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Framework for WASH Sector Data Improvements in Data-Poor Environments, Applied to Accra, Ghana

1
Institute for Integrated Economic Research, The Broadway, London W5 2NR, UK
2
Centre for Environmental Policy, Faculty of Natural Sciences, Imperial College London, South Kensington Campus, London SW7 2AZ, UK
3
Centre for Process Systems Engineering, Department of Chemical Engineering, Imperial College London, South Kensington Campus, London SW7 2AZ, UK
4
Department of Civil and Environmental Engineering, Faculty of Engineering, Imperial College London, South Kensington Campus, London SW7 2AZ, UK
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Centre for Remote Sensing and Geographic Information Services, University of Ghana, Legon, Annie-Jiagge Road, Accra, Ghana
6
Department of Chemical and Biomolecular Engineering, Faculty of Engineering, National University of Singapore, 4 Engineering Drive 4, E5 03-04, Singapore 117585, Singapore
7
Smith School of Enterprise and the Environment, School of Geography and the Environment, University of Oxford, South Parks Road, Oxford OX1 3QY, UK
*
Authors to whom correspondence should be addressed.
Water 2018, 10(9), 1278; https://doi.org/10.3390/w10091278
Received: 12 August 2018 / Revised: 6 September 2018 / Accepted: 8 September 2018 / Published: 18 September 2018
(This article belongs to the Section Urban Water Management)
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Abstract

Improvements in water, sanitation and hygiene (WASH) service provision are hampered by limited open data availability. This paper presents a data integration framework, collects the data and develops a material flow model, which aids data-based policy and infrastructure development for the WASH sector. This model provides a robust quantitative mapping of the complete anthropogenic WASH flow-cycle: from raw water intake to water use, wastewater and excreta generation, discharge and treatment. This approach integrates various available sources using a process-chain bottom-up engineering approach to improve the quality of WASH planning. The data integration framework and the modelling methodology are applied to the Greater Accra Metropolitan Area (GAMA), Ghana. The highest level of understanding of the GAMA WASH sector is achieved, promoting scenario testing for future WASH developments. The results show 96% of the population had access to improved safe water in 2010 if sachet and bottled water was included, but only 67% if excluded. Additionally, 66% of 338,000 m3 per day of generated wastewater is unsafely disposed locally, with 23% entering open drains, and 11% sewage pipes, indicating poor sanitation coverage. Total treated wastewater is <0.5% in 2014, with only 18% of 43,000 m3 per day treatment capacity operational. The combined data sets are made available to support research and sustainable development activities. View Full-Text
Keywords: anthropogenic WASH mapping; WASH planning tool; Accra WASH sector characterization; open data anthropogenic WASH mapping; WASH planning tool; Accra WASH sector characterization; open data
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

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Koppelaar, R.H.E.M.; Sule, M.N.; Kis, Z.; Mensah, F.K.; Wang, X.; Triantafyllidis, C.; Dam, K.H.; Shah, N. Framework for WASH Sector Data Improvements in Data-Poor Environments, Applied to Accra, Ghana. Water 2018, 10, 1278.

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