Measuring and modelling concentrations of plant protection products and trace metals in the South Saskatchewan River
Bibliographic record
Abstract
Organic chemical pollutants are delivered to riverine habitats via basin land use and hydrology interactions. Aquatic organisms eventually absorb these substances, where they might have negative consequences. However, our capacity to reliably predict potential future changes in pollutant concentrations is now constrained by information gaps relating to the links between hydrological, chemical, and biological processes. In the South Saskatchewan River, Canada, in the years 2020 and 2021, concentrations of three pesticide classes (organochlorines, organophosphates, and herbicides) in the water, sediments, and fish were examined. Organochlorine pesticides have been prohibited in Canada since the 1970s; however, methoxychlor and lindane were occasionally found in samples of sediment and fish that may have been contaminated in the past. Organophosphate pesticides, with the exception of malathion and parathion, were close to detection limit in both sampling years in all matrices, while neonicotinoids were below detection in all samples. On the other hand, for both sampling years, consistent levels of the herbicides 2,4-D and dicamba were found in water samples from all locations. Concentrations were on average three times higher in 2020, when river discharge was two times greater, possibly pointing to contaminated sediments being disturbed by high flows, or run-off from the nearby watershed. Of the trace metals, copper and zinc concentrations at several sampling locations exceeded standards for sediment quality. About 18% of the water and sediment samples that were examined had mercury concentrations that were above recommended levels. These discoveries fill in the gaps in monitoring datasets and show significant connections between hydrology and chemistry that can be further investigated in computational models to forecast pollutant trends in freshwater systems. \nTrace metal concentrations were used to model transport and fate in the South Saskatchewan River using an existing model developed for another freshwater system. The River Analysis System from the Hydrologic Engineering Center was paired with a well-known 1-D modelling technique (HEC-RAS). The stream transport module for the WASP (Water Quality Analysis Simulation Program), TOXI, can calculate the flow of water, sediment, and dissolved constituents through branching and ponded segments and is integrated with flow routing for free-flow streams, ponded segments, and backwater reaches. Two metals with primarily anthropogenic and geogenic origins were chosen: copper and nickel. The South Saskatchewan River was analysed in 2020 and 2021 at 10 distinct locations, both upstream and downstream of the City of Saskatoon. By comparing model predictions with copper and nickel concentrations obtained earlier, model performance was assessed. The model functioned reasonably well for sediment samples and did a good job of estimating the levels of copper and nickel in water samples. In both the water and sediment sample segments, the model overestimated concentrations. Diffuse pollutant loads were increased to enable the model to work more precisely. This work shows the predictive power of merging WASP-TOXI and HEC-RAS models for the prediction of contaminant loading, even though numerous default parameter values had to be employed because primary historical data was unavailable. This proof-of-concept study will be useful for future research, including studies on the effects of climate change on the quality of water in the Canadian prairies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".