The application of generalised extreme value distribution (GEVD) requires the estimation of three parameters. Different researchers adopted different techniques for the estimation of the GEVD parameters and no standard comparison amongst those methods are available. This paper investigates the comparison of the commonly used GEVD parameters’ estimations for extreme rainfall modelling. The maximum likelihood estimation, generalised maximum likelihood estimation, Bayesian and L-moments methods were considered in this study to compare the magnitude of the GEVD parameters and the corresponding return level estimations. The analysis was performed using the monthly and yearly extreme rainfall of Tasmania, Australia. The GEVD was fitted to four different data sets using the four parameters estimation techniques. Estimated return levels of the GEVD for all the estimation techniques were compared with the return levels provided by the Australian Rainfall and Runoff (ARR), which is the national guideline for Australian rainfall and flood studies. The outcomes of the analysis suggest that the L-moments method is the better estimator of the return levels when comparing the ARR provided return levels.

广义极值分布（GEVD）的应用需要三个参数的估计。不同的研究人员采用不同的技术估算GEVD参数，并且这些方法之间没有标准的比较。本文研究了用于极端降雨模型的常用GEVD参数估计值的比较。本研究考虑了最大似然估计，广义最大似然估计，贝叶斯和L矩方法，以比较GEVD参数的大小和相应的回报水平估计。使用澳大利亚塔斯马尼亚州的每月和每年极端降雨进行分析。使用四种参数估计技术将GEVD拟合到四个不同的数据集。将所有估算技术的GEVD估算收益水平与澳大利亚降雨和径流（ARR）提供的收益水平进行比较，这是澳大利亚降雨和洪水研究的国家指南。分析结果表明，在比较ARR提供的收益水平时，L矩方法是收益水平的更好估计。