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 Author: Ng J.L.; Huang Y.F.; Yong S.L.S.; Lee J.C.; Ahmed A.N.; Mirzaei M.
Format: Article
Language:English
Published: IWA Publishing 2024
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85201904682&doi=10.2166%2faqua.2024.132&partnerID=40&md5=d3535645c9b3ccc04f708da57e821d3d
id 2-s2.0-85201904682
spelling 2-s2.0-85201904682
Ng J.L.; Huang Y.F.; Yong S.L.S.; Lee J.C.; Ahmed A.N.; Mirzaei M.
Analysing the variability of non-stationary extreme rainfall events amidst climate change in East Malaysia
2024
Aqua Water Infrastructure, Ecosystems and Society
73
7
10.2166/aqua.2024.132
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85201904682&doi=10.2166%2faqua.2024.132&partnerID=40&md5=d3535645c9b3ccc04f708da57e821d3d
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. © 2024 The Authors.
IWA Publishing
27098028
English
Article

author Ng J.L.; Huang Y.F.; Yong S.L.S.; Lee J.C.; Ahmed A.N.; Mirzaei M.
spellingShingle Ng J.L.; Huang Y.F.; Yong S.L.S.; Lee J.C.; Ahmed A.N.; Mirzaei M.
Analysing the variability of non-stationary extreme rainfall events amidst climate change in East Malaysia
author_facet Ng J.L.; Huang Y.F.; Yong S.L.S.; Lee J.C.; Ahmed A.N.; Mirzaei M.
author_sort Ng J.L.; Huang Y.F.; Yong S.L.S.; Lee J.C.; Ahmed A.N.; Mirzaei M.
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
publishDate 2024
container_title Aqua Water Infrastructure, Ecosystems and Society
container_volume 73
container_issue 7
doi_str_mv 10.2166/aqua.2024.132
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-85201904682&doi=10.2166%2faqua.2024.132&partnerID=40&md5=d3535645c9b3ccc04f708da57e821d3d
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. © 2024 The Authors.
publisher IWA Publishing
issn 27098028
language English
format Article
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