A framework of change‐point detection for multivariate hydrological series

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Agricultural Drought Prediction Based on Conditional Distributions of Vine Copulas (2021, methodology): “, 2015, 2018; Zhang & Singh, 2019), change-point detection (Xiong et al., 2015), drought indicator construction (Feng et al.”
Multivariate hydrologic design methods under nonstationary conditions and application to engineering practice (2018, methodology): “The pair copula method has been proven powerful for the construction of the distribution of multivariate random variables through the decomposition of the multivariate probability density into a series of bivariate copulas (Aas et al., 2009; Xiong et al., 2015).”