STOCHASTIC MODELING OF DAILY PRECIPITATION IN ABEOKUTA

  • Akintunde A A
  • Asiribo O E
  • Adebanji A O
  • Adelakun A A
  • Agwuegbo S O
Keywords: Markvo chain, Stationary distribution, Stochastic model, Daily precipitation

Abstract

In this study, the Chapman-Kolmogorov Equation (CKE) was modified and applied to model the daily precipitation data of Abeokuta, Ogun State. The modified equation incorporated the initial distribution of the system as a feedback. The daily precipitation data converges at the 2nd

iteration with the modified CKE. To ascertain the validity of the result, a diagnostic test was conducted with the limiting characteristic equation. The test result showed that the

limiting distribution of the system approached the absolute probability distribution. In addition, the Bayesian Information Criterion technique was used to determine the order of the Markov chain which was observed to be of order one. This gave the best fit for precipitation pattern which is relevant in the development of new growth and yield models of major crops such as corn, sorghum and soya bean; enabling farmers estimate the distribution of crop yield as the growing season progressed.

Issue
2008
Section
Articles