Risk-based flood adaptation assessment for large-scale buildings in coastal cities using cloud computing

Flood risk management (FRM) in coastal cities is a challenging task due to uncertain climate hazards under sea level rise (SLR) and large-scale vulnerable buildings within in the floodplain. This study presents a building-level adaptation framework to evaluate alternative community adaptation strategies relying on cloud computing. We incorporated multiple sources of model uncertainties and randomly generated storm surges in each year of simulation using the extreme value distribution (GEV) theory. Based on a case study in Miami-Dade County, Florida, four adaptation scenarios were designed to evaluate their effectiveness in adaptation. Our sensitivity analysis suggested a positive linear relationship between community flood risk reduction and total community adaptation costs in the life-cycle cost-benefit (LCCB) model. Our results showed that uncertainties of the total community damage based on the LCCB model ranges from $221 million to $2.75 billion. However, when considering social vulnerability, the total community damage increased substantially, ranging from $244 million to $3.44 billion. Nevertheless, a 6ft public seawall based on the upper bound of the GEV distribution with the enforced building elevation policy in flood zones could substantially reduce community flood damage under uncertain sea-level rises.

Automated summary

An adaptation framework for community strategies at the building level was proposed, which relied on cloud computing for evaluation. By incorporating multiple sources of model uncertainties and randomly generated storm surges in each year of simulation, four adaptation scenarios were designed based on a case study in Miami-Dade County, Florida. Sensitivity analysis indicated a positive linear relationship between community flood risk reduction and total community adaptation costs under the life-cycle cost-benefit (LCCB) model.