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Spatial mapping and modeling of arsenic contamination of groundwater and risk assessment through geospatial interpolation technique

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Abstract

Spatial interpolation technique is useful for spatial mapping with sparse data procured from vantage in situ sampling sources. Through spatial interpolation, wall-to-wall mapping of the arsenic concentration in groundwater was accomplished for the whole of the study area by using known concentration value at nearby locations (aquifers) under homogenous terrain conditions. This present study proposes an empirical methodology through interpolation approach for spatial mapping of seasonal and annual groundwater arsenic contamination in the district North 24 Parganas, which happens to be the one of the worst arsenic-affected districts of West Bengal, India, in Bengal Basin. Two types of interpolation approach, Thiessen polygon and Kriging, have been used for spatial mapping of arsenic distribution. On the basis of spatial distribution map, classification has been done for the entire district into seven arsenic concentration zones with various levels of contaminations from arsenic in groundwater (0.01 mg/L as WHO-declared maximum limit for safe zone). In this study, a total of six seasonal (pre-/post-monsoon) data from 2006 to 2008 have been interpreted to examine temporal changes of arsenic concentration in groundwater, and finally, the future trend is projected. Future trend assessment of arsenic contamination has been performed through statistical analysis fitting a linear regression equation. Through this study, it is revealed that the unaffected blocks in the pre-monsoon season (March–April–May) of year 2006 became significantly affected by the end of year 2008. From regression model, it has been predicted that if this trend continues, then, after ten years 2/3 blocks of the said districts will be arsenic affected.

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Acknowledgements

We would like to thank SWID (State Water Investigation Directorate, Govt. of West Bengal, India) for chemical testing of data samples and providing arsenic concentration value of each sample. It is a great pleasure to acknowledge Dr. Pijush Kanti Jana, Head of the Dept. of Library and Information Science, Vidyasagar University, who guided us to make related statistical analysis of this research study by allotting us valuable time from his very busy schedule.

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Author notes

  1. Merina Ghosh

    Present address: Geospatial Delhi Ltd, A Government of NCT of Delhi Company, 3rd Level, C Wing, VikasBhawan-II, Civil Lines, New Delhi, 110054, India

Authors and Affiliations

  1. Department of Geography and Environment Management, Vidyasagar University, Midnapore, West Bengal, 721102, India

    Merina Ghosh

  2. Department of Surveying and Land Studies, The Papua New Guinea University of Technology, Private Mail Bag, Lae, 411, Papua New Guinea

    Dilip Kumar Pal

  3. Department of Environment Science, University of Kalyani, Kalyani, Nadia, West Bengal, 741235, India

    Subhash Chandra Santra

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  1. Merina Ghosh
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  2. Dilip Kumar Pal
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  3. Subhash Chandra Santra
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Correspondence to Merina Ghosh.

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Ghosh, M., Pal, D.K. & Santra, S.C. Spatial mapping and modeling of arsenic contamination of groundwater and risk assessment through geospatial interpolation technique. Environ Dev Sustain 22, 2861–2880 (2020). https://doi.org/10.1007/s10668-019-00322-7

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