Managing coastal flood risks involves selecting a portfolio of different strategies. Analyzing this choice typically requires a model. State-of-the-art coastal risk models provide detailed regional information, but they can be difficult to implement, computationally challenging, and potentially inaccessible. Simple economic damage models are more accessible but may not incorporate important features and thus fail to model risks and trade offs with enough fidelity to support decision making. Here, we develop a new framework to analyze coastal flood risk management. The framework is computationally inexpensive yet incorporates common features of many coastal cities. We apply this framework to an idealized coastal city and assess and optimize two objectives using combinations of risk mitigation strategies against a wide range of future states of the world. We find that optimization using combinations of strategies allows for identification of Pareto optimal strategy combinations that outperform individual strategy options.
|Original language||English (US)|
|Number of pages||13|
|Journal||Environmental Modelling and Software|
|State||Published - Sep 2019|
All Science Journal Classification (ASJC) codes
- Environmental Engineering
- Ecological Modeling