Disaggregation Procedures for Generating Serially Correlated Flow Vectors

The slruclure of disaggregation models places severe constraints on the feasible values of the lagged covanance 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 ofmultisite multiseason models. INTRoDucnoN above, this problem was addressed by Mejia and Rouss le Since their introduction by Valencia and Schaake [1972, [1976]. However, as demonstrated in the first section of is 1973], disaggregation models have been recognized as a rea- paper and by Lane [1980, 1982]. their model fails to perf sonable way to divide annual flows into seasonal flows [Mejia as anticipated. Examination of the causes of that failure re and Rousselle. 1976; Tao and Delleur, 1976; Srikanthan, 1978; the constraints imposed by the disaggregation framework