| Title |
Concept of Trend Analysis of Hydrologic Extreme Variables and Nonstationary Frequency Analysis |
| Keywords |
hydrologic extreme variable;trend analysis;nonstationary;bayesian model;극치수문변량;경향성분석;비정상성;Bayesian 모형 |
| Abstract |
This study introduced a Bayesian based frequency analysis in which the statistical trend analysis for hydrologic extreme series is incorporated. The proposed model employed Gumbel extreme distribution to characterize extreme events and a fully coupled bayesian frequency model was finally utilized to estimate design rainfalls in Seoul. Posterior distributions of the model parameters in both Gumbel distribution and trend analysis were updated through Markov Chain Monte Carlo Simulation mainly utilizing Gibbs sampler. This study proposed a way to make use of nonstationary frequency model for dynamic risk analysis, and showed an increase of hydrologic risk with time varying probability density functions. The proposed study showed advantage in assessing statistical significance of parameters associated with trend analysis through statistical inference utilizing derived posterior distributions. |