Abstract

This engineering-focused study analyzes annual maximum daily rainfall data from the Department of Irrigation and Drainage (DID) Kemaman station in Terengganu, Malaysia, to enhance flood risk management and infrastructure resilience in the region. The study aims to identify the most effective probability distribution for modeling extreme rainfall and to estimate return periods for critical events. Using the robust L-moment method, various distributions were rigorously tested and initially selected through the L-moment ratio diagram (LMRD). The four-parameter Kappa distribution (K4D) emerged as the best fit, as determined by the mean absolute deviation index (MADI) and the mean squared deviation index (MSDI). The validated model enabled the estimation of return periods, indicating that a 2-year event corresponds to 188.66 mm of rainfall, while a 100-year event is expected to reach 475.48 mm. These quantitative insights are essential for designing durable, flood-resilient infrastructure, ensuring that regional development is both sustainable and adaptable to increasing weather variability.

Keywords

Extreme rainfall analysis, Probability distributions, Return period estimation, Flood risk management, L-moment method, Four-parameter kappa distribution.

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