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Predicting groundwater arsenic contamination in Southeast Asia from surface parameters

Abstract

Arsenic contamination of groundwater resources threatens the health of millions of people worldwide, particularly in the densely populated river deltas of Southeast Asia. Although many arsenic-affected areas have been identified in recent years, a systematic evaluation of vulnerable areas remains to be carried out. Here we present maps pinpointing areas at risk of groundwater arsenic concentrations exceeding 10 μg l−1. These maps were produced by combining geological and surface soil parameters in a logistic regression model, calibrated with 1,756 aggregated and geo-referenced groundwater data points from the Bengal, Red River and Mekong deltas. We show that Holocene deltaic and organic-rich surface sediments are key indicators for arsenic risk areas and that the combination of surface parameters is a successful approach to predict groundwater arsenic contamination. Predictions are in good agreement with the known spatial distribution of arsenic contamination, and further indicate elevated risks in Sumatra and Myanmar, where no groundwater studies exist.

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Figure 1: Uniformly classified geological map of Southeast Asia.
Figure 3: Modelled probability of As concentrations exceeding 10 μg l−1 under reducing aquifer conditions.
Figure 2: Model classification results.
Figure 4: Maps of the model verification study area in Southeast Sumatra.

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Acknowledgements

We thank T. Rosenberg, R. Febriamansyah, M.A. Hayatuddin and E. Nofyan for support during groundwater sampling in Sumatra; C. Stengel, T. Rüttimann, M. Langmeier and R. Illi for elemental analyses; K. Abbaspour and B. den Brok for discussions; R. Wildman and H. Rowland for proofreading and the anonymous reviewers for comments.

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Correspondence to Michael Berg.

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Supplementary figures S1-S3 and tables S1-S5 (PDF 1355 kb)

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Winkel, L., Berg, M., Amini, M. et al. Predicting groundwater arsenic contamination in Southeast Asia from surface parameters. Nature Geosci 1, 536–542 (2008). https://doi.org/10.1038/ngeo254

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