Abstract Medium-resolution DEMs have limited applicability to flood mapping in large river systems within data sparse regions such as Sub-Saharan Africa. We present a novel approach for the enhancement of the SRTM (30 m) Digital Elevation Model (DEM) in The Gambia, West Africa: A time-series analysis of flood frequency and land cover was used to delineate differences in the vertical limits between morphological units within an alluvial floodplain. Combined with supplementary river stage data and vegetation removal techniques, these methods were used to improve the estimation of bare-earth terrain in flood modelling applications for a region with no access to high-resolution alternatives. The results demonstrate an improvement in floodplain topography for the River Gambia. The technique allows the reestablishment of small-scale complex morphology, instrumental in the routing of floodwater within a noise-filled DEM. The technique will be beneficial to flood-risk modelling applications within data sparse regions.

中文翻译：

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使用洪水频率检测增强用于水力建模的数字高程模型

摘要 中等分辨率 DEM 在数据稀疏地区（如撒哈拉以南非洲）内的大型河流系统中的洪水制图的适用性有限。我们提出了一种增强西非冈比亚 SRTM (30 m) 数字高程模型 (DEM) 的新方法：洪水频率和土地覆盖的时间序列分析用于描绘形态之间垂直界限的差异。冲积洪泛区内的单位。结合补充的河流水位数据和植被清除技术，这些方法被用于改善无法获得高分辨率替代方法的地区的洪水建模应用中裸地地形的估计。结果表明冈比亚河的洪泛区地形得到了改善。该技术允许重建小规模的复杂形态，有助于在充满噪音的 DEM 内路由洪水。该技术将有利于数据稀疏区域内的洪水风险建模应用。