Abstract
A basic data requirement of a river flood inundation model is a Digital Terrain Model (DTM) of the reach being studied. The scale at which modeling is required determines the accuracy required of the DTM. For modeling floods in urban areas, a high resolution DTM such as that produced by airborne LiDAR (Light Detection And Ranging) is most useful, and large parts of many developed countries have now been mapped using LiDAR. In remoter areas, it is possible to model flooding on a larger scale using a lower resolution DTM, and in the near future the DTM of choice is likely to be that derived from the TanDEM-X Digital Elevation Model (DEM). A variable-resolution global DTM obtained by combining existing high and low resolution data sets would be useful for modeling flood water dynamics globally, at high resolution wherever possible and at lower resolution over larger rivers in remote areas. A further important data resource used in flood modeling is the flood extent, commonly derived from Synthetic Aperture Radar (SAR) images. Flood extents become more useful if they are intersected with the DTM, when water level observations (WLOs) at the flood boundary can be estimated at various points along the river reach. To illustrate the utility of such a global DTM, two examples of recent research involving WLOs at opposite ends of the spatial scale are discussed. The first requires high resolution spatial data, and involves the assimilation of WLOs from a real sequence of high resolution SAR images into a flood model to update the model state with observations over time, and to estimate river discharge and model parameters, including river bathymetry and friction. The results indicate the feasibility of such an Earth Observation-based flood forecasting system. The second example is at a larger scale, and uses SAR-derived WLOs to improve the lower-resolution TanDEM-X DEM in the area covered by the flood extents. The resulting reduction in random height error is significant.
Highlights
Flooding accounts for a substantial proportion of the fatalities and economic losses caused by natural hazards
Original and corrected Intermediate DEM (IDEM) candidate waterline pixel heights were compared to corresponding airborne LiDAR heights (Table 1)
Averaged over the four waterlines considered, it was found that the difference between the original IDEM candidate pixel height and the corresponding LiDAR height had a standard deviation of 1.25 m and a bias of 0.38 m, while for the corrected heights the difference had a standard deviation of only 0.74 m and a similar bias
Summary
Flooding accounts for a substantial proportion of the fatalities and economic losses caused by natural hazards. Flood inundation is difficult to model due to the complexity of the mathematical equations describing the flow, and to uncertainties in the input flow rates, the bottom friction parameters and the river bathymetry These uncertainties can be partly compensated for by updating the model state with observed information as this becomes available, to help keep the model on track. Many floodplains in the developed world have been imaged with high resolution airborne LiDAR or InSAR, giving accurate DTMs that facilitate accurate flood inundation modeling This is not always the case for remote rivers in developing countries. A number of studies have used the SRTM DEM for large-scale hydraulic modeling in river and delta areas (for details see Yan et al, 2015) These have covered many aspects of hydraulic modeling, including water level and water surface slope retrieval, flood extent simulation and water level and discharge prediction. The vertical resolution of ASTER GDEM2 ranges from 7 to 14 m and the DEM contains anomalies and artifacts, leading to high elevation errors on local scales and so hampering its use for flood modeling purposes
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