| 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. |
| Authors |
Kyla R. Drewry  , C. Nathan Jones , Wendy Hayes , R. Edward Beighley , Qi Wang , Jacob Hochard  , Wilson Mize , Jon Fowlkes , Chris Goforth , Kelsey J. Pieper
|
| Journal Info |
American Chemical Society | Environmental Science & Technology , vol: 58
, iss: 12
, pages: 5220 - 5228
|
| Publication Date |
3/13/2024 |
| ISSN |
0013-936X |
Type |
article |
| Open Access |
hybrid
|
| DOI |
https://doi.org/10.1021/acs.est.3c09375 |
| Keywords |
Flood Risk (Score: 0.569299) , Flood Inundation Modeling (Score: 0.557417) , Urban Flooding (Score: 0.548636) , Surface Water Mapping (Score: 0.501796)
|
