Context-Aware Systems and Applications, and Nature of Computation and Communication. 8th EAI International Conference, ICCASA 2019, and 5th EAI International Conference, ICTCC 2019, My Tho City, Vietnam, November 28-29, 2019, Proceedings

Research Article

Predicted Concentration TSS (Total Suspended Solids) Pollution for Water Quality at the Time: A Case Study of Tan Hiep Station in Dong Nai River

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  • @INPROCEEDINGS{10.1007/978-3-030-34365-1_19,
        author={Cong Nguyen},
        title={Predicted Concentration TSS (Total Suspended Solids) Pollution for Water Quality at the Time: A Case Study of Tan Hiep Station in Dong Nai River},
        proceedings={Context-Aware Systems and Applications, and Nature of Computation and Communication. 8th EAI International Conference, ICCASA 2019, and 5th EAI International Conference, ICTCC 2019, My Tho City, Vietnam, November 28-29, 2019, Proceedings},
        proceedings_a={ICCASA \& ICTCC},
        year={2019},
        month={12},
        keywords={Water pollution Geostatistics Kriging Semivariogram},
        doi={10.1007/978-3-030-34365-1_19}
    }
    
  • Cong Nguyen
    Year: 2019
    Predicted Concentration TSS (Total Suspended Solids) Pollution for Water Quality at the Time: A Case Study of Tan Hiep Station in Dong Nai River
    ICCASA & ICTCC
    Springer
    DOI: 10.1007/978-3-030-34365-1_19
Cong Nguyen1,*
  • 1: Nguyen Tat Thanh University
*Contact email: ncnhut@ntt.edu.vn

Abstract

Water is essential for human life and socio-economic development. Water pollution is a concern for all mankind. In Vietnam, due to the development of factories and factories, water pollution has become more severe, including the Dong Nai River. In this article, the author uses the concentration of TSS at the Tan Hiep control station in Dong Nai River, using the Kriging interpolation method to find the appropriate model and give the results of water pollution prediction. Dong Nai river area over time with high reliability. TSS data were monitored continuously for three months (from the beginning of February 2018 to the end of April 2018), the predicted results using Kriging interpolation with high accuracy with regression coefficient equal to 1,005, the coefficient is 0.859 (the best value is 1), the forecast error is 2.258, the standard error is 0.044. It shows that using the Kriging interpolation method is an effective and suitable solution in mathematical problems with time information.