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Flood Modeling in a Data-Poor Region: A Satellite Data-Supported Model for Accra, Ghana Open Access

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Flooding is an environmental issue affecting the Greater Accra Metropolitan area. However, stream gauge data and other data used to support flood models are limited. The objective of this research is to use remote sensing and GIS to support a simple semi-distributed rainfall-runoff model - the SCS Curve Number method - to predict the peak volume and timing of flood waters on the Odaw River in Accra. Spectral Mixture Analysis (SMA) and Normalized Difference Vegetation Index (NDVI) were used to classify the percentage of vegetation, impervious surface and soil cover in each sub-basin. The method was applied using HEC-HMS (Hydrologic Engineering Center's Hydrologic Modeling System) to obtain volume and timing of peak flows and possible channel overflow. Results were compared with published maps of frequently flooded areas and newspaper reports of flooded neighborhoods. Though the method awaits further testing with historical rainfall-runoff relationships from Accra, it can provide auxiliary information to existing flood risk data.

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