Journal of Applied Sciences and Environmental Management (Jan 2015)

Assessment of Anthropogenic Activities on Water Quality of Benin River

  • SU Ayobahan,
  • IM Ezenwa,
  • EE Orogun,
  • JE Uriri,
  • IJ Wemimo

DOI
https://doi.org/10.4314/jasem.v18i4.11
Journal volume & issue
Vol. 18, no. 4

Abstract

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Assessment of water quality was conducted from June to December, 2011 in five stations along the stretch of the Benin River between Ajimele and Koko town in attempt to assess and determine the source of anthropogenic activities affecting the river. Twentyfour parameters have been monitored on 5 sampling stations on a monthly-day-trip. Inter station comparisons and locations of significant differences were carried out using parametric ANOVA and Duncan multiple range tests. Principal Component Analysis (PCA) and Water Quality Index (WQI) were used to establish relationship among water quality parameters and determine the water quality status. First six components of PCA accounted for 90.96% of observed variations and showed similarity between the sampling stations indicating different anthropogenic activities and pollution levels of sampled sites. Factors identified as responsible for variability in the sampling stations are organic pollution, industrial effluent, soil erosion, nutrient loading and human activities, especially in station 4 and 5. WQI for sampling stations 1 and 3 was very poor for drinking (201 - 300) and stations 2, 4 and 5 was unsuitable (> 301) for human consumptions. In the final analysis, this investigation presents the usefulness of PCA and WQI in assessing complex datasets of surface water quality and as well as a call to action for the state and federal ministry of environment to take this issue of water quality degradation in Benin River into consideration, by reducing organic pollution and effluent discharge into the river. An intense and continuous water quality monitoring is highly recommended. © JASEM Keywords: Organic pollution, Industrial effluent, Water Quality Index (WQI), Principal Component Analysis (PCA).