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A logistic regression method for mapping the As hazard risk in shallow, reducing groundwaters in Cambodia

Published online by Cambridge University Press:  05 July 2018

L. Rodríguez Lado ,
D. A. Polya  and
A. Hegan
L. Rodríguez Lado
Affiliation:
European Commission, Directorate General JRC, Institute for Environment and Sustainability, TP 280, Via E. Fermi 1, I-21020 Ispra (VA), Italy
D. A. Polya
Affiliation:
School of Earth, Atmospheric and Environmental Sciences, University of Manchester, SEAES, Williamson Building, Oxford Road, The University of Manchester M13 9PL, UK
A. Hegan*
Affiliation:
European Commission, Directorate General JRC, Institute for Environment and Sustainability, TP 280, Via E. Fermi 1, I-21020 Ispra (VA), Italy School of Earth, Atmospheric and Environmental Sciences, University of Manchester, SEAES, Williamson Building, Oxford Road, The University of Manchester M13 9PL, UK
*
*E-mail: Aimee.Hegan@postgrad.manchester.ac.uk
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Abstract

We combined statistical analyses and GIS capabilities within the statistical environment R to create a semi-automated method for the assessment of As hazard risk in shallow groundwater in Cambodia. Arsenic concentration data for groundwaters of between 16 and 100 m depth were obtained from 1437 geo-referenced wells. We created a binary logistic regression model with these As measurements as the dependent variable and a number of raster maps (DEM-parameters, remote sensing images and geomorphology) as explanatory variables, and considering an As threshold of 10 ppb. This allowed us to make an As hazard map for groundwaters between 16—100 m depth: this can be used to help to identify populations vulnerable to exposure. The logistic regression analysis indicates a good correlation between topographic and geomorphologic environmental variables and the As hazard risk in groundwater. Ease of implementation, and the ability to update, along with objectivity and reproducibility are the main advantages related to this method of analysis.

Keywords

groundwater modellinglogistic regressionrisk assessment
Type
Research Article
Information
Mineralogical Magazine , Volume 72 , Issue 1 , February 2008 , pp. 437 - 440
Copyright
Copyright © The Mineralogical Society of Great Britain and Ireland 2008

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