Devastating cost of future coastal flooding for many developing nations predicted in new study frontiersin
showed that along with the coastal protection, coastal retreat is economically robust for most coastal areas. Over time, as the socioeconomic drivers change, the most appropriate adaptation strategy and rate of application may change. This may particularly take place when lower probabilitybecome more frequent due to the impact of the SLR. However, the main purpose in this study is to demonstrate the lower and the upper limits of the impacts ofchange.
The population data uses an areal dataset with 30arcsec resolution. This dataset relies on a uniform allocation model to disaggregate census estimations. This will introduce local uncertainty in values. However, the resolution of this dataset is consistent with other data used in the global-scale analysis.
No global dataset of absolute values of coastal protection is available. Rather, the DIVA database contains values of the design return periods on a sub-national basis. These were used here with an assumed probability distribution to estimate the corresponding protection levels. Although such an approach is consistent with design standards in each nation, whether such protection levels are always followed is unknown.
A commonly used depth-damage relation, Eq. , is used to estimate infrastructure damage given the depth of flooding and value of assets exposed. Although this approach has precedence in the literature, it is a global average value and will vary in specific locations giving rise to uncertainty.were estimated from integration of the probability distribution function of extreme flooding extent . Based on the results of.
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