Extreme precipitation frequency analysis using a minimum density power divergence estimator

Abstract

The recently observed hydrologic extremes are unlike what has been experienced so far. Both the magnitude and frequency of extremes are important indicators that determine the flood safety design criteria. Therefore, how are design criteria updated faced with these extremes? Both a sudden increase of design rainfall by the inclusion of these extremes and complete ignorance are inappropriate. In this study, the changes in extremes were examined and an alternative way to estimate the design rainfall amounts was developed using the data from 60 stations in South Korea. The minimum density power divergence estimator (MDPDE) with the optimal value of a tuning parameter, α, was suggested as an alternative estimator instead of the maximum likelihood estimator (MLE); its performance was evaluated using the Gumbel (GUM) and the generalized extreme value (GEV) distribution. The results revealed an increase in both the frequency and magnitude of extreme events over the last two decades, which imply that the extremes are already occurring. The performance of the MDPDE was evaluated. The results revealed decreased and adjusted values of the design rainfall compared to MLE. On the other hand, the MDPDE of the GEV distribution with a positive shape parameter, ξ, does not show its advantage conditionally because the GEV distribution has a heavier right tail than the GUM distribution (ξ = 0). In contrast, the results showed the high sensitivity of the MLE to the extremes compared to MDPDE.