Progresses on statistical modeling of non-stationary extreme sequences and its application in climate and hydrological change

被引：0
|
作者：
Lu F. [1 ]
Xiao W. [1 ]
Yan D. [1 ]
Wang H. [1 ]
机构：
[1] State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resources and Hydropower Research, Beijing
来源：
Shuili Xuebao/Journal of Hydraulic Engineering | 2017年 / 48卷 / 04期
关键词：
Climate change; Covariate; Hydrological sequences; Non-stationary; Statistical modeling of extreme values;
D O I：
10.13243/j.cnki.slxb.20160281
中图分类号：
学科分类号：
摘要：
In the context of global warming and average rise in sea level, obvious changes are witnessed with regard to the frequency and intensity of major extreme weather and climate events. Climate change has become an important cause of non-stationarity in hydrology. Several approaches have been proposed to tackle non-stationarity of hydro-meteorological extremes in the literatures. The structures and extreme inference methods of non-stationary sequences model applied usually in climate and hydrology change are summarized in this paper. Some typical examples in statistical modeling of extremes of non-stationary hydrologic sequences are analyzed. The applications demonstrate that changes of hydrology variables according to time or covariates can be reflected by statistical modeling of extremes of non-stationary sequences, and the return period and risk assessment for non-stationary situations can be quite different from those corresponding to stationary conditions. Finally, perspectives on statistical modeling of extremes of non-stationary sequences are proposed. © 2017, China Water Power Press. All right reserved.
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页码：379 / 389
页数：10
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