Urban Rainwater Harvesting Adoption Potential in a Socio-economically Diverse City Using a GIS-based Multi-criteria Decision Method

Annah Ndeketeya, Morgan Dundu

Research output: Contribution to journalArticlepeer-review

5 Citations (Scopus)

Abstract

Rainwater harvesting (RWH) remains an underutilized practice in developing cities, despite its promising potential to supplement available water resources. Socio-economic factors such as capital and household characteristics have been identified as major constraints to the adoption of RWH. Therefore, the purpose of this study is to investigate the extent to which various socio-economic factors influence the potential adoption of RWH in the City of Johannesburg (CoJ). The study employs a Multi-Criteria Decision Analysis (MCDA) approach in ArcMap to run two scenarios, one with socio-economic criteria and the other without. Inputs considered include income and size of the household, tenure-ship and sanitation type. Suitability maps show that more than 50% of the area in the CoJ is suitable for RWH. Further analysis was performed to find the variation in land use, which was categorized into four suitability scales: not suitable, low suitability, medium suitability and high suitability. The results indicate that excluding social and economic criterions leads to overestimating the high suitability category. Findings show the great potential of RWH systems in institutional, business and agricultural properties. Therefore, promoting RWH at the property level is recommended, supported by smart policies to boost its adoption.

Original languageEnglish
Pages (from-to)835-850
Number of pages16
JournalWater Resources Management
Volume37
Issue number2
DOIs
Publication statusPublished - Jan 2023

Keywords

  • GIS
  • Multi-criteria decision analysis
  • Rainwater harvesting
  • Socio-economic factors

ASJC Scopus subject areas

  • Civil and Structural Engineering
  • Water Science and Technology

Fingerprint

Dive into the research topics of 'Urban Rainwater Harvesting Adoption Potential in a Socio-economically Diverse City Using a GIS-based Multi-criteria Decision Method'. Together they form a unique fingerprint.

Cite this