Rainwater Harvesting in Social Housing: An Analysis Across Twelve Cities in Brazil

Rainwater harvesting (RWH) has emerged as a promising technique to improve water security amid the escalating effects of climate change. However, a comprehensive evaluation of various rainwater harvesting solutions is needed to promote sustainable practices in the building sector. This study aims to evaluate the water saving potential in multi- and single-family social housing buildings in twelve cities in Brazil. Computer simulations were performed for 60 scenarios, comprising five social housing reference models and using rainfall data from twelve representative cities of Brazil’s bioclimatic zones. The results show that single-family houses presented a higher potential for potable water savings (20 to 22%) than multi-family housing models (2 to 3%), mainly due to their higher roof-area-to-resident ratio. Single-family buildings exhibit more significant variability in absolute savings (standard deviation), while multi-family buildings are more sensitive to variability relative to their means (higher CVs). Furthermore, due to uneven rainfall distribution and storage limitations, water savings potential does not correlate linearly with total annual rainfall. Normalised results reveal that buildings with a lower population density achieve higher water savings per area and inhabitant. This study demonstrated that building and climate characteristics influence rainwater harvesting, offering valuable insights for promoting sustainable water management practices in social housing.

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Publication Details

Published
2025-02-07
DOI
https://doi.org/10.3390/eesp2025032004
Citations
1
Primary Topic
Urban Stormwater Management Solutions
Type
article
Field-Weighted Citation Impact
0.80

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article

Rainwater Harvesting in Social Housing: An Analysis Across Twelve Cities in Brazil

Igor Catão Martins Vaz, Enedir Ghisi, Morgana Duarte da Silva
1 citations
Urban Stormwater Management Solutions
0.80
article

Rainwater Harvesting in Social Housing: An Analysis Across Twelve Cities in Brazil

Igor Catão Martins Vaz, Enedir Ghisi, Morgana Duarte da Silva
article en
1 citations

Abstract

Rainwater harvesting (RWH) has emerged as a promising technique to improve water security amid the escalating effects of climate change. However, a comprehensive evaluation of various rainwater harvesting solutions is needed to promote sustainable practices in the building sector. This study aims to evaluate the water saving potential in multi- and single-family social housing buildings in twelve cities in Brazil. Computer simulations were performed for 60 scenarios, comprising five social housing reference models and using rainfall data from twelve representative cities of Brazil’s bioclimatic zones. The results show that single-family houses presented a higher potential for potable water savings (20 to 22%) than multi-family housing models (2 to 3%), mainly due to their higher roof-area-to-resident ratio. Single-family buildings exhibit more significant variability in absolute savings (standard deviation), while multi-family buildings are more sensitive to variability relative to their means (higher CVs). Furthermore, due to uneven rainfall distribution and storage limitations, water savings potential does not correlate linearly with total annual rainfall. Normalised results reveal that buildings with a lower population density achieve higher water savings per area and inhabitant. This study demonstrated that building and climate characteristics influence rainwater harvesting, offering valuable insights for promoting sustainable water management practices in social housing.

Universidade Federal de Santa Catarina (BR)
Coordenação de Aperfeiçoamento de Pessoal de Nível Superior, Ministério da Ciência, Tecnologia e Inovação, Conselho Nacional de Desenvolvimento Científico e Tecnológico
Sustainable cities and communities
Openalex Percentile: Top 33%
Urban Stormwater Management Solutions
0.80
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Rainwater Harvesting in Social Housing: An Analysis Across Twelve Cities in Brazil — Igor Catão Martins Vaz, Enedir Ghisi, et al. · (2025) | TGRS Research Map | TGRS