Abstract
This paper proposes a stochastic procedure for generating seasonal flows at multiple locations simultaneously. The proposed procedure uses the technique of singular value decomposition (SVD) to transform a historical flow-data matrix into its standardized principal components (SPCs), and then applies the simple Kaiser’s cut-off rule to retain only the significant SPCs (SSPCs) for further fitting the multivariate autoregressive scheme of order one [MAR(1)] to them. It is shown that the Kaiser’s rule is proper for giving the size of the SSPCs of multisite seasonal-flow records because application of the rule yields only a few more SSPCs for each additional site, and its dimension is reasonably definitive. The comparison of the proposed SVD/MAR(1) procedure with the existing one has demonstrated that the proposed procedure has less parameters than the existing one due to taking into consideration the SSPCs only. In addition, the ability of the parsimonious procedure to reproduce adequately the historical key...
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