Modeling of re-aeration coefficient For Nkisa River, Egbema, Rivers State, Nigeria

Abstract

Abstract This study aimed at developing a model for a coefficient of re-aeration, K2, that may be utilized in conjunction with a de-oxygenation coefficient, K1, to calculate the self-purification capacity, f, of the Nkisa River. The SOLVER function of the Microsoft Excel software employed an iterative least squares fitting routine to produce the optimal goodness of fit between Nkisa data and function. Thus, Nkisa re-aeration models; K22DRY (dry season model), K22RAINY (rainy season model), and K22all-seasons (combined model) were developed and validated statistically as well as graphically resulting in the output with the least error (dry season: sum of square error (SSE) = 0.0005, coefficient of determination (R2) = 0.948, adjusted R2 = 0.937, and root mean square error (RMSE) = 0.009; rainy season: SSE = 0.0483, R2 = 0.81, adjusted R2 = 0.77, and RMSE = 0.08; all seasons: SSE = 0.1004, R2 = 0.93, adjusted R2 = 0.92, and RMSE = 0.08). Its performance was verified by comparing the model with nine previously existing models and Nkisa re-aeration models gave the best interpretation of the conditions of the Nkisa River. The self-purification capacity of the studied river was found to be greater than unity during all studied periods except in March which implies that re-aeration is greater than de-oxygenation.