Hydrological Risk Assessment of the Johor River: Flood Frequency Analysis with L-Moments

Hydrological Risk Assessment of the Johor River: Flood Frequency Analysis with L-Moments

Authors

  • Nur Hanida Othman Faculty of Computer and Mathematical Sciences, Universiti Teknologi MARA Negeri Sembilan Branch, Seremban Campus, 70300 Negeri Sembilan, Malaysia.
  • Basri Badyalina Faculty of Computer and Mathematical Sciences, Universiti Teknologi MARA Johor Branch, Segamat Campus, 85000 Johor, Malaysia.
  • Sheril Haiza Shah Izan Faculty of Computer and Mathematical Sciences, Universiti Teknologi MARA Negeri Sembilan Branch, Seremban Campus, 70300 Negeri Sembilan, Malaysia.
  • Ani Shabri Department of Mathematical Sciences, Faculty of Science,Universiti Teknologi Malaysia, 81310, Johor, Malaysia.
  • Muhammad Fadhil Marsani School of Mathematical Sciences, Universiti Sains Malaysia, 11800 Minden, Penang, Malaysia.
  • Fatin Farazh Ya'acob Faculty of Business and Management, Universiti Teknologi MARA Johor Branch, Segamat Campus, 85000 Johor, Malaysia.

DOI:

https://doi.org/10.24191/jcrinn.v10i2.527

Keywords:

L-Moments, Generalized Pareto, Return period, Hydrological modelling, Flood frequency analysis, Johor River

Abstract

Flooding remains one of the most significant hydrological hazards in Malaysia, particularly within the Johor River Basin. This study conducts a Flood Frequency Analysis (FFA) using the L-Moment method to identify the most suitable probability distribution for modelling annual maximum streamflow at the Kahang River station. A 45-year dataset (1978-2022) was analyzed using three candidate distributions: Generalized Logistic (GLO), Generalized Pareto (GPA), and Pearson Type-III (PE3). The L-Moment Ratio Diagram (LMRD), alongside statistical performance metrics such as MAE, RMSE, MAPE, RMSPE, R2 and Euclidean Distance was employed to evaluate model accuracy. Results reveal that the GPA distribution provides the best fit as it provides smallest value of MAE, MAPE, RMSPE and Euclidean Distance, demonstrating superior accuracy in predicting extreme flood events, particularly for high return periods. The study offers critical insights for flood risk assessment, infrastructure planning, and early warning system development in the region. Lastly, it provided researchers with flood analysis methods using L-moments and extreme value distributions.

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References

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Published

2025-09-01

How to Cite

Othman, N. H., Badyalina, B., Shah Izan, S. H., Shabri, A., Marsani, M. F., & Ya’acob, F. F. (2025). Hydrological Risk Assessment of the Johor River: Flood Frequency Analysis with L-Moments. Journal of Computing Research and Innovation, 10(2), 144–155. https://doi.org/10.24191/jcrinn.v10i2.527

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Section

General Computing
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