This review systematically summarizes the evolution of the concept of groundwater background levels and discusses the transition from the traditional concept of static background values to the contemporary concept of dynamic background levels. Based on this framework, existing assessment approaches are classified into five categories: empirical methods, statistical methods, pre-screening methods, data-driven methods, and integrated assessment methods. Their theoretical basis, applicability, advantages, and limitations are comparatively evaluated, and representative case studies are synthesized to illustrate their practical applications and methodological evolution. The review indicates that groundwater background assessment is shifting from conventional statistical identification toward integrated frameworks that combine multi-source data fusion, hydrogeochemical process constraints, and intelligent data-driven models. Despite substantial methodological advances, several challenges remain, including the quantitative separation of geogenic and anthropogenic contributions, insufficient characterization of the spatiotemporal variability of groundwater background levels, and limited transferability of assessment methods across regions with contrasting hydrogeological settings. Future research should strengthen the integration of hydrogeochemical process-based understanding with data-driven modeling, establish regional groundwater background databases supported by long-term monitoring networks, and promote the transition of groundwater background levels from research-oriented reference values to regionalized and dynamic benchmarks for environmental management. These efforts will provide a more robust scientific basis for groundwater contamination identification, environmental risk management, and the sustainable utilization of groundwater resources. 

groundwater, groundwater background levels (GBLs), hydrogeochemistry, assessment methods; integrated assessment methods