COS 91-1 - Coastal Ecosystems Improve Storm and Flooding Resilience in Puerto Rico

Abstract: As climate change worsens, flooding from extreme weather and sea-level rise continues to threaten coastal populations. Tropical storms are increasing in frequency and intensity – and they regularly cause humanitarian crises. These storms damage key energy infrastructure in isolated island states, leading to prolonged blackouts. Puerto Rico is especially vulnerable to coastal hazards because its electrical grid is still weakened from the 2017 hurricane season. In Puerto Rico, coastal ecosystems such as mangroves, coral reefs, and seagrass beds buffer shorelines and offer natural protection against future storms. To quantify how much these habitats reduce the risk of flooding damage, we used a spatial model that takes in biophysical data and estimates a coastal exposure variable. The input data consisted of GIS layers for ecosystems, geomorphology, sea-level rise, relief, and storm surge. The model used these layers to generate a vulnerability map for every 250m of coastline. Exposure is calculated on a 1-5 scale, with 1 being least exposed to hazards and 5 being most exposed. Puerto Rico’s average exposure was 2.53 with its current habitats and 3.05 if its habitats did not exist. After adding population density to the dataset, the model shows that 250,000 people live on habitat-protected coastlines that would be highly exposed if those habitats disappeared. These coastlines include major port cities with substations and fuel terminals that deliver power to the entire island. As urbanization and global warming further degrade coastal habitats, Puerto Rico loses its best defense against tropical storms. The spatial model can help prioritize which vulnerable communities receive resilience funding and where to avoid siting tourism to preserve ecosystems. Our model also considers the potential for protected areas to conserve habitats under future sea-level rise scenarios. We are currently using the model to create future exposure projections under varying degrees of ecological conservation. In future studies, we will apply the model to other states to explore relationships between populations, ecosystems, and climate across multiple land and seascapes.