Modelling Monthly Rainfall in the Agricultural Hub of Oyo State, Nigeria: A Comparative Probability Distributions Study

Abstract The most appropriate probability distribution for rainfall data varies from one region to the other. The need to research the best distribution for different locations is thus a continuous process. This research was designed to investigate rainfall variability and the best-fit distribution model for monthly rainfall in Oke Ogun, the agricultural hub of Oyo state, Nigeria. Thirty-six years’ rainfall data (1982-2017) were statistically analysed and fitted to ten different probability distributions for each calendar month. Parameters of each distribution were estimated from maximum likelihood estimates. Best fit distribution models for each month were selected using Akaike Information Criteria (AIC), Bayesian Information Criteria (BIC) and Corrected Akaike Information Criteria (CAIC) as model selection criteria. Gamma distribution had the best-fit for six of the twelve-monthly rainfall data. Weibull distribution had best-fit for three months, while Lognormal fitted data for March and July best and Gumbel distribution had best-fit for August. This study will enable adequate integrated water resources management as well as proper water resources evaluation and planning, for agricultural productivity in the Oke Ogun region of Oyo state. Nigeria.