Stochastic model applied to water demand management in Brazil

Author:

Silva Santos Vanessa1ORCID,Gadea Anderson2,Cohim Eduardo2

Affiliation:

1. a Department of Environmental Engineering, Federal University of Bahia, Professor Aristídes Novis Street, Federação, Salvador, BA 40210-630, Brazil

2. b Department of Technology, State University of Feira de Santana, Transnordestina Avenue, Feira de Santana, BA 44036-900, Brazil

Abstract

Abstract The increasing scarcity of water sources near urban areas, coupled with urbanization and population growth, necessitates the development of solutions that optimize water demand management, which entails a more accurate estimation of consumption patterns and implementing measures that promote the rational use of water. A stochastic residential water demand model was built based on the superposition of pulses of constant intensity and variable arrival time and duration applied to the microcomponent consumption at a 1-minute resolution, reflecting the aggregate system contributions to the total instantaneous demand. The model can support the planning of water supply systems (WSSs) and was calibrated using data from Brazilian institutes combined with a literature review of statistical data on users and end uses of water in Brazilian dwellings. Innovatively, it proposes using water demand forecasting to apply demand management measures evaluating the replacement of conventional devices for water-saving ones by analyzing hydrographs of 50–50,000 households, in addition to detailing the influence of the K2 peak factor. The results demonstrated a new water consumption profile with about a 40% reduction in water demand. A new equation for K2 is proposed as an alternative to estimate the demand for small populations fittingly.

Publisher

IWA Publishing

Reference38 articles.

1. A review of household water demand management and consumption measurement

2. Perfil do consumo residencial e usos finais da água;Barreto;Ambiente Construído,2008

3. Simulating Residential Water Demand with a Stochastic End-Use Model

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