Charles Stillwell, Ph.D.
Charlie Stillwell is a Hydrologist for the South Atlantic Water Science Center’s Watershed and Statistical Hydrology Team.
I study hydrology in altered watersheds, particularly those impacted by urbanization. How does development affect flow and water quality? Can green infrastructure counteract hydrologic alteration? I use statistical, data-driven methods to understand these patterns. My research supports water resource decision makers.
Professional Experience
Hydrologist, U.S. Geological Survey, South Atlantic Water Science Center, 2018-present
Education and Certifications
Ph.D. Biological & Agricultural Engineering, North Carolina State University, 2019
M.Eng. Biological & Agricultural Engineering, North Carolina State University, 2016
B.S. Civil Engineering, Drexel University, 2014
Science and Products
Lidar-derived rasters of point density, elevation, and geomorphological features for 2013, 2015, and 2022 for the Greater Raleigh Area, North Carolina Lidar-derived rasters of point density, elevation, and geomorphological features for 2013, 2015, and 2022 for the Greater Raleigh Area, North Carolina
As part of a collaborative study with the City of Raleigh, North Carolina, the U.S. Geological Survey developed a suite of high-resolution lidar-derived raster datasets for the Greater Raleigh Area, North Carolina, using repeat lidar data from the years 2013, 2015, and 2022. These datasets include raster representations of digital elevation models (DEMs), DEM of difference, the ten most...
Datasets for Rapid Assessment of Streambank Erosion Potential for Selected Streams throughout the Greater Raleigh Area, North Carolina, 2022 Datasets for Rapid Assessment of Streambank Erosion Potential for Selected Streams throughout the Greater Raleigh Area, North Carolina, 2022
As part of a collaborative study with the City of Raleigh, North Carolina, the U.S. Geological Survey is assessing streambank erosion potential in selected stream reaches throughout the Greater Raleigh metropolitan area. Rapid field measurement techniques were used to assess streambank stability at 124 stream segments between January and March 2022. Field data were collected using the...
Data and Code for Predicting Flood Damage Probability Across the Conterminous United States Data and Code for Predicting Flood Damage Probability Across the Conterminous United States
This data release contains the associated data described in the related primary publication, "Predicting Flood Damage Probability Across the Conterminous United States" (Collins et al. [2022], see Related External Resources section). Publicly available geospatial datasets and random forest algorithms were used to analyze the spatial distribution and underlying drivers of flood damage...
Application of the North Carolina Stochastic Empirical Loading and Dilution Model (SELDM) to Assess Potential Impacts of Highway Runoff Application of the North Carolina Stochastic Empirical Loading and Dilution Model (SELDM) to Assess Potential Impacts of Highway Runoff
In 2013, the U.S. Geological Survey (USGS) in partnership with the U.S. Federal Highway Administration (FHWA) published a new national stormwater quality model called the Stochastic Empirical Loading Dilution Model (SELDM; Granato, 2013). The model is optimized for roadway projects but in theory can be applied to a broad range of development types. SELDM is a statistically-based...
Predicting flood damage probability across the conterminous United States Predicting flood damage probability across the conterminous United States
Floods are the leading cause of natural disaster damages in the United States, with billions of dollars incurred every year in the form of government payouts, property damages, and agricultural losses. The Federal Emergency Management Agency oversees the delineation of floodplains to mitigate damages, but disparities exist between locations designated as high risk and where flood damages...
Authors
Elyssa Collins, Georgina M. Sanchez, Adam Terando, Charles C. Stillwell, Helena Mitasova, Antonia Sebastian, Ross K. Meentemeyer
Evaluation of two existing flood management structures in U.S. Army Garrison Fort Gordon, Georgia, 2020 Evaluation of two existing flood management structures in U.S. Army Garrison Fort Gordon, Georgia, 2020
Two existing flood management structures in U.S. Army Garrison Fort Gordon, Georgia, were evaluated for potential retrofitting to address water-quality impacts, pursuant of U.S. Army Garrison Fort Gordon’s storm water management program. Stormwater calculations were computed according to the Georgia Stormwater Management Manual, including drainage area delineations, design-storm runoff...
Authors
Charles C. Stillwell
Science and Products
Lidar-derived rasters of point density, elevation, and geomorphological features for 2013, 2015, and 2022 for the Greater Raleigh Area, North Carolina Lidar-derived rasters of point density, elevation, and geomorphological features for 2013, 2015, and 2022 for the Greater Raleigh Area, North Carolina
As part of a collaborative study with the City of Raleigh, North Carolina, the U.S. Geological Survey developed a suite of high-resolution lidar-derived raster datasets for the Greater Raleigh Area, North Carolina, using repeat lidar data from the years 2013, 2015, and 2022. These datasets include raster representations of digital elevation models (DEMs), DEM of difference, the ten most...
Datasets for Rapid Assessment of Streambank Erosion Potential for Selected Streams throughout the Greater Raleigh Area, North Carolina, 2022 Datasets for Rapid Assessment of Streambank Erosion Potential for Selected Streams throughout the Greater Raleigh Area, North Carolina, 2022
As part of a collaborative study with the City of Raleigh, North Carolina, the U.S. Geological Survey is assessing streambank erosion potential in selected stream reaches throughout the Greater Raleigh metropolitan area. Rapid field measurement techniques were used to assess streambank stability at 124 stream segments between January and March 2022. Field data were collected using the...
Data and Code for Predicting Flood Damage Probability Across the Conterminous United States Data and Code for Predicting Flood Damage Probability Across the Conterminous United States
This data release contains the associated data described in the related primary publication, "Predicting Flood Damage Probability Across the Conterminous United States" (Collins et al. [2022], see Related External Resources section). Publicly available geospatial datasets and random forest algorithms were used to analyze the spatial distribution and underlying drivers of flood damage...
Application of the North Carolina Stochastic Empirical Loading and Dilution Model (SELDM) to Assess Potential Impacts of Highway Runoff Application of the North Carolina Stochastic Empirical Loading and Dilution Model (SELDM) to Assess Potential Impacts of Highway Runoff
In 2013, the U.S. Geological Survey (USGS) in partnership with the U.S. Federal Highway Administration (FHWA) published a new national stormwater quality model called the Stochastic Empirical Loading Dilution Model (SELDM; Granato, 2013). The model is optimized for roadway projects but in theory can be applied to a broad range of development types. SELDM is a statistically-based...
Predicting flood damage probability across the conterminous United States Predicting flood damage probability across the conterminous United States
Floods are the leading cause of natural disaster damages in the United States, with billions of dollars incurred every year in the form of government payouts, property damages, and agricultural losses. The Federal Emergency Management Agency oversees the delineation of floodplains to mitigate damages, but disparities exist between locations designated as high risk and where flood damages...
Authors
Elyssa Collins, Georgina M. Sanchez, Adam Terando, Charles C. Stillwell, Helena Mitasova, Antonia Sebastian, Ross K. Meentemeyer
Evaluation of two existing flood management structures in U.S. Army Garrison Fort Gordon, Georgia, 2020 Evaluation of two existing flood management structures in U.S. Army Garrison Fort Gordon, Georgia, 2020
Two existing flood management structures in U.S. Army Garrison Fort Gordon, Georgia, were evaluated for potential retrofitting to address water-quality impacts, pursuant of U.S. Army Garrison Fort Gordon’s storm water management program. Stormwater calculations were computed according to the Georgia Stormwater Management Manual, including drainage area delineations, design-storm runoff...
Authors
Charles C. Stillwell