Hurricane pop-up collage.

In the wake of Hurricane Florence, which killed over fifty people in the Carolinas in September 2018 and caused more than $20 billion in damage, Bass Connections launched a pop-up theme to explore the evolving challenges of hurricane preparedness and resiliency in an age of climate change. From January 2019-May 2020, five teams examined the environmental, agricultural and economic effects of tropical storms in the south, in order to support future emergency preparedness and storm recovery efforts.

By the Numbers

Hurricane pop-up numbers

Team Summaries

Developing Data Tools for Natural Disasters: Implementing Best Practices for Electricity-dependent Medicaid Enrollees

Faculty leaders: Margolis Center for Health Policy (Hilary Campbell) and School of Medicine: Population Health Sciences (Aaron McKethan)

Student participation: 8 undergraduates, 3 graduate students

Community partners: North Carolina Department of Health and Human Services

Geographical focus: North Carolina, Florida, New Jersey

This project team developed algorithms using Medicaid claims data to identify patients who rely on electricity-dependent medical equipment or refrigeration-sensitive medications. When preparing for a crisis such as a hurricane, the resulting list of high-risk patients can be securely shared with emergency responders and local health departments to prioritize recovery efforts. 

The team also interviewed policy, public health, and emergency response officials in North Carolina, Florida and New Jersey to identify best practices and provide state leaders with tools, documentation and training to support emergency preparedness in advance of new storms. 

Understanding Natural and Human Initiation and Transmission of Cascading Hazards (UNHITCH)

Faculty leaders: Nicholas School of the Environment: Environmental Sciences and Policy (Elizabeth Albright, Luana Lima), Pratt School of Engineering: Civil & Environmental Engineering (Mark Borsuk)

Student participation: 9 undergraduates, 3 graduate students

Community partners: Duke Energy, North Carolina Department of Environmental Quality, Duke Data & Visualization Services, Scholars Strategy Network, North Carolina General Assembly

Geographical focus: North Carolina

In September 2018, Hurricane Florence caused $38 billion in damages and 53 fatalities in North Carolina and exemplified how disasters can cause a cascade of secondary and tertiary effects. This project team studied the cascading disasters that occurred in North Carolina as a result of the hurricane, including widespread power outages, coal ash spills and hog-waste lagoon overflows.

Using news analysis, stakeholder interviews, remote sensing data and GIS, the team examined relationships between system failures and environmental and socio-demographic patterns. Team members created conceptual models to identify warning signs and points of intervention, and developed policy briefs with recommendations for energy system failures, coal ash and hog farm management.

Ecological and Social Time Scales in Hurricane Response and Recovery

Faculty leaders: Nicholas School of the Environment: Marine Science and Conservation (Dana Hunt, Jessica Gronniger (postdoctoral fellow)) 

Student participation: 3 undergraduates, 1 graduate student

Community partners: Carteret County Schools; Core Sound Waterfowl Museum & Heritage Center

Geographical focus: Beaufort, North Carolina (Duke Marine Lab)

This project addressed the chemical, biological, economic, infrastructure and human impacts of Hurricane Florence as well as the post-hurricane recovery process. Building on the background and expertise of individuals from the coastal monitoring site at the Duke Marine Lab as well as geomorphic and economic research relating to hurricane response and recovery decision-making, this team explored hurricane-related changes to coastal ecosystems as well as how individual and government decisions influences the recovery and resilience of the built environment and communities.

The team also explored how ecosystems and communities in close proximity but with different geographies and/or socioeconomic histories weathered the storm differently. The team surveyed available data for storm-related changes in physical, biological, chemical, economic and cultural metrics. This work contributed to a successful grant application for a National Science Foundation Research Coordination Network: Collaboratory for Coastal Adaptation over Space & Time.

Deep Learning and Remote Sensing for Coastal Resilience and Disaster Response

Faculty leaders: Nicholas School of the Environment: Marine Science and Conservation (Patrick Gray (Ph.D. student), David Johnston, Justin Ridge) 

Student participation: 5 undergraduates, 1 graduate student

Community partners: The Nature Conservancy (Brian Boutin); National Oceanic and Atmospheric Administration (Carolyn Currin, Jenny Davis); North Carolina Division of Coastal Management (Paula Gilikin, Brandon Puckett); The Nature Conservancy (Aaron McCall); North Carolina Sentinel Site Cooperative (Sarah Spiegler)

Geographical focus: North Carolina Coastal Plain

Remote sensing plays a critical role in the study and management of coastal ecosystems. Unoccupied aerial systems (UAS, also known as drones) complement satellites and are becoming an integral tool in studying and managing coastal systems, providing on-demand remote sensing capabilities at low cost and with modular sensors that can assess a wide variety of variables.

This project team developed a methodology for long-term monitoring of land cover dynamics in the coastal Southeast United States. They did so by leveraging deep learning to automate classification of Landsat 5 satellite imagery into discrete land cover types (e.g. wetland, agriculture, forest). This land cover data continues to be analyzed to better understand long term changes (e.g. wetland migration, urban expansion) and impacts of specific events, namely hurricanes. In addition to increasing understanding of land cover change across the North Carolina Coastal Plain, the change detected in this analysis will guide future drone surveys for areas that experienced substantial change.

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