Introduction

Water quality is a public health safety concern for North Carolina residents, where approximately 25% of the population — or 2.4 million people — rely on private wells for drinking water. By design, water from wells is susceptible to contamination during heavy storms. As floodwater rises, it can enter through the vents and seals of these systems, thereby introducing contaminants into water intended for human consumption. Wells impacted by stormwater intrusions are eight times more likely to have fecal matter in their water, which causes digestive illnesses. As oceans warm and the air holds more moisture, storms are becoming stronger, more frequent, and more likely to cause extreme flooding.

Local health departments across North Carolina have emphasized the importance of developing tools to evaluate the risks posed to water systems after major storms. The North Carolina Department of Health and Human Services (NC DHHS) has noted that determining the extent of water system contamination and identifying infrastructure at risk remains a critical post-storm challenge. Without reliable data, it is hard to prioritize which areas require targeted mitigation and long-term improvements.

Two Flood Events in North Carolina

In 2024 and 2025, North Carolina experienced two major weather events: Hurricane Helene and Tropical Storm Chantal. These storms caused extensive flooding, which placed additional pressure on water infrastructure across the state. 

To improve storm resiliency and support post-storm risk assessments, NASA partnered with Ed Beighley at Northeastern University, Kelsey Pieper at the University of North Carolina at Charlotte, and the NC DHHS Environmental Health Section to develop the Emergency Environmental Health Dashboard, an online data tool that leverages NASA’s historical record of satellite imagery to help assess impacts to water systems and private wells following hurricanes and storms. Funded through NASA’s Water Resources Program, this project demonstrates the potential for satellite data to enhance state and local planning efforts related to extreme weather impacts.

“This project shows the power of partnership,” said Erin Urquhart, program manager for the Water Resources Program. “By combining NASA’s global satellite record with local expertise, we can provide tools to assess the risks to communities and their water resources in the moments they need them most.”

After Hurricane Helene and Tropical Storm Chantal, the dashboard provided valuable quantifiable data to health departments, which supported their ability to evaluate water quality risks and water infrastructure damage. By identifying areas most impacted by storm-related contamination, local officials were better equipped to make strategic decisions about resource allocation and prioritize long-term mitigation measures.

Using NASA Data and ML to Assess Storm Impacts

To develop the dashboard, the science team used a suite of NASA data and modeling techniques such as machine learning to provide local health departments with flood extent and potential impacts to environmental health services like drinking water supplies and fire stations.

Identifying Flood Boundary and Damage 

The process of delineating a flood’s boundary and quantifying damages relies on a three-step process. First, the base layer of the tool establishes ground elevation using a suite of data including data from the Shuttle Radar Topography Mission (SRTM) and the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) aboard the Terra satellite. Next, it obtains flood discharge values from the National Weather Service’s National Water Model. The discharge is then transformed into an estimate of river water surface elevation using a rating curve. Finally, the water surface elevation is used to delineate the flood extent boundary.

In anticipation of flood events occurring when satellite data are not available, the team calibrated their modeling system with data from the Surface Water Ocean Topography (SWOT), Sentinel, and Landsat missions for a range of flow conditions. Then, when a flood occurs, they can produce water extent and elevation estimates in near real-time. This model is continually being improved upon as the leveraged missions collect more data each day.

“The value of our work is being able to look at what happened in the past using the historical record of satellite imagery that NASA has produced,” Beighley said, “because of data latency, satellite orbit characteristics and cloud cover challenges, real-time satellite data might not be available during a disaster.”

The third step of the tool’s process is retrieving rainfall data in near real-time using NASA’s Global Precipitation Measurement (GPM) mission. Beighley and Pieper’s team are developing methods to quickly use GPM data to predict flood damage within 4 to 12 hours.

Identifying Water Contamination Risk

One of Beighley’s students is in the process of developing a machine learning technique to identify well locations likely impacted by water contamination. The model uses NASA’s Moderate Resolution Imaging Spectroradiometer (MODIS) technology and Landsat satellites to derive dynamic land cover and vegetation characteristics, GPM data to uncover rainfall characteristics, and data from the Gravity Recovery and Climate Experiment (GRACE), GRACE Follow-on (GRACE-FO), and Soil Moisture Active Passive (SMAP) missions to help determine pre-event moisture conditions. The team is exploring whether integrating these data and applying machine learning can allow the tool to estimate locations where wells might be impacted by surface water contamination.

Mapping in the Wake of Tropical Storm Chantal

Tropical Storm Chantal put this work to the test. After making landfall on July 6, 2025, Chantal brought heavy rainfall and flooding to eight counties in central and eastern North Carolina. In response, Beighley and Pieper’s team sprang to action. When one student, Reza Jamshidi, produced a flood map of the storm, another, Yuyang Li, worked on integrating the flood extent into a dashboard. 

Yet another student, Kyla Drewry, used that information to estimate impacts to private wells and businesses. They delivered this information, as well as a data package including impact assessments for restaurants, hotels, wells, shelters, and fire stations, to the NC DHHS and environmental health specialists.

“We put our near real-time data into the context of what’s happening,” UNC Charlotte professor Kelsey Pieper said. “We want to empower health departments with actionable data to help inform their emergency decisions.” For example, knowing the number of potentially flooded businesses can help health departments anticipate personnel and resource needs.

In addition to standardized products they provide to all end users, Beighley and Pieper’s team worked to customize specific data products for specific needs. Alamance County, which was deeply impacted by Chantal, sought support for their private well sampling campaign. In response, the team provided specific Geographic Information Systems (GIS) layers that the county could integrate into their own framework, such as the flood height data. 

Since sampling the entire county would take prohibitively large financial and personnel resources, they wanted to make sure they sampled the most impacted neighborhoods that also had the highest density of wells. The team is actively validating their model with the health department’s GPS data on points of high watermarks to check the accuracy of flood height estimates. 

Across North Carolina, the team delivered real-time analysis identifying approximately 17,000 private well users impacted by flooding and 65,000 users within 100 meters of flooded areas. These insights enabled emergency managers to prioritize county-level response and outreach to more than 20% of the 300,000 residents relying on private wells across the 8 affected counties.

Co-Designing In Real Time During Hurricane Helene

Chantal wasn’t the team’s first time putting their data in action. Hurricane Helene hit North Carolina on September 24, 2024, bringing catastrophic flooding that resulted in hundreds of deaths. As the storm unfolded, Beighley and Pieper’s team distributed a decision support system showing the locations of potentially contaminated wells and flood-damaged infrastructure.

“We utilized this tool tremendously after Hurricane Helene because we’re constantly being asked how many people were affected, and we don’t have great data in North Carolina,” said Jon Fowlkes, Deputy Environmental Health Section Chief. 

But not every county had the tools or experience to act using the data. After helping DHHS assess impacts on private wells, the agency asked them to create additional resources: instructional videos and a wellhead model. Andrew Blethen, then Environmental Health Director at AppHealthCare and now at DHHS, shared hours of footage, which the team curated into disinfection tutorials posted on DHHS's YouTube channel.

They also worked with the NC Ground Water Association, DHHS, Catawba Riverkeeper, Yadkin Well Company, and university researchers to design a wellhead model. The model was distributed to every local health department in western North Carolina, which helped staff demonstrate disinfection and sampling procedures to residents.

Working in real time with Beighley and Pieper’s team, NC DHHS On-Site Water Protection Branch Head Wilson Mize was able to translate local health department needs into actionable requests.

“Ed and Kelsey do things differently than most,” Mize said. “They’re there for the counties. They’re there for us. They were there to help the community.”

Reference

Kelsey J. Pieper, Edward Beighley, et al. Responding after Hurricane Helene: Rapidly Estimating Impacts to Environmental Health Services in North Carolina. Environ. Sci. Technol. Lett. 2025, 12, 7, 820–826. DOI: https://doi.org/10.1021/acs.estlett.5c00503