<?xml version="1.0" encoding="UTF-8"?>
<records>
<record>
<language>eng</language>
<publisher>Science and Education Publishing</publisher>
<journalTitle>American Journal of Water Resources</journalTitle>
<eissn>2333-4819</eissn>
<publicationDate>2026-06-26</publicationDate>
<volume>14</volume>
<issue>2</issue>
<startPage>46</startPage>
<endPage>54</endPage>
<doi>10.12691/ajwr-14-2-3</doi>
<publisherRecordId>AJWR20261423</publisherRecordId>
<documentType>article</documentType>
<title language="eng">TL-Moment-Based Regional Frequency Analysis of Extreme Rainfall Using Ward's Clustering and Kappa-Type Distributions</title>
<authors>
<author>
<name>Muhammad Nura</name>
<affiliationId>1</affiliationId>
</author>
<author>
<name>Zahratul Amani Binti Zakaria</name>
<email>muhdnuru@gmail.com</email>
<affiliationId>2</affiliationId>
</author>

</authors>
<affiliationsList>
<affiliationName affiliationId="1">Department of Statistics, Kano State Polytechnic, Kano, Nigeria</affiliationName>
<affiliationName affiliationId="2">Faculty of Computing and Informatics, Universiti Sultan Zainal Abidin, Kampus Besut, 22200 Besut, Terengganu, Malaysia</affiliationName>
</affiliationsList>
<abstract language="eng">Peninsular Malaysia is highly flood-prone. Conventional L-moment regional frequency analysis (RFA) is sensitive to post-2013 extreme monsoon outliers at multiple stations across the peninsula. This study presents the first parallel TL-moment and L-moment RFA for the comprehensive 179-station DID network (1971¨C2023), simultaneously evaluating GEV, GLO, GPA, and K3D-II distributions across three climatologically distinct regions. Ward's minimum-variance hierarchical clustering was applied to TL-moment site characteristics, optimized by the average silhouette width (ASW) criterion. Discordancy, heterogeneity, goodness-of-fit (Z-test), and quantile estimation were executed in strict parallel under both estimation frameworks. Parametric bootstrap (B = 1,000 replicates) was applied to derive 90% confidence intervals for all regional quantiles. Three acceptably homogeneous regions were delineated: R1 (N = 55; west coast, mean = 115.0 mm), R2 (N = 94; interior, mean = 117.7 mm), and R3 (N = 30; east coast interior, mean = 200.9 mm). Under L-moments, GLO was best for R1 and R2; GPA was the sole passing distribution for R3. Under TL-moments, K3D-II was best for R2, GPA for R3. No standard distribution passed for R1 under TL-moments. TL-moment quantiles were 7¨C44% lower than L-moment estimates at T ¡Ý 10 years. Bootstrap 90% CI widths for T = 100 years were 0.076 (R1), 0.037 (R2), and 0.066 (R3) growth-factor units. L-moment and TL-moment quantiles should be used jointly as upper and lower design-rainfall bounds. For life-safety-critical structures, the L-moment estimate is the conservative upper bound.</abstract>
<fullTextUrl format="pdf">https://pubs.sciepub.com/ajwr/14/2/3/ajwr-14-2-3.pdf</fullTextUrl>
<keywords language="eng"><keyword>regional frequency analysis</keyword>
<keyword>TL-moments</keyword>
<keyword>Ward's clustering</keyword>
<keyword>design rainfall</keyword>
<keyword>bootstrap confidence intervals</keyword>
<keyword>monsoon extremes</keyword>
</keywords>
</record>
</records>
