Webinar on Adaptive Planning for Sea Level Rise
This is a past event.
Tuesday, November 19, 2019 at 9:30am to 11:30am
Planning adaptively for rising sea levels, supported by quick-scan tools
The South Florida Water Management District, FIU Sea Level Solutions Center, and Deltares USA have been working together on a Florida Department of Environmental Protection research grant to explore the development and use of quick-scan tools to support the adaptive planning process to prepare for rising sea levels.
On November 19, 9:30-11:30 a.m. EST, we invite you to a webinar in which we walk through the adaptive planning method, show adaptive planning outcomes for the Little-River (C-7) basin in Miami from a previously-funded NOAA project, and demonstrate a prototype for a quick-scan model that assesses adaptation options at a multi-basin scale in Miami.
Why adaptive planning?
Uncertainty in sea level rise and extreme rainfall projections makes it challenging to decide on the best investments for adaptation. Selecting options that work best under a specific projection does not give insight into how the community is protected under more rapid sea level rise, or how the community is protected further into the future than the time-stamp of the scenario.
The dynamic adaptive policy pathways (DAPP) is an alternative method of planning for sea level rise that is not dependent on a sea level rise projection. Rather, it considers how risk evolves as sea levels rise, both with and without a suite of adaptation options. The ability to reduce risk is considered when evaluating an adaptation option, but also its shelf-life: that is, how long that option will keep risk low as sea levels rise.
Why quick-scan tools?
Assessing the effectiveness of adaptation options is often an expensive and time-consuming endeavor involving complex models. The development and use of quick-scan tools can provide tremendous insight into the relative effectiveness of adaptation options. Less-effective options can be weeded out at this early phase, and the detailed modeling of adaptation options can be reserved for the most promising options.