy of DON and that the principal impact factor was the concentration of the extractant. We also found that the widely used previous extraction approaches (high-salinity extraction method) would induce high uncertainty in measuring the DON content in unsaturated zones of different areas. Furthermore, the opposing influences from the ions of extractants can seriously affect the assessment of DON content and hinder comparability even using the same extraction method, which could severely affect the assessment of the DON content in unsaturated zones. Such uncertainty in measurements will eventually influence the observation and evaluation of groundwater nitrogen contamination. Our results demonstrated that the use of the former DON extraction method without considering the research purposes and the specific study areas would lead to a strong bias. Based on detailed response surface analysis, we provide a comprehensive analysis related to the accuracy of DON extraction, which is conducive to improving the extraction accuracy of nitrogen research in global groundwater hydrological processes in the future.