Fuzzy Logic Interference for Characterization of Surface Water Potability in Ikare Rural Community, Nigeria

Abstract

The availability of potable surface water in Nigeria, a typical developing nation, is low, and this information is not readily available to local residents in the country. Therefore, we carried out a low-cost Fuzzy Logic Inference characterization on the quality of surface water in a rural community (with 12 catchment areas) of Ikare, Ondo State of Nigeria. From the numerous water samples taken from the river that runs across the catchment areas, twenty (20) representative water samples were chosen and subjected to physical (temperature, pH), chemical (such as TDS, DO, BOD, metal ion concentrations), and biological (fecal and total coliform) characterizations. Further, five fuzzy sets and Mamdani fuzzy inference system method were used to normalize the parameters for pollution susceptibility analysis. We adopted GIS environment to provide a synoptic and high temporal information about the distribution of the surface water quality, indicating the areas susceptible to pollution. When compared with World Health Organization (WHO) and Nigeria Industrial Standards, we found the waters were generally unsuitable for drinking. Only 8.3% of the studied water samples were moderate for drinking while in linguistic terms for pollutant levels, 16.7%, 50%, and 25% fell in the categories of high, very high, and extremely high, respectively. Through statistical correlation (p < 0.05), we identified the notable water pollutants as fecal coliform, heavy metal, K+, and total dissolved solids. Therefore, we infer that direct excretion into the water channels, dumping of spent oil from mechanic workshop, and effluents from domestic and agricultural wastes are the major sources of the pollutants. Consequently, fuzzy logic analysis proved to be a readily available and reliable method for water potability assessment, especially in rural areas of developing nations.