GC53A-1179
Making Coastal Flood Hazard Maps to Support Decision-Making - What End Users Want

Friday, 18 December 2015
Poster Hall (Moscone South)
Jochen Schubert1, Wing H Cheung2, Adam Luke1, Timu Gallien3, Amir Aghakouchak4, David Feldman1, Richard Matthew1 and Brett F Sanders5, (1)University of California Irvine, Irvine, CA, United States, (2)University of California Irvine, Planning, Policy and Design, Irvine, CA, United States, (3)University of San Diego, San Diego, CA, United States, (4)University of California Irvine, The Henry Samueli School of Engineering, Irvine, CA, United States, (5)University of California Irvine, Civil and Environmental Engineering, Irvine, CA, United States
Abstract:
Growing awareness about accelerating Sea Level Rise (SLR) is contributing to coastal resilience initiatives around the world, with an emphasis on coastal planning, infrastructure adaptation, and emergency preparedness. Maps are the primary tool for communicating flood hazard, and their design raises two fundamental challenges: (1) representing the flood hazard in a scientifically defensible manner considering complexity associated with multiple drivers of flooding (e.g., rainfall, streamflow, storm surge, high tides, waves), urban infrastructure, and human interventions (e.g. pumping, sand bags) and (2) effectively communicating hazard information considering the specific needs of decision-makers.

In this research we rely on a hydrodynamic model of coastal flooding that can be forced by multiple drivers of flooding (rainfall, high water levels, and waves) to simulate extreme flooding scenarios at street-level resolution. Model scenarios include 20%, 10%, 5%, 2% and 1% annual exceedance probability (AEP) scenarios for each possible driver of flooding and for both present and future sea levels. The resulting flood zones and related flood depths are aggregated using GIS techniques and transformed into a set of maps depicting annual exceedance probability, multi-year flood probability, 1% AEP flooding depth, uncertainty associated with model forcing data, and road network accessibility. The usability of each map is assessed through focus group discussions with local stakeholders who have distinct decision-making needs, such as homeowners, planners, and emergency response managers. Findings from this research reveal the mapped flood risk information and visualizations preferred by different decision-makers.