Zalina M D, Desa M N M, Nguyen V T V, Kassim A H M
Faculty of Science, Universiti Teknologi Malaysia, Johor.
Water Sci Technol. 2002;45(2):63-8.
This paper discusses the comparative assessment of eight candidate distributions in providing accurate and reliable maximum rainfall estimates for Malaysia. The models considered were the Gamma, Generalised Normal, Generalised Pareto, Generalised Extreme Value, Gumbel, Log Pearson Type III, Pearson Type III and Wakeby. Annual maximum rainfall series for one-hour resolution from a network of seventeen automatic gauging stations located throughout Peninsular Malaysia were selected for this study. The length of rainfall records varies from twenty-three to twenty-eight years. Model parameters were estimated using the L-moment method. The quantitative assessment of the descriptive ability of each model was based on the Probability Plot Correlation Coefficient test combined with root mean squared error, relative root mean squared error and maximum absolute deviation. Bootstrap resampling was employed to investigate the extrapolative ability of each distribution. On the basis of these comparisons, it can be concluded that the GEV distribution is the most appropriate distribution for describing the annual maximum rainfall series in Malaysia.
本文讨论了对八种候选分布进行比较评估，以得出马来西亚准确可靠的最大降雨量估计值。所考虑的模型有伽马分布、广义正态分布、广义帕累托分布、广义极值分布、耿贝尔分布、对数皮尔逊Ⅲ型分布、皮尔逊Ⅲ型分布和韦克比分布。本研究选取了马来西亚半岛各地17个自动雨量站网络一小时分辨率的年最大降雨量序列。降雨记录长度从23年到28年不等。使用L矩法估计模型参数。每个模型描述能力的定量评估基于概率图相关系数检验，并结合均方根误差、相对均方根误差和最大绝对偏差。采用自助重采样法研究每种分布的外推能力。基于这些比较，可以得出结论，广义极值分布是描述马来西亚年最大降雨量序列最合适的分布。
