Residential water consumption has been analysed by monitoring a Water Distribution System (WDS) in a small town, Piedimonte San Germano, in southern Italy of about 1200 inhabitants. The design of a WDS is usually undertaken with reference to the maximum water required by customers - one of the most onerous operating conditions to which an hydraulic network is exposed. Considering this, the aim of this work has been to contribute to the characterisation of the peak water demand through statistical inferences on a large data sample collected from the system under consideration. Specifically, the data have been analysed for the effect of resampling the raw data with respect to time interval on the estimate of peak demand factor. Formulæ to estimate the maximum flow demand for small town, in relation to the number of users, are thus suggested. In addition, statistical inferences have shown that the stochastic, maximum flow demand is described by the log-normal and Gumbel models. With reference to small residential areas, the parameters of such statistical distributions have been estimated. These have shown that the coefficient of variation (CV) of the peak water demand is a function of the number of users. Although these results are only directly applicable to the specific context from which they have been obtained, the comparison with the sparse data available in the technical literature lead to the belief that the proposed relationships could be extended to other small residential areas.
Peak Water Demand for Small Towns
TRICARICO, Carla;DE MARINIS, Giovanni;GARGANO, Rudy;LEOPARDI, Angelo
2005-01-01
Abstract
Residential water consumption has been analysed by monitoring a Water Distribution System (WDS) in a small town, Piedimonte San Germano, in southern Italy of about 1200 inhabitants. The design of a WDS is usually undertaken with reference to the maximum water required by customers - one of the most onerous operating conditions to which an hydraulic network is exposed. Considering this, the aim of this work has been to contribute to the characterisation of the peak water demand through statistical inferences on a large data sample collected from the system under consideration. Specifically, the data have been analysed for the effect of resampling the raw data with respect to time interval on the estimate of peak demand factor. Formulæ to estimate the maximum flow demand for small town, in relation to the number of users, are thus suggested. In addition, statistical inferences have shown that the stochastic, maximum flow demand is described by the log-normal and Gumbel models. With reference to small residential areas, the parameters of such statistical distributions have been estimated. These have shown that the coefficient of variation (CV) of the peak water demand is a function of the number of users. Although these results are only directly applicable to the specific context from which they have been obtained, the comparison with the sparse data available in the technical literature lead to the belief that the proposed relationships could be extended to other small residential areas.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.