Revealing the distribution characteristics and key driving factors of dissolved organic matter in Baiyangdian Lake inflow rivers from different seasons and sources

The river course is a transitional area connecting the source and receiving water bodies. The dissolved organic matter (DOM) in the river course is an important factor affecting the aquatic environment and ecological health. However, there are shortcomings in studying the differences and quantitative contributions of river DOM in different seasons and sources. In this study, ultraviolet-visible (UV-vis) and three-dimensional fluorescence spectra were used to characterize the optical properties, analyze the spatiotemporal changes, and establish the quantitative relationship between environmental factors and DOM in the inflow rivers of Baiyangdian Lake. The results showed that the relative DOM concentrations in summer and autumn were significantly higher than those in the other seasons (P < 0.001) and that the DOM source (S-R < 1) was mainly exogenous. The fluorescence abundance of protein-like substances (C1 + C2 + C3) was the highest in spring, whereas that of humus C4 was the highest in autumn. Moreover, the inflow rivers exhibited strong autogenetic characteristics (BIX > 1) throughout the year. Self-organizing maps (SOM) indicated that the main driving factors of water quality were NO3--N in spring, autumn, and winter and DO, pH, and chemical oxygen demand (COD) in summer. Random forest analysis showed that the fluorescent components (C1-C4) were closely related to the migration and transformation of nitrogen, and pH and nitrogen were the main predictors of each component. The Mantel test and structural equation model (SEM) showed that temperature and NO3--N significantly influenced the DOM concentration, components, and molecular properties in different seasons. Moreover, the river source also affected the distribution mechanism of DOM in the water body. Our study comprehensively analyzed the response of DOM in inflow rivers in different seasons and water sources, providing a basis for further understanding the driving mechanisms of water quality.