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利用泛滥范围预测洪水事件后私人水井中的微生物污染。

Using Inundation Extents to Predict Microbial Contamination in Private Wells after Flooding Events.

机构信息

Department of Civil and Environmental Engineering, Northeastern University, Boston, Massachusetts 02115, United States.

Department of Biological Sciences, University of Alabama, Tuscaloosa, Alabama 35401, United States.

出版信息

Environ Sci Technol. 2024 Mar 26;58(12):5220-5228. doi: 10.1021/acs.est.3c09375. Epub 2024 Mar 13.

DOI:10.1021/acs.est.3c09375
PMID:38478973
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10976889/
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.

摘要

对于依赖私人水井的居民来说,灾难恢复带来了独特的挑战。洪水事件是井水微生物污染的驱动因素,但观察到的洪水与污染之间的关系有很大差异。在这里,我们研究了不同洪水边界(联邦应急管理局 100 年洪水危险边界、距最近排水引发的泛滥范围的高度以及达特茅斯洪水观测站的卫星衍生范围)在识别飓风佛罗伦萨后井水污染方面的性能。使用这些洪水边界,我们估计约 2600 口井到 108400 口私人水井可能被淹没——根据使用的边界,差异超过两个数量级。使用州生成的常规和佛罗伦萨后测试数据,我们观察到在三种洪水边界内,微生物污染率比常规条件高 7.1-10.5 倍。然而,洪水边界识别受污染样本的能力因洪水类型(例如河流、漫滩、沿海)而异。虽然佛罗伦萨后测试的参与度增加,但总体而言,测试率仍然很低。只有不到 1%的水井接受了测试,因此迫切需要加强水井水质测试工作。这项工作提供了对淹没测绘技术的优势和局限性的理解,这对于指导灾后井水应对和恢复至关重要。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8612/10976889/26e2bca8b059/es3c09375_0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8612/10976889/1b270b70308a/es3c09375_0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8612/10976889/a6714b999171/es3c09375_0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8612/10976889/806d681a7d66/es3c09375_0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8612/10976889/26e2bca8b059/es3c09375_0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8612/10976889/1b270b70308a/es3c09375_0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8612/10976889/a6714b999171/es3c09375_0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8612/10976889/806d681a7d66/es3c09375_0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8612/10976889/26e2bca8b059/es3c09375_0004.jpg

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