A Comprehensive Biogeochemical Assessment of Climate‐Threatened Glacial River Headwaters on the Eastern Slopes of the Canadian Rocky Mountains

• Published in: Journal of geophysical research. Biogeosciences Vol. 129; no. 1
• Main Authors: Serbu, J. A., St. Louis, V. L., Emmerton, C. A., Tank, S. E., Criscitiello, A. S., Silins, U., Bhatia, M. P., Cavaco, M. A., Christenson, C., Cooke, C. A., Drapeau, H. F., Enns, S. J. A., Flett, J. E., Holland, K. M., Lavallee‐Whiffen, J., Ma, M., Muir, C. E., Poesch, M., Shin, J.
• Format: Journal Article
• Language: English
• Published: 01.01.2024
• Subjects: biogeochemistry; climate change; glaciology; hydrology; limnology
• ISSN: 2169-8953; 2169-8961
• DOI: 10.1029/2023JG007745

Climate change is driving the loss of alpine glaciers globally, yet investigations about the water quality of rivers stemming from them are few. Here we provide an overview assessment of a biogeochemical data set containing 200+ parameters that we collected between 2019 and 2021 from the headwaters of three such rivers (Sunwapta‐Athabasca, North Saskatchewan, and Bow) which originate from the glacierized eastern slopes of the Canadian Rocky Mountains. We used regional hydrometric data sets to accurately model discharge at our 14 sampling sites. We created a Local Meteoric Water Line (LMWL) using riverine water isotope signatures and compared it to collected regional rain, snow, and glacial ice signatures. Principal component analyses of river physicochemical measures revealed distance from glacier explained more data variability than other spatiotemporal factors (i.e., season, year, or river). Discharge, chemical concentrations, and watershed areas were then used to model site‐specific open water season yields for 25 parameters. Chemical yields followed what would generally be expected along river continuums from glacierized to montane altitudinal life zones, with landscape characteristics driving chemical sources and sinks. For instance, particulate chemical yields were generally highest near source glaciers with proglacial lakes acting as settling ponds, whereas most dissolved yields varied by parameter and site. As these headwaters continue to evolve with glacier mass loss, the data set and analyses presented here can be used as a contemporary baseline to mark future change against. Further, following this initial assessment of our data set, we encourage others to mine it for additional biogeochemical studies. Plain Language Summary Alpine glaciers are vulnerable to climate change, with their numbers and sizes expected to decline dramatically within the current century. It is known that a decrease in glacier mass will have direct consequences on glacial meltwater quantity, but how this may impact the quality of receiving freshwaters is less understood. Our goal was to record a water quality data set of 200+ physical and chemical parameters for the headwaters of three major rivers draining glaciers on the eastern slopes of the Canadian Rocky Mountains. We first used statistics to model how fast the rivers were flowing at our 14 sampling locations over our 2‐year sampling period. We then looked at how and why water isotopes collected from river, rain, snow, and glacier ice samples differed. We discovered that distance downstream from the glacier explained more statistical variation in our physical and chemical measures than season, year, or river. Finally, at each of our sampling sites, we calculated chemical yields, or the amount of chemical constituent being exported downriver per unit watershed area, and found landscape features like lakes, outwash plains, and forests influence them. We ultimately hope that others use our comprehensive data set to investigate this changing region further. Key Points We assessed a 200+ parameter data set collected from glacial river headwaters on the eastern slopes of the Canadian Rocky Mountains Our findings can act as a contemporary reference for future investigation of glacial headwaters in rapidly evolving alpine regions The possibilities for data exploration of our 260,000+ measure data set are numerous and we encourage others to mine it for new studies