Advances in groundwater contaminant transport modeling in abandoned mining and smelting sites in China towards artificial intelligence and real-time monitoring

Mining and smelting pollution of groundwater has become a significant environmental problem, and the leaching of heavy metals and other toxic substances from abandoned smelting sites is our primary concern. This review focuses on the contribution of contaminant transport in soil through advection, dispersion, and diffusion, as well as chemical reactions, and discusses state-of-the-art numerical and reactive transport models. New tools, such as AI and real-time monitoring systems, are emphasized for their potential to sharpen prediction accuracy and adaptive management. The findings for structural changes were made based on case studies (particularly the Daye and Baiyin smelting areas located in China) that feature these unique challenges, including a lack of data, hydrogeological complexity, and policy gaps common to abandoned smelting areas. The review identifies several specific gaps in research, including a limited focus on emerging contaminants and an insufficient incorporation of socio-environmental elements into models. The recommendations emphazie the importance of cross-disciplinary collaborations, increased geographic attention, and cost-effective monitoring technologies. This review comprehensively synthesizes the state-of-the-art challenges and future perspectives on groundwater contaminant transport modeling, particularly in mining and smelting scenarios. This domain can play a critical role in sustainable environmental management, particularly in the management of groundwater resources globally, by tapping into technological innovations and overcoming existing limitations. • An overview of the physical transport mechanisms for contaminants in groundwater from mining and smelting sites. • Studies of heavy metal behaviour are developed using advanced numerical and reactive transport models. • AI-enabled adaptive groundwater management using real-time monitoring. • The case studies of abandoned Chinese smelting sites illustrate site-specific complexities. • Identifies gaps in emerging contaminant research and the integration of socio-environmental modeling.