With the increasing environmental impacts of human activities, the problem of polygenic multipollutants in groundwater has attracted the attention of researchers. Identifying the hydrobiogeochemical characteristics of the surface sewage that replenishes groundwater is crucial to addressing this problem. The input of polygenic multipollutants into groundwater leads to not only the mechanical superposition of pollutants but also the formation of secondary pollutant types. The evolution of polygenic multipollutants is influenced by aquifer characteristics, carbon sources, microbial abundance, etc. Therefore, this study took a sewage leakage point in Northwest China as the research object, carried out a controlled laboratory experiment on the impact of sewage discharge on groundwater, and, combined with long-term field monitoring results, determined the main hydrobiogeochemical processes of polygenic multipollutants and their secondary pollutants. The results showed that the redox environment and the gradient change in pH were identified as the most critical controlling factors. In oxidative groundwater during the early stage of vertical infiltration, sewage carries a substantial amount of NH₄⁺, which is oxidized to form the secondary pollutant NO₃⁻. As O₂ is consumed, the reduction intensifies, and secondary pollutants NO₃⁻, Mn (IV), and Fe(III) minerals are successively reduced. Compared with the natural conditions of rainwater vertical infiltration, the reaction rates and intensities of various reactions significantly increase during sewage vertical infiltration. However, there is a notable difference in the groundwater pH between sewage and rainwater vertical infiltration. In O₂ and secondary pollutant NO₃⁻ reduction, a large amount of CO₂ is rapidly generated. Excessive CO₂ dissolves to produce a substantial amount of H⁺, promoting the acidic dissolution of Mn (II) minerals and generation of Mn²⁺. Sewage provides a higher carbon load, enhancing Mn (II) acidic dissolution and stimulating the activity of dissimilatory nitrate reduction to ammonium, which exhibits a higher contribution to NO₃⁻ reduction. This results in a portion of NO₃⁻ converted from NH₄⁺ being reduced back to NH₄⁺ and retained in the groundwater, reducing the denitrification’s capacity to remove secondary NO₃⁻. This has important implications for pollution management and groundwater remediation, particularly monitored natural attenuation.

Leakage is important in groundwater cycle research and water resource management, the key is to construct the spatial distribution of aquitard. Influenced by natural and anthropogenic factors, the density of boreholes restricts the accuracy of aquitard structure. This paper explores the K-Nearest Neighbor (KNN) method to construct multi-layer aquitard structure in the hinterland of Songnen Plain, Northeast China, with limited boreholes, and compare it with Inverse Distance Weight (IDW) and Ordinary Kriging (OK) methods to evaluate the leakage. The KNN needs to first identify the eigenvalue-k of each layer, which is used to enhance the trainset to obtain the testset with a larger amount of sample data enhanced, and to make a prediction to obtain the 3-dimensional structure of aquitard. KNN is more accurate than the IDW and OK. The aquitrad structure obtained by the KNN is different from the IDW and OK, the thickness difference is 3.53%-54.00%, the area difference is 2.28%-23.91%, and the difference in leakage can be up to 24.51%. KNN also has a high degree of identification of aquitard edges, which can help the prevention of groundwater pollution. The results provide guidance for water balance analysis, borehole engineering design, water resources management and exploitation.