Literature DB >> 21879851

Application of geostatistics with Indicator Kriging for analyzing spatial variability of groundwater arsenic concentrations in Southwest Bangladesh.

M Manzurul Hassan1, Peter J Atkins.   

Abstract

This article seeks to explore the spatial variability of groundwater arsenic (As) concentrations in Southwestern Bangladesh. Facts about spatial pattern of As are important to understand the complex processes of As concentrations and its spatial predictions in the unsampled areas of the study site. The relevant As data for this study were collected from Southwest Bangladesh and were analyzed with Flow Injection Hydride Generation Atomic Absorption Spectrometry (FI-HG-AAS). A geostatistical analysis with Indicator Kriging (IK) was employed to investigate the regionalized variation of As concentration. The IK prediction map shows a highly uneven spatial pattern of arsenic concentrations. The safe zones are mainly concentrated in the north, central and south part of the study area in a scattered manner, while the contamination zones are found to be concentrated in the west and northeast parts of the study area. The southwest part of the study area is contaminated with a highly irregular pattern. A Generalized Linear Model (GLM) was also used to investigate the relationship between As concentrations and aquifer depths. A negligible negative correlation between aquifer depth and arsenic concentrations was found in the study area. The fitted value with 95 % confidence interval shows a decreasing tendency of arsenic concentrations with the increase of aquifer depth. The adjusted mean smoothed lowess curve with a bandwidth of 0.8 shows an increasing trend of arsenic concentration up to a depth of 75 m, with some erratic fluctuations and regional variations at the depth between 30 m and 60 m. The borehole lithology was considered to analyze and map the pattern of As variability with aquifer depths. The study has performed an investigation of spatial pattern and variation of As concentrations.

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Year:  2011        PMID: 21879851     DOI: 10.1080/10934529.2011.598771

Source DB:  PubMed          Journal:  J Environ Sci Health A Tox Hazard Subst Environ Eng        ISSN: 1093-4529            Impact factor:   2.269


  3 in total

1.  Predicting arsenic concentrations in groundwater of San Luis Valley, Colorado: implications for individual-level lifetime exposure assessment.

Authors:  Katherine A James; Jaymie R Meliker; Barbara E Buttenfield; Tim Byers; Gary O Zerbe; John E Hokanson; Julie A Marshall
Journal:  Environ Geochem Health       Date:  2014-01-16       Impact factor: 4.609

2.  Spatial modeling of ecological areas by fitting the limiting factors for As in the vicinity of mine, Serbia.

Authors:  Dragan Cakmak; Veljko Perovic; Elmira Saljnikov; Darko Jaramaz; Biljana Sikiric
Journal:  Environ Sci Pollut Res Int       Date:  2013-11-27       Impact factor: 4.223

3.  Use of Principal Components Analysis and Kriging to Predict Groundwater-Sourced Rural Drinking Water Quality in Saskatchewan.

Authors:  Lianne McLeod; Lalita Bharadwaj; Tasha Epp; Cheryl L Waldner
Journal:  Int J Environ Res Public Health       Date:  2017-09-15       Impact factor: 3.390

  3 in total

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