Uncertainty in determining extreme precipitation thresholds

被引:36
作者
Liu, Bingjun [1 ,2 ]
Chen, Junfan [1 ]
Chen, Xiaohong [1 ,2 ]
Lian, Yanqing [3 ]
Wu, Lili [4 ]
机构
[1] Sun Yat Sen Univ, Dept Water Resources & Environm, Guangzhou 510275, Guangdong, Peoples R China
[2] Sun Yat Sen Univ, Guangdong High Educ Inst, Key Lab Water Cycle & Water Secur Southern China, Guangzhou 510275, Guangdong, Peoples R China
[3] Univ Illinois, Prairie Res Inst, Champaign, IL 61820 USA
[4] Pearl River Hydraul Res Inst, Guangzhou 510611, Guangdong, Peoples R China
基金
中国国家自然科学基金;
关键词
Pearl River Basin; Extreme precipitation threshold; Non-parametric method; Parametric method; Detrended fluctuation analysis method; FLUCTUATION ANALYSIS; RAINFALL; RUNOFF;
D O I
10.1016/j.jhydrol.2013.09.002
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
Extreme precipitation events are rare and occur mostly on a relatively small and local scale, which makes it difficult to set the thresholds for extreme precipitations in a large basin. Based on the long term daily precipitation data from 62 observation stations in the Pearl River Basin, this study has assessed the applicability of the non-parametric, parametric, and the detrended fluctuation analysis (DFA) methods in determining extreme precipitation threshold (EPT) and the certainty to EPTs from each method. Analyses from this study show the non-parametric absolute critical value method is easy to use, but unable to reflect the difference of spatial rainfall distribution. The non-parametric percentile method can account for the spatial distribution feature of precipitation, but the problem with this method is that the threshold value is sensitive to the size of rainfall data series and is subjected to the selection of a percentile thus make it difficult to determine reasonable threshold values for a large basin. The parametric method can provide the most apt description of extreme precipitations by fitting extreme precipitation distributions with probability distribution functions; however, selections of probability distribution functions, the goodness-of-fit tests, and the size of the rainfall data series can greatly affect the fitting accuracy. In contrast to the non-parametric and the parametric methods which are unable to provide information for EPTs with certainty, the DFA method although involving complicated computational processes has proven to be the most appropriate method that is able to provide a unique set of EPTs for a large basin with uneven spatio-temporal precipitation distribution. The consistency between the spatial distribution of DFA-based thresholds with the annual average precipitation, the coefficient of variation (CV), and the coefficient of skewness (CS) for the daily precipitation further proves that EPTs determined by the DFA method are more reasonable and applicable for the Pearl River Basin. (C) 2013 Elsevier B.V. All rights reserved.
引用
收藏
页码:233 / 245
页数:13
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