Analysing the variability of non-stationary extreme rainfall events amidst climate change in East Malaysia

Climate change is intensifying the occurrence of extreme rainfall events, drawing attention to the importance of understanding the return period concept within the realm of extreme weather studies. This study evaluates the stationarity of extreme rainfall series on both monthly and annual series acr...

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Published in:AQUA-WATER INFRASTRUCTURE ECOSYSTEMS AND SOCIETY
Main Authors: Ng, Jing Lin; Huang, Yuk Feng; Yong, Stephen Luo Sheng; Lee, Jin Chai; Ahmed, Ali Najah; Mirzaei, Majid
Format: Article; Early Access
Language:English
Published: IWA PUBLISHING 2024
Subjects:
Online Access:https://www-webofscience-com.uitm.idm.oclc.org/wos/woscc/full-record/WOS:001259950100001
author Ng
Jing Lin; Huang
Yuk Feng; Yong
Stephen Luo Sheng; Lee
Jin Chai; Ahmed
Ali Najah; Mirzaei
Majid
spellingShingle Ng
Jing Lin; Huang
Yuk Feng; Yong
Stephen Luo Sheng; Lee
Jin Chai; Ahmed
Ali Najah; Mirzaei
Majid
Analysing the variability of non-stationary extreme rainfall events amidst climate change in East Malaysia
Engineering; Water Resources
author_facet Ng
Jing Lin; Huang
Yuk Feng; Yong
Stephen Luo Sheng; Lee
Jin Chai; Ahmed
Ali Najah; Mirzaei
Majid
author_sort Ng
spelling Ng, Jing Lin; Huang, Yuk Feng; Yong, Stephen Luo Sheng; Lee, Jin Chai; Ahmed, Ali Najah; Mirzaei, Majid
Analysing the variability of non-stationary extreme rainfall events amidst climate change in East Malaysia
AQUA-WATER INFRASTRUCTURE ECOSYSTEMS AND SOCIETY
English
Article; Early Access
Climate change is intensifying the occurrence of extreme rainfall events, drawing attention to the importance of understanding the return period concept within the realm of extreme weather studies. This study evaluates the stationarity of extreme rainfall series on both monthly and annual series across East Malaysia, employing the Augmented Dickey-Fuller, Phillips Perron, and Kwiatkowski-Phillips-Schmidt-Shin tests. To model these extreme rainfall series, various probability distributions were applied, followed by goodness-of-fit tests to determine their adequacy. The study identified the stationary and non-stationary return values at 25-, 50-, and 100-year return periods. Additionally, maps depicting the spatial distribution for non-stationary increment were generated. The results indicated that extreme monthly rainfall exhibited stationary characteristics, while extreme yearly rainfall displayed non-stationary characteristics. Among the tested probability distributions, the generalised extreme value distribution was found to be superior in representing the characteristics of the extreme rainfall. Furthermore, a significant finding is that the non-stationary rainfall exhibits higher return values than those of stationary rainfall across all return periods. The northeast coast of Sabah highlighted as the most affected area, with notably high return values for extreme rainfall.
IWA PUBLISHING
2709-8028
2709-8036
2024


10.2166/aqua.2024.132
Engineering; Water Resources
gold
WOS:001259950100001
https://www-webofscience-com.uitm.idm.oclc.org/wos/woscc/full-record/WOS:001259950100001
title Analysing the variability of non-stationary extreme rainfall events amidst climate change in East Malaysia
title_short Analysing the variability of non-stationary extreme rainfall events amidst climate change in East Malaysia
title_full Analysing the variability of non-stationary extreme rainfall events amidst climate change in East Malaysia
title_fullStr Analysing the variability of non-stationary extreme rainfall events amidst climate change in East Malaysia
title_full_unstemmed Analysing the variability of non-stationary extreme rainfall events amidst climate change in East Malaysia
title_sort Analysing the variability of non-stationary extreme rainfall events amidst climate change in East Malaysia
container_title AQUA-WATER INFRASTRUCTURE ECOSYSTEMS AND SOCIETY
language English
format Article; Early Access
description Climate change is intensifying the occurrence of extreme rainfall events, drawing attention to the importance of understanding the return period concept within the realm of extreme weather studies. This study evaluates the stationarity of extreme rainfall series on both monthly and annual series across East Malaysia, employing the Augmented Dickey-Fuller, Phillips Perron, and Kwiatkowski-Phillips-Schmidt-Shin tests. To model these extreme rainfall series, various probability distributions were applied, followed by goodness-of-fit tests to determine their adequacy. The study identified the stationary and non-stationary return values at 25-, 50-, and 100-year return periods. Additionally, maps depicting the spatial distribution for non-stationary increment were generated. The results indicated that extreme monthly rainfall exhibited stationary characteristics, while extreme yearly rainfall displayed non-stationary characteristics. Among the tested probability distributions, the generalised extreme value distribution was found to be superior in representing the characteristics of the extreme rainfall. Furthermore, a significant finding is that the non-stationary rainfall exhibits higher return values than those of stationary rainfall across all return periods. The northeast coast of Sabah highlighted as the most affected area, with notably high return values for extreme rainfall.
publisher IWA PUBLISHING
issn 2709-8028
2709-8036
publishDate 2024
container_volume
container_issue
doi_str_mv 10.2166/aqua.2024.132
topic Engineering; Water Resources
topic_facet Engineering; Water Resources
accesstype gold
id WOS:001259950100001
url https://www-webofscience-com.uitm.idm.oclc.org/wos/woscc/full-record/WOS:001259950100001
record_format wos
collection Web of Science (WoS)
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