Water quality, basin characteristics, and discharge greatly affect CDOM in highly turbid rivers in the Yellow River Basin, China

Abstract

Significant variations exist in water quality parameters and inherent optical properties (IOPs) in highly turbid rivers. For rivers in the Yellow River (YR) Basin, 83.33% of the collected samples exhibited high turbidity, and the absorption of non-algal particles (NAPs) was the main contributor to total water absorption. In this study, we investigated the compositions of chromophoric dissolved organic matter (CDOM) using the absorption index and fluorescence components, examined the quantitative effects of environmental factors on CDOM at the sub-basin scale and identified where and how carbon was produced in the area. The humic-like component (FR5) of CDOM was the main component in the tributaries and the main stream of the YR, especially for the Huangshui River, with FR5 accounting for 58.12%. Water quality parameters greatly affected CDOM in turbid rivers. Dissolved organic carbon and electrical conductivity were positively correlated with the CDOM concentration (p < 0.05), while dissolved oxygen, pH, chlorophyll-a and turbidity significantly affected CDOM composition (p < 0.01). Basin characteristics exerted significant influences on CDOM. The spectral slope (S275-295) increased as the altitude of the sub-basins increased. The percentage of built-up area exerted the most significant effects on CDOM composition, with high correlations with tryptophan-like protein (FR2) and FR5 (r > 0.59, p < 0.01). Forest percentage and grassland percentage showed positive correlations with CDOM concentration (r = 0.36, p < 0.05) and S275-295 (r = 0.30, p < 0.05), respectively. Moreover, the discharge from rivers in the YR Basin showed that the carbon flux of rivers in the YR Basin is more likely to be limited by dissolved organic matter (DOM) sources although negative but nonsignificant effects of discharges on CDOM parameters were shown. Consequently, additional research is necessary to clarify this correlation. This research is crucial and necessary for improving the accuracy of CDOM evaluation with remote sensing, revealing the influencing mechanisms and monitoring carbon cycling.