Probabilistic Analysis of Peak Daily Rainfall for Prediction purposes in Selected Areas of Northern Nigeria

Abstract

In this study, probability analysis was performed on peak daily rainfall data in order to predict rainfall interval values and to determine the best fit functions in some parts of Nigeria. The selected towns are Kaduna, Kano, Yola, Jos, Damaturu and Maiduguri. The obtained peak daily rainfall values were subjected to Gumbel, Log-Gumbel, Normal, Log-Normal, Pearson and Log-Pearson probability distributions. Mathematical equation for probability distribution functions were established for each town and used to predict peak rainfall. The predicted values were subjected to goodness of fit tests such as Chi-square, Correlation Coefficient, Coefficient of Determination and Errors of Estimates to determine how best the fits are. The model that satisfies the tests adequately was selected as the best fit model. The study revealed that the peak rainfall at Kaduna, Jos, Kano, Yola and Damaturu are best fitted by log-Gumbel, while log- Pearson distribution is suitable for predicting peak rainfall in Maiduguri. The result also shows that the occurrences of peak daily rainfall depth of 100 mm and above are rare in the selected areas.

Keywords: Peak rainfall, Probability distribution models, Return period, Probability interval and goodness of fit tests