Comparison of parametric and non-parametric disaggregation models for the top-down generation of water demand time series

This study presents a “top-down” procedure for generating synthetic time series of hourly nodal water demands based on the application of disaggregation models already presented in the literature in the field of hydrology. More specifically, a parametric and a nonparametric disaggregation model are compared to assess their performance in reproducing, on a nodal level, the main statistics of the time series of historically observed water demands. Moreover, with regard to the nonparametric model, two variants of the original formulation are proposed. The proposed procedures were evaluated with reference to a case study based on a time series of the water demands of 21 users of the water distribution system of the town of Milford (Ohio). The results obtained showed that both the parametric and nonparametric models enable water demand time series to be generated which are statistically similar to the time series of observed values, representing a valid tool for generating synthetic series of nodal water demands from a spatially aggregate time series using a top-down approach.