Determination of Water Quality Index for Otamiri River Chokocho Rivers State

Authors

  • Thankgod Felix Nwokocha Department of Civil and Environmental Engineering, University of Port Harcourt Choba, Rivers State, Nigeria. Author
  • John N. Ugbebor Department of Civil and Environmental Engineering, University of Port Harcourt Choba, Rivers State, Nigeria. Author
  • Ngozi U Udeh Department of Civil and Environmental Engineering, University of Port Harcourt Choba, Rivers State, Nigeria Author

DOI:

https://doi.org/10.31181/sa21202419

Keywords:

Water quality index, Global positioning system, Water, Pollutants

Abstract

This study examined the water quality of the Otamiri River, which is located in the state of Rivers, Nigeria. The objectives of the study were to gain an understanding of the concentrations of pollutants (such as ammonia, PH, COD, turbidity, dissolved oxygen, Zinc Cadmium, and Lead) and to determine the Water Quality Index (WQI) of the river in order to ascertain whether or not the water is safe to drink. During the course of the study, ten water samples were collected from ten different places, and their coordinates were determined by utilizing a Global Positioning System (GPS) between the hours of 6 and 7 each morning. The WQI analysis was carried out using the Excel application tool, employing equations 2.1, 2.2, 2.3, and 2.4. The drinking water quality standards established by the World Health Organization (WHO) and the WQI rating published by Robert and Icka [1] served as references for the analysis. Results showed that the river had 96.19 for March, 69.65 for April, 64.67 for May, 57.75 for June, 64.33 for July, and 51.22 for August, implying that the Otamiri River was unsafe for drinking purposes for March, April and May with WQI values of 90.19, 69.65 and 64.67 respectively while in June, July.

References

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Published

2024-07-03

How to Cite

Nwokocha, T. F. ., Ugbebor, J. N., & Udeh, N. U. . (2024). Determination of Water Quality Index for Otamiri River Chokocho Rivers State. Systemic Analytics, 2(1), 106-119. https://doi.org/10.31181/sa21202419