Water quality monitoring programmes generate large volumes of observations, but converting these records into reproducible environmental assessments and regulatory evaluations remains challenging. Here, we present tikatuwq, an open-source R package for discrete freshwater monitoring data. Its modular workflow integrates data import, unit harmonization, validation, computation of the Water Quality Index (WQI/IQA) and Trophic State Index (TSI/IET), parameter-level analysis, visualization, and automated reporting. Regulatory assessment is implemented as a separate component based on Brazil’s CONAMA Resolution 357/2005, enabling environmental indicators and applicable legal thresholds to be examined within a reproducible workflow. We demonstrate the package using 976 parameter-level observations from 52 site–campaign records collected at four stations along the Buranhém River (Bahia, Brazil) between 2020 and 2024. After removing two duplicate records and excluding two brackish-water campaigns, 48 distinct freshwater site–campaign records were retained for the primary analysis. Mean WQI values were classified as Good at all four stations. The river-specific Lamparelli TSI indicated oligotrophic conditions at two stations and mesotrophic conditions at the other two. WQI and TSI showed a moderate negative correlation (Pearson r = −0.46; n = 48). Of 466 parameter–campaign assessments against applicable Class 2 freshwater thresholds, 433 (92.9%) met the selected screening criteria; thermotolerant coliforms accounted for most exceedances. By bringing environmental indices and parameter-level regulatory screening together, tikatuwq supports transparent, reproducible assessments of freshwater monitoring data while retaining a modular structure for future adaptation to other regulatory frameworks.
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Santos et al. (2026) studied this question.
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