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

Publication date

2024-05

Authors

Zaresefat, MojtabaORCID 0000-0002-7363-953X
Schenkeveld, W.D.C.ISNI 0000000507309876
Derakhshani, RezaORCID 0000-0001-7499-4384ISNI 0000000512522591
Griffioen, J.ORCID 0000-0001-6307-0100ISNI 000000039033097X

Editors

Advisors

Supervisors

Document Type

Article
Open Access logo

License

cc_by

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.

Keywords

ArcGIS, Cartography, Conditional functions, Geostatistics, Groundwater monitoring, Non-numerical indices, Water Science and Technology, Geography, Planning and Development, Environmental Engineering, Environmental Chemistry

Citation

Zaresefat, M, Schenkeveld, W, Derakhshani, R & Griffioen, J 2024, 'Innovative mapping of groundwater redox status and cation exchange conditions in a GIS environment', Groundwater for Sustainable Development, vol. 25, 101188. https://doi.org/10.1016/j.gsd.2024.101188