The probability distribution of annual maximum hourly and daily rainfall in Kemaman

The world’s most catastrophic and repetitive event is known to be flood, which extremely affects the health, safety, welfare and economy of community. Malaysia has experienced uttermost rainfall events during the monsoon seasons that last for several hours and consequently lead to flash flood. The l...

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Bibliographic Details
Main Author: Aasha, Thiaharajan
Format: Undergraduates Project Papers
Language:English
Published: 2018
Subjects:
Online Access:http://umpir.ump.edu.my/id/eprint/27841/
http://umpir.ump.edu.my/id/eprint/27841/
http://umpir.ump.edu.my/id/eprint/27841/1/The%20probability%20distribution%20of%20annual%20maximum%20hourly%20and%20daily%20rainfall.pdf
id ump-27841
recordtype eprints
spelling ump-278412020-02-13T04:05:24Z http://umpir.ump.edu.my/id/eprint/27841/ The probability distribution of annual maximum hourly and daily rainfall in Kemaman Aasha, Thiaharajan TC Hydraulic engineering. Ocean engineering The world’s most catastrophic and repetitive event is known to be flood, which extremely affects the health, safety, welfare and economy of community. Malaysia has experienced uttermost rainfall events during the monsoon seasons that last for several hours and consequently lead to flash flood. The location of interest of this study is Kemaman district of Terengganu, Malaysia since it undergoes the unforeseeable loss and brunt every year due to extreme intensity of rainfall. Annual maximum hourly and daily rainfall data at nine stations in Kemaman district are collected and the probability distributions are analysed for these set of data. The objectives of this study are: (i) to perform the probability distribution analysis using Log-Pearson Type III Distribution and Gumbel Distribution for annual maximum hourly and daily rainfall in Kemaman, (ii) to estimate the most appropriate probability distribution for annual maximum hourly and daily rainfall in Kemaman and (iii) to estimate the annual maximum hourly and daily rainfall intensity for selected return periods. In this study, the goodness of fit test for the distribution are tested using Kolmogorov-Smirnov and Anderson-Darling tests. Based on the output generated for fitness tests, Log-Pearson Type III Distribution proves to be the most appropriate probability distribution function for annual maximum hourly and daily rainfall for Kemaman district. The estimated extreme rainfall intensity for various return period can be used as the basic inputs in hydrologic design such as in the design of storm sewers culverts and other hydraulic structures as well as inputs to rainfall runoff models. 2018-06 Undergraduates Project Papers NonPeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/27841/1/The%20probability%20distribution%20of%20annual%20maximum%20hourly%20and%20daily%20rainfall.pdf Aasha, Thiaharajan (2018) The probability distribution of annual maximum hourly and daily rainfall in Kemaman. Faculty of Civil Engineering and Earth Resources, Universiti Malaysia Pahang. https://efind.ump.edu.my/cgi-bin/koha/opac-detail.pl?biblionumber=90901
repository_type Digital Repository
institution_category Local University
institution Universiti Malaysia Pahang
building UMP Institutional Repository
collection Online Access
language English
topic TC Hydraulic engineering. Ocean engineering
spellingShingle TC Hydraulic engineering. Ocean engineering
Aasha, Thiaharajan
The probability distribution of annual maximum hourly and daily rainfall in Kemaman
description The world’s most catastrophic and repetitive event is known to be flood, which extremely affects the health, safety, welfare and economy of community. Malaysia has experienced uttermost rainfall events during the monsoon seasons that last for several hours and consequently lead to flash flood. The location of interest of this study is Kemaman district of Terengganu, Malaysia since it undergoes the unforeseeable loss and brunt every year due to extreme intensity of rainfall. Annual maximum hourly and daily rainfall data at nine stations in Kemaman district are collected and the probability distributions are analysed for these set of data. The objectives of this study are: (i) to perform the probability distribution analysis using Log-Pearson Type III Distribution and Gumbel Distribution for annual maximum hourly and daily rainfall in Kemaman, (ii) to estimate the most appropriate probability distribution for annual maximum hourly and daily rainfall in Kemaman and (iii) to estimate the annual maximum hourly and daily rainfall intensity for selected return periods. In this study, the goodness of fit test for the distribution are tested using Kolmogorov-Smirnov and Anderson-Darling tests. Based on the output generated for fitness tests, Log-Pearson Type III Distribution proves to be the most appropriate probability distribution function for annual maximum hourly and daily rainfall for Kemaman district. The estimated extreme rainfall intensity for various return period can be used as the basic inputs in hydrologic design such as in the design of storm sewers culverts and other hydraulic structures as well as inputs to rainfall runoff models.
format Undergraduates Project Papers
author Aasha, Thiaharajan
author_facet Aasha, Thiaharajan
author_sort Aasha, Thiaharajan
title The probability distribution of annual maximum hourly and daily rainfall in Kemaman
title_short The probability distribution of annual maximum hourly and daily rainfall in Kemaman
title_full The probability distribution of annual maximum hourly and daily rainfall in Kemaman
title_fullStr The probability distribution of annual maximum hourly and daily rainfall in Kemaman
title_full_unstemmed The probability distribution of annual maximum hourly and daily rainfall in Kemaman
title_sort probability distribution of annual maximum hourly and daily rainfall in kemaman
publishDate 2018
url http://umpir.ump.edu.my/id/eprint/27841/
http://umpir.ump.edu.my/id/eprint/27841/
http://umpir.ump.edu.my/id/eprint/27841/1/The%20probability%20distribution%20of%20annual%20maximum%20hourly%20and%20daily%20rainfall.pdf
first_indexed 2023-09-18T22:43:40Z
last_indexed 2023-09-18T22:43:40Z
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