Muhammad Nura¹, Zahratul Amani Binti Zakaria^2,

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 (1971–2023), 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 7–44% lower than L-moment estimates at T ≥ 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.

regional frequency analysis, TL-moments, Ward's clustering, design rainfall, bootstrap confidence intervals, monsoon extremes