Abstract
The aim of this paper is to present a comprehensive approach for spatial and temporal demand profiling in water distribution systems. Multiple linear regression models for estimating network design parameters and decision trees for predicting daily demand patterns are presented. Proposed approach is a four-step procedure: data collection, data processing, data characterization, and spatial and temporal demand profiling. Continuous flow measurements and infrastructure and billing data were collected from a large set of water network areas and combined with census data. Main results indicate that family structures (i.e., families with elderly or adolescents), individuals’ mobility (i.e., people employed in the tertiary sector and university graduates) and public consumption (i.e., public spaces’ irrigation) are key-variables to profile water demand. Profiling models are of the utmost importance to describe water demand in areas with no monitoring but with similar socio-demographic characteristics to the ones analyzed, to improve network operation and to support network planning and design in new areas. Obtained models have been tested for new areas, showing good prediction performances.
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