A Municipal Flood Early-Warning Framework for Community-Centred Development in Urban Uganda

Urban flood early-warning services in Uganda face interconnected challenges involving incomplete rainfall records, limited monitoring infrastructure, intermittent power and communications, and fragmented arrangements for warning and response. Guided by the World Meteorological Organization’s (WMO) people-centred early-warning framework and the Sendai Framework for Disaster-Risk Reduction, this paper develops a structured pre-deployment municipal framework linking risk knowledge, monitoring, communication, preparedness and accountable governance. The empirical component analyses daily Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) for Bwaise, Kalerwe and Mbarara, Uganda, for 2010–2024 and compares the two available Kampala-area series with ERA5 Ag precipitation estimates. Daily product-to-product correlations were 0.425 and 0.401; after monthly aggregation, they increased to 0.768 and 0.750. These results indicate temporal scale sensitivity but do not validate either product against ground rainfall. The weaker daily agreement supports a design in which gridded products provide historical context rather than serving as sole operational triggers: locally installed rain gauges and, where appropriate, water-level sensors are proposed to supply site-specific observations, subject to calibration and field evaluation. The framework was developed through an applied design-synthesis process that mapped the rainfall findings, documented resilient monitoring requirements and published governance and participation literature onto a nine-stage warning-service lifecycle. It specifies proposed responsibilities, resilient data handling, community participation procedures and indicators of readiness, continuity and usefulness. The resulting contribution is a structured planning resource for municipal adaptation and pilot design; field validation, stakeholder testing and local cost assessment remain necessary before operational adoption.