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

系统地梳理国内外地下水背景值概念的发展历程, 分析其由静态本底值向动态背景值不断演进的理论内涵; 在此基础上, 归纳经验评价、统计分析、预筛选、数据驱动及多方法集成5类地下水背景值评估方法, 比较不同方法的理论基础、适用条件、优势及局限性, 并结合国内外典型案例总结各类方法的应用特点与发展趋势。综合分析结果表明, 地下水背景值评估正由以统计识别为核心的经验评价阶段, 逐步向多源数据融合、水文地球化学过程约束和智能模型协同驱动的综合评估阶段演进。当前的研究面临人为活动与自然过程贡献难以定量分离、背景值时空动态表征不足以及复杂区域方法迁移能力有限等问题。未来的地下水背景值研究中应进一步加强水文地球化学过程约束与数据驱动模型的融合, 完善区域背景值数据库和长期监测体系, 推动地下水背景值由科研评价指标向区域化和动态化环境管理基准转变, 为地下水污染的精准识别、环境风险管控及地下水资源的可持续利用提供科学支撑。