Innovative mapping of groundwater redox status and cation exchange conditions in a GIS environment

Mojtaba Zaresefat, Walter Schenkeveld, Reza Derakhshani, Jasper Griffioen

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

Understanding the complexities of regional groundwater quality is crucial for managing groundwater resources. Groundwater quality assessment involves investigating specific dissolved groundwater components, for example, comparing them to established standards. To fully understand all aspects of groundwater quality, one should assess composite properties, one being the redox status and another being the cation exchange condition. The first may, for example, impose a control on the degradation of organic micropollutants. While groundwater numerical indices can be easily interpolated and visualised using various GIS applications, consistently mapping the redox status and cation exchange conditions as non-numerical indices remains challenging. Furthermore, no study has yet conducted a regional-scale mapping of cation exchange classes in a GIS environment using extensive groundwater samples. To deepen our understanding of these groundwater components, we employed ArcGIS in this study to map the redox and cation exchange conditions in two stages. First, we mapped the groundwater components of interest, including Cl, SO4, SO4/Cl, Fe, NO3 and base exchanges of Na and Mg, by the most appropriate interpolation method identified by a geostatistical analysis. Then, variables were combined, and the conditional functions were used in ArcMap's Math toolbox to determine redox status or cation exchange classes. Our innovative GIS method for mapping regional redox status and cation exchange conditions was developed for 3,350 groundwater sampling locations in the coastal lowlands of the Western Netherlands. The method was successful, with generally 75%–95% similarity between predicted and observed situations for most classes. The introduced method is more straightforward than others and can map other non-numerical linguistic indices like Wilcox groundwater and irrigation water classifications, as well.
Original languageEnglish
Article number101188
JournalGroundwater for Sustainable Development
Volume25
Early online date26 Apr 2024
DOIs
Publication statusPublished - May 2024

Bibliographical note

Publisher Copyright:
© 2024 The Authors

Funding

This research is part of a PhD project by the first author, Mojtaba Zaresefat, who would like to express his sincere gratitude for the financial support from the I.R. Iran government's scholarship programme, funded by the Ministry of Science, Research and Technology (MSRT). Joy Burrough and Adam Frick are gratefully acknowledged for providing linguistic advice. Finally, the paper's two anonymous reviewers are thanked for their constructive feedback.

FundersFunder number
I.R. Iran government's
Ministry of Science Research and Technology

    Keywords

    • ArcGIS
    • Cartography
    • Conditional functions
    • Geostatistics
    • Groundwater monitoring
    • Non-numerical indices

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