中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
Analysis of the nonstationarity characteristics and future trends of flood extremes in the Dongting Lake Basin

文献类型:期刊论文

作者Gao, Yunpeng2; Xia, Jun1,3; Chen, Xingwei2; Zou, Lei1; Huang, Jie2; Yu, Jiarui4
刊名JOURNAL OF HYDROLOGY-REGIONAL STUDIES
出版日期2022-12-01
卷号44页码:19
关键词Flood extreme Nonstationarity Future trend GAMLSS model Dongting Lake Basin
DOI10.1016/j.ejrh.2022.101217
通讯作者Xia, Jun(xiaj@igsnrr.ac.cn)
英文摘要Study region: Dongting Lake Basin of China. Study focus: This study aimed to analyze the nonstationary characteristics and future trends of flood extremes in the Dongting Lake Basin. The spatiotemporal variations in the flood extremes that occurred over the past 60 years were explored using the trend-free prewhitening-MK (TFPW-MK) method, the nonstationary characteristics of flood extremes were detected using the Pettitt test, and the nonstationarity analysis was performed using the GAMLSS model. Furthermore, a combination of TFPW-MK and the Hurst exponent was employed to predict the future trends in flood extremes. New hydrological insights for the region: (1) Evident variations were observed in the flood extremes from most hydrometric stations. Among the 10 stations with a decreasing extreme trend, seven exhibited evident decreases. Such decreases probably result from the impact of water conservancy projects. Among the remaining six stations with an increasing extreme trend, two exhibited evident increases. Such increases probably result from the effect of highly extreme precipitation. (2) Flood extremes from most (9 of 16) stations showed nonstationarity. The lognormal distri-bution was the optimal distribution of extreme values for nonstationary stations, whereas the Gamma distribution was the optimal distribution of extreme values for stationary stations. Despite the preferable fitting efficiency of the GAMLSS model, its simulation performance for nonstationary stations that showed significant trends must be improved. (3) The flood extremes of the 14 stations will maintain existing trends in the future. The Xiangtan Station exhibited anti persistence and might show a decreasing trend in the future, whereas Shimen Station did not show persistence.
WOS关键词RIVER-BASIN ; FREQUENCY-ANALYSIS ; STATIONARITY ; RESERVOIRS ; CLIMATE ; LOCATION ; INDEXES ; MODELS ; TESTS ; RISK
资助项目Strategic Priority Research Program of the Chinese Academy of Sciences ; National Natural Science Foundation of China ; [XDA23040304] ; [41890823]
WOS研究方向Water Resources
语种英语
出版者ELSEVIER
WOS记录号WOS:000876530000003
资助机构Strategic Priority Research Program of the Chinese Academy of Sciences ; National Natural Science Foundation of China
源URL[http://ir.igsnrr.ac.cn/handle/311030/186411]  
专题中国科学院地理科学与资源研究所
通讯作者Xia, Jun
作者单位1.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Water Cycle & Related Land Surface Proc, Beijing 100101, Peoples R China
2.Fujian Normal Univ, Coll Geog Sci, Fuzhou 350007, Peoples R China
3.Wuhan Univ, State Key Lab Water Resources & Hydropower Engn Sc, Wuhan 430000, Peoples R China
4.Hohai Univ, Coll Hydrol & Water Resources, Nanjing 210098, Peoples R China
推荐引用方式
GB/T 7714
Gao, Yunpeng,Xia, Jun,Chen, Xingwei,et al. Analysis of the nonstationarity characteristics and future trends of flood extremes in the Dongting Lake Basin[J]. JOURNAL OF HYDROLOGY-REGIONAL STUDIES,2022,44:19.
APA Gao, Yunpeng,Xia, Jun,Chen, Xingwei,Zou, Lei,Huang, Jie,&Yu, Jiarui.(2022).Analysis of the nonstationarity characteristics and future trends of flood extremes in the Dongting Lake Basin.JOURNAL OF HYDROLOGY-REGIONAL STUDIES,44,19.
MLA Gao, Yunpeng,et al."Analysis of the nonstationarity characteristics and future trends of flood extremes in the Dongting Lake Basin".JOURNAL OF HYDROLOGY-REGIONAL STUDIES 44(2022):19.

入库方式: OAI收割

来源:地理科学与资源研究所

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