Performance analysis of open-source DEMs in tsunami inundation modelling

In natural hazard modeling, underestimation is not acceptable, since it will produce unreliable and inadequate information for decision makers to work on during hazard mitigation planning. Including tsunami inundation modeling, result of the natural hazard models is highly sensitive to the accuracy of input data. High resolution elevation data, such as light detection and ranging (LiDAR) Digital Elevation Models (DEMs) can provide modeling results that are closer to the reality. However, gathering such high-resolution datasets is expensive, time consuming and is usually not open to public access. Moreover, required computational time with those high-resolution datasets is significantly long. Therefore, open-source DEMs such as, Advanced Land Observing Satellite (ALOS) World 3D (AW3D30), Advanced Spaceborne Thermal Emission and Reflection Radiometer Global Digital Elevation Model (ASTER GDEM) and Shuttle Radar Topography Mission (SRTM) are usually the first preferred data sets. This study aims to analyse the performances of AW3D30, ASTER GDEM, and SRTM for tsunami modeling by comparing them with high-resolution LiDAR DEM tsunami modeling results. For the selected test site of this study, among these three open-source DEMs, tsunami simulations performed with ASTER GDEM exhibits an underestimated coverage of tsunami inundation areas and the maximum flow depth values in those areas and should not be preferred. Whereas, the comparisons of the simulation results using SRTM and AW3D30 as input DEMs revealed that, inundated areas are not less than the LiDAR reference and their error is lower at land use based flow depth analysis. Therefore, AW3D30 and SRTM can be accepted to use in tsunami modeling for the test site of this study considering their limited accuracy and low resolutions, when there is no available higher resolution data with good accuracy or if a rapid hazard assessment is required. However, it should be noted that open-source DEMs may have substantial errors or inadequacy on other coastal areas with different settings. Therefore, it is advised to be cautious in the usage of open-source DEMs in tsunami inundation modeling.

Automated summary

This study analyzes the performance of AW3D30, ASTER GDEM, and SRTM in tsunami modeling. The results show that ASTER GDEM underestimates tsunami inundation areas and flow depth values, and should not be preferred. On the other hand, SRTM and AW3D30 yield results that are similar to the LiDAR reference, making them suitable for tsunami modeling at the test site.