A Stochastic Model of Daily Rainfall for Universiti Pertanian Malaysia, Serdang. - Bardaie, Muhamad Zohadie; Abdul Salam, Ahmad Che (1981)
An application of stochastic process for describing and analysing daily the rainfall pattern at Universiti Pertanian Malaysia (V.P.M.), Serdang, is presented. A model based on the first-order Markov chain was developed. The model uses historical rainfall data to estimate the markov transition probabilities. The year is divided into four seasons, each is represented by a separate transition probability matrix. The range of rainfall values is divided into eleven states, thus resulting in a 11 X 11 transition probability matrix for each season. The model is capable of simulating a daily rainfall record of any length for the area. It is evaluated by comparing the simulation result with observed data for a one-year period.