This research aimed at identifying flood conditioning factors and hazard rating in Yola North Local Government Area, Adamawa State, Nigeria with geospatial technology. The data used include ASTER with 30m spatial resolution, Landsat 9 OLI multispectral data (2023), and flood and non-flood points. This research was achieved by preparing flood conditioning factors and assessed flood hazard rating in the study area. The data used for this research includes; the satellite imageries covering the study area of 1980-2021, Digital Elevation Model, Curvature, Aspect, Slope, Topographic Roughness Index (TRI), Topographic Wetness Index (TWI), Stream Power Index (SPI), Sediment Transport Index (STI), Land Use/Land Cover (LULC) measurements, Distance To The River, Soil, Rainfall, Total Flow Accumulation, Flood Points and Non-Flood Points to achieve the stated objectives. The data were used as an input for Geospatial analysis. The study analyzed land use, aspect values, distance to streams, flow accumulation, and other factors to assess flood risk. Built-up areas (33%), farmland (25%), and bare land (18%) were identified as significant land use types. Aspect values ranged from low (-1 to 63) to high (289 to 358). Distance to streams ranged from 250m to over 2000m. Areas with high flow accumulation and direction values are prone to flooding. Rainfall ranged from 0mm to 348.1mm in August. River basin values indicated larger catchment areas in some areas. Slope values ranged from 0.76 (low) to 13 (high). Soil characteristics and SPI, STI, TRI, TWI, and NDWI values also indicated varying levels of flood risk. The study’s results can be used to inform flood mitigation strategies. The results showed that 58% of the area has a low degree of hazard, while 18% has an extreme hazard, 17% has a significant hazard, and 6% has a moderate hazard. The study identified areas prone to flooding, including those with low elevation, proximity to water bodies, and poor drainage. The findings suggest that land use patterns, topography, and soil characteristics significantly influence flood risk rating in the study area. Therefore, the results of this study are useful in flood mitigation strategies, such as identifying flood-prone areas for targeted interventions, designing drainage systems and flood protection infrastructure, and planning evacuation routes and emergency response plans.
Keywords: : GIS, Flood, Yola North, conditional factor, hazard rating
