A Stochastic Model of Daily Rainfall for Universiti Pertanian Malaysia, Serdang.

• Main Authors: Bardaie, Muhamad Zohadie, Abdul Salam, Ahmad Che
• Format: Article
• Language: English; English
• Published: 1981
• Online Access: http://psasir.upm.edu.my/id/eprint/2079/1/A_Stochastic_Model_of_Daily_Rainfall_for_Universiti.pdf; http://psasir.upm.edu.my/id/eprint/2079/
• Institution: Universiti Putra Malaysia

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.