Identifying High Yielding Stormwater Harvesting Sites in Africa
J.R. Fortuin (TU Delft - Civil Engineering & Geosciences)
LC Rietveld – Mentor (TU Delft - Sanitary Engineering)
Job van der Werf – Graduation committee member (TU Delft - Water Systems Engineering)
Juan Aguilar Lopez – Graduation committee member (TU Delft - Hydraulic Structures and Flood Risk)
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Abstract
Africa is the world’s second driest continent, supporting 15% of the global population with only 9% of the global renewable water resource. The 2015 to 2018 drought in the Western Cape of South Africa, where a Day-Zero scenario was narrowly avoided, highlighted the need to start looking at alternative water resources in conjunction with preserving the current water resources.
Globally, the water sector is moving towards a circular water economy - where all water sources, including wastewater, stormwater and rainwater are treated as a resource that can be used, recycled, and replenished into the system. Stormwater harvesting (SWH) has successfully been implemented in countries such as Australia, Israel, Singapore & South Africa.
The success of any SWH scheme depends on effective site selection. Yet, there is little guidance available, and site choices have traditionally relied on the subjective judgment of urban water managers. This demonstrates the need for an objective, data-driven approach that integrates multiple spatial datasets to identify optimal SWH locations.
This research develops such a method: an integrated hydrological and GIS-based screening tool that identifies high yield (hotspot) SWH sites using publicly available datasets in Africa. The collection models showed that high yielding stormwater harvesting sites can be identified with publicly available data, with all 4 weightings consistently pointing out the top 8 stormwater harvesting sites.
The storage and distribution models showed that with a storage facility that has a capacity of 10x the maximum daily demand, high reliability figures can be achieved in excess of 80% in terms of volume and time-based reliability. The storage and distribution models also showed that if the storage capacity can be increased, the reliability and resilience of the facility can also be increased.
The study also has some limitations and intrinsic uncertainties, and the framework should be used as a screening tool.
This study places focus on stormwater harvesting as an integral part of sustainable management of urban water and presents a robust, adaptable and scalable tool that can support urban areas across Africa to address the growing water demand challenges.