Changes in extreme rainfall and its implications for design rainfall using a Bayesian quantile regression approach

Hydrology Research

Tae-Woong Kim¹  Hyun-Han Kwon²  Sumiya Uranchimeg²  Byungsik Kim³ 

[1] Department of Civil and Environmental Engineering, Hanyang University, Ansan, Republic of Korea;Department of Civil and Environmental Engineering, Sejong University, Seoul, Republic of Korea;Department of Urban and Environmental Disaster Prevention, Kangwon National University, Gangwon-do, Republic of Korea;

关键词: bayesian quantile regression;    design rainfall;    distribution;    extreme rainfall;    nonstationarity;    uncertainty;   

DOI  :  10.2166/nh.2020.003

来源: DOAJ

【 摘 要 】

This study aims to explore possible distributional changes in annual daily maximum rainfalls (ADMRs) over South Korea using a Bayesian multiple non-crossing quantile regression model. The distributional changes in the ADMRs are grouped into nine categories, focusing on changes in the location and scale parameters of the probability distribution. We identified seven categories for a distributional change in the selected stations. Most of the stations (28 of 50) are classified as Category III, which is characterized by an upward trend with an increase in variance in the distribution. Moreover, stations with a downward trend with a decrease in the variance pattern (Category VII) are mainly distributed on the southern Korean coast. On the other hand, Category I stations are mostly located in eastern Korea and primarily show a statistically significant upward trend with a decrease in variance. Moreover, this study explored changes in design rainfall estimates for different categories in terms of distributional changes. For Categories I, II, III, and VI, a noticeable increase in design rainfall was observed, while Categories IV, V, and VII showed no evidence of association with risk of increased extreme rainfall.

【 授权许可】

Unknown