Abstract
Elevation data based on NASA’s Shuttle Radar Topography Mission (SRTM) have been widely used to evaluate threats from global sea level rise, storm surge, and coastal floods. However, SRTM data are known to include large vertical errors in densely urban or densely vegetated areas. The errors may propagate to derived land and population exposure assessments. We compare assessments based on SRTM data against references employing high-accuracy bare-earth elevation data generated from lidar data available for coastal areas of the United States. We find that both 1-arcsecond and 3-arcsecond horizontal resolution SRTM data systemically underestimate exposure across all assessed spatial scales and up to at least 10m above the high tide line. At 3m, 1-arcsecond SRTM underestimates U.S. population exposure by more than 60%, and under-predicts population exposure in 90% of coastal states, 87% of counties, and 83% of municipalities. These fractions increase with elevation, but error medians and variability fall to lower levels, with national exposure underestimated by just 24% at 10m. Results using 3-arcsecond SRTM are extremely similar. Coastal analyses based on SRTM data thus appear to greatly underestimate sea level and flood threats, especially at lower elevations. However, SRTM-based estimates may usefully be regarded as providing lower bounds to actual threats. We additionally assess the performance of NOAA’s Global Land One-km Base Elevation Project (GLOBE), another publicly-available global DEM, but do not reach any definitive conclusion because of the spatial heterogeneity in its quality.
Highlights
Understanding the exposure of coastal nations and communities to sea level rise and coastal flooding is critical in informing policymakers about the potential benefits of protective strategies, as well as in building awareness of the tangible effects of climate change
At the municipality and county levels, to prevent very large relative error values occurring due to exceptionally small levels of exposure in certain locations, we only consider those places in which estimated exposure under both lidar and Shuttle Radar Topography Mission (SRTM)/Global Land 1-km Base Elevation Project (GLOBE) exceeds 1% of the total population/land area of that place
We see that error variability at subnational spatial scales is high under both digital elevation models (DEMs)’s, but drops considerably at higher water heights, especially under SRTM
Summary
Understanding the exposure of coastal nations and communities to sea level rise and coastal flooding is critical in informing policymakers about the potential benefits of protective strategies, as well as in building awareness of the tangible effects of climate change. We characterize bias and variability in exposure error based on global DEMs, including any behavior with respect to flood level and spatial scale.
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