2021-2024 Pesticide Risk Metric data with flow and water level

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We applied the expanded PRM of Neelamraju et al (2025 - see citation 1 below) to estimate the combined toxicity of mixtures of 42 pesticides detected in water samples collected by the Great Barrier Reef Catchment Loads Monitoring Program. The data set was filtered to 11 monitoring sites and 3 sampling years (2021-2024) for research into the appropriate handling of sampling bias in the GBRCLMP pesticide data sets. This work underpins the publication Neelamraju et al (2026 - see citation 2 below). The data set includes time series estimates of pesticide mixture toxicity alongside various hydrological and temporal variables. See Neelamraju et al (2026) for full methods and explanation of variables. A summary is provided below. Mixture toxicity was calculated for every water sample in the time series for all sites and years included in the study, then clipped to the wet season window (first flush + 182 days) for further analysis. Hydrological variables were prepared for the dual purposes of, a) quantification of bias in the existing simple imputation approach, and b) for testing and development of more appropriate infilling methods, with the relative suitability of each variable assessed for this purpose based on model performance and practical applicability. Mixture toxicity estimates for the five PRM groups (other herbicides, fungicides, insecticides, PSII herbicides, and total PAF) were aligned to the flow and time-based explanatory variables using time-matching thresholds: ±30 minutes for discharge data and ±5 minutes for water level data. This process created a matrix of observed and missing PRM data aligned to the explanatory variables, for each of the five PRM groups, for every day of the wet season at each site and sampling year. Five model-based approaches were tested and compared to find the most suitable infilling approach. For the GBRCLMP dataset, MICE PMM proved effective, producing defensible results where toxicity bias was evident. See linked records for published code (GitHub) and paper. 1. Neelamraju, Cath A., Mann, Reinier M., Bainbridge, Zoe T., Mitchell, Hannah C., and Turner, Ryan D. R. (2025). Improvement in mixture risk assessment: a multi-national application of the Pesticide Risk Metric. Environmental Advances 22 100676 100676. https://doi.org/10.1016/j.envadv.2025.100676 2. Neelamraju, Cath A., Mann, Reinier M., Bainbridge, Zoe T., Orr, D., and Turner, Ryan D. R. (2026). From gaps to clarity: Time series imputation for improved assessment of pesticide mixture toxicity and aquatic ecosystem risk. (draft).