Flood frequency analysis of daily water levels using the L-moment and TL-moment approaches at river stations in Pahang
The application of flood frequency analysis is essential for understanding and managing the risks associated with extreme water level events. This study examines the Pahang River basin, specifically focusing on water levels at Sungai Pahang (Temerloh) and Sungai Lipis (Benta). Probability distributi...
Saved in:
Published in | Mathematical Modeling and Computing Vol. 12; no. 3; pp. 709 - 723 |
---|---|
Main Authors | , , , , , , , |
Format | Journal Article |
Language | English |
Published |
2025
|
Online Access | Get full text |
Cover
Loading…
Summary: | The application of flood frequency analysis is essential for understanding and managing the risks associated with extreme water level events. This study examines the Pahang River basin, specifically focusing on water levels at Sungai Pahang (Temerloh) and Sungai Lipis (Benta). Probability distributions and return period concepts are applied to assess flood occurrences. The study has two main objectives: first, to determine the most suitable probability distribution for modeling flood events among the Generalized Extreme Value (GEV), Generalized Logistic (GLO), and Generalized Pareto (GPA) distributions, using both L-moments and TL-moments for parameter estimation; and second, to estimate expected water levels for return periods of 2, 5, 10, 50, and 100 years using the identified best-fit distributions. The study employs the Mean Absolute Deviation Index (MADI) and Ratio Diagram tools to evaluate distribution performance to achieve these objectives. The results indicate that the GLO distribution, estimated using TL-moments (1;0), provides the best fit for the water level data. The findings suggest that water levels in Sungai Pahang and Sungai Lipis will likely exceed the critical danger thresholds of 33 meters and 75 meters within the next 5 and 10 years, respectively, highlighting the need for proactive flood management strategies. |
---|---|
ISSN: | 2312-9794 2415-3788 |
DOI: | 10.23939/mmc2025.03.709 |