Modelling historical variability of phosphorus and organic carbon fluxes to the Mackenzie River, Canada

• Published in: Hydrology Research
• Main Authors: Rajesh R. Shrestha, Terry D. Prowse, Lois Tso
• Format: Article in Journal/Newspaper
• Language: English
• Published: IWA Publishing 2019
• Subjects: c–q relationship; doc and tp fluxes; historical trends; loadest model; statistical modelling; subarctic; River; lake; and water-supply engineering (General); TC401-506; Physical geography; GB3-5030; Canada; Hay River; Liard; Mackenzie River; Mackenzie river; Subarctic
• Online Access: https://doi.org/10.2166/nh.2019.161; https://doaj.org/article/e044765d67524446b4eaf7b28d95ffbb

This study provides an improved statistical modelling framework for understanding historical variability and trends in water constituent fluxes in subarctic western Canada. We evaluated total phosphorus (TP) and dissolved organic carbon (DOC) fluxes for the Hay, Liard and Peel tributaries of the Mackenzie River. The TP and DOC concentrations primarily exhibit chemodynamic relationships with discharge, with the exception of the chemostatic relationship between DOC and discharge for the Hay River. With this understanding, we explored a number of enhancements in the load estimation model that included the use of (i) linear regression and logarithmic models, (ii) air-temperature as an alternate input variable and (iii) quantile mapping for bias-correction. Further, we evaluated uncertainties in the simulation of fluxes and trends by using a bootstrapping method. The modelled TP and DOC fluxes show considerable seasonal and interannual variability that generally follow the runoff dynamics. The annual and seasonal trends are mostly small and insignificant, with the largest significant increases occurring in the winter months. These trends are amplified compared with discharge, suggesting the possibility of pronounced changes with large changes in discharge. Additionally, the results provide evidence that directly using limited water constituent samples for trend analysis can be problematic.