Gumbel–Hougaard Copula for Trivariate Rainfall Frequency Analysis

By Lei Zhang, Vijay P. Singh. 2007

173 citations recorded by the source corpus.

Subfields: Global and Planetary Change, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/c7953059f93e7c4c6823c91f80fcd31b154d68e4

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In Global and Planetary Change

In Statistics and Probability

Citations in the corpus

A comparative copula‐based bivariate frequency analysis of observed and simulated storm events: A case study on Bartlett‐Lewis modeled rainfall (2011, background): “Pioneering work in copula‐based bivariate frequency analysis are the studies of De Michele and Salvadori [2003] and Favre et al. [2004], followed by several other contributions [e.g., De Michele et al., 2005; Genest and Favre, 2007; Kao and Govindaraju, 2007; Zhang and Singh, 2007a].”
Multivariate multiparameter extreme value models and return periods: A copula approach (2010, background): “In fact, the Gumbel copula G represents a sort of “standard” MEV model in hydrology [see, e.g., Yue, 2000a, 2000b; Zhang and Singh, 2007 and references therein]; in particular, it is the only Archimedean copula that is also MEV [Genest and Rivest, 1989].”
Hydrological uncertainty processor based on a copula function (2018, methodology): “So the conditional cdf Fnðsnjh0; hnÞ and pdf fnðsnjh0; hnÞ are rewritten as (Zhang and Singh 2007c): Fnðsnjh0; hnÞ ¼ PðU3 u3jU1 ¼ u1;U2 ¼ u2Þ ¼ @ 2Cðu1; u2; u3Þ=@u1@u2 cðu1; u2Þ (9) fnðsnjh0;hnÞ ¼ 1cðu1;u2Þ @3Cðu1;u2;u3Þ @u1@u2@u3 du3 dsn ¼ cðu1;u2;u3Þ cðu1;u2Þ fSnðsnÞ (10) where cðu1; u2; u3Þ ¼…”
Drought Analysis Using Copulas (2013, methodology): “For example, they have been used for rainfall frequency analysis (De Michele and Salvadori 2003; Grimaldi and Serinaldi 2006; Kao and Govindaraju 2007; Zhang and Singh 2007; Kuhn et al. 2007), flood frequency analysis (Favre et al.”
Bivariate Flood Frequency Analysis with Historical Information Based on Copula (2013, methodology): “…(a) flexibility in choosing arbitrary marginals and structure of dependence, (b) extension to more than two variables, and (c) separate analysis of marginal distribution and dependence structure (Salvadori and De Michele 2007; Genest and Favre 2007; Zhang and Singh 2007a; Serinaldi et al. 2009).”
A continuous rainfall model based on vine copulas (2015, unknown): “Some applications can be found in the modelling of trivariate rainfall (Zhang and Singh, 2007; Kao and Govindaraju, 2008; Salvadori and De Michele, 2006; Grimaldi and Serinaldi, 2006), trivariate ﬂoods (Serinaldi et al. (2010).”
Fitting bivariate copulas to the dependence structure between storm characteristics: A detailed analysis based on 105 year 10 min rainfall (2010, background): “The work of Salvadori [2004], Salvadori and De Michele [2004], and Salvadori et al. [2007] (and references therein) provides a nice theoretical framework for copula-based frequency analysis of storms, floods, droughts, etc., and several of these concepts have been applied in studies of De Michele et”
Multivariate return periods in hydrology: a critical and practical review focusing on synthetic design hydrograph estimation (2012, background): “However, limited applications have been developed with more than two variables (Vandenberghe et al., 2010; Pinya et al., 2009; Kao and Govindaraju, 2008, 2007; Genest et al., 2007; Serinaldi and Grimaldi, 2007; Zhang and Singh, 2007; Grimaldi and Serinaldi, 2006a,b).”
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”
Bivariate drought frequency analysis using the copula method (2012, methodology): “…and Serinaldi 2006a; Kao and Govindaraju 2007), for rainfall frequency analysis (De Michele and Salvadori 2003; Grimaldi and Serinaldi 2006b; Zhang and Singh 2007; Singh and Zhang 2007), for estimating groundwater parameters (Bardossy 2006), geostatistical interpolation (Bardossy and Li…”