Nilo Nascimento, Erick Chaib, Felipe Rodrigues, Brenner Maia
Wednesday 1 july 2015
9:45 - 10:00h at Europe 1 & 2 (level 0)
Themes: (ST) Computational methods, (T) Water engineering
Parallel session: 8E. Engineering - Computational
In a scenario of relative water scarcity, it is advisable to implement public policies aiming at maintaining adequate potable water supply. A relevant alternative regarding water supply policies is the use of rainwater harvesting in residential buildings in order to meet the households non-potable water demands. This paper suggests a methodology to evaluate the potential for drinking water savings in urban large-scales using rainwater for non-potable domestic supply. Hydraulic and financial assessments were performed, taking as case study Belo Horizonte, a 2.4 million-inhabitant city that is the capital of the state of Minas Gerais, in Brazil. In order to deal with the variability of dwelling characteristics (e.g.: roof area, garden and paved areas, toilets, etc.) in the urban area, 16 standard building projects were created, based on Brazilian technical standards, and correlated to the actual dwelling characteristics as described in the Belo Horizonte municipal cadaster. In parallel, a water demand function for Belo Horizonte in relation to family income was also developed, based on census data and a 14-year water consumption time series. This function allowed estimating non-potable water consumption demand as a function of family income and dwelling characteristics. Roof area and a 28-year rainfall time series allowed estimating the offer of non-potable water through rainfall harvesting for the study area. Results suggest that, in a scenario of widespread use of domestic rainwater harvesting systems, one can get the equivalent of two months of drinking water supply as drinking water annual savings. On the other hand, for the scenario adopted, results suggest financial feasibility of the systems, although with a high payback and internal return rates very close to the attractive interest rates. These results suggest that these systems dissemination may require innovative funding models and other economic tools to promote them for large-scale use.