Flood hazard maps showing information on extent, severity and probability integrated in a flood hazard index in Burkina Faso, Benin and Ghana.

Robust risk assessment requires accurate flood intensity area mapping to allow for the identification of populations and elements at risk. However, available flood maps in West Africa lack spatial variability while global datasets have resolutions too coarse to be relevant for local scale risk assessment. Consequently, local disaster managers are forced to use traditional methods such as watermarks on buildings and media reports to identify flood hazard areas. In this study, remote sensing and Geographic Information System (GIS) techniques were combined with hydrological and statistical models to delineate the spatial limits of flood hazard zones in selected communities in Ghana, Burkina Faso and Benin. The approach involves estimating peak runoff concentrations at different elevations and then applying statistical methods to develop a Flood Hazard Index (FHI). Results show that about half of the study areas fall into high intensity flood zones. Empirical validation using statistical confusion matrix and the principles of Participatory GIS show that flood hazard areas could be mapped at an accuracy ranging from 77% to 81%. This was supported with local expert knowledge which accurately classified 79% of communities deemed to be highly susceptible to flood hazard. The results will assist disaster managers to reduce the risk to flood disasters at the community level where risk outcomes are first materialized.

A multi-scale participatory process was used to extend the classical approach of indicator development for risk assessment in West Africa. The approach followed a step-wise procedure to develop Indicator Reference Sheet based on conceptual risk assessment framework and combined with knowledge of local experts iteratively selected through snowball approach. Existing risk assessment frameworks being modified to account for multiple hazards were merged into a coherent framework to categorize the components of risks. Local experts including at risk populations were constituted into technical working groups to elicit important processes shaping risks at multiple spatial scales. The results showed that more than half of the designated local level indicators and over two-third of macro scale indicators are rarely used in present risk assessments in the region. Additionally, although an indicator may be common to three countries, their differential rankings will result in differences in explaining the risks faced by people in different societies. However, there were indicators that were unique to each country and this has wider implications for risk assessment that uses common indicators for different countries for comparative purposes. An important output of the study is the identification of locally and nationally evaluated indicator sets for assessing the risk to natural hazards. While it has neither been optimal to completely neglect classical approaches nor to take as an absolute fact opinions from local experts, more emphasis should be paid to the latter in risk assessment that is supposed to serve the very people on whose behalf the assessment is done.