Five variants of a procedure for spatial aggregation of synthetic water demand time series

Abstract

A comparison of five variants of a procedure for spatial aggregation of synthetic water demand time series is presented. This procedure allows for the spatial aggregation of hourly synthetic water demand time series preserving mean and variance at user level in such a way that the statistics of the spatially aggregated time series are reproduced (mean, variance, lag-1 temporal correlation, lag-1 temporal covariance). Five different ways of application of the methodology are considered and compared. Application to a case study consisting of the water demands of 21 users highlights that the variants considered show different levels of effectiveness in reproducing the statistics of interest and different computational burden, but overall represent a valid tool for the bottom-up generation of synthetic water demand time series.