Data-Driven Analysis Based on Graphical and Statistical Modelling of the Water Quality of Niger Delta Region of Nigeria
DOI:
https://doi.org/10.37256/ccds.212021478Keywords:
data-driven analysis, data science, contamination, modelling, Niger Delta, water qualityAbstract
Data-driven models derived from data science tools have been used to investigate water quality in some parts of the Niger Delta Region (NDR) of Nigeria. 11 communities were affected in this study. 11 water samples obtained from 25 available sources collected from January 2019 to December 2019 include rainwater, surface water and groundwater. These samples were analysed for their physicochemical and bacteriological parameters. The physical characteristics of the water points range from pH of 6.61-7.2, electrical conductivity (EC) of 450-1742 unit, the turbidity of 0.72-13.65 unit, and total dissolved solids (TDS) of 225-794. The chemical scientific dataset generated were subjected to several scientific data models such as principal component analysis (PCA), piper, Pie, Collins, and Schoeller interpretation. There is a piece of evidence that the water resources are potable in sections where Escherichia coli and total coliforms do not exceed the international and regional recommended limits of 0 per 100 ml of the sample. Also, the community water points are good for livestock and excellent for both recreation and irrigation purposes. Possible water contamination sources include faecal pollution from shallow wells and unconfined aquifers. Land use planning, enactment and implementation of environmental laws are necessary for this region to have effective surface water and groundwater resource management.
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Copyright (c) 2020 Davidson E. Egirani, Mohd T. Latif, Ifeoma M. Ugwu, Alfred W. Opukumo
This work is licensed under a Creative Commons Attribution 4.0 International License.