Cyanobacterial blooms present challenges for water treatment, especially in regions like the Canadian prairies where poor water quality intensifies water treatment issues. Buoyant cyanobacteria that resist sedimentation present a challenge as water treatment operators attempt to balance pre-treatment and toxic disinfection by-products. Here, we used microscopy to identify and describe the succession of cyanobacterial species in Buffalo Pound Lake, a key drinking water supply. We used indicator species analysis to identify temporal grouping structures throughout two sampling seasons from May to October 2018 and 2019. Our findings highlight two key cyanobacterial bloom phases – a mid-summer diazotrophic bloom of Dolichospermum spp. and an autumn Planktothrix agardhii bloom. Dolichospermum crassa and Woronchinia compacta served as indicators of the mid-summer and autumn bloom phases, respectively. Different cyanobacterial metabolites were associated with the distinct bloom phases in both years: toxic microcystins were associated with the mid-summer Dolichospermum bloom and some newly monitored cyanopeptides (anabaenopeptin A and B) with the autumn Planktothrix bloom. Despite forming a significant proportion of the autumn phytoplankton biomass (greater than 60%), the Planktothrix bloom had previously not been detected by sensor or laboratory-derived chlorophyll-a. Our results demonstrate the power of targeted taxonomic identification of key species as a tool for managers of bloom-prone systems. Moreover, we describe an autumn Planktothrix agardhii bloom that has the potential to disrupt water treatment due to its evasion of detection. Our findings highlight the importance of identifying this autumn bloom given the expectation that warmer temperatures and a longer ice-free season will become the norm.

Flow management has the potential to significantly affect water quality. Shallow lakes in arid regions are especially susceptible to flow management changes which can have important implications for the formation of cyanobacterial blooms. Here, we reveal water quality shifts across a gradient of managed source water inflow regimes. Using in situ monitoring data, we studied a seven-year time span during which inflows to a shallow, eutrophic drinking water reservoir transitioned from primarily natural landscape runoff (2014 to 2015) to managed flows from a larger upstream reservoir (Lake Diefenbaker; 2016 to 2020) and identified significant changes in cyanobacteria (as phycocyanin) using generalized additive models to classify cyanobacterial bloom formation. We then connected changes in water source with shifts in chemistry and the occurrence of cyanobacterial blooms using principal components analysis. Phycocyanin was greater in years with managed reservoir inflow from mesotrophic Lake Diefenbaker (2016 to 2020) but dissolved organic matter (DOM) and specific conductivity, important determinants of drinking water quality, were greatest in years when landscape runoff dominated lake water source (2014 to 2015). Most notably, despite changing rapidly, it took multiple years for lake water to return to a consistent and reduced level of DOM after managed inflows from upstream Lake Diefenbaker were resumed, an observation that underscores how resilience may be hindered by weak resistance to change and slow recovery. Environmental flows for water quality are rarely defined yet here it appears trade-offs exist between poor water quality via elevated conductivity and DOM, and higher bloom risk. Taken together, our findings have important implications for water managers who must protect water quality while adapting to projected hydroclimatic change.

Inland waters are hotspots of greenhouse gas (GHG) emissions, and small water bodies are now well known to be particularly active in the production and consumption of carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O). High variability in physical, chemical, and environmental parameters affect the production of these GHG, but currently the mechanistic underpinnings are unclear, leading to high uncertainty in scaling up these fluxes. Here, we compare the relative magnitudes and controls of emissions of all three major GHG in twenty pairs of natural wetland ponds and constructed reservoirs in Canada’s largest agricultural region. While gaseous fluxes of CO2 and CH4 were comparable between the two waterbody types, CH4 ebullition was greater in wetland ponds. Carbon dioxide levels were associated primarily with metabolic indicators in both water body types, with primary productivity paramount in agricultural reservoirs, and heterotrophic metabolism a stronger correlate in wetland ponds. Methane emissions were positively driven by eutrophication in the reservoirs, while competitive inhibition by sulfur-reducing bacteria may have limited CH4 in both waterbody types. Contrary to expectations, N2O was undersaturated in both water body types, with wetlands a significantly stronger and more widespread N2O sink than were reservoirs. These results support the need for natural and constructed water bodies for regional GHG budgets and identification of GHG processing hotspots.

Excess nutrients in aquatic ecosystems is a major water quality problem globally. Worsening eutrophication issues are notable in cold temperate areas, with pervasive problems in many agriculturally dominated catchments. Predicting nutrient export to rivers and lakes is particularly difficult in cold agricultural environments because of challenges in modelling snow, soil, frozen ground, climate, and anthropogenic controls. Previous research has shown that the use of many popular small basin nutrient models can be problematic in cold regions due to poor representation of cold region hydrology. In this study, the Cold Regions Hydrological Modelling Platform (CRHM), a modular modelling system, which has been widely deployed across Canada and cold regions worldwide, was used to address this problem. CRHM was extended to simulate biogeochemical and transport processes for nitrogen and phosphorus through a complex of new process-based modules that represent physicochemical processes in snow, soil and freshwater. Agricultural practices such as tillage and fertilizer application, which strongly impact the availability and release of soil nutrients, can be explicitly represented in the model. A test case in an agricultural basin draining towards Lake Winnipeg shows that the model can capture the extreme hydrology and nutrient load variability of small agricultural basins at hourly time steps. It was demonstrated that fine temporal resolutions are an essential modelling requisite to capture strong concentration changes in agricultural tributaries in cold agricultural environments. Within these ephemeral and intermittent streams, on average, 30%, 31%, 20%, and 16% of the total annual load of NO3, NH4, SRP and partP occurred during the episodic snowmelt freshet ~9 days, accounting for 21% of the annual flow), but shows extreme temporal variation. The new nutrient modules are critical tools for predicting nutrient export from small agricultural drainage basins in cold climates via better representation of key hydrological processes, and a temporal resolution more suited to capture dynamics of ephemeral and intermittent streams.