Multisite ARMA(1,1) and Disaggregation Models for Annual Streamflow Generation

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Abstract
Disaggregation and multisite autoregressive moving average (ARMA)(1,1) time‐series models provide simple and efficient frameworks for generation of multisite synthetic streamflow sequences that exhibit long‐term persistence. This paper considers multisite ARMA(1,1) models whose Φ and Θ matrices are diagonal; a Monte Carlo study examined the efficiency of three procedures for estimating individual Φ‐θ values for each site and two estimators of the covariance matrix of the innovations. Also included in the study was a univariate ARMA(1,1) model of the aggregate flows with a simple disaggregation algorithm to generate flows at the individual sites. In the realm of most hydrologic interest, simple diagonal multisite ARMAl(1,1) models performed adequately and it is not necessary to fit the more cumbersome nondiagonal models. The disaggregation procedure coupled with an ARMA(1,1) aggregate flow model did as well as the multivariate diagonal ARMA(1,1) models.