Despite floods and droughts accounting for 80% and 70% disaster related deaths and economic loss respectively in Sub-Saharan Africa (SSA), there have been very few attempts in SSA to quantify flood-related vulnerability and risk, especially as they relate to the rural poor. This thesis quantifies and profiles the flood risk of rural communities in SSA focusing on the Lower Shire Valley, Malawi. Given the challenge of hydrometeorological data quality in SSA to support quantitative flood risk assessments, the work first reconstructs and extends hydro-meteorological data using Artificial Neural Networks (ANNs). These data then formed the input to a coupled IPCC-Sustainable Development Frameworks for quantifying flood vulnerability and risk. Flood risk was obtained by integrating hazard and vulnerability. Flood hazard was characterised in terms of flood depth and inundation area obtained through hydraulic modelling of the catchment with Lisflood-FP, while the vulnerability was indexed through analysis of exposure, susceptibility and capacity and linked to social, economic, environmental and physical perspectives. Data on these were collected through structured interviews carried out with the communities and stakeholders in the valley and later analysed. The implementation of the entire analysis within a GIS environment enabled the visualisation of spatial variability in flood risk in the valley. The results show predominantly medium levels in hazardousness, vulnerability and risk. The vulnerability is dominated by a high to very high susceptibility component largely because of the high to very high socio-economic and environmental vulnerability. Economic and physical capacities tend to be predominantly low but social capacity is significantly high, resulting in overall medium levels of capacity-induced vulnerability. Exposure manifests as medium. Both the vulnerability and risk showed marginal spatial variability. Given all this, the thesis argues for the need to mainstream disaster reduction in the rather plethoric conventional socio-economic developmental programmes in SSA. Additionally, the low spatial variability in both the risk and vulnerability in the valley suggests that any such interventions need to be valley-wide to be effective.