Research
When I joined East Carolina University, my goal was to do research to benefit eastern North Carolina with a focus on water quality impairment of coastal bodies of water. It didn't take long for me to learn that flooding was the greatest challenge facing most eastern North Carolina communities so the use of nature based solutions and new technology to address flooding quickly became a top priority for my research.
The research team is currently leading efforts to reduce flooding through active water management on forested or agricultural lands. The team uses the latest technology in the field to better understand and quantify what is occurring in the monitored systems. The use of sensors that can collect parameters including nutrient concentrations, water flow, and soil moisture at a high temporal resolution have provided great insight into the systems that have been monitored and will continue to do so as further advances in monitoring technology are made.
The research team is currently leading efforts to reduce flooding through active water management on forested or agricultural lands. The team uses the latest technology in the field to better understand and quantify what is occurring in the monitored systems. The use of sensors that can collect parameters including nutrient concentrations, water flow, and soil moisture at a high temporal resolution have provided great insight into the systems that have been monitored and will continue to do so as further advances in monitoring technology are made.
Flood Reduction Through Wetland Restoration
Looking upstream to the Atlantic White Cedar plot from the location where the water control structure will be installed in late 2025.
The widespread flooding from Hurricanes Matthew (2016) and Florence (2018) brought flooding to the forefront of the water resources challenges being faced in eastern North Carolina. Our team has partnered with the NC Division of Soil & Water and the NC Forest Service to restore the hydrologic conditions needed for the growth of Atlantic White Cedar in one area of Bladen Lakes State Forest. The water will be actively managed prior to and during extreme rainfall events to minimize the volume and flow of water leaving the site. Outside these times of extreme rainfall, the water will be managed to better replicate the natural hydroperiod of Atlantic White Cedar forests that once covered a much larger area in the region. The ECU partners on this project include the Center for Sustainable Energy and Environmental Engineering, the Department of Engineering, the Center for IoT Engineering and Innovation, and the Department of Technology Systems.
Lake Mattamuskeet
Lake Mattamuskeet from Highway 94
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A monitoring station in a waterfowl impoundment.
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The Lake Mattamuskeet watershed has been a focus of research for the Etheridge Lab since 2016. The goal of our last National Science Foundation funded project (1940072) was to link the local knowledge of local communities with the expertise of undergraduate engineering students completing their capstone projects to develop community-driven designs to address flooding and water quality challenges. This framework was applied in the Lake Mattamuskeet watershed during the 2020-2021 school year to assist with the implementation of the Lake Mattamuskeet Watershed Restoration Plan. The use of engineering students and community engagement to advance engineering design provided a low-cost approach for resource-limited coastal communities to evaluate alternative ways of addressing the challenges facing the community.
The efforts of all the partners on this project resulted in $10 million being given to the NC Wildlife Resources Commission to dredge Outfall Canal and the North Carolina Coastal Federation being awarded over $16.8 million to implement conservation practices across the lake's watershed. Our team will be participating in the monitoring to quantify the benefits of these solutions.
We are finalizing our research on the water quality leaving waterfowl impoundments under different management schemes. The high frequency water quality monitoring allowed us to identify what conditions promote the export of nutrients to the eutrophic lake. The end goal of this research is to improve the management of the waterfowl impoundments to reduce nutrient export and improve the health of the lake. Initial results can be found in our articles published in Wetlands and Water, Air, & Soil Pollution.
The efforts of all the partners on this project resulted in $10 million being given to the NC Wildlife Resources Commission to dredge Outfall Canal and the North Carolina Coastal Federation being awarded over $16.8 million to implement conservation practices across the lake's watershed. Our team will be participating in the monitoring to quantify the benefits of these solutions.
We are finalizing our research on the water quality leaving waterfowl impoundments under different management schemes. The high frequency water quality monitoring allowed us to identify what conditions promote the export of nutrients to the eutrophic lake. The end goal of this research is to improve the management of the waterfowl impoundments to reduce nutrient export and improve the health of the lake. Initial results can be found in our articles published in Wetlands and Water, Air, & Soil Pollution.
Coastal Agriculture and Watershed Resiliency
We are in the middle phases of a large interdisciplinary project funded by the National Science Foundation (2009185). The goal of this project is to evaluate how perceptions of ecosystem health, various policies, and sea level rise alter land use decisions by farmers, which can change ecosystem outcomes. This will be accomplished through coupling a human systems model (perception and policy) with a natural systems model (land use and ecosystem outcomes). The results of this work can be applied both in and outside of our study watershed to support rural agricultural economies and promote healthy ecosystems. The Tar-Pamlico River basin is the focus of this study. Our lab is responsible for calibrating and validating a SWAT+ model for the watershed that can be integrated with a human systems model. Some of our initial results have been published in Science of the Total Environment, Journal of Environmental Management, and Journal of Hydrology: Regional Studies.
Well Water Safety
Private wells are the drinking water source for over 43 million U.S. households and could potentially be vulnerable to contamination. The goal of this research was to identify households in North Carolina most likely to be exposed to contaminants during severe weather. Our team attempted to use econometric and machine learning techniques combined with statewide well water quality, hydrological, and meteorological data to predict contamination during extreme events. One of our findings was that machine learning models using weather and readily available soil information were not successful in predicting contamination risk for nitrate. The low level of contamination likely contributed to the poor performance of the models. More information on these models can found in the Journal of the American Water Resources Association article. This work was supported by the Environmental Protection Agency (R840181 and RD836942) and the National Science Foundation (1902282).
Public Engagement in Science
Through projects funded by the National Science Foundation (1644650) and the United States Fish and Wildlife Service, our lab has worked with citizens of Bogue Banks and Hyde County, respectively, to solve water related problems that are being faced by their communities. For the project on Bogue Banks, citizen scientists collected groundwater and surface water level data to improve the modeling of groundwater and surface water interactions on the island. The Hyde County project was focused on learning about water management on agricultural operations that use pumps to control drainage.
Past Research Projects
- Quantifying the water quality benefits of a constructed brackish marsh and tidal stream system located downstream of row crop agricultural production.
- Improving the modeling of nitrogen transformation processes at the watershed scale in the INCA-N model in areas with agriculture as the predominant land use.
