Derivation of low flow distribution functions using copulas

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Application of copulas for regional bivariate frequency analysis of meteorological droughts in Turkey (2016, methodology): “…Archimedean copulas are applied to develop bivariate probability distributions as they are more convenient and easy to construct and have been comprehensively used in hydrologic applications (Zhang and Singh 2007a, b; Singh and Zhang 2007; Zhang et al. 2012a, b; Zhao et al. 2012; Yu et al. 2014).”
Use of a nonstationary copula to predict future bivariate low flow frequency in the Connecticut river basin (2016, background): “Low flow is also important for basin restoration, water supply, and hydro-electricity production (Yu 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;…”
Maximum entropy-Gumbel-Hougaard copula method for simulation of monthly streamflow in Xiangxi river, China (2015, background): “Yu et al. (2014) proposed a copula-based distribution of low flows.”