Effects of Sediment and Algal Growth on Water Quality of Water Samples from Water Conveyance Channel

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Authors: Junpeng Liu, Pan Hu, Hongzhao Gao, Tongtong Wang, Haicheng Jiang, Yue Wang, Xinyong Liu, Qu Liang, Mianda Huang, Di Fu
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Abstract

The permanganate index is a comprehensive indicator used to evaluate water quality, as it indicates the pollution level of organic and inorganic oxidizable substances in water. In this study, the permanganate index was chosen because it effectively reflects the pollutants released from both sediment resuspension and algal growth, providing a more holistic water quality assessment than parameters targeting individual pollutants. Since sediment and algae are potential causes for the increase in Imn, it is imperative to explore their individual and combined effects. In this study, we artificially added sediment to water to simulate eutrophic water for algae growth. The sediment and surface water were obtained from the end of an artificial channels. We cultured algae for 41 days and observed the changes in Imn, algal density, nitrogen, and phosphorus. The results showed that organic matter in sediment and algal growth increased in Imn in the water. The sediment resuspension released organic matter into the water, resulting in a significant increase in Imn. On the first day of the experiment, the addition of 1.6% sediment in the water sample led to an increase in Imn of 14.7 mg/L. The dissolved phosphate in sediment also stimulated the growth of algae resulting in release of reducing metabolites and further increase in Imn. The Imn of the 1.6% sediment treatment group increased to 30.1 mg/L by day 41 of culture. Correlation analysis showed that Imn was positively correlated with algal density, whereas total phosphorus content was significantly negatively correlated with algal density.

Fields of Study & Subjects

Constructed Wetlands for Wastewater Treatment Aquatic Ecosystems and Phytoplankton Dynamics Soil and Water Nutrient Dynamics

Publication details

Journal / source
Chiang Mai Journal of Science
Volume
53
Issue
1
Pages
1–12
Publication date
6 January 2026