Assessment of Rainwater Harvesting Potential from Roof Catchments through Clustering Analysis
Rainwater harvesting from rooftop catchments represents a climate change adaptation measure that is especially significant in areas affected by water scarcity. This article develops a Geographic Information Systems-based methodology to evaluate the spatial distribution of rainwater catchment potenti...
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doaj-40f2b291ed6f4d3d96343f2bb7f6bc352020-11-25T03:29:43ZengMDPI AGWater2073-44412020-09-01122623262310.3390/w12092623Assessment of Rainwater Harvesting Potential from Roof Catchments through Clustering AnalysisRubén Villar-Navascués0Alfredo Pérez-Morales1Salvador Gil-Guirado2Water and Territory research group, Interuniversity Institute of Geography, University of Alicante, 03690 San Vicente del Raspeig, SpainDepartment of Geography, University of Murcia, 30001 Murcia, SpainDepartment of Geography, University of Murcia, 30001 Murcia, SpainRainwater harvesting from rooftop catchments represents a climate change adaptation measure that is especially significant in areas affected by water scarcity. This article develops a Geographic Information Systems-based methodology to evaluate the spatial distribution of rainwater catchment potential to identify the most favorable urban areas for the installation of these infrastructures. Since performance and water saving potential of rainwater harvesting systems greatly depends on population density and roof size, this assessment was performed for each residential plot on a per capita basis, based on cadastral data and a method of demographic disaggregation. Furthermore, to evaluate spatial variation of runoff coefficient per building, a supervised classification was carried out to consider the influence of roof types on the rainwater catchment potential. After calculating rainwater catchment potential per capita for each residential plot, the spatial clustering of high (hot spots) and low values (cold spots) was assessed through the Getis-Ord General G statistic. Results indicate a spatial pattern of high rainwater catchment potential values in low-density urban areas, where rainwater catchment systems are expected to offer a better performance and a shorter amortization period. These results may be useful for the enactment of local legislation that regulates the obligation to install these infrastructures or offers subsidies for their implementation.https://www.mdpi.com/2073-4441/12/9/2623rainwater harvestingGISspatial analysiswater consumptionSpain |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Rubén Villar-Navascués Alfredo Pérez-Morales Salvador Gil-Guirado |
spellingShingle |
Rubén Villar-Navascués Alfredo Pérez-Morales Salvador Gil-Guirado Assessment of Rainwater Harvesting Potential from Roof Catchments through Clustering Analysis Water rainwater harvesting GIS spatial analysis water consumption Spain |
author_facet |
Rubén Villar-Navascués Alfredo Pérez-Morales Salvador Gil-Guirado |
author_sort |
Rubén Villar-Navascués |
title |
Assessment of Rainwater Harvesting Potential from Roof Catchments through Clustering Analysis |
title_short |
Assessment of Rainwater Harvesting Potential from Roof Catchments through Clustering Analysis |
title_full |
Assessment of Rainwater Harvesting Potential from Roof Catchments through Clustering Analysis |
title_fullStr |
Assessment of Rainwater Harvesting Potential from Roof Catchments through Clustering Analysis |
title_full_unstemmed |
Assessment of Rainwater Harvesting Potential from Roof Catchments through Clustering Analysis |
title_sort |
assessment of rainwater harvesting potential from roof catchments through clustering analysis |
publisher |
MDPI AG |
series |
Water |
issn |
2073-4441 |
publishDate |
2020-09-01 |
description |
Rainwater harvesting from rooftop catchments represents a climate change adaptation measure that is especially significant in areas affected by water scarcity. This article develops a Geographic Information Systems-based methodology to evaluate the spatial distribution of rainwater catchment potential to identify the most favorable urban areas for the installation of these infrastructures. Since performance and water saving potential of rainwater harvesting systems greatly depends on population density and roof size, this assessment was performed for each residential plot on a per capita basis, based on cadastral data and a method of demographic disaggregation. Furthermore, to evaluate spatial variation of runoff coefficient per building, a supervised classification was carried out to consider the influence of roof types on the rainwater catchment potential. After calculating rainwater catchment potential per capita for each residential plot, the spatial clustering of high (hot spots) and low values (cold spots) was assessed through the Getis-Ord General G statistic. Results indicate a spatial pattern of high rainwater catchment potential values in low-density urban areas, where rainwater catchment systems are expected to offer a better performance and a shorter amortization period. These results may be useful for the enactment of local legislation that regulates the obligation to install these infrastructures or offers subsidies for their implementation. |
topic |
rainwater harvesting GIS spatial analysis water consumption Spain |
url |
https://www.mdpi.com/2073-4441/12/9/2623 |
work_keys_str_mv |
AT rubenvillarnavascues assessmentofrainwaterharvestingpotentialfromroofcatchmentsthroughclusteringanalysis AT alfredoperezmorales assessmentofrainwaterharvestingpotentialfromroofcatchmentsthroughclusteringanalysis AT salvadorgilguirado assessmentofrainwaterharvestingpotentialfromroofcatchmentsthroughclusteringanalysis |
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1724577516153208832 |