A procedure for spatial aggregation of synthetic water demand time series is presented. Starting from synthetic water demand\udtime series generated at user level and reproducing mean and variance of the corresponding observed series, the procedure\udallows the aggregated series to preserve the statistics of interest observed at the aggregation level considered. The procedure\uduses a method proposed by Iman and Conover (1982): the synthetic user water demand time series are reordered to preserve the\udobserved spatial correlations of appropriate lag-time; then, the spatial aggregation of these series leads to a series representative\udof the user group reproducing the corresponding means and variances for the different hours of the generic day. Four different\udways of performing this aggregation have been investigated and compared. Application to a case study consisting of the water\uddemands of 21 users highlights that the approaches considered show different levels of effectiveness in reproducing the\udstatistics, but overall the procedure proposed is a valid tool for the bottom-up generation of synthetic water demand time series.
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