Early Warning Systems in Flood Management, Spatial Integration and Blind Spot Identification in Southwestern Nigeria

Abstract

Flooding remains one of the most destructive and recurrent hazards across Southwestern Nigeria. Rapid urbanization, deficient drainage infrastructure, and the variable rainfall regimes that characterized the region combine to produce loss patterns that have worsened measurably over the past two decades. Yet spatial data on flood risk and the operational reach of Early Warning Systems (EWS) have never been formally integrated at a scale useful for policy. This gap necessitated the application of a Geographic Information System-based multi-criteria analysis approach, flood susceptibility indices were derived for all 137 Local Government Areas (LGAs) across six states. Those indices were then overlaid against a spatially explicit binary classification of EWS coverage, constructed from NEMA, SEMA, NIHSA, and NiMet institutional records, to identify and quantify warning blind spots. Results show that LGAs classified as High or Very High susceptibility cover approximately 52% of the combined land area of Lagos, Ogun, and Ondo states. Of the 137 LGAs assessed, 39 met the operational blind spot threshold. The estimated resident population within those LGAs, drawn from NPC 2023 LGA-level figures, exceeds 4.6 million people. EWS deficits are concentrated in peri-urban and rural LGAs where susceptibility is highest and institutional capacity is weakest. The study offers a transferable LGA-proxy methodology applicable to other data-scarce settings across Sub-Saharan Africa and contributes a quantified baseline against which progress toward the UN EW4All 2027 universal coverage target can be measured