Intensity-Duration-Frequency Curves for Dependent Datasets

被引:3
作者
El Hannoun, Wafaa [1 ]
Makhoukhi, Anas Boukili [2 ]
Zoglat, Abdelhak [1 ]
El Adlouni, Salah-Eddine [2 ]
机构
[1] Mohammed V Univ Rabat, Fac Sci, Lab Math Stat & Applicat, Rabat 1014, Morocco
[2] Univ Moncton, Dept Math & Stat, Moncton, NB E1A 3E9, Canada
基金
加拿大自然科学与工程研究理事会;
关键词
conditional quantile estimation; eastern Canada; extreme precipitation; IDF curves; Moncton area; multivariate models; vine copulas; IDF-CURVES; RAINFALL DEPTH; ANNUAL MAXIMUM; COPULA; PRECIPITATION; MODEL; AFRICA; EVENTS;
D O I
10.3390/w15142641
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Intensity-duration-frequency (IDF) curves of precipitation are a reference decision support tool used in hydrology. They allow the estimation of extreme precipitation and its return periods. Typically, IDF curves are estimated using univariate frequency analysis of the maximum annual intensities of precipitation for different durations. It is then assumed that the annual maxima of different durations are independent to simplify the parameter estimation. This strong hypothesis is not always verified for every climatic region. This study examines the effects of the independence hypothesis by proposing a multivariate model that considers the dependencies between precipitation intensities of different durations. The multivariate model uses D-vine copulas to explore the intraduration dependencies. The generalized extreme values distribution (GEV) is considered a marginal model that fits a wide range of tail behaviors. An illustration of the proposed approach is made for historical data from Moncton, in the province of New Brunswick (Eastern Canada), with climatic projections made through three scenarios of the Representative Concentration Pathway (RCP).
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页数:17
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