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Two linear methods, including the simple linear addition and linear addition by expansion, and numerical simulations were employed to estimate storm surges and associated flooding caused by Hurricane Andrew for scenarios of sea level rise (SLR) from 0.15 m to 1.05 m with an interval of 0.15 m. The interaction between storm surge and SLR is almost linear at the open Atlantic Ocean outside Biscayne Bay, with slight reduction in peak storm surge heights as sea level rises. The nonlinear interaction between storm surges and SLR is weak in Biscayne Bay, leading to small differences in peak storm surge heights estimated by three methods. Therefore, it is appropriate to estimate elevated storm surges caused by SLR in these areas by adding the SLR magnitude to storm surge heights. However, the magnitude and extent of inundation at the mainland area by Biscayne Bay estimated by numerical simulations are, respectively, 22–24 % and 16–30 % larger on average than those generated by the linear addition by expansion and the simple linear addition methods, indicating a strong nonlinear interaction between storm surge and SLR. The population and property affected by the storm surge inundation estimated by numerical simulations differ up to 50–140 % from that estimated by two linear addition methods. Therefore, it is inappropriate to estimate the exacerbated magnitude and extent of storm surge flooding and affected population and property caused by SLR by using the linear addition methods. The strong nonlinear interaction between surge flooding and SLR at a specific location occurs at the initial stage of SLR when the water depth under an elevated sea level is less than 0.7 m, while the interaction becomes linear as the depth exceeds 0.7 m.

The potential impacts of sea level rise (SLR) on 95% of the land areas of the Florida Keys were estimated through analysis of a digital elevation model (DEM) derived from airborne light detection and ranging (LiDAR) measurements in a geographic information system. The topographic detail of the LiDAR DEM allowed projections of land, population, and property inundation in 0.15 m increments across a broad range of SLR scenarios for the next century. The results showed that a 0.6 m SLR by 2100 would inundate about 70% of the total land surface, but smaller percentages of the population (17%) and real property (12%). A 1.5 m rise in sea level during the same period would inundate 91% of the land surface, 71% of the population and 68% of property in the study area. Comparison of inundation dynamics indicates that the Lower Florida Keys are more susceptible to SLR than the Upper Florida Keys. The inundation dynamics exhibit non-linear behavior and demonstrate tipping points in inundation processes beyond which the inundation of land, population, and property speeds up. Acceleration of SLR will amplify the non- linear inundation, causing tipping points to be reached sooner.

By analyzing a digital elevation model (DEM) derived from airborne light detection and ranging (LIDAR) data and airborne height finder measurements, this study demonstrates that a 1.5 m sea-level rise by 2100 would cause inundation of large areas of Miami-Dade County, southern Broward County, and Everglades National Park. Inundation processes are non-linear: inundation is gradual before reaching a threshold, and speeds up rapidly afterwards due to the regional topography. Accelerated sea-level rise will cause the threshold to be reached sooner by amplifying the non-linear inundation, and must be considered in policy-making. Comparison of inundated areas extracted from 30 m LIDAR and USGS DEMs indicates that the vertical accuracy of a DEM has a great effect on delineation of inundation areas. For a 1.5 m sea-level rise, the inundated area delineated by USGS DEM for Broward County is 1.65 times greater than that indicated by the LIDAR DEM.

One of the most certain consequences of global warming is an increase of global (eustatic) sea level. The resulting inundation from rising seas will heavily impact low-lying areas; at least 100 million persons live within one meter of mean sea level and are at increased risk in the coming decades. The very existence of some island states and deltaic coasts is threatened by sea level rise. An additional threat affecting some of the most heavily developed and economically valuable real estate will come from an exacerbation of sandy beach erosion. As the beach is lost, fixed structures nearby are increasingly exposed to the direct impact of storm waves, and will ultimately be damaged or destroyed unless expensive protective measures are taken. It has long been speculated that the underlying rate of long-term sandy beach erosion is two orders of magnitude greater than the rate of rise of sea level, so that any significant increase of sea level has dire consequences for coastal inhabitants. We present in this paper an analytical treatment that indicates there is a highly multiplicative association between long-term sandy beach erosion and sea level rise, and use a large and consistent data base of shoreline position field data to show that there is reasonable quantitative agreement with observations of 19th and 20th century sea levels and coastal erosion. This result means that the already-severe coastal erosion problems witnessed in the 20th century will be exacerbated in the 21st century under plausible global warming scenarios.