Author:
Yan Guanghan,Yin Xueyan,Wang Xing,Huang Minsheng
Abstract
AbstractIn this study, 15 sampling sites were set up in Dongting Lake, a typical river-connected lake in China, to investigate water quality and diatioms in March, June, September and December from year 2017 to 2022. Seven diatom indices, including relative abundance of diatoms (RAD), percentage motile diatoms (PMD), generic diatom index (GDI), diatom quotient (DU), pollution tolerance index for diatoms (PTI), trophic diatom index (TDI), and Pampean diatom index (IDP), were selected to screen the adaptability of water quality assessment comparing with the Nemero index (NI), which is simple to calculate and has always been the main method for water quality assessment in Dongting Lake. The results from 2017 to 2019 showed that the diatom density in Dongting Lake ranged from 0.7 × 104 to 85.5 × 104 ind./L, with a certain decreasing trend. The spatial and temporal changes of some water quality factors were obvious, just like the temperature of water (WT), ammonia nitrogen (NH4+–N), dissolved oxygen (DO) and the comprehensive trophic level index (∑TLI) ranged from 45.99 to 50.72, with an average value of 47.85, indicating that the overall condition of Dongting Lake was medium nutrition. Correlation analysis showed that PTI, RAD and PMD could represent the information of DU, GDI, TDI and IDP, and were significantly positively correlated with DO (p < 0.01), while significantly negatively correlated with electrical conductivity (Cond), potassium permanganate (CODMn), biochemical oxygen demand (BOD5), chemical oxygen demand (CODCr) and ∑TLI (p < 0.001). The index verification results from year 2020 to 2022 showed that PTI, RAD and PMD were all significantly positively correlated with NI (p < 0.001). Taking into account the data integrity of the index calculation and the difficulty degree, RAD was finally selected as the biological indicator for evaluating the water quality of Dongting Lake. The results of this study provide a new path or alternative method for water quality assessment of the river-connected lakes.
Funder
National Key R&D Program of China
Publisher
Springer Science and Business Media LLC