Assessing Flood Vulnerability in Nigeria: A Model-Based Evaluation

Abstract

Several attempts to achieve the Sustainable Development Goals (SDGs) 7 & 13 such as ensuring environmental sustainability, fighting the effects of climate change, have been adopted to address the yearly flood event in different states across the country. Despite these efforts, the threat of flooding is taking on a different dimension yearly. Because of the similarities in the complexity of the flooding factors in different states in the country, this study adopts the integration of Hydrologic Engineering Centre’s Geospatial Hydrologic Modelling System (HEC-GeoHMS) for modelling and mapping of flood using Abeokuta and its adjoining hydrological catchments as a case study. The catchments were delineated into 24 sub basins (to make it easier to identify areas of the landscape that are most sensitive or susceptible to flood) and their properties were extracted from a 10 m Digital Elevation Model of the area. Rainfall from January 2020 to December 2023 and discharge data from Ogun-Osun River basin Development Authority (OORBDA) were entered to develop the meteorological model. The resulting model was then calibrated by optimizing the model parameters and thereafter validated. Three statistical evaluation criteria used for the validation of the model showed that there is a good simulation between the observed and estimated values (REp= -0.24%, REv = 0.02%, NSE=88.16%, and R<sup>2</sup>= 0.732). Python regression analysis corroborated the outcome of the modelled hydrological characteristics of the area, thus, demonstrating that the different hydrological properties of the catchments’ diverse landscape, coverage area, and climatic conditions are contributors of flood disasters.