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Impact of dependence in river flow data on flood frequency analysis based on regression in quantile plots: Analysis and solutions
Author(s) -
Boniphace E. R.,
Willems P.
Publication year - 2011
Publication title -
water resources research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.863
H-Index - 217
eISSN - 1944-7973
pISSN - 0043-1397
DOI - 10.1029/2010wr010160
Subject(s) - quantile , extreme value theory , plot (graphics) , estimator , quantile regression , statistics , generalized extreme value distribution , flood myth , mathematics , frequency analysis , regression analysis , flow (mathematics) , geography , geometry , archaeology
Quantile‐quantile plots (QQ plots) are often applied to investigate tail behavior in extreme value analysis. When used for flood frequency analysis, based on river flow data, dependence in these data affects the extreme value distribution's tail behavior in the QQ plot. This problem is investigated on the basis of both synthetic and observed river flow series. The synthetic series are generated on the basis of a stochastic simulation procedure, which allows the real statistical flow properties to be known. Through simulation study, we demonstrate that serial dependence causes bending behavior in the QQ plot in the region of higher quantiles. This leads to the estimating error when the slope of the QQ plot is used as an estimator in the extreme value analysis. A correction method is proposed by modifying the plotting position using the extremal index.