AN AGGREGATION DISAGGREGATION APPROACH FOR HYDROLOGIC TIME-SERIES MODELING

This paper describes the development and application of a new methodology to solve the failure of the disaggregation model. Based on the concept of aggregation, the parameters of the annual model are estimated from the parameters of the periodic model fitted to the seasonal series. Covariance estimates required in the parameter estimation procedure of the disaggregation model are calculated based on the derived annual model and the fitted periodic model. The covariance estimates are used in conjunction with the moment equations of the disaggregation model to produce the parameters for this model. The proposed methodology provides a linkage between the aggregation and disaggregation approaches for hydrologic time-series simulations. Using this methodology, the modelling in theory can preserve the additivity and many historical moments. The most significant advantage of this methodology over the existing remedies for the Mejia and Rousselle model is the preservation of over-year seasonal correlations.