Athabasca River Basin Research Articles

Effects of naturally sourced bitumen samples from Alberta oil sands region (Canada) on aquatic benthic invertebrates: A case study with Chironomus riparius

Athabasca oil sands in Alberta, Canada, are large bitumen deposits and are one of the world's largest petroleum reserves. This research contributes to the growing body of knowledge on the influence of this naturally occurring bitumen on freshwaters. Using laboratory-based exposure studies, we examined the life cycle responses of the aquatic midge Chironomus riparius to both naturally formed solid bitumen incorporated in the sediment and its corresponding aqueous extracts, denominated as elutriates. The 28-day partial life cycle assay involved bitumen samples from two distinct geological origins in the Athabasca River Basin (Clearwater and McMurray formations), comprising both weathered and freshly collected bitumen from a total of 4 different rivers. Our results demonstrate a measurable impact of sediment-embedded bitumen on C. riparius life history traits, namely on their growth and emergence patterns. Furthermore, we observed that bitumen samples from the Ells River (McMurray formation), which were freshly collected from exposed river bank soil deposits, exerted the strongest effects on most studied eco-physiological endpoints. Bitumen extracts from the Steepbank River and Athabasca River in the McMurray Formation and Steepbank River in the Clearwater Formation followed, underscoring the geographical variance in bitumen-induced toxicity. Exposure to elutriates, simulating “weathered” bitumen generally did not induce adverse effects in C. riparius life-cycle endpoints compared to elutriates prepared from freshly eroded bank soils. This emphasizes the importance of considering bitumen sources, their age, and the aquatic receiving environment when assessing potential adverse exposure effects. Our study shows that exposure to freshly eroded soils/sediments can potentially affect benthic invertebrates. More research is needed to understand how hydrological changes affect bitumen sediment exposure and the associated risks to aquatic biota.

Assessment of hydrological baseline condition and its alteration in Athabasca River Basin, Canada

Study regionAthabasca River Basin (ARB), Canada. Study focusThis study aimed to characterize the flow regime of the ARB, a basin with diverse hydroclimatic and geological characteristics. Forty-two different flow indicators from the Indicators of Hydrological Alteration (IHA) and Cold regions Hydrological Indicators of Change (CHIC) were employed. The natural range of these indicators was established for the baseline period (1961–1990), and subsequent alterations during the recent period (1991–2020) were systematically examined. Principal Component Analysis (PCA) was applied to identify pivotal indicators shaping the basin's flow regime. In addition, trends of key indicators were examined at eight distinct locations within the basin. New hydrological insights for the study regionThe findings indicate spatiotemporal variation between the basin's upper and lower parts. The upstream region exhibited an earlier peak flow (9 days), an earlier ice break-up (17 days), and a shorter ice cover duration (22 days) compared to the downstream region. Increased winter and spring flow have led to an augmentation of annual flow by 3.8 % in the upper region. In contrast, downstream flow experienced a decline throughout the year (11.38 %), which was found to be statistically significant at a rate of 3.24 m3/s/year. Alteration analysis revealed a shift toward the 'low category' (below their defined baseline range) for most indicators in the recent period, underscoring a transition towards a diminishing flow regime, with an overall alteration ranging at low to moderate levels (19–38 %). Late summer flow reduction (8–25 %) can have critical implications, given the rising water demand in the basin. The study identified eleven key indicators encapsulating the basin's flow regime variability range. It was found that ice cover, its break-up, and spring freshet significantly influence the flow regime of the basin. The findings from this study will assist decision-makers in making more informed decisions for the holistic management of water resources in the basin.

Least-Squares Triple Cross-Wavelet and Multivariate Regression Analyses of Climate and River Flow in the Athabasca River Basin

Abstract River flow monitoring is a critical task for land management, agriculture, fishery, industry, and other concerns. Herein, a robust least squares triple cross-wavelet analysis is proposed to investigate possible relationships between river flow, temperature, and precipitation in the time–frequency domain. The Athabasca River basin (ARB) in Canada is selected as a case study to investigate such relationships. The historical climate and river flow datasets since 1950 for three homogeneous subregions of the ARB were analyzed using a traditional multivariate regression model and the proposed wavelet analysis. The highest Pearson correlation (0.87) was estimated between all the monthly averaged river flow, temperature, and accumulated precipitation for the subregion between Hinton and Athabasca. The highest and lowest correlations between climate and river flow were found to be during the open warm season and cold season, respectively. Particularly, the highest correlations between temperature, precipitation, and river flow were in May (0.78) for Hinton, July (0.54) for Athabasca, and September (0.44) for Fort McMurray. The new wavelet analysis revealed significant coherency between annual cycles of climate and river flow for the three subregions, with the highest of 33.7% for Fort McMurray and the lowest of 4.7% for Hinton with more coherency since 1991. The phase delay analysis showed that annual and semiannual cycles of precipitation generally led the ones in river flow by a few weeks mainly for the upper and middle ARB since 1991. The climate and river flow anomalies were also demonstrated using the baseline period 1961–90, showing a significant increase in temperature and decrease in precipitation since 1991 for all the three subregions. Unlike the multivariate regression, the proposed wavelet method can analyze any hydrometeorological time series in the time–frequency domain without any need for resampling, interpolation, or gap filling.

Macroscale composite principal-monotonicity distributed projection of climate-induced hydrologic changes: Tempo-spatial variabilities, and variation decompositions

A macroscale composite principal-monotonicity distributed hydro-projection system is developed through hybridizing advanced statistical hydroclimatic systems analysis methods of verified superiorities. The system can enhance accuracies and feasibilities of climate-informed hydrologic projections, quantitatively reveal climate-induced hydro-magnitude and -variability changes, and decompose variations of the changes with factors such as time, space, scales and greenhouse gas (GHG) emissions. The system of high adaptability for worldwide watersheds is applied to a representative large cold-region watershed, Athabasca River Basin in Canada. Incremental ratios of river discharges with climate change are projected to enlarge at fine timescales, e.g., from 3.4% (octo-decadal) to 7.0% (monthly). According to mixed-level multifactorial analyses, variations of the ratios are dominated by catchments (59.2%) and GHG emissions (19.6%) at annual and longer timescales, and the dominance increases with timescales. At intra-annual timescales, the dominator becomes interactive tempo-spatial variations (62.6%) of the ratios. GHG emissions and their interaction with catchments pose significant or even leading effects on trends of discharge changes. Ratios of changes (i.e., decreases mostly) in tempo-spatial variabilities of discharges are generally the most significant for interannual variabilities, in warm seasons, at downstream catchments, under high GHG emissions, and by the late 21st century. Their variation is dominated by individual factorial effects (78.0%), e.g., catchments (50.3%) and GHG emissions (16.2%); the dominance declines from interannual (89.0%), temporal (79.4%), intra-annual (75.6%) to spatial (67.9%) variabilities. Interactions of the factors in explaining variations of spatial and interannual variabilities are non-negligible in warm and cool seasons, respectively. These findings can help advance macroscale distributed climate-informed hydrologic projections and, accordingly, scientize assessment, adaptation and mitigation of hydrologic hazards over climate-sensitive cold regions.

Investigating hydrological transport pathways of dissolved organic carbon in cold region watershed based on a watershed biogeochemical model

Dissolved organic carbon (DOC) is a significant component of regional and global carbon cycles and an important surface water quality indicator. DOC affects the processes of solubility, bioavailability and transport for a number of contaminants, such as heavy metals. Therefore, it is crucial to understand DOC fate and transport in the watershed and the transport pathways of DOC load. We modified a previously developed watershed-scale organic carbon model by incorporating the DOC load from glacier melt runoff and used the modified model to simulate periodic daily DOC load in the upper Athabasca River Basin (ARB) in the cold region of western Canada. The calibrated model achieved an overall acceptable performance for simulating daily DOC load with model uncertainties mainly from the underestimation of peak loads. Parameter sensitivity analysis indicates that the fate and transport of DOC load in upper ARB are mainly controlled by DOC production in the soil layers, DOC transport at the soil surface, and reactions in the stream system. The modeling results indicated that the DOC load is mainly from the terrestrial sources and the stream system was a negligible sink in the upper ARB. It also indicated that rainfall-induced surface runoff was the major transport pathway of DOC load in the upper ARB. However, the DOC loads transported by glacier melt runoff were negligible and only accounted for 0.02% of the total DOC loads. In addition, snowmelt-induced surface runoff and lateral flow contributed 18.7% of total DOC load, which is comparable to the contribution from the groundwater flow. Our study investigated the DOC dynamics and sources in the cold region watershed in western Canada and quantified the contribution of different hydrological pathways to DOC load, which could provide a useful reference and insight for understanding watershed-scale carbon cycle processes.

Estimation of groundwater contributions to Athabasca River, Alberta, Canada

Study regionThe Athabasca River Basin (ARB), Canada Study focusThis study investigates the dynamic interactions that occur between surface water and groundwater systems within the Athabasca River Basin (ARB). The integrated surface-subsurface model of the ARB was first calibrated under monthly normal transient flow conditions to observed surface water and groundwater data, after which the model was forced with monthly average transient data to evaluate model performance. From these results, groundwater contribution to the Athabasca River system was calculated using simulated surface water-groundwater exchange fluxes. These estimates are compared to those obtained from an isotope-based balance analysis which also estimated groundwater contribution to the Athabasca River. New hydrological insights for the regionThe results from this study suggest that the groundwater system in the basin has a high degree of interaction with the surface water system. Specifically, the groundwater contribution to the surface water system along the Athabasca River ranges from 34% (high flow season) to 63% (low flow season) with an overall average annual groundwater contribution of 45%. These results indicate that the groundwater system needs to be considered when analyzing potential climate change impacts on future water availability and extreme hydroclimatic events.

Trends of hydroclimatic variables and outflow in the Athabasca River basin

Our study focuses on assessing trends of hydroclimatic variables and their impact on the runoff regime in the Athabasca River basin in two periods (from the beginning of monitoring until 2011 and 1971−2011). Applied methods included the Mann-Kendall statistical test, linear regression, multiplicative decomposition of data series, the Indicators of Hydrologic Alteration, and the Range of Variability Approach. Temperature records indicated a strong regional warming trend, which influenced decreased snowfall and a declining trend in spring runoff. Our results indicate that between 1971 and 2011 median discharge values decreased by > 20% on the lower and middle courses of the Athabasca River. Although on the upper course the median long-term minimum discharge increased due to the melting of mountain glaciers, on the middle and lower courses a significant decrease occurred. The discharge variability has also increased. All factors and changes are important because they affect the Athabasca-Peace delta’s ecosystem and socioeconomic activities on the lower course.

Development of a macroscale distributed hydro-modeling method: Bayesian principal-monotonicity inference

At macroscales (e.g., large river basins, nations, continents, or the globe), hydro-hazard mitigation under climate change requires accurate, applicable hydrologic models, especially over cold regions of complicated hydroclimatic relations. As an effort to address such a challenge, we innovate a macroscale distributed hydro-modeling method, Bayesian principal-monotonicity inference (BaPMI), based on climate classification, representative-grids selection, statistical hydrology, surrogates-based Bayesian optimization, and variance-based sensitivity analyses. The method is applied to a typical large cold-region watershed, i.e., Athabasca River Basin in Canada, and reveals a series of findings such as the following representatives. BaPMI shows promising skills in quantitatively characterizing macroscale cold-region hydrology under overall impacts of heterogeneous climates. Bayesian optimization of which hyperparameters are insensitive decreases hydro-modeling computational time by up to 96.3% and, together with climate classification, largely enhances BaPMI applicability while ensuring modeling accuracies. Individual BaPMI hydro-model parameters can explain over ¾ of the variation of hydro-modeling accuracies and, due to their interaction, joint calibration is required for avoiding underestimation of the impacts. Climatic conditions dominating cross-scale uppermost hydrologic variations consist of night temperature (40%), day temperature (38%), and precipitation (22%) for all catchments; all river flows along the mainstem are associated with upstream climatic events such as glacier melts. Climatic impacts decline from upstream to downstream and from summer, spring, winter to autumn; this may relate to tempo-spatial heterogeneity of soil, vegetation, geology, human interference and other non-climatic factors. Without this study, macroscale distributed hydrologic modeling would lack one advanced method (i.e., BaPMI) that can immunize against effects of data uncertainty, subjective judgement and climatic collinearity, adapt to complicated hydroclimatic relations and diverse hydro-variable(s) distributions, reveal cross-scale uppermost hydrologic variations and, through inexpensive computations, enhance hydro-modeling accuracies to avoid climatic-impact underestimation. The findings of this study could facilitate BaPMI applications and advance macroscale (cold-region) hydrology.

Evaluating the Impact of Land Cover and Topography on Meteorological Parameters’ Relations and Similarities in the Alberta Oil Sands Region

Herein, the focus was on the identification of similarities in the weather parameters collected within 19 stations, consisting of 3 weather networks located in the Lower Athabasca River Basin operated under the Oil Sands Monitoring program. These stations were then categorised into seven distinct groups based on comparable topography and land cover. With regard to weather parameters, these were air temperature (AT), precipitation (PR), relative humidity (RH), solar radiation (SR), atmospheric/barometric pressure (BP), snowfall depth (SD), and wind speed/direction (WSD). For all seven groups, relational analysis was conducted for every station pair using Pearson’s coefficient (r) and average absolute error (AAE), except for wind direction and wind speed. Similarity analysis was also performed for each station pair across all seven groups using percentage of similarity (PS) measures. Our similarity analysis revealed that there were no similarities (i.e., PS value < 75%) for: (i) SR, PR, and WSD for all groups; (ii) AT for all groups except group G3; (iii) RH for group G7; and (iv) BP for group G1. This study could potentially be decisive in optimizing or rationalising existing weather networks. Furthermore, it could be constructive in the development of meteorological prediction models for any place and that requires input from surrounding stations.

Long Term Trend Analysis of River Flow and Climate in Northern Canada

Changes in water resources within basins can significantly impact ecosystems, agriculture, and biodiversity, among others. Basins in northern Canada have a cold climate, and the recent changes in climate can have a profound impact on water resources in these basins. Therefore, it is crucial to study long term trends in water flow as well as their influential factors, such as temperature and precipitation. This study focused on analyzing long term trends in water flow across the Athabasca River Basin (ARB) and Peace River Basin (PRB). Long term trends in temperature and precipitation within these basins were also studied. Water flow data from 18 hydrometric stations provided by Water Survey of Canada were analyzed using the Mann-Kendall test and Sen’s slope. In addition, hybrid climate data provided by Alberta Environment and Parks at approximately 10 km spatial resolution were analyzed for the ARB and its surrounding regions during 1950–2019. Trend analysis was performed on the water flow data on monthly, seasonal, and annual scales, and the results were cross-checked with trends in temperature and precipitation and land use and land cover data. The overall temperature across the basins has been increasing since 1950, while precipitation showed an insignificant decrease during this period. Winter water flow in the upper ARB has been slowly and steadily increasing since 1956 because of the rising temperatures and the subsequent slow melting of snowpacks/glaciers. The warm season flows in the middle and lower subregions declined up to 1981, then started to show an increasing trend. The middle and lower ARB exhibited a rapid increase in warm-season water flow since 2015. A similar trend change was also observed in the PRB. The gradual increase in water flow observed in the recent decades may continue by the mid-century, which is beneficial for agriculture, forestry, fishery, and industry. However, climate and land cover changes may alter the trend of water flow in the future; therefore, it is important to have a proper management plan for water usage in the next decades.

Wavelet-based spatiotemporal analyses of climate and vegetation for the Athabasca river basin in Canada

Monitoring spatiotemporal changes in climate and vegetation coverage are crucial for various purposes, including water, hazard, and agricultural management. Climate has an impact on vegetation, however, studying their relationship is challenging. We implemented the Least-Squares Wavelet (LSWAVE) software for investigating trend, coherency, and time lag estimation between climate and vegetation time series. We utilized Normalized Difference Vegetation Index (NDVI) time series provided by the Terra satellite and hybrid climate time series. We found that the seasonal cycles of climate and NDVI are coherent with time delay. For the entire Athabasca River Basin (ARB), the most coherent component was the annual cycle with 84% annual coherency between vegetation and temperature and 46% between vegetation and precipitation. The annual cycles of temperature and precipitation led the ones in vegetation by about two and three weeks, respectively. Relatively lower coherency was observed in the mountainous region (upper ARB) and higher coherency in the middle ARB. From the cross-spectrograms, a clear time delay pattern was observed between the annual cycles of climate and vegetation since 2000 but not for other high-frequency seasonal cycles. The results also highlighted the advantages of LSWAVE algorithms over traditional algorithms, such as linear regression and correlation. Furthermore, we analyzed the annual land use and land cover data provided by the Terra and Aqua satellites and discussed their linkage with the climate and NDVI results.

Soil CO2 Emission Largely Dominates the Total Ecosystem CO2 Emission at Canadian Boreal Forest

The natural carbon dioxide (CO2) emission from the ecosystem, also termed as the ecosystem respiration (Reco), is the primary natural source of atmospheric CO2. The contemporary models rely on empirical functions to represent decomposition of litter with multiple soil carbon pools decaying at different rates in estimating Reco variations and its partitioning into autotrophic (Ra) (originating from plants) and heterotrophic (originating mostly from microorganisms) respiration (Rh) in relation to variation in temperature and soil water content. Microbially-mediated litter decomposition scheme representation are not very popular yet. However, microbial enzymatic processes play integral role in litter as well as soil organic matter (SOM) decomposition. Here we developed a mechanistic model comprising of multiple hydro-biogeochemical modules in the soil and water assessment tool (SWAT) code to explicitly incorporate microbial-enzymatic litter decomposition and decomposition of SOM for separately estimating regional-scale Ra, Rh and Reco. Modeled annual mean Reco values are found varying from 1,600 to 8,200 kg C ha−1 yr−1 in 2000–2013 within the boreal forest covered sub-basins of the Athabasca River Basin (ARB), Canada. While, for the 2000–2013 period, the annual mean Ra, Rh and soil CO2 emission (Rs) are varying within 800–6,000 kg C ha−1 yr−1, 700–4,200 kg C ha−1 yr−1 and 1,200–5,000 kg C ha−1 yr−1, respectively. Rs generally dominates Reco with nearly 60–90% contribution in most of the sub-basins in ARB. The model estimates corroborate well with the site-scale and satellite-based estimates reported at similar land use and climatic regions. Mechanistic modeling of Reco and its components are critical to understanding future climate change feedbacks and to help reduce uncertainties particularly in the boreal and subarctic regions that has huge soil carbon store.

Multifactorial Principal‐Monotonicity Inference for Macro‐Scale Distributed Hydrologic Modeling

AbstractMacro‐scale distributed hydrologic modeling advanced hydro‐system understandings and scientized relevant human activities. However, it faces challenges of hydrometeorological heterogeneities, parametric interactions, data uncertainty, computational expensiveness, and other complexities, especially over cold regions with intense climatic changes. As an effort to address them, a multifactorial principal‐monotonicity inference (MFPMI) method is developed through integrating, extending, or improving climate classification, hydrologic modeling, and sensitivity analysis. MFPMI is applied to an undammed macro‐scale high‐latitude cold‐region watershed, Athabasca River Basin (ARB) in Canada. MFPMI mitigates the underestimation of climatic impacts on streamflows in process‐based models, hydrologic classification, large‐scale hydroclimatic data deconstruction, parametric‐interaction neglection, and climatic homogenization; its superiority is particularly evident for highly heterogeneous climates. Dominant climatic impacts on ARB streamflows of various regimes increase from tributaries to the mainstem and decrease from up‐ through down‐ to mid‐stream catchments, possibly due to the offset effects of non‐climatic factors (e.g., vegetation and soil). The impacts also decline with streamflow magnitudes, and vary with seasons, spatial scales and lead months rather than temporal resolutions. Streamflow magnitudes, catchments and metrics differ compositions of the climate conditions explaining cross‐scale uppermost discharge variations. In spite of this, streamflow increases with temperature and precipitation, and headwater climates play part of dominant roles in forcing discharges throughout ARB. Accuracy metrics differentiate parameters and accordingly structures of MFPMI models, and hydroclimatic data uncertainty is high for high flows, fine temporal scales or low climatic impacts, increasing uncertainty in hydrologic simulations and climatic‐impact estimates. This study helps advance modeling and understandings of macro‐scale cold‐region hydrology.

Late Pleistocene aeolian deposition and human occupation on the eastern edge of the deglacial corridor, northeastern Alberta, Canada

AbstractThe lower Athabasca River basin in northeastern Alberta contains one of the highest known concentrations of prehistoric archaeological sites in the boreal forests of western Canada. This is due to the combination of readily available sources of lithic raw material stone near a major travel corridor, and extensive archaeological survey conducted in advance of oil sands mining. Typological studies have proposed immediate post-glacial occupations that were contemporaneous with, or immediately followed, the catastrophic glacial Lake Agassiz flood through the area at the end of the Pleistocene. Here, we complement the typology age estimates by using stratigraphic relations and infrared stimulated luminescence (IRSL) dating of aeolian material to determine the age of initial human occupation, and reconstruct the environment encountered by early inhabitants of the region. We find that the first occupations in our study area took place near the Pleistocene-Holocene boundary (ca. 11.3 ± 0.8 ka BP), shortly after catastrophic flooding from Lake Agassiz. The post-flood environment was dominated by cold climatic conditions that supported permafrost, presumably during the late Pleistocene, and underwent significant aeolian deposition. Our results indicate that this area represents a portion of the eastern edge of the deglacial corridor into which plants, animals, and humans dispersed following retreat of the Laurentide Ice Sheet.

Variability in flow and tracer-based performance metric sensitivities reveal regional differences in dominant hydrological processes across the Athabasca River basin

Study regionAthabasca River basin, Alberta, Canada (156,000 km2). Study focusHydrology often relies upon hydrologic models in data-sparse regions; however, it is unclear if such models are reliably accurate, or if internal process simulations are reasonable representations of watershed function. Standard model evaluation and calibration approaches often prioritize accurate reproduction of recorded streamflow, ignoring process simulation fidelity, regardless of the intended model application. This study evaluates whether combined use of streamflow and isotope tracer performance metrics can improve representation of simulated streamflow-generating processes within a large river basin, the Athabasca watershed, to inform calibration of a process-based, distributed hydrologic model. New hydrological insights for the regionFlow-based performance metrics were found to be sensitive to processes influencing streamflow volume and timing, but insensitive to internal flow paths and storage volumes. Although somewhat less reliable than flow metrics, isotope tracer performance metrics are found to be most sensitive to processes influencing mixing and water age, and appreciably responsive to many other processes. We demonstrate that process-based hydrologic models for rivers such as the Athabasca River cannot be optimally calibrated using streamflow metrics alone, as such optimizations cannot tune parameters or process representations to which the objective function is insensitive. Importantly, isotope tracers have demonstrable value for informing process-based hydrologic model optimization by providing a window into the sub-surface black box within complex regional-scale simulations.

Investigating the impacts of glacier melt on stream temperature in a cold-region watershed: Coupling a glacier melt model with a hydrological model

Stream temperature is a significant indicator for biodiversity and ecosystem health of stream ecosystem. The impacts of glacier melt processes on stream temperature, such as the cooling effect, have not been explicitly considered in process-based models, which limit model capability in simulating stream temperature in glacierized cold regions. We coupled a temperature index-based glacier melt model with the SWAT equilibrium temperature model to overcome this limitation. The coupled model was tested and applied in the upper Athabasca River basin in western Canada to simulate daily streamflow and stream temperature. It showed a good performance for stream temperature simulation with percent bias (PBIAS) less than ±5% and Nash-Sutcliffe efficiency (NSE) and coefficient of determination (R2) values greater than 0.85. The impact of glacier melt runoff on streamflow and stream temperature simulation was investigated by turning the melt model on and off. The results illustrate that the coupled model accurately reproduces the impacts of glacier melt by simulating higher streamflow and lower stream temperature during the melt season. In particular, the progressive reduction in the cooling effect of glacier melt runoff on stream temperature from headwater to downstream was well represented. Finally, the role of glacier melt runoff affecting stream temperature under climate change was assessed by the scenario simulations. This analysis revealed that an increase in glacier melt runoff in the near future would alleviate the average and peak stream temperature increase during the melt season, while a decrease in glacier melt runoff in the distant future would ultimately aggravate the stream temperature increase. Therefore, the impact of glacier melt runoff should be explicitly considered in process-based models to accurately model stream temperature and predict future climate change impact on the thermal regime in the glacierized watersheds. The model coupling framework developed in this study could be a useful tool for simulating stream temperature in glacierized watersheds.

Population genetics of Bull Trout (Salvelinus confluentus) in the upper Athabasca River basin.

Freshwater ecosystems are negatively impacted by a variety of anthropogenic stressors, with concomitant elevated rates of population decline for freshwater aquatic vertebrates. Because reductions in population size and extent can negatively impact genetic diversity and gene flow, which are vital for sustained local adaptation, it is important to measure these characteristics in threatened species that may yet be rescued from extinction. Across its native range, Bull Trout (Salvelinus confluentus) extent and abundance are in decline due to historic overharvest, invasive non‐native species, and habitat loss. In Alberta's Eastern Slope region, populations at the range margin have progressively been lost, motivating us to better understand the amount and distribution of genetic variation in headwater habitats and some downstream sites where they continue to persist. Across this region, we sampled 431 Bull Trout from 20 sites in the Athabasca and Saskatchewan River basins and assayed 10 microsatellite loci to characterize within‐ and among‐population genetic variation. The Saskatchewan and Athabasca River basins contained similar levels of heterozygosity but were differentiated from one another. Within the Athabasca River basin, five genetically differentiated clusters were found. Despite the evidence for genetic differentiation, we did not observe significant isolation‐by‐distance patterns among these sites. Our findings of ample genetic diversity and no evidence for hybridization with non‐native Brook Trout in headwater habitats provide motivation to ameliorate downstream habitats and remove anthropogenic barriers to connectivity towards the goal of long‐term persistence of this species.

Application of the Least-Squares Wavelet software in hydrology: Athabasca River Basin

Study regionAthabasca River Basin (ARB) in Alberta, Canada. Study focusUnderstanding the historical streamflow variability within basins is crucial to reduce the effect of utmost events, such as drought and floods on agriculture, fishery, and other human activities. The Least-Squares Wavelet software (LSWAVE) is applied to estimate the trend and seasonal components of sixty-year-long climate and discharge time series and to study the impact of climate change on streamflow over time. New hydrological insights for the regionThe seasonal components of the discharge and precipitation time series including annual and semi-annual are coherent with phase discrepancy. The mean temperature has been gradually increasing since 1960, and it is projected to increase by approximately 2 °C during the mid-century which may reduce the snowpack volume during the spring. From the recurring pattern of spectral peaks in the spectrograms and jumps in the trend component of streamflow time series, the blue water is projected to increase during the mid-century, in particular in early 2030s. The results also highlight the potential of LSWAVE in analyzing climate and hydrological time series without any need for interpolation, gap-filling, and de-spiking.

Modelling groundwater quality of the Athabasca River Basin in the subarctic region using a modified SWAT model

Groundwater is a vital resource for human welfare. However, due to various factors, groundwater pollution is a paramount environmental concern. It is challenging to simulate groundwater quality dynamics with the Soil and Water Assessment Tool (SWAT) because it does not adequately model nutrient percolation processes in the soil. The objectives of this study were to extend the SWAT module to simulate groundwater quality for the parameters nitrate and Total Dissolved Solids (TDS). The results of the SWAT model for the Athabasca River Basin in Canada revealed a linear relationship between observed and calculated groundwater quality. This result achieved satisfactory values for coefficient of determination (R2), Nash-Sutcliffe efficiency (NSE), and percent bias (PBIAS). For nitrate, the model performance measures R2 ranged from 0.66–0.83 during calibration and NSE from 0.61–0.83. R2 is 0.71 during validation and NSE ranged from 0.69–0.75. Likewise, for TDS, the model performance measures R2 ranged from 0.61–0.82 during calibration and from 0.58–0.62 during validation. When coupled with soil zone and land surface processes, nitrate and TDS concentrations in groundwater can be simulated with the SWAT model. This indicated that SWAT may be helpful in evaluating adaptive management scenarios. Hence, the extended SWAT model could be a powerful tool for regional-scale modelling of nutrient loads, and to support and effective surface and groundwater management.

Runoff Projection from an Alpine Watershed in Western Canada: Application of a Snowmelt Runoff Model

The rising global temperature is shifting the runoff patterns of snowmelt-dominated alpine watersheds, resulting in increased cold season flows, earlier spring peak flows, and reduced summer runoff. Projections of future runoff are beneficial in preparing for the anticipated changes in streamflow regimes. This study applied the degree–day Snowmelt Runoff Model (SRM) in combination with the MODIS to remotely sense snow cover observations for modeling the snowmelt runoff response of the Upper Athabasca River Basin in western Canada. After assessing its ability to simulate the observed historical flows, the SRM was applied for projecting future runoff in the basin. The inclusion of a spatial and temporal variation in the degree–day factor (DDF) and separation of the DDF for glaciated and non-glaciated areas were found to be important for improved simulation of varying snow conditions over multiple years. The SRM simulations, driven by an ensemble of six statistically downscaled GCM runs under the RCP8.5 scenario for the future period (2070–2080), show a consistent pattern in projected runoff change, with substantial increases in May runoff, smaller increases over the winter months, and decreased runoff in the summer months (June–August). Despite the SRM’s relative simplicity and requirement of only a few input variables, the model performed well in simulating historical flows, and provides runoff projections consistent with historical trends and previous modeling studies.