New elevation data triple estimates of global vulnerability to sea-level rise and coastal flooding
Digital elevation models (DEMs) are used to set median coastal elevations, but this new study finds significant data gaps for coastal elevations across the Global South. A deep learning model is developed to correct for these errors, potentially tripling areas at risk.
Study link: Nature Communications (2019)
Currently, most estimates of global mean sea-level rise this century stand below 2 meters. This quantity is comparable to the positive vertical bias of NASA’s SRTM, one of the main digital elevation models (DEMs) used to assess global and national population exposures to extreme coastal water levels. This and other DEMs are biased towards northern countries where accurate elevation data (derived from detailed LiDAR scans) is available. Gravitational effects shift sea levels in complex ways and vary by latitude, and it in many regions of the world current coastal elevation levels are not accurate.
CoastalDEM is a new DEM utilizing convolutional neural networks to reduce SRTM error. Employing CoastalDEM, the study finds that 190 M people (150–250 M, 90% CI) currently occupy global land below projected high tide lines for 2100 under low carbon emissions, up from 110 M today, for a median increase of 80 M. These figures triple SRTM-based values. Under high emissions, CoastalDEM indicates up to 630 M people live on land below projected annual flood levels for 2100, and up to 340 M for mid-century, versus roughly 250 M at present. The study estimates that one billion people now occupy land less than 10 m above current high tide lines, including 230 M below 1 m.
This study has significant implications for both land use planning and development of high-population areas, as well as marine conservation planning.
Lead researchers: Scott Kulp & Benjamin Strauss, Climate Central