Spatiotemporal variations of dissolved organic matter in a typical multi-source watershed in northern China: a fluorescent evidence

Abstract

The amount of dissolved organic matter (DOM) in a multi-source watershed is important for complete management and assessing the river basin's long-term safety. Based on this, we study the composition, spatiotemporal changes, and primary sources of DOM using the excitation-emission matrix (EEM) and parallel factor analysis (PARAFAC). The relationship between DOM composition and water quality was also discussed. It was found that the DOM in the North Canal River watershed was composed of two similar humic acid-like components (230, 335/400 nm and 260, 360/450 nm) and a tryptophan-like component (280/290-350 nm). The intensity of DOM shows obvious seasonal spatiotemporal variations. In terms of time, the relative concentration of DOM in winter is significantly higher than that in other seasons due to the influence of water volume, temperature, and photochemical degradation factors. As for the aspect of space, under the combined effect of land use and multiple sources of pollution, the relative concentration of tryptophan-like in the mainstream was significantly higher than tributaries, while the relative concentration of humic-like components in the tributaries was higher than that in the mainstream. The chief sources of DOM in the North Canal River watershed include human-derived point sources and agricultural non-point sources in the main channel, as well as terrestrial and microbiological sources in the tributaries. Moreover, the composition of DOM is significantly related to water quality indicators, especially nitrogen and phosphorus, which shows that DOM can have an indicative impact on the trophic status in the North Canal River. The findings of this study could have a predictive effect and provide a scientific foundation for water quality monitoring and pollution control in the North Canal River watershed.

Keywords: Dissolved organic matter; Multi-source; North Canal River watershed; Spatiotemporal variations.