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...
Published in: | Aqua Water Infrastructure, Ecosystems and Society |
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2024
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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 |
accesstype |
|
record_format |
scopus |
collection |
Scopus |
_version_ |
1812871794874384384 |