Climate change is raising global sea levels and threatening coasts around the world with increased risk of flooding. In California, 600,000 people are at risk of flooding in a scenario with 2 meters of sea level rise combined with a 100 year storm (Barnard et al. 2019). The population bordering San Francisco Bay accounts for two-thirds of future flooding impacts in California, and the cost of building a Bay-wide seawall for the combination of 2 meters of sea level rise and a 100 year storm could reach $450 billion (Barnard et al. 2019). There is ample evidence for the beneficial role that wetlands can play in reducing flood risks, in addition to providing other co-benefits (Narayan et al. 2017; Foster-Martinez et al. 2018; Pinsky, Guannel, and Arkema 2013; Reed et al. 2018; Callaway et al. 2012). In California and the Bay Area, there is strong interest across sectors to invest in nature-based adaptation. While coastal development has altered or removed about 90% of the Bay’s historic tidal wetlands (Veloz et al. 2013), restoring part of the Bay’s shoreline can help communities adapt to sea level rise. High and rising flood risk and opportunity for wetland conservation and restoration make San Francisco Bay well suited to serve as a study site for an investigation of the potential for marshes as nature-based solutions for flood defense – in particular, how marsh habitat conservation and restoration can protect the county’s levee system from overtopping, breaching, and hydraulic failure. The Coastal Resilience Lab at UCSC is looking for an undergraduate student to work with graduate student Rae Taylor-Burns and professor Borja Reguero to advance this work through a mixture of field and computer tasks.
Possible tasks include:
• Field surveys of Bay Area marshes and levees to create a dataset detailing levee height and vegetation types and densities in key marshes fronting vulnerable sections of the levee system
• Analysis of data from NOAA tide gauges and buoys to investigate historical extreme water levels in San Francisco Bay
• Explore machine learning approaches to predict levee overtopping
• Creation of an Esri StoryMap that showcases the work done over the summer
If the project team is selected for the award, the undergraduate student will receive compensation of
$4000 and will be expected to work ~200 hours on the project over the course of summer quarter. There will be an opportunity to present findings at a lab meeting at the end of the summer, and potentially other opportunities to present if the student is interested. How to apply Please email email@example.com by March 7 if you are interested.
Include in your email:
• Why you are interested in this project
• Any relevant coursework or experience you have