THE BEST FIT PROBABILITY DISTRIBUTION MODEL FOR THE ESTIMATION OF EXTREME RAINFALL IN LIMBANG, SARAWAK

Abstract

In Malaysia, the increment of annual rainfall patterns is causing frequent floods, mainly in Sabah and Sarawak. Limbang river basin was selected as a case study due to it was facing of high-risk flooding 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 fit 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 fit tests, Chi-Square, Kolmogorov Smirnov test, and the Log-Normal was found to be the best fit model for the station of Panduran. The Log-Pearson type III was found to be the best-fit 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 fit probability distributions and could be used by a design engineer in the future.

Keywords

• flood
• return period
• gumbel distribution