Seasonal dynamics of chromophoric dissolved organic matter in Poyang Lake, the largest freshwater lake in China

有色溶解有机物 溶解有机碳 生物地球化学循环 环境科学 湿地 旱季 光谱斜率 水文学(农业) 水质 湖泊生态系统 流域 水生生态系统 生态系统 生态学 海洋学 地质学 浮游植物 营养物 地理 生物 天文 岩土工程 地图学 谱线 物理
作者
Qi Huang,Lizhen Liu,Jiacong Huang,Dianwei Chi,Adam T. Devlin,Huawu Wu
出处
期刊:Journal of Hydrology [Elsevier BV]
卷期号:605: 127298-127298 被引量:35
标识
DOI:10.1016/j.jhydrol.2021.127298
摘要

Chromophoric dissolved organic matter (CDOM) plays a vital role in the biogeochemical cycles of elements in aquatic ecosystems. Seasonal dynamics of CDOM of the lake are sensitive indicators of the biogeochemical processes and water quality, which are critical to the water security of the lake. Thus, a field investigation of the CDOM and dissolved organic carbon (DOC) properties was conducted during four hydrological seasons in 2016 to track the temporal variability of CDOM and DOC properties and to explore the influence of rivers and wetlands on the quantity and quality of CDOM in Poyang Lake. The results showed that the alternations of flood and dry periods have a different influence on the quantity and quality of CDOM and DOC in the main lake and the river mouths districts. DOC and aromaticity in the main lake district were more influenced by seasonal variations, while CDOM concentrations and molecular weight in the river mouths were more affected. CDOM fluorescent components in both these districts varied obviously across the hydrological seasons. More terrestrial humic-like substances with higher aromaticity and lower DOC in the rising and flood season than in the dry and retreating season. The contributing rate of CDOM and its terrestrial humic-like substances from input rivers to the lake in the rising season can account for more than 50%, which was more than that in the flood season. Flooding causes wetlands to contribute a higher abundance of CDOM and DOC with lower aromaticity to the lake, contrary to the CDOM features in the flood season, highlighting the important role of wetlands in the organic carbon pool. The DOC can be modeled using CDOM fluorescent and optical parameters by the Support Vector Regression (SVR) method, which provides a tool for DOC dynamic monitoring and water quality management.
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