Detection of Abrupt Changes in Precipitation Extremes over South Korea Using a Bayesian Approach
- Title
- Detection of Abrupt Changes in Precipitation Extremes over South Korea Using a Bayesian Approach
- Author
- 김태웅
- Keywords
- Bayesian model selection; Change point analysis; Extreme rainfall; Frequency analysis; Generalized Pareto distribution
- Issue Date
- 2016-10
- Publisher
- 대한토목학회
- Citation
- KSCE 2016 CONVENTION PROGRAM, Page. 75-76
- Abstract
- Change point (CP) analysis of extreme rainfall plays a key role to consider non-stationarity in
predicting flood or drought under climate change. This study provided a Bayesian framework to
detect the existence of the CP in extreme rainfalls. Unlike most published works assuming a
normal distribution, it allows for the model to use a generalized Pareto distribution (GPD) to fit
the extreme rainfall over a high threshold with a CP. The proposed approach was applied to the
extreme rainfall data from five selected stations in South Korea. Results indicated that the
employed methodology can precisely capture the CP existed in GPD.
- URI
- http://www.dbpia.co.kr/Journal/ArticleDetail/NODE07076841https://repository.hanyang.ac.kr/handle/20.500.11754/102832
- Appears in Collections:
- COLLEGE OF ENGINEERING SCIENCES[E](공학대학) > CIVIL AND ENVIRONMENTAL ENGINEERING(건설환경공학과) > Articles
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