A Stochastic Model of Daily Rainfall for Universiti Pertanian Malaysia, Serdang.
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 prob...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English English |
| Published: |
1981
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| 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/ |
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| Summary: | 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. |
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