**4. Discussion**

Observed copper concentrations in water were consistent and followed similar trends to the observed values for most of the sampling time points. An exception to that is the observed values in the October 2020 sampling time points, where the copper concentration values were significantly higher than that of the trend following the WASP simulated values. This could be attributed to roadwork and bridge construction in the area, which would have been impossible for the model to cover. In sediment samples, the majority of the WASP simulated values were underestimated compared to the observed values, with a few exceptions. This could be the result of the continuous accumulation of metals in sediments over many years, which was not accounted for in the current modelling exercise.

Modelled nickel concentrations in water samples across 2020 and 2021 also followed a similar trend, without major discrepancies from the observed values. For sediment samples, there were a few instances where the observed values were higher than those of the modelled progression. The model tended to underestimate the nickel concentrations for sediment samples, following a similar trend to the copper concentrations for sediment samples.

During simulations, the model was found to be underestimating the concentrations at downstream segments. Additional diffuse loads were added to compensate for matching the simulated values with measured values. This significantly improved the accuracy for both metals. For water samples, additional loads (~1–3 kg/day) were included at major segments (sampling stations) as diffuse loads. The loads were increased 100-fold for the calibration of sediment samples. Calibration process determined these amounts. Copper and nickel are both known to sequester in the sediment bed and are less likely to be suspended in water. Copper, as mentioned above, enters the environment mainly through anthropogenic sources [4]. The release and remobilization of sediment-bound copper have been well-documented in various studies; however, the overall impacts are minor [39,40]. Mobility of nickel, on the other hand, is site-specific and depends on the soil type and pH [41]. These observations can be attributed to the higher observed values of nickel and copper in the sediment samples in the current study.

The model used in the current study is an extension of the previously developed model 1D WASP and HEC-RAS coupling [32] and quasi-2D [33,34]. In the study [38], the mixing of vanadium and sediment was modelled with a quasi-2D modelling approach in the lower Athabasca River. The authors observed a marked increase in vanadium concentration along the river. The model was successful in capturing the transverse mixing from tributary water with mainstream water.

As mentioned earlier, modelling freshwater systems is challenging, involving many complex processes that affect contaminants' transport and fate [42], which demands sensitive methods to obtain accurate results for different metals. With limited data availability, understanding metal speciation becomes difficult in such systems [43]. The current study for the South Saskatchewan River system serves as a preliminary study focusing on trace metal transport and fate. This study also provides an understanding of how the concentrations of trace metals (Cu and Ni) vary across upstream and downstream of the South Saskatchewan River. There were a few CCME ISQG exceedances for Cu concentrations, and there are no guidelines outlined for Ni (as of now). Although there may be no immediate danger just yet, contamination of aquatic systems cannot be excluded. Further

study involving more metals in the model with sufficient input parameters would be an ideal recommendation.

#### **5. Conclusions**

The aim of this study was to better understand trace metal fate and interaction in the South Saskatchewan River. Two trace metals, copper (Cu) and nickel (Ni), were selected on the basis of their presence in the region. Copper is used in a wide range of products such as construction, pipes, industrial equipment, etc., resulting in widespread anthropogenic contamination with Cu. In contrast, nickel has a geogenic background in Saskatchewan and is transferred to the aquatic environment by effluents, leachates, and runoff from mining activities and the general land surface.

A 1D modelling approach was successfully applied in studying the trends and patterns of trace metal fate in the river and sediment. The simulations provided interesting data for both the trace metals and gave an insight into how the metals travel and react between water and sediment in the South Saskatchewan River.

A number of parameters needed to be assumed due to the lack of availability of consistent raw data for the modelling of these two trace metals. Improved availability of these parameter values would help make the model more efficient and accurate in predicting future trends with increased/decreased flows.

**Supplementary Materials:** The following supporting information can be downloaded at: https: //www.mdpi.com/article/10.3390/w15020265/s1, Trace metal concentrations can be found in the spreadsheet attached Table S1: Heavymetal concentrations.xlsx.

**Author Contributions:** Conceptualization, S.P., P.S., M.B. and K.-E.L.; methodology, S.P. and P.S.; software, S.P. and P.S.; writing—original draft preparation, S.P. and P.S.; writing—review and editing, M.B. and K.-E.L.; supervision, M.B. and K.-E.L. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research was funded University of Saskatchewan's New Faculty Graduate Student Support Program (NFGSSP), Global Water Futures (GWF), Canada First Research Excellence Funds, and the Canada Foundation for Innovation (CFI)—38581.

**Data Availability Statement:** All the research data supporting reported results can be found in the Supplementary Materials.

**Conflicts of Interest:** The authors declare no conflict of interest.

#### **References**


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