Spatio-Temporal Variations of Water Quality and Planktonic Algal Communities in Qingshan Reservoir, China
Zhenbo Xu 1,2,3
Weijun Fu 1,2
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College of Environmental and Resource Sciences, Zhejiang A&F University, Lin’an 311300, China
Key Laboratory of Soil Contamination Bioremediation of Zhejiang Province, Zhejiang A&F University, Lin’an311300, China
Ecological Environmental Monitoring Station, Lin’an, Hangzhou 311300, China
State Key Laboratory of Subtropical Silviculture, Zhejiang A&F University, Lin’an, Hangzhou 311300, China
Shixing Testing Co.LTD, Lin’an, Hangzhou 311300, China
Shengjia He   

College of Environmental and Resource Sciences, Zhejiang A&F University, Lin’an 311300, China
Submission date: 2022-06-15
Final revision date: 2022-08-29
Acceptance date: 2023-01-03
Online publication date: 2023-02-24
Publication date: 2023-04-14
Pol. J. Environ. Stud. 2023;32(3):2405–2416
Based on the monitoring data of conventional water quality in Qingshan Reservoir from 2018 to 2019, principal component analysis (PCA) and comprehensive nutritional status index (TLI) are used to evaluate water quality, planktonic algal communities, and eutrophication degree of Qingshan reservoir. The results showed that: 1) from 2018 to 2019, the annual average TLI is 56.54, indicating that the reservoir is in a slightly eutrophic state, which is conducive to algae growth; 2) the water quality of Qingshan Reservoir has obvious temporal and spatial variability: the water environment quality commonly decreased in the order winter>spring>autumn>summer, and exit zone>buffer zone>entry zone; meanwhile, the algal biomass in summer and autumn was significantly higher than that in spring and winter, and most of the algae were concentrated in the surface water except in January and decreased with the increase of depth; And related to the water quality environment, the biomass of cyanobacteria and green algae in Qingshan Reservoir is relatively high in summer, while diatom is the dominant species in spring and winter. We come to the conclusion that targeting at region and time will be more effective for the treatment of reservoir eutrophication.