Flood risk mapping and urban infrastructural susceptibility assessment using a GIS and analytic hierarchical raster fusion approach in the Ona River Basin, Nigeria

The topical climate change effect, along with several uncontrolled anthropogenic activities, has resulted in a global flood disaster that continues to wreak havoc on human ecology. The hydraulic and integrated modelling approaches appear to stand out in the sequence of flood risk models that have be...

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Veröffentlicht in:International journal of disaster risk reduction 2022-07, Vol.77, p.103097, Article 103097
Hauptverfasser: Nkeki, Felix Ndidi, Bello, Ehiaguina Innocent, Agbaje, Ishola Ganiy
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Sprache:eng
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Zusammenfassung:The topical climate change effect, along with several uncontrolled anthropogenic activities, has resulted in a global flood disaster that continues to wreak havoc on human ecology. The hydraulic and integrated modelling approaches appear to stand out in the sequence of flood risk models that have been presented because of their predictive accuracy. The former has a high probability of under predicting and the latter has a high tendency to over-predict. This study proposed a modelling approach that combines the hydraulic and integrated models using analytical hierarchical raster fusion techniques to strengthen the weaknesses of the individual models. This study seeks to undertake a flood inundation model, a runoff model, and raster fusion models using GIS and HEC-RAS rain-on-grid methods to map flood risk and perform a flood infrastructural susceptibility assessment in the Ona river basin of Ibadan city. The flood risk model's main findings revealed that 48.2% of the Ona river basin is exposed from moderate to very high flood risk. It was revealed that rainfall introduces excess stormwater into the basin, but the stream channels associated with physical features are the major influencing factors. Also vulnerable to very high flood magnitudes include places with high building, road and rail network density, and locations with a high density of damaged bridges and culverts. This study shows that the robust modelling approach presented here yielded insightful results that can be used by relevant authorities to implement flood management models and define priorities for flood catastrophe risk planning, early warning, and preparedness. [Display omitted] •GIS & HEC-RAS methods were used to map the spatial distribution of flood risk.•The flood risk model revealed that 48.2% of the basin is exposed to very high to moderate flood risk.•Floodplain along the main river is exposed to very high flood risk magnitude.•Downstream section exhibits an intensified flood risk level concerning the spatial spread at all risk categories.•Areas with high buildings, bad bridges and culverts, road and rail network densities are highly susceptible to flooding.
ISSN:2212-4209
2212-4209
DOI:10.1016/j.ijdrr.2022.103097