Caracterização do consumo residencial de água na área urbana de Viçosa-MG

• Autor(a) principal: Pimenta, João Francisco de Paula
• Data de Publicação: 2011
• Tipo de documento: Dissertação
• Idioma: por
• Título da fonte: LOCUS Repositório Institucional da UFV
• Texto Completo: http://locus.ufv.br/handle/123456789/3815
• topic: Agua; Consumo residencial; Variação temporal; Fatores intervenientes; Water; Residential consumption; Temporal variation; Intervening factors; CNPQ::ENGENHARIAS::ENGENHARIA CIVIL

The main objectives of this work were to investigate the temporal evolution and the spatial distribution of the effective residential water consumption, total and per capita, in Viçosa - MG, and to identify factors that influence these variables. The following secondary data from different sources (Viçosa Municipality, Viçosa water utility, the Brazilian Institute of Geography and Statistics IBGE, and CENSUS - an NGO based in Viçosa ), covering different periods of time from 1996 to 2010,were used: measured residential water consumption, number of residential water connections, and climate, demographic, socioeconomic and residential typology data. These data, as well as the water consumption evaluation, were analysed both on a global basis (i.e. for the urban area of Viçosa as a whole) and grouped into 10 " urban planning regions" (as defined in the CENSUS studies). Considerable differences in per capita water consumption between different urban regions were detected, which were related to socio-spatial segregation revealed by socioeconomic factors in the different regions, such as income and residential typology. The per capita water consumption showed no marked changes over the years, but the total water consumption (global and in the different urban areas) increased, being influenced by population growth. While demographic factors influenced more clearly the total water consumption, the per capita consumption was determined mostly by socioeconomic factors. Variables such as the number of water connections and the building s area demonstrated potential for being used in predictive models of water consumption.