Agent-based modeling to evaluate community flood adaptation strategies using cloud computing

Keywords: Sea-level rise, Decision-making, Cloud computing, Climate adaptation, Sensitivity analysis, Agent-based model
Session Type: Virtual Paper Abstract
Day: Sunday
Session Start / End Time: 2/27/2022 08:00 AM (Eastern Time (US & Canada)) - 2/27/2022 09:20 AM (Eastern Time (US & Canada))
Room: Virtual 16

Abstract

Community flood risk management (FRM) for vulnerable buildings is a challenging task in coastal communities due to uncertain climate hazards and massive high-risk buildings in floodplains. This study presents a dynamic agent-based model to evaluate alternative community adaptation strategies relying on cloud computing. We randomly generated storm surges in each year of simulation based on the Monte Carlo simulation. We chose a case study area in Miami-Dade County, Florida by considering uncertainties of local discount rate and adaptation costs. Adaptation scenarios were designed to consider cost-benefit of private risk mitigation, social vulnerability of local stakeholders, and public risk mitigation efforts. Our results showed that the average community damage based on the life-cycle cost-benefit (LCCB) model ranges from $200 million to $2 billion. Nevertheless, a 6ft public seawall with enforced building elevation policy in flood zones could more substantially reduce flood damage under uncertain sea-level rise. Our sensitivity analysis also suggested a linear relationship between community flood risk reduction and discount factors in the LCCB adaptation model.