Uncertainties in coastal infrastructure’s exposure to sea level rise and storm surge flooding: a long-term analysis in the San Francisco Bay Area between 2000 and 2100

Authors: Yiyi He*, UC Berkeley, Yang Ju, University of California Berkeley, Sarah lindbergh, University of California, Berkeley
Topics: Hazards and Vulnerability, Geographic Information Science and Systems, Environmental Science
Keywords: Climate Change, Hydro-dynamic Modeling, Transportation Fuel Sector, Uncertainty Analysis
Session Type: Paper
Day: 4/10/2018
Start / End Time: 4:40 PM / 6:20 PM
Room: Napoleon B1, Sheraton 3rd Floor
Presentation File: No File Uploaded

Climate change induced sea-level-rise (SLR) and storm surge inundation post great threats to coastal infrastructures. The uncertainties from multiple climate scenarios need to be addressed in exposure analysis as well as in engagement with stakeholders. To understand these uncertainties, San Francisco Bay Area (Bay Area) is chosen as the study site due to the high concentration of transportation fuel sector (TFS) infrastructure. It is set as an example to analyze the infrastructure exposure to rising sea level and intensified storms under various climate scenarios and planning horizons between 2000 and 2100. For each climate scenario and planning horizon combination, a hydrodynamic model was employed to simulate coastal flooding surfaces during a 72-hour window with the highest sea level representing the worst case in that combination. We then intersected the simulated surfaces with TFS infrastructures to identify their flooding exposure and communicated the results with TFS stakeholders to identify their adaptation options. The results showed increased exposure and greater uncertainties over the century, and lessons were learned during the engagement process. This research highlights the importance of uncertainties in climate change exposure analysis and stakeholder outreach.

Abstract Information

This abstract is already part of a session. View the session here.

To access contact information login