CHARACTERIZATION OF SURFACE WATER QUALITY AND POLLUTION IN IKARE AKOKO, ONDO STATE. NIGERIA

Abstract

The research characterize surface water quality in order to analyze the pollution level in Ikare, Ondo state using Water Quality Index and Fuzzy Logic Inference method and as well compared the effectiveness of the two methods used in evaluating water quality status. A total of 20 samples were utilized within the 12 catchment area, as at the time of sampling some of the stream were perennial which affected the sampling method. Physical analyses such as temperature were conducted in-situ while chemical and microbiological parameter such as DO, BOD, pH, Mg2+, K+, Ca2+Zn, Pb, Cd, Cu, Na+, TDS, Feacal and Total Coliform were analyzed in the laboratory. The analyzed result were compared with WHO/Nigeria standard so as to determine the potability of the water and the pollution level of the area was evaluated using Water Quality Index and Fuzzy Logic Inference method. A three step approach (assigning of weight, relative weight and rating scale) was used to calculate the water quality index method while fuzzy logic method was carried out by defining the membership function using five fuzzy sets. Mamdani fuzzy inference system method was used to normalize the parameter. Descriptive statistics was used to explain the result while a chloropleth map was used to explain the spatial distribution. Crosstabs analysis in SPSS and python programming language was used to validate the effectiveness of both methods. For the validation a set of rules was created. This rules were used to test the level of interaction between the input parameter and the output result. The result of the analysis after been compared with WHO/Nigerian standard for drinking water indicated that surface water in the area is bad for drink which is due to the high: feacal and total coliform, TDS, heavy metal present in the water. In comparison of the both methods using crosstab and python programming language, the study concluded that Fuzzy logic inference is more adequate than WQI method for evaluation of water quality because Fuzzy logic method considered all parameter as pollutant with respect to their standard.