ORIGINAL RESEARCH
Spatio-Temporal Variations of Water Quality
and Planktonic Algal Communities in Qingshan
Reservoir, China
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1
College of Environmental and Resource Sciences, Zhejiang A&F University, Lin’an 311300, China
2
Key Laboratory of Soil Contamination Bioremediation of Zhejiang Province, Zhejiang A&F University,
Lin’an311300, China
3
Ecological Environmental Monitoring Station, Lin’an, Hangzhou 311300, China
4
State Key Laboratory of Subtropical Silviculture, Zhejiang A&F University, Lin’an, Hangzhou 311300, China
5
Shixing Testing Co.LTD, Lin’an, Hangzhou 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
Corresponding author
Shengjia He
College of Environmental and Resource Sciences, Zhejiang A&F University, Lin’an 311300, China
Pol. J. Environ. Stud. 2023;32(3):2405-2416
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ABSTRACT
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.