气候变化领域集成服务门户(CCPortal): Covariates for nonstationary modeling of extreme precipitation in the Pearl River Basin; China

CCPortal

DOI	10.1016/j.atmosres.2019.06.017
	Covariates for nonstationary modeling of extreme precipitation in the Pearl River Basin; China
	Su C.; Chen X.
发表日期	2019
ISSN	0169-8095
起始页码	224
结束页码	239
卷号	229
英文摘要	Nonstationarity of extreme precipitation has been reported in previous research. As a consequence, the hydrological frequency analysis that is primarily used in water-related infrastructure design in a nonstationary context is a current interest in hydrology. Covariates are critical elements in the nonstationary modeling of hydrological extremes. However, a covariate can be any physical process that exerts influences on hydrological extremes and it is important to find the best covariates for modeling the nonstationarity. Furthermore, the significance of and the spatial differences among the best covariates have yet to be investigated. Thus, in this study, the Pearl River Basin (PRB) was used as the study area and the wet/dry season maximum daily precipitation (WMP, DMP) data were used to determine the best covariates for the extreme precipitation based on the generalized extreme value (GEV) theory. The significance of the best covariates and the spatial differences between them were also investigated. The results showed that the best covariates for extreme precipitation exhibited large differences in spatial distribution. Furthermore, the El Niño-Southern Oscillation (ENSO) was found to be the best covariate for both the WMP and DMP in most of the PRB. The results also showed that there were differences in the performances of different indices used to represent the same climatic factor and significance test should be performed for the best covariates because the best covariate may not be a significant covariate. In addition, significant uncertainties were found in the nonstationary modeling of extreme precipitation due to the introduction of covariates. © 2019 Elsevier B.V.
英文关键词	Best covariates; Extreme precipitation; Nonstationarity; Pearl River basin; Spatial differences
语种	英语
scopus关键词	Atmospheric pressure; Climatology; Gems; Rivers; Uncertainty analysis; Watersheds; Covariates; Extreme precipitation; Non-stationarities; Pearl River basin; Spatial differences; Precipitation (meteorology); atmospheric modeling; extreme event; frequency analysis; hydrological modeling; numerical model; precipitation assessment; spatial analysis; China; Guangdong; Zhujiang Basin
来源期刊	Atmospheric Research
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/162236
作者单位	Center for Water Resources and Environment, Sun Yat-sen University, Guangzhou, 510275, China; Guangdong Engineering Technology Research Center of Water Security Regulation and Control for Southern China, Sun Yat-sen University, Guangzhou, 510275, China; Key Laboratory of Water Cycle and Water Security in Southern China of Guangdong High Education Institute, Sun Yat-sen University, Guangzhou, 510275, China
推荐引用方式 GB/T 7714	Su C.,Chen X.. Covariates for nonstationary modeling of extreme precipitation in the Pearl River Basin; China[J],2019,229.
APA	Su C.,&Chen X..(2019).Covariates for nonstationary modeling of extreme precipitation in the Pearl River Basin; China.Atmospheric Research,229.
MLA	Su C.,et al."Covariates for nonstationary modeling of extreme precipitation in the Pearl River Basin; China".Atmospheric Research 229(2019).