The Optimum Economic Response to Substantial Sea-Level Rise is Wide-spread Protection of Developed Coastal Areas

Rapid sea-level rise<!–[if supportFields]> XE “sea-level rise (SLR)” <![endif]–><!–[if supportFields]><![endif]–> (> 1 m/century) raises concern as it is believed that this would lead to large losses and a widespread forced coastal retreat. Anthoff et al. (2010) aimed to estimate economic damages caused by substantial sea-level rise and clarify the extent societies can protect themselves from rising sea levels. While the costs of sea-level rise increase with greater rise due to growing damage and protection costs, the integrated assessmentmodel (FUND) suggests that an optimum response in a benefit-cost sense remains widespread protection of developed coastal areas. The benefits of protection increase significantly with time due to the economic growth assumed in the SRES socio-economic scenarios. In terms of the four components of costs considered in FUND, protection dominates, with substantial costs from wetland loss. The regional distribution of costs shows that a few regions experience most of the costs, especially East and South Asia, North America, and Europe<!–[if supportFields]> XE “Europe” <![endif]–><!–[if supportFields]><![endif]–>. The analysis and computer model contain some limitations so that protection may not be as widespread as suggested in the FUND results. However, the FUND analysis shows that protection is more likely and rational than is widely assumed, even with a large rise in sea level. —Michelle Schulte
Anthoff, D., Nicholls, R., Tol, R., 2010. The economic impact of substantial sea-level rise<!–[if supportFields]> XE “sea-level rise (SLR)” <![endif]–><!–[if supportFields]><![endif]–>.
Mitigation and Adaptation Strategies for Global Change 15, 321–355.

The authors utilize the Coastal Module of FUND 2.8n to calculate damages caused by various scenarios of sea-level rise<!–[if supportFields]> XE “sea-level rise (SLR)” <![endif]–><!–[if supportFields]><![endif]–> over the next century. The model is driven by five distinct socio-economic scenarios (four well-known SRES scenarios and a control scenario) of population and GDP (gross domestic product) growth on a per country scale. Sea-level rise is treated as a linear interpolation with three distinct scenarios of 0.5 m, 1.0 m, and 2.0 m above 2005 sea levels in 2100. Rising sea levels are assumed to have four damage cost components: the value of dryland cost, the value of wetland cost, the cost of protection (with dykes) against rising sea levels and the costs of displaced people that are forced to leave their original place of settlement due to dryland loss. FUND determines the peak amount of protection based on the socio-economic situation, the expected damage of sea-level rise if no protection existed, and the necessary protection costs.
The number of people displaced is a linear function of dryland loss and the average population density in a country. The area of dryland loss is assumed to be a linear function of sea-level rise<!–[if supportFields]> XE “sea-level rise (SLR)” <![endif]–><!–[if supportFields]><![endif]–> and protection level up to 2 m of sea-level rise. Wetland value, on the other hand, is assumed to be proportional to per capita income with a correction for wetland scarcity and a cap. Conceptually, the value of wetlands at first rises very rapidly with income, but it increases much more slowly if incomes and wetland values are very high. The average annual protection costs are assumed to be a bilinear function of the rate of sea-level rise as well as the proportion of the coast that is protected. The level of protection is based on a cost-benefit analysis that compares the costs of protection (the actual construction of the protection and the value of the wetland lost due to the protection) with the benefits, i.e. the avoided dryland loss. The authors also continue on to create functions to control for the value of the wetlands lost due to protection and the value of the dryland lost if no protection takes place. Lastly, Anthoff et al. used a standard Ramsey discount rate to compute the net present value total damage costs for the period of 2005–2100.
First, the authors analyzed the global damage costs by socio-economic and sea-level rise<!–[if supportFields]> XE “sea-level rise (SLR)” <![endif]–><!–[if supportFields]><![endif]–> scenario. Anthoff et al. found that while the choice of socio-economic scenario has an influence on the global damage costs from sea-level rise, the damage costs vary more depending on the sea-level rise scenario. The damage costs for a 1 m rise are between 4.8 and 5.2 times as high as the damage costs for the 0.5 m sea-level rise, depending on the scenario. The increase in costs from 1 m to 2 m is only 2.0 times the damage cost of the 1 m sea-level rise scenario. The overall difference between the SRES scenarios is small.
Secondly, the authors broke apart the damage costs by socio-economic and sea-level rise<!–[if supportFields]> XE “sea-level rise (SLR)” <![endif]–><!–[if supportFields]><![endif]–> scenarios. At a 0.5 m sea-level rise, protection costs followed by wetland loss are the most important damage cost component for each socio-economic situation. Protection costs are affected by dryland loss and migration costs more so than the socio-economic scenario. When the sea-level rise is then increased to 1.0 m, the wetland costs are the damage components that react roughly linearly. Protection costs increase between 4.2 to 6.6 times compared to the lower sea-level rise while dryland loss and migration costs increase by an order of magnitude. While the step from 0.5 m to 1 m sea-level rise changed the distribution of costs between the four components significantly, the step to the 2 m scenario has no such surprises. All costs roughly double compared to the 1 m scenario. This is not surprising since the model does not have a change in cost assumptions in this step.
Thirdly, sea-level rise<!–[if supportFields]> XE “sea-level rise (SLR)” <![endif]–><!–[if supportFields]><![endif]–> damages are not evenly distributed over the world. The regional distribution of the costs shows that a few regions experience most of the costs, especially South Asia, South America, North America, Europe<!–[if supportFields]>XE “Europe” <![endif]–><!–[if supportFields]><![endif]–>, East Asia, and Central America. Next, under a scenario of no protection, the costs of sea-level rise increase greatly due to the increase in land loss and population displacement; this scenario shows the significant benefits of the protection response in reducing the overall costs of sea-level rise. Furthermore, dikes along the coastline can significantly lower total damages, but only when economic growth enables this sometimes costly investment in protection to occur. Hence protection and economic growth are coupled. In densely populated and rich countries, dike building has a high return in that a small expense prevents substantial damage. If people are dispersed and poor, the pay-off to coastal protection is much smaller. For the 0.5 m sea-level rise, total damages are between 3.4 and 3.7 times higher when no protection is built for that scenario. For 1 m and 2 m sea-level rise the damages in the no-protection scenario are only around 1.4 times as high compared to a protection scenario. This change is due to an increase in magnitude of protection costs as illustrated previously.

Protection may not become as widespread as suggested in this analysis, especially for the 2 m sea-level rise<!–[if supportFields]> XE “sea-level rise (SLR)” <![endif]–><!–[if supportFields]><![endif]–> scenario. The aggregated scale of analysis in FUNDmay overestimate the extent of likely protection in certain countries. Also, the SRES socio-economic scenarios are quite optimistic about future economic growth. Lower growth will reduce the capactiy to protect. The benefit-cost approach implies a proactive approach to protection, while historical experience shows that protection is in reaction to actual or near coastal disaster. Lastly, the economics of who pays and who benefits in coastal protection influence society’s choices and ability to protect the coast. Despite all of this, the authors assert that the FUND analysis shows that protection is more likely and rational than is widely assumed, even with a large rise in sea level.

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