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Drewry KR, Jones CN, Hayes W, Beighley RE, Wang Q, Hochard J, Mize W, Fowlkes J, Goforth C, Pieper KJ. Using Inundation Extents to Predict Microbial Contamination in Private Wells after Flooding Events. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2024; 58:5220-5228. [PMID: 38478973 DOI: 10.1021/acs.est.3c09375] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/27/2024]
Abstract
Disaster recovery poses unique challenges for residents reliant on private wells. Flooding events are drivers of microbial contamination in well water, but the relationship observed between flooding and contamination varies substantially. Here, we investigate the performance of different flood boundaries─the FEMA 100 year flood hazard boundary, height above nearest drainage-derived inundation extents, and satellite-derived extents from the Dartmouth Flood Observatory─in their ability to identify well water contamination following Hurricane Florence. Using these flood boundaries, we estimated about 2600 wells to 108,400 private wells may have been inundated─over 2 orders of magnitude difference based on boundary used. Using state-generated routine and post-Florence testing data, we observed that microbial contamination rates were 7.1-10.5 times higher within the three flood boundaries compared to routine conditions. However, the ability of the flood boundaries to identify contaminated samples varied spatially depending on the type of flooding (e.g., riverine, overbank, coastal). While participation in testing increased after Florence, rates were overall still low. With <1% of wells tested, there is a critical need for enhanced well water testing efforts. This work provides an understanding of the strengths and limitations of inundation mapping techniques, which are critical for guiding postdisaster well water response and recovery.
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Affiliation(s)
- Kyla R Drewry
- Department of Civil and Environmental Engineering, Northeastern University, Boston, Massachusetts 02115, United States
| | - C Nathan Jones
- Department of Biological Sciences, University of Alabama, Tuscaloosa, Alabama 35401, United States
| | - Wesley Hayes
- Department of Civil and Environmental Engineering, Northeastern University, Boston, Massachusetts 02115, United States
| | - R Edward Beighley
- Department of Civil and Environmental Engineering, Northeastern University, Boston, Massachusetts 02115, United States
| | - Qi Wang
- Department of Civil and Environmental Engineering, Northeastern University, Boston, Massachusetts 02115, United States
| | - Jacob Hochard
- Haub School of Environment and Natural Resources, University of Wyoming, Laramie, Wyoming 82072, United States
| | - Wilson Mize
- Division of Public Health, North Carolina Department of Health and Human Services, Raleigh, North Carolina 27609, United States
| | - Jon Fowlkes
- Division of Public Health, North Carolina Department of Health and Human Services, Raleigh, North Carolina 27609, United States
| | - Chris Goforth
- State Laboratory of Public Health, North Carolina Department of Health and Human Services, Raleigh, North Carolina 27609, United States
| | - Kelsey J Pieper
- Department of Civil and Environmental Engineering, Northeastern University, Boston, Massachusetts 02115, United States
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Deriving River Discharge Using Remotely Sensed Water Surface Characteristics and Satellite Altimetry in the Mississippi River Basin. REMOTE SENSING 2022. [DOI: 10.3390/rs14153541] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/04/2023]
Abstract
River discharges are critical for understanding hydrologic and ecological systems, yet in situ data are limited in many regions of the world. While approximating river discharge using satellite-derived water surface characteristics is possible, the key challenges are unknown channel bathymetry and roughness. Here, we present an application for merging mean river-reach characteristics and time-varying altimetry measurements to estimate river discharge for sites within the Mississippi River Basin (USA). This project leverages the Surface Water and Ocean Topography (SWOT) River Database (SWORD) for approximating mean river-reach widths and slopes and altimetry data from JASON-2/3 (2008-Present) and Sentinel-3A/B (2015-Present) obtained from the Hydroweb Theia virtual stations. River discharge is calculated using Manning’s Equation, with optimized parameters for surface roughness, bottom elevation, and channel shape determined using the Kling–Gupta Efficiency (KGE). The results of this study indicate the use of optimized characteristics return 87% of sites with KGE > −0.41, which indicates that the approach provides discharges that outperform using the mean discharge. The use of precipitation to approximate missing flows not observed by satellites results in 66% of sites with KGE > −0.41, while the use of TWSA results in 65% of sites with KGE > −0.41. Future research will focus on extending this application for all available sites in the United States, as well as trying to understand how climate and landscape factors (e.g., precipitation, temperature, soil moisture, landcover) relate to river and watershed characteristics.
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