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Disaggregation Procedures for Generating Serially Correlated Flow Vectors
Author(s) -
Stedinger Jery R.,
Vogel Richard M.
Publication year - 1984
Publication title -
water resources research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.863
H-Index - 217
eISSN - 1944-7973
pISSN - 0043-1397
DOI - 10.1029/wr020i001p00047
Subject(s) - covariance , estimator , flow (mathematics) , covariance matrix , mathematics , lag , econometrics , mathematical optimization , computer science , statistics , geometry , computer network
The structure of disaggregation models places severe constraints on the feasible values of the lagged covariance of generated flow vectors. A new and simple class of disaggregation models is presented which employ the Valencia‐Schaake disaggregation model structure but allow the models' innovations to be serially correlated. These models can reproduce (1) the covariance matrix of the disaggregated flows, (2) their covariance with the upper level flows, and (3) reasonable approximations to the lag one covariance of the disaggregated flow vectors given the constraints imposed by a disaggregation approach. The Mejia‐Rousselle disaggregation model is shown, in general, to fail to reproduce the anticipated variances and covariances of the disaggregated flows because the model and its parameter estimators are not self‐consistent. The paper closes with a discussion of practical modeling considerations and of staged disaggregation procedures which reduce the size of multisite multiseason models.