Use of Spatial Data in the Simulation of Domestic Water Demand in a Semiarid City: The Case of Campina Grande, Brazil

In the face of urban expansion, ensuring sustainable water consumption is paramount. This study aims to develop a domestic water demand forecast model that considers population heterogeneity and the urban area distribution in a city in the Brazilian Semiarid Region. The methodology comprises three m...

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Main Authors: Higor Costa de Brito, Iana Alexandra Alves Rufino, Mauro Normando Macedo Barros Filho, Ronaldo Amâncio Meneses
Format: Article
Language:English
Published: MDPI AG 2023-11-01
Series:Urban Science
Subjects:
Online Access:https://www.mdpi.com/2413-8851/7/4/120
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author Higor Costa de Brito
Iana Alexandra Alves Rufino
Mauro Normando Macedo Barros Filho
Ronaldo Amâncio Meneses
author_facet Higor Costa de Brito
Iana Alexandra Alves Rufino
Mauro Normando Macedo Barros Filho
Ronaldo Amâncio Meneses
author_sort Higor Costa de Brito
collection DOAJ
description In the face of urban expansion, ensuring sustainable water consumption is paramount. This study aims to develop a domestic water demand forecast model that considers population heterogeneity and the urban area distribution in a city in the Brazilian Semiarid Region. The methodology comprises three main steps: (1) spatial data collection to identify explanatory variables for a future Land Use and Cover (LULC) model; (2) simulation of LULC data for 2030, 2040, and 2050 using the MOLUSCE plugin; and (3) estimation of domestic water demand based on projected urban area expansion and a linear regression model incorporating demographic indicators of household income, residents per household, total population, and gender. The results demonstrated a consistent LULC simulation, indicating an urban expansion of 4 km<sup>2</sup> between 2030 and 2050, with reductions of 0.6 km<sup>2</sup> in natural formations and 3.4 km<sup>2</sup> in farming areas. Using LULC data, the study predicted a 14.21% increase in domestic water consumption in Campina Grande for 2050 compared to 2010, equivalent to an increase of 2,348,424.96 m<sup>3</sup>. Furthermore, the spatial analysis draws a spatial profile of water consumption among residents, highlighting the areas with the highest per capita consumption. Thus, this research offers a consistent approach to estimating water demand in regions with limited consumption data, providing valuable insights for decision-makers to consider in urban planning.
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spelling doaj.art-c027631cf857451c8b3718ffbb10aec02023-12-22T14:46:45ZengMDPI AGUrban Science2413-88512023-11-017412010.3390/urbansci7040120Use of Spatial Data in the Simulation of Domestic Water Demand in a Semiarid City: The Case of Campina Grande, BrazilHigor Costa de Brito0Iana Alexandra Alves Rufino1Mauro Normando Macedo Barros Filho2Ronaldo Amâncio Meneses3Center for Technology and Natural Resources, Federal University of Campina Grande, Campina Grande 58429900, BrazilCenter for Technology and Natural Resources, Federal University of Campina Grande, Campina Grande 58429900, BrazilCenter for Technology and Natural Resources, Federal University of Campina Grande, Campina Grande 58429900, BrazilCenter for Technology and Natural Resources, Federal University of Campina Grande, Campina Grande 58429900, BrazilIn the face of urban expansion, ensuring sustainable water consumption is paramount. This study aims to develop a domestic water demand forecast model that considers population heterogeneity and the urban area distribution in a city in the Brazilian Semiarid Region. The methodology comprises three main steps: (1) spatial data collection to identify explanatory variables for a future Land Use and Cover (LULC) model; (2) simulation of LULC data for 2030, 2040, and 2050 using the MOLUSCE plugin; and (3) estimation of domestic water demand based on projected urban area expansion and a linear regression model incorporating demographic indicators of household income, residents per household, total population, and gender. The results demonstrated a consistent LULC simulation, indicating an urban expansion of 4 km<sup>2</sup> between 2030 and 2050, with reductions of 0.6 km<sup>2</sup> in natural formations and 3.4 km<sup>2</sup> in farming areas. Using LULC data, the study predicted a 14.21% increase in domestic water consumption in Campina Grande for 2050 compared to 2010, equivalent to an increase of 2,348,424.96 m<sup>3</sup>. Furthermore, the spatial analysis draws a spatial profile of water consumption among residents, highlighting the areas with the highest per capita consumption. Thus, this research offers a consistent approach to estimating water demand in regions with limited consumption data, providing valuable insights for decision-makers to consider in urban planning.https://www.mdpi.com/2413-8851/7/4/120domestic water demandland use and land coverurban sprawlsemiarid regionurban water
spellingShingle Higor Costa de Brito
Iana Alexandra Alves Rufino
Mauro Normando Macedo Barros Filho
Ronaldo Amâncio Meneses
Use of Spatial Data in the Simulation of Domestic Water Demand in a Semiarid City: The Case of Campina Grande, Brazil
Urban Science
domestic water demand
land use and land cover
urban sprawl
semiarid region
urban water
title Use of Spatial Data in the Simulation of Domestic Water Demand in a Semiarid City: The Case of Campina Grande, Brazil
title_full Use of Spatial Data in the Simulation of Domestic Water Demand in a Semiarid City: The Case of Campina Grande, Brazil
title_fullStr Use of Spatial Data in the Simulation of Domestic Water Demand in a Semiarid City: The Case of Campina Grande, Brazil
title_full_unstemmed Use of Spatial Data in the Simulation of Domestic Water Demand in a Semiarid City: The Case of Campina Grande, Brazil
title_short Use of Spatial Data in the Simulation of Domestic Water Demand in a Semiarid City: The Case of Campina Grande, Brazil
title_sort use of spatial data in the simulation of domestic water demand in a semiarid city the case of campina grande brazil
topic domestic water demand
land use and land cover
urban sprawl
semiarid region
urban water
url https://www.mdpi.com/2413-8851/7/4/120
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