Literature DB >> 23892715

Probability-based nitrate contamination map of groundwater in Kinmen.

Chen-Wuing Liu1, Yeuh-Bin Wang, Cheng-Shin Jang.   

Abstract

Groundwater supplies over 50% of drinking water in Kinmen. Approximately 16.8% of groundwater samples in Kinmen exceed the drinking water quality standard (DWQS) of NO3 (-)-N (10 mg/L). The residents drinking high nitrate-polluted groundwater pose a potential risk to health. To formulate effective water quality management plan and assure a safe drinking water in Kinmen, the detailed spatial distribution of nitrate-N in groundwater is a prerequisite. The aim of this study is to develop an efficient scheme for evaluating spatial distribution of nitrate-N in residential well water using logistic regression (LR) model. A probability-based nitrate-N contamination map in Kinmen is constructed. The LR model predicted the binary occurrence probability of groundwater nitrate-N concentrations exceeding DWQS by simple measurement variables as independent variables, including sampling season, soil type, water table depth, pH, EC, DO, and Eh. The analyzed results reveal that three statistically significant explanatory variables, soil type, pH, and EC, are selected for the forward stepwise LR analysis. The total ratio of correct classification reaches 92.7%. The highest probability of nitrate-N contamination map presents in the central zone, indicating that groundwater in the central zone should not be used for drinking purposes. Furthermore, a handy EC-pH-probability curve of nitrate-N exceeding the threshold of DWQS was developed. This curve can be used for preliminary screening of nitrate-N contamination in Kinmen groundwater. This study recommended that the local agency should implement the best management practice strategies to control nonpoint nitrogen sources and carry out a systematic monitoring of groundwater quality in residential wells of the high nitrate-N contamination zones.

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Year:  2013        PMID: 23892715     DOI: 10.1007/s10661-013-3319-8

Source DB:  PubMed          Journal:  Environ Monit Assess        ISSN: 0167-6369            Impact factor:   2.513


  12 in total

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2.  Aquifer vulnerability assessment to heavy metals using ordinal logistic regression.

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3.  Predicting ground water nitrate concentration from land use.

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Journal:  Ground Water       Date:  2005 May-Jun       Impact factor: 2.671

4.  Spatial variability of shallow groundwater level, electrical conductivity and nitrate concentration, and risk assessment of nitrate contamination in North China Plain.

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Journal:  Environ Int       Date:  2005-08       Impact factor: 9.621

5.  Nitrate contamination in private wells in rural Alabama, United States.

Authors:  Aiguo Liu; Jinghua Ming; Ramble O Ankumah
Journal:  Sci Total Environ       Date:  2005-06-15       Impact factor: 7.963

6.  Pesticides in water supply wells in Zealand, Denmark: a statistical analysis.

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7.  Assessing nitrate contamination and its potential health risk to Kinmen residents.

Authors:  Chen-Wuing Liu; Chun-Nan Lin; Cheng-Shin Jang; Min-Pei Ling; Jeng-Wei Tsai
Journal:  Environ Geochem Health       Date:  2010-11-25       Impact factor: 4.609

8.  Determining the probability of arsenic in groundwater using a parsimonious model.

Authors:  Jin-Jing Lee; Cheng-Shin Jang; Chen-Wuing Liu; Ching-Ping Liang; Sheng-Wei Wang
Journal:  Environ Sci Technol       Date:  2009-09-01       Impact factor: 9.028

9.  Blue babies and nitrate-contaminated well water.

Authors:  L Knobeloch; B Salna; A Hogan; J Postle; H Anderson
Journal:  Environ Health Perspect       Date:  2000-07       Impact factor: 9.031

10.  Calcium, magnesium, and nitrate in drinking water and gastric cancer mortality.

Authors:  C Y Yang; M F Cheng; S S Tsai; Y L Hsieh
Journal:  Jpn J Cancer Res       Date:  1998-02
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  1 in total

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Journal:  Environ Geochem Health       Date:  2016-09-28       Impact factor: 4.609

  1 in total

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