An assessment tool to improve rural groundwater access: Integrating hydrogeological modelling with socio-technical factors

Abstract

Sustainable exploitation of groundwater resources for drinking water provision in rural communities in sub-Sahara Africa remains elusive due to the limited knowledge of these hydrogeological systems. This is exacerbated by poor maintenance of existing infrastructure, limited technical capacity, the socio-economic characteristics of the area and poor governance. Assessing the likelihood of a given individual user experiencing water shortage calls for an interdisciplinary approach. After a preliminary multifactorial analysis incorporating a range of variables from technical to societal, it was found that most of the overall risk of water shortage for an individual household could be attributed to three factors; (1) Proximity, specified as the distance to the closest supply well (determined by geographical parameters), (2) Availability of good quality water in the wells (determined by hydrogeological understanding and modelling), and (3) Sustainability (determined by socio-technical and socio-economic parameters). In the latter case, a distinction was made between hardware functionality- the water point's performance considering a sufficient yield and reliability through time- and software functionality, based on a combination of socioeconomic data from surveys and analysed using Multiple Factor Analysis (MFA). All three factors are eventually mapped onto indicators in the range of [0–1] and then represented in a Geographical Information System based on the partition of the entire spatial domain (e.g., counties, villages, and neighbourhoods). The three indicators are then combined in a final index based on the product of the three factors, thus mapping time-dependent overall risk and allowing the assessment of temporal risk-evolution scenarios. The methodology is applied to Kwale County, Kenya, where community handpumps and groundwater points comprise the main water supply system. Apart from mapping the present situation, the methodology is finally used to assess the impact of future climate scenarios.