Estimation of the distribution of annual runoff from climatic variables using copulas

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A continuous rainfall model based on vine copulas (2015, unknown): “The use of vine copulas is becoming popular in ﬁnance (see e.g. Nikololoupoulos et al. (2012); Zhang (2014); Mendes and Accioly (2014)) and geophysics and hydrology (see e.g. Gräler (2014); Xiong et al. (2014); Gyasi-Agyei and Melch-ing (2012); Gräler et al. (2013)).”
A framework of change‐point detection for multivariate hydrological series (2015, background): “…and De Michele, 2004; Favre et al., 2004; Grimaldi and Serinaldi, 2006; Serinaldi and Grimaldi, 2007; Zhang and Singh, 2007; Genest and Favre, 2007; Salvadori et al., 2007; Kao and Govindaraju, 2008; Salvadori and De Michele, 2010; Mediero et al., 2010; Volpi and Fiori, 2012; Xiong et al., 2014].”
Hydrological uncertainty processor based on a copula function (2018, methodology): “Since the denominator ð1 0 cðu1; u2; u3Þdu2 cannot be obtained directly by an analytic method, the Monte Carlo sampling technique (Xiong et al. 2014, Yu et al. 2014) is applied by the following steps: a. Generate M random numbers u2 from uniform distribution U(0, 1); b. Compute the value of cðu1;…”
Probabilistic modeling of flood characterizations with parametric and minimum information pair-copula model (2016, methodology): “In a similar study, Xiong et al. (2014) have developed an annual rainfall-runoff model using the canonical vine copula derivation approach and employed in 40 watersheds in two large basins in China.”