Evaluation of open-access global digital elevation models (AW3D30, SRTM and ASTER) for flood modelling purposes
- 1. Universidad Nacional Autónoma de México
Description
Elevation data in the form of Digital Elevation Models (DEMs) has been recognised as a
basic piece of information for the accurate representation of topographic controls exerted in
hydrologic and hydraulic models. Yet many practitioners rely on open-access global datasets
usually obtained from space-borne survey due to the cost and sparse coverage of sources of
higher resolution. In may 2016 the Japanese Aerospace eXploration Agency (JAXA) publicly
released an open-access global DEM at an horizontal resolution of 30 m, the ALOS World
3D-30m (AW3D30). So far no published study assessed the flood modelling capabilities of this
new product. The purpose of this investigation is twofold. Firstly, to present an assessment
of the capacity of the AW3D30 DEM for flood modelling purposes and secondly, to compare
its performance with regards to computed water levels and flood extent maps calculated using
other freely available 30 m DEMs for model setup (e.g. SRTM and ASTER GDEM). For
this comparison, the reference to reality is given by the water levels and flood extent maps
computed with the same numerical model but using a LiDAR based DEM (5 m of spatial
resolution re-sampled to 30 m). The numerical model employed in this investigation is based
on a damped partial inertia approximation of the Saint-Venant equations on a regular raster
grid, which is forced with a simple and synthetic rainfall storm event. Numerical results
using different elevation data in model setup are compared for two regions with contrasting
topographic gradients (steep and smooth). Results with regards to water depth and flood
extent show that AW3D30 DEM performs better than the SRTM DEM. Notably, in the case
of mountainous regions results derived with the AW3D30 DEM are comparable in skill to those
obtained with a LiDAR derived DSM, suggesting its suitability in the numerical reproduction
of flood events. This encouraging performance paves the way to more accurate modelling for
both data-scarce regions and global flood models.
Notes
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evaluation-dem-urban.pdf
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Additional details
Related works
- Is previous version of
- 10.31223/osf.io/vqgx4 (DOI)