Flood Frequency Analysis using L-Moment For Segamat River

Abstract

Flood frequency analysis is critical in water system design and estimating flood recurrence. This study aims to conduct the flood frequency analysis on Segamat River streamflow site to find the optimum distribution that fits the flood frequency data. In terms of estimating parameters, the L-moment method is more robust and more efficient than the maximum likelihood method. Besides, the L-moment method is not affected by sampling variability. Therefore, in this study, we applied the technique of L-moment for parameter estimation on five candidate distributions, the generalised Pareto (GPA) distribution, generalised extreme value (GEV) distribution, generalised logistic (GLO) distribution, log-Pearson 3 (LP3) distribution, and log-normal (LN3) distribution. The rank score approach is implemented to determine the optimum distribution for the annual Segamat River peak flow. Probability distribution identification is essential and it is a fundamental step in statistical analysis. The goodness of fit test and efficiency assessment are employed to evaluate the distributions' performance. The results show that the LN3 distribution is selected as the optimum function for the yearly peak flow for the Segamat River streamflow site. The outcome of this study can be used to understand the flood frequency analysis for the Segamat River.