Frequency analysis of low-flow has specific application in planning of water supply systems and determination of minimum available flow. As low-flows are characterized by several non-independent futures, univariate frequency analysis is usually not appropriat. Copulas have high capability in analysis of extreme events and modeling of dependence structures. In this study, using copula functions from Archimedean and meta-Elliptical families, the optimal procedure in copula application were presented. In addition, it was tried to decrease the difficulty of calculating return periods and design quantiles in a multivariate framework. Some case studies involving low-flow events in 5 selected hydrometry stations from Caspian Sea watershed were used to illustrate the new concepts outlined in this work. The results indicated the performance of meta-Elliptical copulas for representation of dependence structures of low-flow variables. In the second part of the study, using wood volume V , diameter D , and total height H data collected from 1,386 beech trees in Italy, copula regression were compared with four benchmark regression models for computing V given the values of D and H . The copula-based model with parametric marginals is definitely outperformed by its competitors, whereas the copula-based model with nonparametric marginals provides quite accurate point estimates but biased interval estimates of V . Keywords: Copula, Multivariate frequency analysis, Low-flow, Hydrological drought, Copula-based regression, Dependence
