Arid
DOI10.1016/j.watres.2016.01.023
Contrasting regional and national mechanisms for predicting elevated arsenic in private wells across the United States using classification and regression trees
Frederick, Logan1; VanDerslice, James2; Taddie, Marissa2; Malecki, Kristen3; Gregg, Josh2; Faust, Nicholas2; Johnson, William P.1
通讯作者Johnson, William P.
来源期刊WATER RESEARCH
ISSN0043-1354
出版年2016
卷号91页码:295-304
英文摘要

Arsenic contamination in groundwater is a public health and environmental concern in the United States (U.S.) particularly where monitoring is not required under the Safe Water Drinking Act. Previous studies suggest the influence of regional mechanisms for arsenic mobilization into groundwater; however, no study has examined how influencing parameters change at a continental scale spanning multiple regions. We herein examine covariates for groundwater in the western, central and eastern U.S. regions representing mechanisms associated with arsenic concentrations exceeding the U.S. Environmental Protection Agency maximum contamination level (MCL) of 10 parts per billion (ppb). Statistically significant covariates were identified via classification and regression tree (CART) analysis, and included hydrometeorological and groundwater chemical parameters. The CART analyses were performed at two scales: national and regional; for which three physiographic regions located in the western (Payette Section and the Snake River Plain), central (Osage Plains of the Central Lowlands), and eastern (Embayed Section of the Coastal Plains) U.S. were examined. Validity of each of the three regional CART models was indicated by values >85% for the area under the receiver-operating characteristic curve. Aridity (precipitation minus potential evapotranspiration) was identified as the primary covariate associated with elevated arsenic at the national scale. At the regional scale, aridity and pH were the major covariates in the arid to semi-arid (western) region; whereas dissolved iron (taken to represent chemically reducing conditions) and pH were major covariates in the temperate (eastern) region, although additional important covariates emerged, including elevated phosphate. Analysis in the central U.S. region indicated that elevated arsenic concentrations were driven by a mixture of those observed in the western and eastern regions. (C) 2016 Elsevier Ltd. All rights reserved.


英文关键词Arsenic Groundwater chemistry Mechanism Prediction Classification and regression trees
类型Article
语种英语
国家USA
收录类别SCI-E
WOS记录号WOS:000371189100030
WOS关键词DRINKING-WATER ; NEW-ENGLAND ; BLADDER-CANCER ; GROUNDWATER ; CONTAMINATION ; MORTALITY ; EXPOSURE
WOS类目Engineering, Environmental ; Environmental Sciences ; Water Resources
WOS研究方向Engineering ; Environmental Sciences & Ecology ; Water Resources
资源类型期刊论文
条目标识符http://119.78.100.177/qdio/handle/2XILL650/196799
作者单位1.Univ Utah, Dept Geol & Geophys, Salt Lake City, UT 84112 USA;
2.Univ Utah, Sch Med, Dept Family & Preventat Med, Salt Lake City, UT 84112 USA;
3.Univ Wisconsin, Survey Hlth Wisconsin, Madison, WI 53706 USA
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GB/T 7714
Frederick, Logan,VanDerslice, James,Taddie, Marissa,et al. Contrasting regional and national mechanisms for predicting elevated arsenic in private wells across the United States using classification and regression trees[J],2016,91:295-304.
APA Frederick, Logan.,VanDerslice, James.,Taddie, Marissa.,Malecki, Kristen.,Gregg, Josh.,...&Johnson, William P..(2016).Contrasting regional and national mechanisms for predicting elevated arsenic in private wells across the United States using classification and regression trees.WATER RESEARCH,91,295-304.
MLA Frederick, Logan,et al."Contrasting regional and national mechanisms for predicting elevated arsenic in private wells across the United States using classification and regression trees".WATER RESEARCH 91(2016):295-304.
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