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Barcelona, Spain

Fontdecaba S.,Polytechnic University of Catalonia | Sanchez-Espigares J.A.,Polytechnic University of Catalonia | Marco-Almagro L.,Polytechnic University of Catalonia | Tort-Martorell X.,Polytechnic University of Catalonia | And 2 more authors.
Water Resources Management | Year: 2013

The aim of this project is to assign domestic water consumption to different devices based on the information provided by the water meter. We monitored a sample of Barcelona and Murcia with flow switches that recorded when a particular device was in use. In addition, the water meter readings were recorded every 5 and 1 s, respectively, in Barcelona and Murcia. The initial work used Barcelona data, and the method was later verified and adjusted with the Murcia data. The proposed method employs an algorithm that characterizes the water consumption of each device, using Barcelona to establish the initial parameters which, afterwards, provide information for adjusting the parameters of each household studied. Once the parameters have been adjusted, the algorithm assigns the consumption to each device. The efficacy of the assignation process is summarized in terms of: sensitivity and specificity. The algorithm provides a correct identification rate of between 70 % and 80 %; sometimes even higher, depending on how well the chosen parameters reflect household consumption patterns. Considering the high variability of the patterns and the fact that use is characterized by only the aggregate consumption that the water meter provides, the results are quite satisfactory. © 2013 Springer Science+Business Media Dordrecht.

Fontdecaba S.,Polytechnic University of Catalonia | Grima P.,Polytechnic University of Catalonia | Marco L.,Polytechnic University of Catalonia | Rodero L.,Polytechnic University of Catalonia | And 6 more authors.
Water Resources Management | Year: 2012

Water management has become a vital concern for both water supply companies and public administrations due to the importance of water for life and current scarcity in many areas. Studies exist that attempt to explain which factors influence water demand. In general, these studies are based on a small sample of consumers and they predict domestic water consumption using ordinary least squares regression models with a small number of socioeconomic variables as predictors, usually: price, population, population density, age, and nationality. We have followed a different approach in two ways; one, in the scope of the study: we have included in the study all consumers of the Barcelona area and as many socioeconomic variables as possible (all the available data from official statistics institutions); and also in the methodology: first, we have segmented clients into homogeneous socioeconomic groups that, as we show later in the Barcelona case, also have homogeneous water consumption habits. This allows for a better understanding of water consumption behaviours and also for better predictions through modeling water consumption in each segment. This is so because the segments' inner variability is smaller than the general one; thus, the models have a smaller residual variance and allow for more accurate forecasts of water consumption. The methodology was applied to the Barcelona metropolitan area, where it was possible to construct a database including both water consumption and socioeconomic information with more than one million observations. Data quality was a primary concern, and thus a careful exploratory data analysis procedure led to a careful treatment of missing observations and to the detection and correction or removal of anomalies. This has resulted in a stable division of the one million water consumers into 6 homogeneous groups and models for each of the groups. Although the methodology has been developed and applied to the Barcelona area, it is general and thus can be applied to any other region or metropolitan area. © 2011 Springer Science+Business Media B.V.

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