Rooftop Rainwater Harvesting for Mombasa: Scenario Development with Image Classification and Water Resources Simulation

Mombasa faces severe water scarcity problems. The existing supply is unable to satisfy the demand. This article demonstrates the combination of satellite image analysis and modelling as tools for the development of an urban rainwater harvesting policy. For developing a sustainable remedy policy, roo...

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Main Authors: Robert O. Ojwang, Jörg Dietrich, Prajna Kasargodu Anebagilu, Matthias Beyer, Franz Rottensteiner
Format: Article
Language:English
Published: MDPI AG 2017-05-01
Series:Water
Subjects:
Online Access:http://www.mdpi.com/2073-4441/9/5/359
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spelling doaj-2904d3f68b5e4265828956eb5793c3302020-11-24T23:31:57ZengMDPI AGWater2073-44412017-05-019535910.3390/w9050359w9050359Rooftop Rainwater Harvesting for Mombasa: Scenario Development with Image Classification and Water Resources SimulationRobert O. Ojwang0Jörg Dietrich1Prajna Kasargodu Anebagilu2Matthias Beyer3Franz Rottensteiner4Coast Water Services Board, Mikindani Street, Off Nkurumah Road, 90417-80100 Mombasa, KenyaInstitute of Hydrology and Water Resources Management, Leibniz Universität Hannover, Appelstr. 9A, 30167 Hannover, GermanyInstitute of Hydrology and Water Resources Management, Leibniz Universität Hannover, Appelstr. 9A, 30167 Hannover, GermanyDepartment B2.3, Groundwater Resources—Quality and Dynamics, Federal Institute for Geosciences and Natural Resources (BGR), Stilleweg 2, 30655 Hannover, GermanyInstitute of Photogrammetry and GeoInformation, Leibniz Universität Hannover, Nienburger Str.1, 30167 Hannover, GermanyMombasa faces severe water scarcity problems. The existing supply is unable to satisfy the demand. This article demonstrates the combination of satellite image analysis and modelling as tools for the development of an urban rainwater harvesting policy. For developing a sustainable remedy policy, rooftop rainwater harvesting (RRWH) strategies were implemented into the water supply and demand model WEAP (Water Evaluation and Planning System). Roof areas were detected using supervised image classification. Future population growth, improved living standards, and climate change predictions until 2035 were combined with four management strategies. Image classification techniques were able to detect roof areas with acceptable accuracy. The simulated annual yield of RRWH ranged from 2.3 to 23 million cubic meters (MCM) depending on the extent of the roof area. Apart from potential RRWH, additional sources of water are required for full demand coverage.http://www.mdpi.com/2073-4441/9/5/359Mombasaroof rainwater harvestingwater supplywater demandintegrated water resources managementWEAP
collection DOAJ
language English
format Article
sources DOAJ
author Robert O. Ojwang
Jörg Dietrich
Prajna Kasargodu Anebagilu
Matthias Beyer
Franz Rottensteiner
spellingShingle Robert O. Ojwang
Jörg Dietrich
Prajna Kasargodu Anebagilu
Matthias Beyer
Franz Rottensteiner
Rooftop Rainwater Harvesting for Mombasa: Scenario Development with Image Classification and Water Resources Simulation
Water
Mombasa
roof rainwater harvesting
water supply
water demand
integrated water resources management
WEAP
author_facet Robert O. Ojwang
Jörg Dietrich
Prajna Kasargodu Anebagilu
Matthias Beyer
Franz Rottensteiner
author_sort Robert O. Ojwang
title Rooftop Rainwater Harvesting for Mombasa: Scenario Development with Image Classification and Water Resources Simulation
title_short Rooftop Rainwater Harvesting for Mombasa: Scenario Development with Image Classification and Water Resources Simulation
title_full Rooftop Rainwater Harvesting for Mombasa: Scenario Development with Image Classification and Water Resources Simulation
title_fullStr Rooftop Rainwater Harvesting for Mombasa: Scenario Development with Image Classification and Water Resources Simulation
title_full_unstemmed Rooftop Rainwater Harvesting for Mombasa: Scenario Development with Image Classification and Water Resources Simulation
title_sort rooftop rainwater harvesting for mombasa: scenario development with image classification and water resources simulation
publisher MDPI AG
series Water
issn 2073-4441
publishDate 2017-05-01
description Mombasa faces severe water scarcity problems. The existing supply is unable to satisfy the demand. This article demonstrates the combination of satellite image analysis and modelling as tools for the development of an urban rainwater harvesting policy. For developing a sustainable remedy policy, rooftop rainwater harvesting (RRWH) strategies were implemented into the water supply and demand model WEAP (Water Evaluation and Planning System). Roof areas were detected using supervised image classification. Future population growth, improved living standards, and climate change predictions until 2035 were combined with four management strategies. Image classification techniques were able to detect roof areas with acceptable accuracy. The simulated annual yield of RRWH ranged from 2.3 to 23 million cubic meters (MCM) depending on the extent of the roof area. Apart from potential RRWH, additional sources of water are required for full demand coverage.
topic Mombasa
roof rainwater harvesting
water supply
water demand
integrated water resources management
WEAP
url http://www.mdpi.com/2073-4441/9/5/359
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AT prajnakasargoduanebagilu rooftoprainwaterharvestingformombasascenariodevelopmentwithimageclassificationandwaterresourcessimulation
AT matthiasbeyer rooftoprainwaterharvestingformombasascenariodevelopmentwithimageclassificationandwaterresourcessimulation
AT franzrottensteiner rooftoprainwaterharvestingformombasascenariodevelopmentwithimageclassificationandwaterresourcessimulation
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