Date of Award
Master of Science (MS)
Atmospheric and Earth Science
Thomas L. Sever
Digital elevation models., Floodplains--Monitoring., Flood forecasting., Niger., West Africa.
Recent data has estimated annual flood loss at over 2.3 billion of dollars in damage a year globally, a figure likely to increase as populations grow, people move to flood prone areas, and flooding dynamics change. Digital Elevation Models (DEMs) are a primary input into many flood models; therefore, the accuracy and resolution of these data sets have implications for model accuracy yet are incompletely understood. In this age of technology, more DEMs are becoming open and freely available which leads to decision makers needing to understand which is best for their specific use case. This study compares the absolute vertical accuracy of four global and freely available DEMs, SRTM, ASTER, ALOS, and MERIT to a high-resolution LiDAR DEM, then applies the Height Above Nearest Drainage (HAND) model to these five DEMs to investigate the impact of resolution and error on the flood extent. The ALOS DEM showed the lowest RMSE of 1.19 m in comparison to the LiDAR data, while ASTER had the highest RMSE of 4.2 m. The results of the HAND model showed that at floods under three meters, the higher resolution DEMs had less flood extent; however, once the flood height exceeded the three meters the higher the resolution the DEM, the larger the flood extent. These findings suggest that it is important to address both absolute error and relative error as well as resolution when applying a DEM to a flood model.
Muench, Rebekke, "Assessment of global elevation model errors impact on flood extents in southern Niger" (2020). Theses. 313.