Data-Driven Analysis Based on Graphical and Statistical Modelling of the Water Quality of Niger Delta Region of Nigeria

Abstract

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. Eleven communities were affected in this study. Eleven water samples obtained from twenty-five available sources, collected from January 2019 to December 2019, included rainwater, surface water, and groundwater. These samples were analysed for their physicochemical and bacteriological parameters. The physical characteristics of the water points ranged from a pH of 6.61–7.2, electrical conductivity (EC) of 450–1742 units, turbidity of 0.72–13.65 units, and total dissolved solids (TDS) of 225–794. The chemical dataset generated was subjected to several scientific data models such as principal component analysis (PCA), Piper, Pie, Collins, and Schoeller interpretations. There is 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 sample. In addition, 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, as well as the enactment and implementation of environmental laws, is necessary in this region to ensure effective surface water and groundwater resource management.