Using direct policy search to identify robust strategies in adapting to uncertain sea-level rise and storm surge. (September 2018) - Garner, Gregory G.; Keller, Klaus
Abstract: Sea-level rise poses considerable risks to coastal communities, ecosystems, and infrastructure. Decision makers are faced with uncertain sea-level projections when designing a strategy for coastal adaptation. The traditional methods are often silent on tradeoffs as well as the effects of tail-area events and of potential future learning. Here we reformulate a simple sea-level rise adaptation model to address these concerns. We show that Direct Policy Search yields improved solution quality, with respect to Pareto-dominance in the objectives, over the traditional approach under uncertain sea-level rise projections and storm surge. Additionally, the new formulation produces high quality solutions with less computational demands than an intertemporal optimization approach. Our results illustrate the utility of multi-objective adaptive formulations for the example of coastal adaptation and point to wider-ranging application in climate change adaptation decision problems. Highlights: Sea level rise poses risk to coastal communities, ecosystems, and infrastructure. Traditional formulations are often silent on tradeoffs, tail events, and learning. A multi-objective formulation allows explicit assessment of tradeoffs. Direct policy search provides endogenous state-based learning under uncertainty. Reformulating the problem could save millions on investment costs and damages.