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Hydrological quantile estimation is crucial for the design and management of hydraulic infrastructure. In the frequency analysis of extreme rainfall, it is important to select the most appropriate probability distribution that can adequately reproduce the extreme rainfall quantiles. In statistical hydrology, various distributions such as the generalized extreme value (GEV), generalized logistic (GLO), and Gumbel (GUM) distributions have been used widely. The GEV and GUM distributions are often suggested as the appropriate probability models for data on cases of extreme rainfall in Korea. However, the GEV, GUM, and GLO distributions have a limit for reproducing the statistical characteristics of data because they either have one shape parameter or do not have one at all. However, the Burr XII (BUR) distribution has two shape parameters and has a high flexibility for fitting data. Therefore, it has been widely used in the hydrological field and others. In this study, the applicability and suitability of the BUR distribution were examined for annual maximum rainfall data in Korea. The performance of the BUR distribution was compared with those of the conventional distributions using the Monte Carlo simulation. As a result, it was found that the GEV and BUR distributions are more appropriate models for Korean extreme rainfall data compared to the GUM and GLO distributions.

Applicability of Burr XII Distribution for Rainfall Frequency Analysis using Monte Carlo Simulation