Assessment of probability distributions of groundwater quality data in Gwale area, north-western Nigeria

Abstract

Groundwater quality plays an important role in human, animal, and plant health. Measurements of water quality are random variables that need a probabilistic model. The interest in fitting probability distribution in modeling water quality data remains strong in hydrology and engineering. This paper has been designed to find the best fitting probability distribution of calcium concentration of groundwater collected from 28 sampling sites in Gwale area, Kano state, Northwestern Nigeria. The parameter estimates for the groundwater data are analyzed using gamma, logistic, lognormal, normal, and Weibull distributions. The statistics measure such as the Akaike information criterion (AIC), Bayesian information criterion, log-likelihood, and Kolmogorov-Smirnov (K-S) test are computed to compare the fitted distributions. The most suitable distribution has been selected using these statistics measures. The result indicates that the logistic distribution with the highest log-likelihood value, and the smallest AIC and BIC values were found to fit the calcium concentration of groundwater data than other competing distributions. This research describes the use of probability distribution in modeling groundwater quality data and could be used to describe groundwater quality data in any other location.