To map flood risk area, cells were defined as river by setting a flow accumulation threshold of 10 km2. This threshold was specified by taking references of previous research which has been done, e.g. Brakebill and Preston, 2003, Arthur etal., 2005, Hagen et al., 2010, and adjusted by various tests and visually comparing with high-resolution aerial photos. Based on this, we created a river network for the Malawi country. We created a Euclidean allocation grid from those stream elevations, so each cell to its nearest stream cell was assigned the elevation value of the stream cell. Then we subtract the Euclidean grid from the true elevation grid and get the difference of elevation. It indicates to how much the elevation of a particular cell is higher than the elevation of its nearest stream. Therefore, based on elevation, we created variable width buffers on the stream segments. The buffers show the elevation no more than 100 meters higher than that of its nearest stream. They are in five categories: Lower than 5m, 6-10m, 11-25m, 26-50m and 51 to 100m, indicating from a high to low flooding risk.
We use Karonga town as an example to map the flood risk area (Figure 1). The highest elevation difference is 1352 m, and we list elevation differences below 100 m as high risk areas. Among these areas, we delineated five categories as <5m, <10m, <25m, <50m and < 100m. We selected a buffer area of 2.5km as high risk zone. The selection of the buffer width is based on López L 2009’s research, in which different buffer areas are involved in flood risk assmessment. However, areas within the high risk distance but with a higher elevation level may not necessarily a “flooding risk” spot. In this light, we focus on 2.5 km buffer areas to the rivers, but within these buffer zones, we further map variable “sub-buffer” areas on the stream segments based on elevation differences.
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