A resampling method for generating synthetic hydrological time series with preservation of cross‐correlative structure and higher‐order properties

摘要: [1] Based on existing techniques in nonlinear physics that work the Fourier domain, we develop a multivariate, wavelet-based method for generation of synthetic discharge time series. This approach not only retains cross-correlative structure original data (which makes it preferable to principal component methods merely preserve correlations) but also replicates properties data. We argue temporal asymmetry typical hydrograph is most important form nonlinearity Using derivative skewness as measure and an example set 35 years daily from 107 gauging stations United States, compare two approaches records. generate then study fitting generalized extreme value distribution annual maxima total flux The series provides error bands fitted give different way assessing credible return periods. It found best studying extremes match each individually, rather than formulate global threshold criterion.