Hydrochem, an Integrated R Package for the Analysis and Visualization of Hydrochemical Data
Hydrochemical data are essential for understanding groundwater flow, hydrobiogeochemical processes, contamination sources, and assessing groundwater quality. Despite the increasing availability of complex hydrochemical datasets, current tools for processing and visualizing these data-mainly spreadsheets and commercial GUI software-have significant limitations in scalability, reproducibility, and flexibility. Programming languages such as R offer powerful alternatives but remain underutilized in hydrogeochemistry because of the perceived complexity of coding. To address this gap, we present hydrochem, an open-source R package designed to facilitate comprehensive hydrochemical data analysis through user-friendly and customizable functions. The package supports essential tasks such as unit conversion, handling of censored data, ionic balance calculation, water type classification, and a range of hydrochemical indices relevant to water quality. It also provides advanced graphical tools including Piper, Durov, Stiff, Collins, Schoeller, Gibbs, and ternary diagrams to support the interpretation of water chemistry. By integrating reproducible workflows and leveraging the broader R ecosystem, hydrochem lowers the technical barrier for hydrogeochemists and environmental scientists, thereby facilitating the analysis of hydrochemical datasets of varying complexity, improving the reliability of results, and supporting informed water resource management decisions.
Authors
- Raphaël Bondu (ORCID: https://orcid.org/0000-0003-3838-6693)
- Guillaume Cinkus (ORCID: https://orcid.org/0000-0002-2877-6551)
Institutions
- Centre National de la Recherche Scientifique (FR)
- Université d'Avignon et des Pays de Vaucluse (FR)
- Université de Montpellier (FR)
- Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement (FR)
- Institut de Recherche pour le Développement (FR)
Publication Details
- Journal
- Ground Water
- Published
- 2026-10-16
- DOI
- https://doi.org/10.1111/gwat.70110
- Primary Topic
- Water Quality and Pollution Assessment
- Type
- article
- Field-Weighted Citation Impact
- 0.00