Intra-seasonal rainfall and piped water revenue variability in rural Africa. (September 2022) - Armstrong, Andrew; Dyer, Ellen; Koehler, Johanna; Hope, Rob
Graphical abstract: Highlights: We examine monthly rainfall against rural piped water revenue in three countries. Areas with consistent seasonal rainfall have a third less revenue during wet months. Revenues appear stable in areas with frequent dry intervals during the wet season. Tariff level, connection type, and payment approach do not alter revenue patterns. Intra-seasonal rainfall analysis can enhance rural piped water revenue planning. Abstract: Rainfall patterns influence water usage and revenue from user payments in rural Africa. We explore these dynamics by examining monthly rainfall against 4, 888 records of rural piped water revenue in Ghana, Rwanda, and Uganda and quantifying revenue changes over 635 transitions between dry and wet seasons. Results show operators experience revenue variability at regional and intra-seasonal scales. Revenues fall by an average of 30 percent during the wettest months of the year in climate regimes with consistent wet season rainfall. However, seasonally stable revenues are observed in areas where consecutive dry days are common during the wet season, potentially reflecting a dependency on reliable services. We also find changes in tariff level, waterpoint connection type, and payment approach do not consistently prevent or increase seasonal revenue variability. Local revenue generation underpins delivery of drinking water services. Where rainfall patterns remain consistent, piped water operators can expect to encounter seasonal revenue reductions regardless of whether services are provided on or off premises and of how services are paid for. Revenue projections that assume consistent volumetric demand year-round may lead to shortfalls that threaten sustainability and undermine the case for future investment. Intra-seasonal rainfall analysis can enhance rural piped water revenue planning by offering localised insight into demand dynamics and revealing where climate variability may increase dependency on reliable services.