Analysis of pollution sources in Qinhuai River based on water quality grouping and hydrochemical characteristics

Abstract

[Objective] To identify the major pollution sources in typical river sections within highly urbanized watersheds and enhance the scientific and precise management of urban river water quality, the Qinhuai River Basin in Nanjing was selected as a case study. By integrating the fluorescence characteristics of dissolved organic matter(DOM) with hydrochemical parameters, an evaluation framework is developed for pollution source analysis and water quality correlation.[Methods] Water samples from typical cross-sections of the main and tributary channels of the Qinhuai River were analyzed using three-dimensional excitation-emission matrix(EEM) fluorescence spectroscopy combined with parallel factor analysis(PARAFAC) to extract DOM fluorescent components. Fluorescence indices such as SUVA254 and spectral slope(S_R) were used to further interpret their source characteristics. Meanwhile, cations(K⁺, Ca²⁺, Na⁺, Mg²⁺) and other water quality indicators were measured, and the correlation analysis with the water quality index(WQI) was conducted to explore the evolution patterns of river water quality under multi-source pollution.[Results] The result showed that the fluorescent components C1—C4 were associated with surface runoff, sewage discharge, and sediment release, respectively. Among them, C3 was significantly elevated near sewage discharge points, C4 indicated endogenous release from sediments, and C2 showed composite characteristics of multiple sources. No significant correlations were observed among DOM spectral indices, suggesting strong interference from endogenous DOM on fluorescence signals, which limited their ability to be used independently for pollution source identification. Hydrochemical analysis revealed a negative correlation between cation concentrations and water quality conditions. The concentrations of the four ions synchronously increased in regions with low WQI, indicating that sewage concentration effects dominated their distribution. A significant positive correlation was observed between Na⁺ and NO^-₃-N. Combined with effluent monitoring data from sewage treatment plants, this indicated that the tailwater of sewage treatment plants was the primary source of total nitrogen in the watershed.[Conclusion] The combined analysis of DOM spectral characteristics and hydrochemical indicators helps identify key pollution types and driving factors in urban rivers, providing technical support for refined pollution control and zoned management strategies in urban river systems.

Keywords

urban rivers / pollution source / water quality composite index / dissolved organic matter / cation concentration / three-dimensional fluorescence spectroscopy / source apportionment / urban water governance