Application of copulas for derivation of drought severity–duration–frequency curves

By M. Janga Reddy, Poulomi Ganguli. 2012

155 citations recorded by the source corpus.

Subfields: Ecology, Evolution, Behavior and Systematics, Global and Planetary Change

View Paper: https://www.semanticscholar.org/paper/4b4db13b68ea684248b18c6cec5e06cb6e8a48a4

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Ecology, Evolution, Behavior and Systematics

1. F. Tosunoğlu
2. Vijay P. Singh
3. İ. Can
4. M. Janga Reddy
5. R. Palmer
6. U. F. ABDUL RAUF
7. Panlop Zeephongsekul
8. Kuk‐Hyun Ahn

In Global and Planetary Change

1. F. Tosunoğlu
2. Shenglian Guo
3. M. Janga Reddy
4. İ. Can
5. Vijay P. Singh
6. Chong-yu Xu
7. R. Palmer
8. Kuk‐Hyun Ahn

Citations in the corpus

• Bivariate frequency analysis of nonstationary low‐flow series based on the time‐varying copula (2015, methodology): “, 2007) has been widely applied (De Michele and Salvadori, 2003; Favre et al., 2004; Salvadori and De Michele, 2004a; Grimaldi and Serinaldi, 2006; Zhang and Singh, 2006; Zhang and Singh, 2007; Evin and Favre, 2008; Kao and Govindaraju, 2008; Bárdossy and Pegram, 2009; Serinaldi et al., 2009; Wang e”
• Multivariate drought characteristics using trivariate Gaussian and Student t copulas (2013, methodology): “Parameters of Gaussian and Student t copulas are computed using the maximum pseudo-likelihood estimation method (Nadarajah and Kotz, 2005; Nadarajah, 2006; Shiau, 2006; Shiau et al., 2007; Song and Singh, 2010a; Lee and Salas, 2011; Reddy and Ganguli, 2011).”
• Use of a nonstationary copula to predict future bivariate low flow frequency in the Connecticut river basin (2016, methodology): “These indices have been widely used in copula modelling (Genest et al., 2009; Janga Reddy and Ganguli, 2012; Maity et al., 2013; Fu and Butler, 2014b).”
• Copula based analysis of rainfall severity and duration: a case study (2013, methodology): “For each station, the best fitted distribution for each rainfall characteristic is subsequently selected using the Kolmogorov–Smirnov distance criterion d–max (Reddy and Ganguli 2012) and p-values and these are displayed in Table 4.”
• Multivariate modeling of droughts using copulas and meta-heuristic methods (2014, methodology): “This study adopted the elitist-mutated PSO method (Nagesh Kumar and Janga Reddy 2007) for estimating parameters of copula models and solving the nonlinear function of return periods for deriving SDF curves.”
• Application of copulas for regional bivariate frequency analysis of meteorological droughts in Turkey (2016, methodology): “For example, the Ali–Mikhail–Haq copula is only useful for modeling variables in which the correlation coefficient falls between -0.1817, 0.3333 (Reddy and Ganguli 2012).”
• Spatio-temporal analysis and derivation of copula-based intensity–area–frequency curves for droughts in western Rajasthan (India) (2013, methodology): “Janga Reddy and Ganguli (2012) applied four different classes of bivariate copulas—Archimedean, extreme value, Plackett, and elliptical families for modelling joint distribution of drought characteristics, and noted that extreme value class Gumbel–Hougaard copula family performed better as compared ”