Keywords
food, return period, Gumbel distribution
Document Type
Research Article
Abstract
In Malaysia, the increment of annual rainfall patterns is causing frequent foods, mainly in Sabah and Sarawak. Limbang river basin was selected as a case study due to it was facing of high-risk fooding problem mainly during the transition of climate. This study was aimed to estimate the frequency of rainfall under various return periods and to identify the best ft model probability distribution of annual maximum rainfall based on twenty-four hours sample in Limbang. The three statistical models were used, which are Gumbel, Log-Pearson type III, and Log-Normal. Based on the goodness of ft tests, Chi-Square, Kolmogorov Smirnov test, and the Log-Normal was found to be the best ft model for the station of Panduran. The Log-Pearson type III was found to be the best-ft distribution model for the rest of the stations, which occupies almost more than 90%. The maximum values of expected rainfall were calculated using the best ft probability distributions and could be used by a design engineer in the future.
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Recommended Citation
Tahir, T.; Hashim, A. M.; Takaijudin, H.; Yusof, K. Wan; and Osman, M.
(2021)
"The Best Fit Probability Distribution Model for the Estimation of Extreme Rainfall in Limbang, Sarawak,"
Platform: A Journal of Engineering (PAJE): Vol. 5:
Iss.
1, Article 4.
Available at:
https://journal.utp.edu.my/paje/vol5/iss1/4
Publication Date
31-3-2021
First Page
39
Last Page
45


