Open Access iconOpen Access

ARTICLE

crossmark

Correlation Analysis of Turbidity and Total Phosphorus in Water Quality Monitoring Data

Wenwu Tan1, Jianjun Zhang1,*, Xing Liu1, Jiang Wu1, Yifu Sheng1, Ke Xiao2, Li Wang2, Haijun Lin1, Guang Sun3, Peng Guo4

1 College of Engineering and Design, Hunan Normal University, Changsha, 410081, China
2 Hunan Institute of Metrology and Test, Changsha, 410014, China
3 Big Data Institute, Hunan University of Finance and Economics, Changsha, 410205, China
4 Department of Information and Communication Technology, University Malaysia Sabah, Sabah, 88400, Malaysia

* Corresponding Author: Jianjun Zhang. Email: email

Journal on Big Data 2023, 5, 85-97. https://doi.org/10.32604/jbd.2022.030908

Abstract

At present, water pollution has become an important factor affecting and restricting national and regional economic development. Total phosphorus is one of the main sources of water pollution and eutrophication, so the prediction of total phosphorus in water quality has good research significance. This paper selects the total phosphorus and turbidity data for analysis by crawling the data of the water quality monitoring platform. By constructing the attribute object mapping relationship, the correlation between the two indicators was analyzed and used to predict the future data. Firstly, the monthly mean and daily mean concentrations of total phosphorus and turbidity outliers were calculated after cleaning, and the correlation between them was analyzed. Secondly, the correlation coefficients of different times and frequencies were used to predict the values for the next five days, and the data trend was predicted by python visualization. Finally, the real value was compared with the predicted value data, and the results showed that the correlation between total phosphorus and turbidity was useful in predicting the water quality.

Keywords


Cite This Article

APA Style
Tan, W., Zhang, J., Liu, X., Wu, J., Sheng, Y. et al. (2023). Correlation analysis of turbidity and total phosphorus in water quality monitoring data. Journal on Big Data, 5(1), 85-97. https://doi.org/10.32604/jbd.2022.030908
Vancouver Style
Tan W, Zhang J, Liu X, Wu J, Sheng Y, Xiao K, et al. Correlation analysis of turbidity and total phosphorus in water quality monitoring data. J Big Data . 2023;5(1):85-97 https://doi.org/10.32604/jbd.2022.030908
IEEE Style
W. Tan et al., "Correlation Analysis of Turbidity and Total Phosphorus in Water Quality Monitoring Data," J. Big Data , vol. 5, no. 1, pp. 85-97. 2023. https://doi.org/10.32604/jbd.2022.030908



cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
  • 261

    View

  • 179

    Download

  • 0

    Like

Share Link