This study investigates residential water consumption in Adama city, Ethiopia, to inform water-sensitive interventions. Using a combination of top-down and bottom-up data collection, and integrating machine learning with spatial and socioeconomic analyses, the study identifies key factors influencing water consumption and predicts daily household water use. Findings reveal significant variations in consumption across urban areas, highlighting the need for improved water conservation habits and sustainable water management practices.
