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DOI10.1029/2018WR023106
Predicting geogenic Arsenic in Drinking Water Wells in Glacial Aquifers, North-Central USA: Accounting for Depth-Dependent Features
Erickson, M. L.; Elliott, S. M.; Christenson, C. A.; Krall, A. L.
2018-12-01
发表期刊WATER RESOURCES RESEARCH
ISSN0043-1397
EISSN1944-7973
出版年2018
卷号54期号:12页码:10172-10187
文章类型Article
语种英语
国家USA
英文摘要

Chronic exposure to arsenic (As) via drinking groundwater is a human health concern worldwide. Probabilities of elevated geogenic As concentrations in groundwater were predicted in complex, glacial aquifers in Minnesota, north-central USA, a region that commonly has elevated As concentrations in well water. Maps of elevated As hazard were created for depths typical of drinking water supply and with well construction attributes common for domestic wells. Conventional variables describing aquifer properties and materials, position on the hydrologic landscape, and soil geochemistry were among the most influential for predicting the probability of elevated As. We also found that certain well construction attributes were influential in predicting As hazard. Smaller distances between the top of the well screen and overlying aquitard (proximity) and shorter well screen lengths were each associated with higher probabilities of elevated As. Influential predictor variables, which are either mapped across the region or are well construction attributes, are proxies in the model for measurable physical or geochemical causes of elevated As (e.g., redox condition, till or aquifer sediment chemistry, and water chemistry), which are not mapped across the region. Our setting shares some important characteristics with deltaic and other high-As aquifers in Southeast Asia: late Quaternary age, complex layering of coarse- and fine-grained materials, low-As sediment concentrations, and geochemical controls on As mobilization. Translating three-dimensional geologic and geochemical understanding of As mobility to quantifiable variables for modeling with powerful, flexible statistical tools could improve predictions and help identify safer groundwater supply options in the USA, Southeast Asia, and elsewhere.


Plain Language Summary This study demonstrates that certain well construction attributes are influential in predicting arsenic (As) concentrations in drinking water wells. Smaller distances between the top of the well screen and overlying aquitard, and shorter well screen lengths, were each associated with higher probabilities of elevated As. Chronic exposure to As via drinking groundwater is a human health concern worldwide, and Minnesota, USA, commonly has elevated As concentrations in well water. This study describes a new, novel, and important finding from an As probability model: Controllable well construction choices (not just location or depth) influence As concentrations in drinking water from wells.


英文关键词groundwater arsenic probability model geochemistry machine learning domestic well
领域资源环境
收录类别SCI-E
WOS记录号WOS:000456949300009
WOS关键词GROUNDWATER-FLOW ; CENTRAL VALLEY ; WEST-BENGAL ; SHALLOW GROUNDWATER ; CONTAMINATION ; HYDROSTRATIGRAPHY ; SEDIMENTS ; SYSTEM ; RELEASE ; NITRATE
WOS类目Environmental Sciences ; Limnology ; Water Resources
WOS研究方向Environmental Sciences & Ecology ; Marine & Freshwater Biology ; Water Resources
引用统计
文献类型期刊论文
条目标识符http://119.78.100.173/C666/handle/2XK7JSWQ/21554
专题资源环境科学
作者单位US Geol Survey, Mounds View, MN 55112 USA
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GB/T 7714
Erickson, M. L.,Elliott, S. M.,Christenson, C. A.,et al. Predicting geogenic Arsenic in Drinking Water Wells in Glacial Aquifers, North-Central USA: Accounting for Depth-Dependent Features[J]. WATER RESOURCES RESEARCH,2018,54(12):10172-10187.
APA Erickson, M. L.,Elliott, S. M.,Christenson, C. A.,&Krall, A. L..(2018).Predicting geogenic Arsenic in Drinking Water Wells in Glacial Aquifers, North-Central USA: Accounting for Depth-Dependent Features.WATER RESOURCES RESEARCH,54(12),10172-10187.
MLA Erickson, M. L.,et al."Predicting geogenic Arsenic in Drinking Water Wells in Glacial Aquifers, North-Central USA: Accounting for Depth-Dependent Features".WATER RESOURCES RESEARCH 54.12(2018):10172-10187.
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