The Maldives, an island nation south of India, is extremely vulnerable to sea level rise. With 80% of the nation only around 1 metre above sea level, it is predicted that approximately 77% of its land area will be underwater by 2100. Measures have been taken by authorities to mitigate potential damages brought by sea level rise and extreme weather.
Earth.Org has mapped what extreme flooding could look like by 2100 to illustrate the need for action.
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Known as the “ Treasure Island”, Maldives is made up of 26 ringed shaped atolls and with a population of 450,000. The nation is also the flattest country on Earth making it extra sensitive to small changes in sea level.
Headlines warning of the island states imminent submersion seems to have numbed the general public. Since the 1950s sea level in and around the Maldives has been rising fast on a geophysical scale, but a rate of 0.8 to 1.6 millimetre per year can seem slow to humans. 2100 seems far away, but in a person’s lifetime, the Maldives could experience a 50-centimetre sea level rise and lose around 80% of its land. If sea level were to rise by 1 metre, which seems like according to a recent Climate Central article, the islands would lose 85% of their surface to the ocean.
Much of its housing and critical infrastructures, such as hospitals, airports and harbours, are concentrated on the coastline. Extreme levels of sea rise will not be necessary to force costly adaptation or relocation. It may not be economically feasible to save the island, but maybe the possibility of losing this idyllic island to the oceans will stir some into action.
Earth.Org has modelled what mild and extreme flooding events could look like in the Maldives’ most populous island, Malé by 2100 under a high emissions scenario as a call for awareness.
Sea level rise projections by 2100 for two scenarios with the amount of rise in meters indicated (mild = 1m; extreme = 3m). Population displacement indicated bottom right.
Methodology
Global mean sea level is projected to rise by 2m at the end of this century. However, in order to determine local sea level rise (SLR), one has to take into account local coastal flood levels which could be 2.8m above Mean Higher-High Water (MHHW) at extreme forecasts. These local levels bring variability to the projected SLR from 1m to 6.5m (eg. Rio vs Kolkata).
The SLR scenarios used in this study are based on the forecasts from Climate Central – Coastal Risk Screening Tool with the following parameters:
- Sea level Projection Source
- Coastal Flood Level
- Pollution Scenario
- Luck
Sea level Projection Source
From two highly cited journals by Kopp et al., estimating SLR mainly due to ocean thermal expansion and ice melt. The mid-range scenario projected 0.5-1.2m of SLR based on different representative concentration pathways (RCP) defined by the IPCC. While the pessimistic scenario added more mechanisms of ice-sheet melting, estimating SLR at 1m-2.5m in 2100, with a projection of 10m SLR at 2300.
Coastal Flooding
More frequent coastal flooding is a direct impact of sea-level rise. Based on the Global tides and surge reanalysis by Muis et al., (2016), it is estimated that the extreme coastal water level could be from 0.2 – 2.8m over the mean level. While in extreme cases like China and the Netherlands it could experience 5-10m of extreme sea levels. Here, the coastal local flood level is added on top of the projected SLR.
Pollution Scenario
Allows choosing the RCP, the greenhouse gas concentration trajectory defined by the IPCC. The mild level is based on RCP4.5, of 2°C temperature rise; while the Extreme level is based on RCP 8.5, of 4°C temperature rise.
Luck
Applies to the baseline SLR, defined in the “Sea level projection” section, upon which we add flooding. “Mild” refers to the mid-range scenario of 0.5-1.2m, and “extreme” to the pessimistic scenario of 1-2.5m. We used the high-end value of each scenario (mild = 1m; extreme = 2.5m).
Mapping and methodology by Braundt Lau.
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References:
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Kulp, Scott A., and Benjamin H. Strauss. “New elevation data triple estimates of global vulnerability to sea-level rise and coastal flooding.” Nature communications 10.1 (2019): 1-12.
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Florczyk, A. J., Corbane, C., Ehrlich, D., Freire, S., Kemper, T., Maffenini, L., Melchiorri, M., Politis, P., Schiavina, M., Sabo, F. & Zanchetta, L. (2019). GHSL Data Package 2019 Public Release.
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Kopp, R. E., DeConto, R. M., Bader, D. A., Hay, C. C., Horton, R. M., Kulp, S., Oppenheimer, M., Pollard, D. & Strauss, B. H. (2017). Evolving Understanding of Antarctic Ice-Sheet Physics and Ambiguity in Probabilistic Sea-Level Projections. Earth’s Future, 5(12), 1217–1233.
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Kopp, R. E., Horton, R. M., Little, C. M., Mitrovica, J. X., Oppenheimer, M., Rasmussen, D. J., Strauss, B. H. & Tebaldi, C. (2014). Probabilistic 21st and 22nd Century Sea-Level Projections at a Global Network of Tide-Gauge Sites. Earth’s Future, 2(8), 383–406.
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Kulp, S. A. & Strauss, B. H. (2019). New Elevation Data Triple Estimates of Global Vulnerability to Sea-Level Rise and Coastal Flooding. Nature Communications, 10(1), 4844. Retrieved June 21, 2020, from http://www.nature.com/articles/s41467-019-12808-z
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Muis, S., Verlaan, M., Winsemius, H. C., Aerts, J. C. J. H. & Ward, P. J. (2016). A Global Reanalysis of Storm Surges and Extreme Sea Levels. Nature Communications, 7.