Bivariate Flood Frequency Analysis Using the Copula Method

By Lianjun Zhang, Vijay P. Singh. 2006

493 citations recorded by the source corpus.

Subfields: Environmental Engineering, Global and Planetary Change

View Paper: https://www.semanticscholar.org/paper/35ccd11c131e306d0e07747c0ac648e78523814a

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In Environmental Engineering

In Global and Planetary Change

Citations in the corpus

A bivariate frequency analysis of extreme rainfall with implications for design (2007, methodology): “Not surprisingly, the Frank family has been a popular choice for constructing dependence structure [De Michele and Salvadori, 2003; Favre et al., 2004; Grimaldi and Serinaldi, 2006b; Salvadori and De Michele, 2006; Zhang and Singh, 2006, 2007 ].”
Meta-elliptical copulas for drought frequency analysis of periodic hydrologic data (2010, background): “... analyses (De Michele and Salvadori 2003; Shiau 2003; Favre et al. 2004; Salvadori and De Michele 2004, 2006, 2007; De Michele et al. 2005 ;B ardossy 2006 ;B a´rdossy and Li 2008; Grimaldi and Serinaldi 2006a, b; Dupuis 2007; Gebremichael and Krajewski 2007; Genest and Favre 2007; Genest et al. 2”
Metaelliptical copulas and their use in frequency analysis of multivariate hydrological data (2007, unknown): “[49] As shown by Genest et al. [1995] and Shih and Louis [1995], the value of q that maximizes the rank-based pseudo likelihood is asymptotically normal under weak regularity conditions.”
Measure of Correlation between River Flows Using the Copula-Entropy Method (2013, methodology): “2007), flood frequency analysis (Favre et al. 2004; Shiau et al. 2006; Zhang and Singh 2006; Renard and Lang 2007; Chen et al. 2010), drought frequency analysis (Shiau 2006; Kao and Govindaraju 2010; Song and Singh 2010; Chen et al.”
Hydrological uncertainty processor based on a copula function (2018, methodology): “Using the copula function, the conditional cdf Gnðhnjh0Þ and pdf gnðhnjh0Þ can be rewritten as (Zhang and Singh 2006): Gnðhn h0Þ ¼ PðU2 u2j jU1 ¼ u1Þ ¼ @Cðu1; u2Þ @u1 (5) gnðhnjh0Þ ¼ @ 2Cðu1;u2Þ @u1@u2 du2 dhn ¼ cðu1;u2Þ fHðhnÞ (6) where cðu1; u2Þ is the density function of Cðu1; u2Þ, and cðu1; u2Þ…”
Identification of suitable copulas for bivariate frequency analysis of flood peak and flood volume data (2011, background): “…of the Clayton copula as a suitable model for this flood peak flow and volume data is at odds with the results reported by De Michele et al. (2005), Zhang & Singh (2006), and Genest & Favre (2007), Poulin et al. (2007) and Karmakar & Simonovic (2009), wherein GH copula had been adjudged better…”
Multivariate drought characteristics using trivariate Gaussian and Student t copulas (2013, background): “…the multivariate Kendall’s return period (KRP) corresponding to the standard definition of multivariate return period (for a thorough review, see Zhang and Singh, 2006, 2007a, 2007b, 2007c, and references therein) is defined as Tp ¼ #1 p ¼ # 1 KC tð Þ ¼ # 1 P u 2 Id : C uð Þ≤t (11) where u ¼…”
Bivariate flood frequency analysis: Part 1. Determination of marginals by parametric and nonparametric techniques (2008, background): “, 1999; Yue, 2001) but with many restrictive assumptions (Zhang and Singh, 2006).”
Frequency analysis of droughts using the Plackett copula and parameter estimation by genetic algorithm (2010, background): “For given marginal distributions, copulas can separate the effects of dependence from the effects of marginal distributions, and construction of multivariate distributions only needs to consider the relationship among the corresponding correlated random variables (De Michele and Salvadori 2003; Favr”
Trivariate statistical analysis of extreme rainfall events via the Plackett family of copulas (2008, methodology): “For other applications in hydrology, Favre et al. [2004], De Michele et al. [2005], Grimaldi and Serinaldi [2006a], Zhang and Singh [2006] , and Renard and Lang [2007] applied copulas in multivariate flood frequency analysis.”
Bivariate flood frequency analysis. Part 2: a copula‐based approach with mixed marginal distributions (2009, methodology): “Zhang and Singh (2006) exploit Archimedean copulas to construct bivariate joint distributions of peak flow and volume, and volume and duration.”
Drought characterization: a probabilistic approach (2009, methodology): “Bivariate distributions have also been applied to frequency analysis of flood characteristics, such as flood peak, volume, and duration (Yue 1999; Zhang and Singh 2006 ).”
Bivariate flood frequency analysis using the copula function: a case study of the Litija station on the Sava River (2015, background): “…(Grimaldi and Serinaldi, 2006b), flood coincidence risk analysis (Chen et al., 2012), geostatistical models (Bardossy, 2006) and, indeed, flood frequency analysis (Grimaldi and Serinaldi, 2006a; Zhang and Singh, 2006; Renard and Lang, 2007; Zhang and Singh, 2007b; Karmakar and Simonovic, 2009).”