Analyzing flood frequency based on annual maxima and peaks-over-threshold approaches in Selangor
Flood Frequency Analysis (FFA) refers to a statistical approach for estimating the probability and magnitude of flood occurrences. Annual Maximum (AM) is the most applied approach in FFA, focusing on the most extreme event during the period of time. In fact, it is also crucial to take both smaller a...
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| Main Authors: | , , , , , , |
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| Format: | Conference or Workshop Item |
| Language: | en |
| Published: |
IEEE
2025
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| Subjects: | |
| Online Access: | https://umpir.ump.edu.my/id/eprint/47304/2/Analyzing%20Flood%20Frequency%20Based%20on%20Annual%20Maxima%20and%20Peaks%20Over%20Threshold%20Approaches%20in%20Selangor.pdf https://umpir.ump.edu.my/id/eprint/47304/ https://doi.org/10.1109/AiDAS67696.2025.11213675 |
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| Summary: | Flood Frequency Analysis (FFA) refers to a statistical approach for estimating the probability and magnitude of flood occurrences. Annual Maximum (AM) is the most applied approach in FFA, focusing on the most extreme event during the period of time. In fact, it is also crucial to take both smaller and frequent flood events into consideration when performing flood frequency analysis. Therefore, another approach named Peaks-Over-Threshold (POT) method provides a more precise way of computing floods by including noteworthy high flow events (even if they are not the most extreme of the year), but it is usually underemployed because of its complexities in threshold selection. This research attempts to compare these two approaches in the flood frequency analysis for streamflow stations in Selangor. This study employs the L-moment approach to estimate the parameters of three candidate distributions, which are the Generalised Pareto (GPA) distribution, the Generalised extreme value (GEV) distribution, and the Generalised logistic (GLO) distribution. Then, the L-moment diagram will be implemented to ascertain the optimum distribution for the data series. Additionally, each data series' distribution performance will be evaluated using the goodness of fit test and efficiency assessment; mean absolute error (MAE), root mean square error (RMSE) and BIAS. These findings indicate that the combination of POT and GPA provides a more reliable and accurate estimate of flood frequency in Selangor, as this model yields the lowest values in the performance assessments. The results of this study are expected to support improved flood risk assessment and infrastructure planning in Selangor and similar flood-prone areas. |
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