Water scarcity in African cities often linked to deficiencies in service delivery than limitations in available water resources. These limitations have created a situation where multiple service providers enter the urban space to meet the gap in providing access to water. In this context, water resources managers emerge as the only entity with a common picture of how water resources are managed. They require more sophisticated resource planning tools that will allow a range of stakeholders, including water service providers, to gain a common understanding of the specific water needs of different communities across the urban landscape. In this paper, using Nairobi as a case study, we demonstrate how moving from simplified linear regressions of water demand to spatial regressions that consider uncertainty improves understanding of the water scarcity picture. The results show that high-income suburbs such as Kitisuru and Highridge and newer developments in Ngong to the south do not have water stress but have higher groundwater extraction rates. Lower income neighborhoods to the east such as Umoja and Kasarani are water stressed. Spatial regression analysis also mirrors this finding where population density and poverty rates correlate negatively to borehole density. Based on the calculated water stress and spatial regression, we are able to predict that over the next 17 years, there will be an additional 1,442 boreholes constructed if this rising demand is unmet by corresponding development in water infrastructure and distribution networks. This corresponds to an additional groundwater extraction rate of 54,150 m3/day. Mapping water scarcity across Africa's urban areas improves how infrastructure investments are prioritized, increases transparency on the use and risks to the water resource, and builds consensus around the true picture of service delivery in water scarce areas.
Keywords: Water scarcity, Nairobi, Water demand, Spatial mapping