Quantifying multidimensional drought propagation risks under climate change: A vine-copula Bayesian factorial analysis method

Quantitative assessment of multidimensional drought propagation risks under climate change is essential to systematically identify and predict multiple influences of various droughts on natural environment and human society. In this study, a vine-copula Bayesian factorial analysis (abbreviated as VCBFA) method is developed through incorporating vine copula, Bayesian model averaging (BMA), and factorial analysis (FA) within a general framework. …