Hydrology & Terrestrial Ecosystems


Multi-model Intercomparison Project on the Saskatchewan-Nelson-Churchill River Basin (Nelson-MiP)

First Author: Mohamed Ismaiel Ahmed, Postdoctoral associate

Additional Author(s): Tricia Stadnyk, Alain   Pietroniro, Hervé Awoye, Ajay Bajracharya, Juliane Mai, Bryan Tolson, Hongren   Shen, James Craig, Wouter Knoben, Martyn Clark, Hongli Liu, Shervan Gharari,   Kristina Koenig, Shane Wruth, Phillip Slota, Mark Gervais, Kevin Sagan, Rajtantra   Lilhare, Stephen Dery, Scott Pokorny, Hank Venema, Ameer Muhammad, Curtis   Hallborg, Mahkameh Taheri

Abstract: Hydrologic models   have been utilized over the past few decades to understand and simulate the   hydrologic cycle and predict various risks to the communities (floods or   droughts) globally. However, running these models on large-scale domains with   numerous managed and unmanaged lake/wetland systems (such as the complex   prairie environment) might be problematic. This intercomparison study is the   first of a series of studies under the intercomparison project of the   international transboundary Nelson-Churchill River Basin (NCRB) in North   America (Nelson-MiP), which encompasses major areas of the prairie region. In   this intercomparison study, the performance of nine hydrologic and land   surface models is compared at unregulated basins within NCRB to better identify   a set of models that has realistic representation of the different hydrologic   processes, which can be used to predict streamflow accurately, especially   under future climate change in such complex environments. Results show that   most of the participating models have significant discrepancies in simulating   the streamflow and internal hydrologic variables (e.g., evapotranspiration   and snow water equivalent) over prairie basins due to some model structural   deficiencies. This study identifies the limitations across the participating   models for future model structural improvements/developments. This study’s   outcomes can help practitioners in accurately predicting the NCRB streamflow,   which is crucial for better water resource management and allocation over   that basin.

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Spatial trends and distribution of Surface Temperature and Ice thickness on Sub-artic lakes using remote sensing and modelling

First Author: Gifty Attiah, Wilfrid Laurier University


Additional Author(s): Homa Kheyrollah Pour, Wilfrid Laurier UniversityAndrea Scott, University of Waterloo


Abstract: Sub-artic lakes are crucial to the physical, biological and climate processes of a region. Ice covered for majority of the year these lakes are sensitive to regional climate and their freeze-up, break-up and ice duration are good indicators of changes in climate. Additionally, lake ice is a valuable resource to northern communities because ice roads are constructed (e.g., the ice longest road in Yellowknife, (NWT), spreading over 80 lakes) during winter to haul goods to and from industrial establishments (e.g., mines) and for travel within and between communities. The shorter ice duration and decrease in thickness, however, are a major detriment to the ongoing use of ice roads due to climate warming. Studies show that a one-degree increase or decrease in air temperature leads to a 6-day almost linear change in ice cover duration making it an essential climate variable to monitor. Crucial knowledge on lake ice processes and temperature is however limited in availability especially in monitoring sub-artic lakes due to logistical difficulties in collecting direct measurements. To address this limitation, this study uses remote sensing data coupled with a thermodynamic lake ice model to monitor the spatial distribution of surface temperature, duration, and thickness of lake ice.


Over 500 small to medium lakes in Northwest Territories which is a lake-rich region with several small lakes, are monitored from 1984 to 2021. Monitoring on such a large scale for small to medium lakes has not been conducted in this region previously, hence this study provides a novel approach to demonstrating the temporal and spatial trends of lake ice cover in this region. To effectively simulate lake ice thickness, an algorithm-based lake surface temperature (LST) for each lake was derived from the thermal bands of Landsat, which showed good agreement with in-situ data (1.88°C > RMSE >1.54(°C)). Increasing temperature trends were observed for both ice cover and open water periods for lakes studied. The derived LST are used as an input in spatially distributed thermodynamic model in addition to other input variables such as (wind speed (m s-1), mean air temperature(°C), relative humidity (%), snow depth(m) and cloud cover (0-1)) derived from reanalysis (ERA5). Daily spatial distribution of ice thickness was simulated for each lake on a 100m spatial resolution from 1984 to present. To evaluate model estimations of ice thickness field work was conducted to collect ice thickness measurements across 10 lake sites in Northwest West Territories.

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Analysis of carbon and water cycle variability in Canadian watersheds using coupled MESH-CLASSIC model

First Author: Daniel Mutton, 1,2. 1 School of Earth, Environment, and Society, McMaster University, Hamilton, Ontario, Canada 2 McMaster Centre for Climate Change, McMaster University, Hamilton, Ontario, Canada

Additional Author(s): M. Altaf Arain1,2, Bruce Davidson3, Daniel Princz3. 1 School of Earth, Environment, and Society, McMaster University, Hamilton, Ontario, Canada 2 McMaster Centre for Climate Change, McMaster University, Hamilton, Ontario, Canada 3 Environment and Climate Change Canada, Saskatoon, Saskatchewan, Canada


Abstract: Recent advances in the Mod´elisation Environmentale Communautaire Surface and Hydrology system (MESH) allows for vector-based routing to better represent the reality of the catchment structure and water processes within the catchment. MESH has also been coupled with the Canadian Land Surface Scheme including Biogeochemical Cycles (CLASSIC) allows for the simulation of carbon, water, and energy cycles at a catchment scale. In this study, the MESH-CLASSIC model was tested in three catchments across Canada, the Groundhog River catchment (a Boreal Forest catchment in northern Ontario), the Big Creek catchment (a managed agricultural catchment in southern Ontario), and the White Gull Creek catchment (a boreal forest and wetland in northern Saskatchewan). The vector-based MESH-CLASSIC model simulations were performed for historic and future climate change scenarios, RCP 4.5 and 8.5. Model biases in simulating hydrological processes such as stream flow, evapotranspiration, snow mass, and soil moisture will be evaluated, and model performance will be evaluated with underperforming areas identified with the intent to improve these processes and the model’s capability. Early research suggests that the model overestimates streamflow and snow mass estimates, as well as predicts major events will start earlier than they do.


A process-based sensitivity guided calibration of the VIC model

First Author: Samah Larabi, Pacific Climate Impacts Consortium, University of Victoria, Victoria, British Columbia, Canada


Additional Author(s): Markus A. Schnorbus, Pacific Climate Impacts Consortium, University of Victoria, Victoria, British Columbia, Canada


Abstract: Land surface models have large numbers of parameters the sensitivities of which can vary spatially over large spatial domains. In past applications of these models over large domains, calibration has often relied on adjustment of few select parameters that are assumed to have consistent sensitivity regardless of the presence of large hydro-climatic gradients. This approach limits the flexibility of the model to operate effectively under varying hydro-climatic conditions (i.e., model agility). In this study, we explore a sensitivity guided process-based calibration applied to the Variable Infiltration Capacity Model (VIC) over five basins with dissimilar hydroclimatic conditions. A global sensitivity analysis was used to evaluate the sensitivity of 44 VIC parameters to streamflow, evapotranspiration, and snow cover area. This study shows that expanding parameter calibration beyond the traditionally selected parameters improves model performance to simulate internal hydrologic processes. Regardless of the hydroclimatic conditions, fifteen parameters are consistently recommended for calibration which includes eleven soil parameters and four vegetation parameters (root fractions, spring LAI and minimum stomatal resistance). The recommended soil parameters are the thickness of the three soil layers, maximum velocity of baseflow i.e., dsmax, the fraction of dsmax where non-linear baseflow begins, variable infiltration curve parameter, fraction of maximum soil moisture where non-linear baseflow occurs, bulk density, fractional soil moisture content at the critical point and residual moisture. Additional parameters should also be considered depending on the dominance of hydrological processes, such as snow parameters in snow-dominated regions. Overall, this study shows that calibration guided by a multi-objective sensitivity analysis improves model agility and accuracy.


Modelling highly disturbed basins: the Upper Columbia and Okanagan River Basins

First Author: Zelalem Tesemma, Centre for Hydrology, University of Saskatchewan, Saskatoon


Additional Author(s): John Pomeroy, Alain Pietroniro, Centre for Hydrology, University of Saskatchewan, Saskatoon


Abstract: The Upper Columbia and Okanagan River basins are important mountain headwaters to provide biodiversity and ecosystem services and to supply water for hydropower dams and reservoir operations in British Colombia, Canada, and the northwest United States. However, the impact of forest disturbance by forest harvesting, disease, and wildfire and then recovery, and deglaciation on the basin hydrology has not been thoroughly studied. The impact of largescale forest disturbances in the basin on the magnitude of recent flooding has not been fully investigated. This study aims to develop a methodology to simulate forest disturbance and regrowth in a hydrological land surface model and then use the model to investigate the impact of forest disturbance on the basin hydrology. An enhanced version of MESH (Modélisation Environnementale communautaire - Surface Hydrology) that incorporated mountain hydrology and vector base routing was setup over a total of 2177 model sub-basins; 1822 for the Upper Columbia and 355 for the Okanagan and Similkameen River basins. Subbasin areas range from 0.005 to 366 km2. The Global Multiscale Model (GEM) with precipitation replaced by the Canadian Precipitation Analysis (CaPA) (~10 km), version RDRS v2 meteorological forcings were used to drive the model. As forest and glaciers are important to the hydrology of the study basin, a particular attention was given in the basin discretization to these. Glaciers were grouped into three classes based on elevation band: high, mid, and low elevation glacier and the albedo value of the three classes were separately computed from the available MODIS albedo remote sensing data. Forests were segregated into four classes based on their species into Hemlock, Fir, Pine, and Spruce. In addition, forest harvesting, regrowth and wildfire were treated separately from mature forest. The wildfire areas were variable from year to year but parameterized in a similar way as barren land. However, forest harvesting, and regrowth were further segregated into three groups by age as Fresh Clear-cut, Clear-cut up to 5 years old and Clear-cut aged 5 years and above and parametrized using MODIS LAI data. The methodology developed to model forest disturbance and regrowth is innovative in a continental scale hydrological model. The preliminary results of the forest disturbance and regrowth model in MESH will be demonstrated.


Assessment of Groundwater Flow Significance in Hydrologic Models

First Author: Xin Tong PhD student (University of Waterloo)


Additional Author(s): Walter A. Illman1, Young-Jin Park, David L. Rudolph (University of Waterloo), and Steven J. Berg (University of Waterloo; Aquanty Inc.)


Abstract: Groundwater plays a vital role in the hydrologic cycle as it is the largest component of available freshwater. Therefore, diagnosing and predicting hydrologic changes and water futures in Cold Regions will have to account for groundwater. Hydrologic models play an important role in this process. There is a wide spectrum of models of varying complexities available to simulate surface water/groundwater flow and transport. The various users of such models question what level of complexities need to be considered within these different models to achieve project objectives. Currently, there are no clear guidelines or criteria to assist users in selecting appropriate hydrologic models for a specific application. Hydrological models range from lumped parameter models to spatially distributed models to discretize the watershed and represent key hydrologic processes.

The main objective of this project is to examine the significance of shallow/deep groundwater flow in both unsaturated and saturated zones on surface water flow predictions through high-resolution numerical simulations with HydroGeoSphere (HGS) (Aquanty Inc, 2021), a 3D physics-based, fully-integrated hydrologic model. The spatial and temporal variations in surface water and groundwater fluxes including its distributions are investigated using data from the well-instrumented Alder Creek Watershed (ACW) (~79 km2) within the Grand River Basin in southern Ontario. In particular, five integrated hydrologic models with an increasing level of complexity to represent the subsurface using HGS have been developed to highlight the significance of groundwater fluxes on surface water flow through: 1) a (2-D) model incorporating only overland flow data without considering the subsurface; 2) a model with a thin soil layer (1-meter deep); 3) a 7-layer model witha shallow subsurface consisting of heterogeneous and anisotropic hydraulic parameters; 4) a 10-layer model with a deeper subsurface consisting of homogeneous and uniform hydraulic parameters; and 5) a 10-layer model with detailed subsurface information on hydrostratigraphy consisting of heterogeneous and anisotropic hydraulic parameters. In addition, Raven (Craig et al., 2020) an object-oriented hydrological model based on hydrological response units (HRUs) is constructed based on individual modules corresponding to specific hydrological processes. The five HGS models and the Raven model all share the same high-resolution topography information, landcover representation, temporal precipitation records, and evapotranspiration data.

Forward simulation results of a three-year hydrological cycle with the HGS and Raven models are qualitatively and quantitatively compared. Results reveal that models that treat the subsurface more accurately lead to improved predictions of surface water distribution and hydrographs.


Drivers of hydrological response for distinct wetland complexes in a high latitude alpine watershed.

First Author: Lauren Bourke, McMaster University


Additional Author(s): Sean K. Carey, McMaster University

Abstract: Alpine wetlands in northern landscapes are abundant and critical for runoff regulation and seasonal water storage. Although extensive work has been conducted on water table dynamics in temperate wetlands, little has been conducted on the hydrology and heterogeneity of water table responses of high latitude alpine wetlands. This research aims to compare the hydrological response of two distinct subarctic alpine wetland types near Whitehorse, YT; a valley bottom wetland and a perched wetland system. Each wetland was instrumented with a series of well nests and pressure transducers to evaluate hydrological gradients and water table changes.Weekly isotopic samples of hydrogen (d2H) and oxygen (d18O) were taken to identify source waters for the wetlands and evaluate their degree of evaporative fractionation. As the perched wetland dried early in the season, both d18O and d2H increased, while in the valley bottom d18O and d2H values remained consistent. The deviation from the local Meteoric Water Line was calculated using line-condition excess (lc-excess), and the perched wetland had greater kinetic fractionation (mean lc-excess = -13.2 ‰), compared to the valley bottom (-3.6 ‰). After snowmelt, water tables dropped consistently at both wetlands, leading to rapid drying of the perched ponds, however, the valley bottom wetland remained wet throughout the summer as it was sustained by flow from adjacent hillslopes. During rain events, water level response at the perched wetland was relatively consistent with comparable magnitudes between each well. In the valley bottom wetland, the lower elevation wells showed a greater sensitivity to rain events. These results suggest that the position of wetlands in the landscape plays a critical role in how wetlands store and cycle water; valley bottom wetlands remain wet and serve as an important dry season reservoir of water, while perched wetlands rapidly go dry after initial snowmelt contributions.


Quantifying Groundwater Storage and Discharge in Alpine Environments

First Author: Brayden Ralph, University of Calgary


Additional Author(s): Masaki Hayashi, University of Calgary


Abstract: Major rivers that originate in mountainous areas provide the main water supply for more than one third of the world's population. These rivers typically exhibit a four-to-five-month high flow period driven by snowmelt and rain, followed by a seven-to-eight-month low flow period sustained by groundwater discharge from mountain headwaters. Recent small-scale and field-based studies have identified talus slopes, moraines, rock glaciers, and alpine meadows as the main landforms responsible for storing and discharging groundwater in these headwater environments and have further classified them as alpine aquifers. However, there has not been much progress upscaling our current small-scale understanding of alpine aquifers to the watershed-scale. This study aims to upscale our knowledge of alpine aquifers by developing a geospatial modelling approach that can 1) map the spatial extent and distribution of different aquifers that are common in alpine watersheds and 2) employ a numerical groundwater flow model to simulate annual groundwater storage and discharge for a given watershed. The Opabin sub-watershed, located within the Lake O'Hara watershed in British Columbia will be used as the pilot site. Over the past 15 years, numerous research studies have thoroughly characterized the aquifers present and developed an extensive library of relevant hydrological data. Present aquifers will be identified and differentiated from one another using an object-oriented classification technique that incorporates remote sensing imagery and a digital elevation model, that cover the extent of the watershed. After, the extent of the aquifers will be extracted from the classified map and discretized in a numeric groundwater flow model. Representative storage and discharge characteristics derived from the existing library of field-data will then be assigned to each aquifer, enabling the model to simulate the annual propagation of snowmelt and rain through the aquifers present and in doing so, effectively quantify annual groundwater storage and discharge in the Opabin sub-watershed. The resulting model will be calibrated and validated using measured stream discharge data from Opabin creek, and the model efficacy will be evaluated by applying it to two other watersheds in the Canadian Rockies, specifically within the Bow River basin. The new modelling approach will provide an efficient tool to quantify and predict the annual groundwater contributions from mountain headwaters to major rivers, which will in turn help downstream populations sustainably manage their water supply.

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Effects of microforms on the evaporation of peat-bryophyte-litter column in a montane peatland in Canadian Rocky Mountain

First Author: Yi Wang, Hydrometeorology Research Group, University of Waterloo


Additional Author(s): Richard Petrone, Hydrometeorology Research Group, University of Waterloo


Abstract: Peatland microtopography contains hummocks (local high points) and hollows (local low points). Little is known about how the evaporation of peat (P), peat-bryophyte (BP), peat-litter (LP) and peat-bryophyte-litter (LBP) columns vary with peatland microforms. Whether there are fine-scale variations in peatland evaporation, and if they are critical when being upscaled to the entire peatland ecosystem is yet to be answered. Our study found that evaporation was significantly affected by the cover type (P, BP, LP or LBP) and the interaction effect of the cover type and microform, based on field evaporation experiments in a montane peatland in Canadian Rocky Mountains during the growing season of 2021. Mean daily evaporation of P-Hummock and P-Hollow was 14.16 and 11.76 g d-1, respectively; BP-Hommock and BP-Hollow is 9.57 and 14.38 g d-1, respectively; LBP-Hummock and LBP-Hollow is 9.44 and 9.91 g d-1, respectively; and evaporation of LP-Hummock and LP-Hollow is 5.68 and 7.64, respectively. Peatland microform indirectly affected evaporation by interacting with cover type, modifying the vertical profile of soil temperature, and changing the key environmental drivers of evaporation. Moreover, we tested the ability of two widely used models in modelling the spatial variation of peatland evaporation. We found that the Penman-Monteith (P-M) model and bryophyte layer model in the Atmosphere-Plant Exchange Simulator (APES) were able to yield satisfactory results based on field measurements of soil temperature and soil moisture. Our study provides valuable information supporting the evaluation on the hydrological state of peatland ecosystems.


The drying of the Arctic and active layer development: a case study from the Western Canadian Arctic

First Author: Brampton Dakin

Additional Author(s): David Rudolph, Philip Marsh, Fereridoun Reza Nezhad


Abstract: As the Arctic climate warms there have been observed changes in snowfall and rainfall, as well as increasing evaporation, deepening of the active layer, changes in soil water storage, and changes in slope runoff. These combine to impact streamflow and runoff in poorly understood ways. Previous research has shown that it is not clear whether these changes will result in the Arctic becoming wetter or dryer. The summer of 2021 was an example of the latter for the Inuvik area, with the 7th warmest summer and driest July on record (Environment and Climate Change Canada). This presented a unique opportunity to study a warm and dry summer that may be an example of a future drying Arctic allowing insight into what might be expected. The research outlined here will address this issue using a physics-based model, GEOtop, to carry out numerical experiments. GEOtop is a permafrost hydrology model able to explore the processes controlling frost table depths and runoff over the summer. GEOtop is designed to handle micro topographies common across much of the Arctic tundra. We will apply GEOtop to a long-term research watershed in the western Canadian Arctic. Specifically, we will focus on Siksik Creek, a sub catchment of Trail Valley Creek Research (TVC) watershed, located 50 km north of Inuvik. Field data was collected throughout the summer of 2021. Data collection included measurements of frost table depths; water table depths; and stratigraphy and soil thicknesses across mineral earth hummocks and their inter-hummock zones. These data were collected along 15 transects that included a variety of terrain and vegetation types found in TVC. In addition to analyzing the 2021 field data, there is climate and streamflow data from other years across the 30-year period of record at TVC. We will then apply GEOtop to investigate the effects of a changing climate on the hydrology of the Siksik Creek region.

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Impacts of tall shrub expansion on the hydrological dynamics of a low-arctic catchment

First Author: Cory Wallace, McMaster University


Additional Author(s): Evan Wilcox, Wilfrid Laurier University; Qianyu Chang, Guelph University; Anna Coles, Government of the Northwest Territories; Oliver Sonnentag, Université de Montréal; Philip Marsh, Wilfrid Laurier University; Aaron Berg, University of Guelph; Jennifer Baltzer, Wilfrid Laurier University


Abstract: Shrub productivity and areal extent is increasing across much of the circumpolar arctic. Substantial focus has been placed on understanding the potential influence of this shrub expansion on global-scale surface energy balance feedbacks, including increased transport of water to the atmosphere, decreases in albedo, and changes to the carbon cycle. Much of our understanding of these processes has been informed by fine-scale studies, which document important impacts of shrub cover on hydrological conditions such as soil moisture, thaw depth, snow redistribution, and evapotranspiration. Despite this understanding, the cumulative effects of these local impacts have yet to be extended to hydrological responses at a regional or catchment scale.


Here we propose a conceptual model which considers the various hydrologically relevant ecosystem impacts of shrub expansion and generates specific hypotheses about how they may influence catchment-scale streamflow response to summer rainfall events. In particular, we expect increased shrub cover to increase evapotranspirative fluxes and interception, resulting in less total discharge and hydrographs with longer receding limbs. We test these hypotheses using time series of Normalized Difference Vegetation Index (NDVI), climatic variables, and streamflow responses collected from Trail Valley Creek, a watershed at the northern edge of the taiga-tundra ecotone of the Northwest Territories. As expected, maximum NDVI increased across much of the watershed, with 63% of pixels greening significantly from 2000 to 2019 and no pixels significantly browning. While both rainfall and discharge showed long term increases, the timing of these trends was inconsistent such that months showing increasing rainfall never displayed increasing streamflow. We propose that the lack of direct streamflow response to changing rainfall may be explained by shrub expansion across the basin. Our next steps are to test this by comparing individual storm responses in climatically similar years early and late in the time series to isolate the shrub response. Evidence of such a response would suggest shrub expansion may mediate future streamflow-climate relationships, complicating predictions of water resource availability in arctic systems.

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Mapping thermokarst land systems

First Author: Jason Paul


Additional Author(s): Steve Kokelj, Northwest Territories Geological Survey


Abstract: Permafrost has a profound influence over physical and biological processes shaping circumpolar environments. Models project widespread thawing of near-surface permafrost over the coming century, which will eradicate thin sporadic permafrost at its southern extent and shift the discontinuous zone northward. Anthropogenic climate change has intensified thermokarst processes such that ice-rich permafrost regions are being modified at increasingly rapid rates. Understanding how thaw-driven landscape change will manifest across a diverse range of biophysical environments, and anticipating the ecosystem, biogeochemical, carbon, and societal consequences remains a major knowledge gap in Arctic change science. The Thermokarst Collective (TKC) is a northern-driven mapping project initiated by the Northwest Territories Geological Survey to develop a comprehensive mapping inventory of remote-sensed thermokarst features across the entirety of the NWT. Hydrological, mass wasting, and periglacial thermokarst features are mapped within 7.5 x 7.5 km grid cells using Sentinel 10 m resolution imagery. In addition, a systematic aerial inventory and characterization of thaw-sensitive permafrost terrain was undertaken in summers of 2020 and 2021. During this time the project has assessed approximately 28,000 km of flight lines and compiled about 8,000 permafrost landform observations and thermokarst terrain attributes. These data are complemented with over 20,000 georeferenced oblique photographs that are being organized in a geospatial database. Here we present a some comparisons between TKC generated feature data with mapped or modelled features from published research examining particular regions of the NWT. The spatial data from this project show significant departures from modelled terrain sensitivity products highlighting the utility of broadscale empirical datasets. This mapping inventory characterizes over 25 variables describing thermokarst and periglacial landforms. We illustrate the depth of the datasets through exploring within and between regional variation in the suite of landforms that describe permafrost sensitivity. These analyses highlight that variation in geological and paleoenvironmental legacy and climate drivers combine to yield a diverse array of thermokarst and periglacial landform assemblages indicating the terrain consequences of permafrost thaw will vary in complex ways across the northern landscape. The novel and holistic approach to characterizing permafrost terrain taken in this project yields significant potential for exploring variation in terrain consequences of permafrost thaw, and provides a geological basis for re-framing how we think about what permafrost thaw will mean to the landscapes, ecosystems and communities of the north.


The Influence of Weather Seasonality on Well Vulnerability in Cold Regions

First Author: Haoyu Yin, University of Waterloo

Additional Author(s): Andrew Wiebe, McGill University; David Rudolph, University of Waterloo; Jeffrey McKenzie, McGill University.


Abstract: The residents of Carmacks, Yukon Territory, rely heavily on groundwater as their water supply, and a municipal pumping well surrounded by an oxbow of the Yukon River supplies most of the demand for the Little Salmon Carmacks First Nation. The high level of dependence on groundwater at Carmacks makes groundwater protection necessary. Human activities, such as land-use practices and waste disposal in landfills may, impact groundwater quality, and remediation will be costly and difficult once the Łots'an and Chu íntthi Aquifers have been contaminated. Further, the increasing flooding risk at Carmacks is another threat to groundwater quality. A well vulnerability assessment is recommended to understand the impacts of anthropogenic activities and flooding, where accurate well capture zone estimation is integral. Methods for calculating well capture zones with analytical solutions are limited to simple cases and steady state assumptions, but numerical methods can incorporate flow boundaries posed by surface water features and produce capture zone simulations that deal with variable hydrological conditions. Therefore, a fully integrated surface water-groundwater numerical model, HydroGeoSphere (HGS), is used to simulate well capture zones under three scenarios which represent different situations. The first scenario focuses on the well capture zone under a steady-state flow field, the second scenario examines the impacts of seasonal weather changes on the well capture zone, and the third scenario analyzes the influence of flooding hazards on the well capture zone. Based on initial results, flooding and changes in seasonal weather likely influence the extent and orientation of the capture zone compared with a steady-state scenario The research outcomes are expected to advance well vulnerability assessment in Carmacks and provide insight for future groundwater studies in cold regions.


Posterior-informed feature importance method for examining how large-scale climatic indices influence hydrological processes in Continental US

First Author: kailong Li, Global institute for water security

Additional Author(s): Saman Razavi, Global institute for water security


Abstract: Feature importance has been widely used for machine learning models to examine the relative significance of model predictors. This study developed a posterior-informed feature importance method (PIFI) for hydrological inference. The proposed PIFI is based on the bootstrap aggregated Wilks statistics and stratified sampling Bayesian model averaging (SSBMA). Each Wilks statistics is considered an ensemble member of SSBMA, and its posterior probabilities are evaluated based on a spectrum of streamflow quantile ranges. Compared with conventional feature importance methods such as permutation feature importance (PFI) and mean decrease in impurity (MDI), the proposed PIFI can help investigate the varying significance of a predictor in response to the variations of streamflow. PIFI has been applied to the Catchment Attributes and Meteorological (CAMELS) dataset, which contains forcing and hydrologic response data for 673 basins across the contiguous United States that spans a very wide range of hydroclimatic conditions. In attempting to demonstrate the relative importance of meteorological data and large-scale climatic indices on streamflow, we used monthly mean values of meteorological data in CAMELS dataset and four commonly used large-scale climatic indices (including Nino3.4, Pacific decadal oscillation (PDO), interdecadal Pacific oscillation (IPO) and Pacific North American index (PNA)) to simulate the monthly streamflows. Our results suggest that Nino3.4 strongly influences both low and high flows, whereas IPO indicates the most substantial influence over median flows. These results can help us better understand how drought and flood may be associated with large-scale climatic indices.


Climate change in global terrestrial water storage at the daily timescale

First Author: Fei Huo, Global Institute for Water Security, University of Saskatchewan

Additional Author(s): Li Xu, Global Institute for Water Security; Yanping Li, Global Institute for Water Security; Zhenhua Li, Global Institute for Water Security.


Abstract: Climatologists use formal detection and attribution methods to identify externally forced signals in the observed climate record. Even with these widely used methods, it is still difficult to detect climate change in terrestrial water storage (TWS) at global scale due to the brevity of the time series from global freshwater observations. In this study, we applied a novel method to identify relationship between annual global mean TWS and daily weather patterns (including surface air temperature and humidity fields) using hydrological simulations from ISIMIP2b, yielding fingerprints of anthropogenically forced change. Reanalysis datasets are projected onto the fingerprints to detect climate change at daily scale. It is found that approximately 80% of days for most years since 2016 have informed climate change signals, with high inter-annual variability. While strong signals of forced climate change in global mean TWS could not be uniformly detected from each day during the studied period, the fraction of days detected started to surge from the mid-1970s. Climate change signals in global mean TWS have been accumulated over the last few decades, and our results show that such signals will probably be uniformly detected in every day in the next few decades.

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Exploring Impacts of Climate Variability and Disturbance on the Carbon Dynamics of a Young Temperate Coniferous Forest

First Author: Farbod Tabaei, McMaster Centre for Climate Change


Additional Author(s): M. Altaf Arain, McMaster Centre for Climate Change

Abstract: The vital role of forests in the global carbon cycle is well-established, but the influence of management practices on forest carbon dynamics remains overlooked. Forest thinning is a common practice conducted following afforestation or stand plantation to sustain and improve the carbon sequestration rates of the forest ecosystem. Using the eddy covariance (EC) method, this study investigates the impacts of thinning on the forest carbon exchange. In January 2021, selective thinning was conducted on a 48-year-old white pine (Pinus strobus) plantation in Southern Ontario, Canada, to remove approximately 20% of the trees on site. By utilizing eddy covariance CO2 fluxes and meteorological measurements, gross primary productivity (GPP), ecosystem respiration (RE) and net ecosystem productivity (NEP) were estimated following thinning. Study results will show the extent of changes in CO2 fluxes by comparing them to data from the previous nine years. Previous studies conducted on an adjacent 83-year-old white pine plantation indicated insignificant effects of thinning, and small reduction of NEP primarily due to increased RE in the first post-thinning year while stand remained a net carbon sink. A complete understanding of the response of forest carbon dynamics to thinning in young plantation forests is critical to guiding future forest management efforts. Further, past research has indicated improved tolerance to droughts following thinning, providing the potential to enhance carbon sequestration rates and growth in temperate coniferous forests.


Uncertainty estimations for mapping lake ice using random forest on MODIS TOA reflectance data

First Author: Dr. Nastaran Saberi, Reserch associate, Department of Geography and Environmental Management, University of Waterloo


Additional Author(s): Prof. Claude Duguay, Department of Geography and Environmental Management, University of Waterloo; Dr. Andrea Scott, Department of Systems Design Engineering, University of Waterloo


Abstract: Lake ice coverage products are a requirement identified by the climate community for improving numerical weather prediction and atmospheric reanalysis products, as well as for climate monitoring as determined by the Global Climate Observing System (GCOS). There are many suitable sources of observations available for mapping and monitoring lake ice coverage such as optical satellite data with the most practical ones from the Moderate Resolution Imaging Spectroradiometer (MODIS) over the last two decades. Considering the limitation of the presence of cloud cover and daylight dependency to capture imagery by optical sensors, the high revisit time of NASA’s Terra and Aqua satellites that carry MODIS allows for the production of lake ice maps required for operational and research-based projects.


Building on our previous research findings concluded from a GWF-supported project on lake ice cover mapping of Lake Erie from RADARSAT data, we are proposing a method to characterize inherent uncertainties (aleatoric) and model uncertainties (epistemic) for the production of daily lake ice maps. Random Forest (RF) is used for classifying lake ice, water, and cloud and for measuring and quantifying predictive uncertainty. As RF is an ensemble-based approach, it allows learning different hypotheses (different trees); and therefore, it provides different expected outcome. The total uncertainty in a prediction can be calculated by the (Shannon) entropy of the predictive posterior distribution, whereas calculating the entropy of each probability distribution and then computing the average gives the aleatoric uncertainty. Epistemic uncertainty is then calculated by subtracting aleatoric from total uncertainties. Uncertainty estimates expands product usability, making researchers aware of aleatoric and epistemic uncertainty when incorporating ice fractions in their physical/numerical lake models in the form of direct integration of observation error variance or as a quality control flag.


Remote sensing application for evapotranspiration and crop growth estimation in Corn and Grape fields in Southern Ontario

First Author: Nur Hussain, PhD Candidate. School of Geography and Earth Sciences and McMaster Centre for Climate Change, McMaster University, Hamilton, Ontario, L8S 4L8, Canada

Additional Author(s): M. Altaf Arain, Professor, School of Geography and Earth Sciences and McMaster Centre for Climate Change, McMaster University, Hamilton, Ontario, L8S 4L8, Canada.


Abstract: Evapotranspiration (ET) is one of the main influencing factors in the water balance of crop ecosystems. This study focuses on the application of remote sensing (RS) data to estimate ET and crop growth in corn and grape fields in southern Ontario. Sentinel-2 high-resolution (10 m) satellite-derived land surface albedo, Enhanced Vegetation Index (EVI), Normal Difference Vegetation Index (NDVI), Normal Difference Water Index (NDWI), Vegetative Water Content (VgWC), Leaf Area Index (LAI), and Gross Primary Production (GPP) are used to evaluate crop growth and water use. Atmospheric and radiometric corrections are applied to drive traditional Vegetation Indices (VIs) and test empirical models for this study. LAI is estimated by applying the PROSAIL, awidely used coupled PROSPECT and SAIL radiative transfer model, considering their correctness for retrieving biophysical and biochemical components for agricultural crops. GPP is estimated by using the Land Surface Energy Balance (LSEB) model utilizing the Light Use Efficiency (LUE). The Penman-Monteith energy balance equation is used to estimate ET through the Surface Energy Balance Algorithm in the Land (SABLE) model. Eddy Covariance (EC) flux measurements of GPP and ET are also utilized to validate the study results. This study will help to explore the energy and water balances, different crop characteristics and crop water stress in changing environments, especially due to extreme weather events. The result of this study will help to enhance crop yields and develop agricultural management, drought mitigation and crop water stress reduction strategies.


Keywords: Evapotranspiration, Water balance, Energy balance, Remote Sensing, Crop water stress, PROSPECT model, Agriculture.


A detailed look at Phosphorous accumulation in a 12-year old multi-cell bioretention system using sequential extractions

First Author: Ariel Lisogorksy, University of Waterloo

Additional Author(s): Elodie Passeport, University of Toronto; Philippe Van Cappellen, University of Waterloo; Chris Parsons, Environment and Climate Change Canada; Mahyar Shafii, University of Waterloo; Bowen Zhou, University of Waterloo; Fereidoun Rezanezhad, University of Waterloo


Abstract: Bioretention cells are an increasingly popular family of urban stormwater management structures that intercept runoff from impervious surfaces. When incorporated into urban catchments, they have been shown to favorably reduce the ‘flashiness’ and overall volume of flow resulting from storm events by promoting storage, groundwater infiltration and evapotranspiration. Studies looking at their impact on Phosphorus (P) have produced varied and conflicting outcomes. Studies looking at more detailed P geochemistry of bioretention systems are necessary to identify the processes that are most likely to be responsible for the divergences in behavior. The SEDEX sequential extraction technique was used to analyze concentrations of six phosphorous fractions in samples collected from a set of12-year-old bioretention cells in Mississauga, ON. P variation in the system was best explained in terms of changes within the redox sensitive (Fe/Mn associated) and organic matter associated ( organic P, humic bound and extractable p) systems which were further corroborated similar trends in Fe/Mn and organic carbon concentrations in the samples. Comparatively, Ca associated P fractions appear to have remained invariant spatially despite evidence for increased Ca concentrations within the media. These results, in addition to the heavy surface bias in concentrations and estimated accumulation rates observed suggest that the system has potential to continue accumulating P for some time and that surface dredging or biomass removal from the surface may be effective for system maintenance. On the other hand, increased concentrations within redox-sensitive pools suggest that anoxic conditions such as those produced during severe flooding may cause this system and others like it to undergo intense leaching events.


Seasonal Resilience of Microbial Communities in Agricultural Soils

First Author: Grant Jensen, University of Waterloo

Additional Author(s): Konrad Krogstad, University of Waterloo; Fereidoun Rezanezhad, University of Waterloo; Laura Hug, University of Waterloo

Abstract: Microbial activity persists in agricultural soils throughout the non-growing season (NGS) and related freeze-thaw cycles (FTCs), with peak activity during thaw events.Climate change is expected to increase the frequency of FTCs with a less stable snowpack in temperate regions, which may hasten microbial consumption of fall-amended fertilizers, decreasing potency come the growing season. We conducted a high-resolution examination of the impacts of freeze-thaw and nutrient stress on microbial communities in agricultural soils across both soil depth and time. Four soil columns were incubated under a climate model of a NGS including precipitation, temperature, and thermal gradient with depth over 60 days. Two columns were amended with fertilizer, and two incubated as unamended soil. The impacts of repeated FTCs and nutrient stress on bacterial, archaeal, and fungal soil community members were determined, providing a deeply sampled longitudinal view of soil microbial response to NGS conditions. Geochemical changes from flow-through leachate and amplicon sequencing of 16S and ITS rRNA genes were used to assess community response to fertilizer and FTCs over time. Despite significant nitrification observed in fertilized samples there were no decisive microbial diversity, core community, or nitrogen cycling population trends or changes observed in response to nutrient stress. The impact of FTCs was observable as an increase in community alpha diversity during FTCs. Community compositions shifted across a longer time frame than individual FTCs, with bulk changes to the community in each phase of the experiment (pre-FTC, during FTC, and post-FTC).Our experiment demonstrates microbial community composition remains relatively stable for archaea, bacteria, and fungi through a non-growing season, and independent of nutrient availability. This observation contrasts canonical thinking that FTCs have significant and prolonged effects on microbial communities. Earlier work has focused on permafrosts and other soils experiencing rare FTCs. In temperate agricultural soils regularly experiencing such perturbations, the response to freeze-thaw and fertilizer stress may be muted by a more resilient community, or be controlled at the level of gene expression rather than population turn-over. These results clarify the impacts of winter-freeze thaws on fertilizer consumption, with implications for agricultural best practices and modeling of biogeochemical cycling.

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The Effects of Winter Pulsed Warming and Snowmelt on Nitrogen Cycling in Agricultural Soils: A Lysimeter Study

First Author: Danielle Green, University of Waterloo


Additional Author(s): Fereidoun Rezanezhad, University of Waterloo; Sean Jordan, University of Guelph; Claudia Wagner-Riddle, University of Guelph; Hugh Henry, University of Western Ontario; Philippe Van Cappellen, University of Waterloo; Steph Slowinski, University of Waterloo


Abstract: In cold regions, climate change is expected to result in warmer winter temperatures and increased temperature variability. Coupled with changing precipitation regimes, these changes can decrease soil insulation by reducing snow cover, exposing soils to colder temperatures and more frequent and extensive soil freezing and thawing. Freeze-thaw events can exert an important control over winter soil processes and the cycling of nitrogen (N), with consequences for soil health and nearby water quality. These impacts are especially important for agricultural soils and practices in cold regions. We conducted a lysimeter experiment to assess the effects of winter pulsed warming and snowmelt on N cycling in agricultural soils. We monitored the subsurface soil temperature, moisture, and pore water geochemistry together with air temperature, precipitation, and greenhouse gas fluxes in 18 agricultural field-controlled lysimeter systems (surface area of 1 m2 and depth of 1.5 m) at the University of Guelph’s Elora Research Station over one winter (December 2020 to April 2021). The lysimeters featured two soil types (loamy sand and silt loam) and two corn-soybean based crop rotations. The study presented here is for 4 lysimeters managed under a corn-soybean-winter wheat rotation with cover crops. Additionally, ceramic infrared heaters located above some of the plots (n=6) were turned on after each snowfall event to keep the soil surface snow-free for the entire winter. Pore water samples collected from different depths in the lysimeters were analyzed for dissolved organic and inorganic carbon (DOC, DIC), total dissolved nitrogen (TDN), nitrate (NO3-), nitrite (NO2-), chloride (Cl-), and ammonium (NH4+). Nitrous oxide (N2O) fluxes were measured using automated soil gas chambers installed on each lysimeter. The results from the snow-free lysimeters were compared to those of lysimeters without heaters. As expected, the removal of the insulating snow cover was found to cause more intense soil freeze-thaw events which, in turn, altered the pore water N distributions and leaching to the groundwater, as well as the soil N2O gas emissions. Overall, our study illustrates the important role of winter snow cover dynamics in modulating the coupled responses of soil moisture, temperature, and N cycling.


Review and recommendations for microplastics migration during soil column experiments

First Author: Clement Alibert, Water Institute and Department of Earth and Environmental Sciences, University of Waterloo


Additional Author(s): Mathilde Duval (Water Institute and Department of Earth and Environmental Sciences, University of Waterloo), Stephanie Slowinski (Water Institute and Department of Earth and Environmental Sciences, University of Waterloo), Fereidoun Rezanezhad (Water Institute and Department of Earth and Environmental Sciences, University of Waterloo), Philippe Van Cappellen(Water Institute and Department of Earth and Environmental Sciences, University of Waterloo)


Abstract: Microplastics (MPs) are now recognized as a major and significant environmental contaminant. The continued production of plastics coupled to their degradation and the transport of macro- and micro-plastics has resulted in widespread contamination of many environmental systems, including most remote ones. Although lentic aquatic systems are usually considered to be the final receivers of MPs, soils are also an important receiver of microplastic contamination, even if they are a temporary reservoir that the microplastics eventually lost from via runoff to surface water or percolation to groundwater. MPs in soil may also enhance or slow down the migration of other contaminants already present in soils via chemical or physical associations with these other contaminants. However, the mechanisms controlling MP migration through a soil profile and the relative potential for MP loss from soil via runoff or percolation are not yet well understood. Some reasons for this knowledge gap include the lack of systematic and comprehensive analysis techniques for MPs in soils, and a lack of field and experimental data. As a result, there is a deficit in the ability to model microplastics transport in soils, which will be necessary for modelling their watershed-scale fate and transport. In this research, we review the existing literature that exists about microplastic transport experiments in soils and highlight key knowledge gaps that should be addressed. The transport and mobility of MPs in soils are mainly controlled by their size, shape, and surface properties, which collectively control the physical and chemical interactions of MPs with their surrounding environment. There is a lack of experiments of microplastic migration in soils under controlled conditions testing the effect of size, shapes, density, material type, surface properties, extent of MP degradation, and soil composition. We also noticed that experimental setups and conditions are quite variable from one laboratory to another. The main goal of this study is to standardize a method under controlled conditions to fill the main gaps regarding the transport of microplastics in soil systems by considering the main key parameters such as: downward vertical migration, microplastic types/sizes/shapes/aged and soil types. Results obtained by testing and monitoring the effect of all those parameters under controlled conditions will help for the development microplastics transport modeling in soil systems.


Comparing soil organic matter hydrolysis under variable temperature and moisture levels with isothermal calorimetry

First Author: Saraswati Saraswati, Department of Earth and Environmental Sciences, University of Waterloo


Additional Author(s): Philippe Van Cappellen, Department of Earth and Environmental Sciences, University of Waterloo


Abstract: Soil microbial communities fulfil their energy requirements by producing enzymes to decompose soil organic matter (SOM). The catabolic reactions that enable the breakdown of SOM release energy used to drive anabolic (biosynthetic) reactions in the cells. In accordance to the Second Law of thermodynamics, net microbial metabolism, that is catabolism plus anabolism, must dissipate part of the energy generated as heat. Therefore, the precise measurement of the heat flow during the microbial processing of SOM soils can underpin process-based models of SOM degradation under various biogeochemical conditions. One precise tool to measure heat flows during reactions is isothermal calorimetry. With an isothermal calorimeter, the power-time curve can be acquired with extremely high precision (±20 μW). In turn, information on both kinetics (reaction rate) and thermodynamics (reaction enthalpy, Gibbs energy, and entropy) can be inferred from the power-time curve. However, so far only a few studies have used isothermal calorimetry to study SOM degradation in different ecosystems (e.g., wetlands, forest soils, permafrost zones, etc.). As a first step, we experimentally determined the optimum soil temperatures and moisture contents that yield the greatest heat flow during the hydrolytic decomposition of artificial organic and mineral soils. In the experiment, a calorimeter was used to record the heat flows during the reaction of SOM with different hydrolase enzymes (glucosidase, glucosaminidase, sulfatase), at five temperatures (15, 20, 25, 30, and 35 oC) and two moisture contents (35% and 65%). As expected, the organic soils exhibited significantly higher heat flows than mineral soils. The optimum temperatures for decomposition were all around 25 oC, irrespective of the moisture content. In this presentation, we will share our preliminary experimental results and discuss some of the implications in cold region peatlands impacted by climate change.

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Impacts of Freeze Thaw Cycles on Methanogenic Toluene Biodegradation: Experiment and Numerical Simulation

First Author: Mehdi Ramezanzadeh


Additional Author(s): Stephanie Slowinski (1),Fereidoun Rezanezhad (1), Kathleen Murr (1), Christina Lam (1), Christina Smeaton (2), ClementAlibert (1), Marianne Vandergriendt (1) and Philippe Van Cappellen (1)(1) University of Waterloo,(2) Memorial University of Newfoundland (Grenfell Campus)


Abstract: In hydrocarbon-contaminated soils in cold regions , freeze-thaw cycles (FTCs) modulate the biogeochemical and physical processes controlling petroleum hydrocarbons (PHCs) biodegradation and the generation of associated by-products methane (CH4) and carbon dioxide (CO2). Thus, understanding the effects of FTCs on the soil biodegradation of PHCs is critical for the environmental risk assessment and the design of remediation strategies for contaminated soils in cold regions. In this study, we developed a diffusion-reaction model that accounts for the effects of FTCs on methanogenic toluene biodegradation. The model is verified against data generated in a 200 day-long batch experiment with soil collected from a PHC contaminated site in Canada. The fully saturated soil was exposed to successive 4-week FTCs under anoxic conditions with temperatures fluctuating between -10°C and +15°C. We measured the headspace concentrations and 13C compositions of CH4 and CO2, and analyzed the porewater for acetate, sulfate, dissolved organic and inorganic carbon, and toluene concentrations. The numerical model represents solute diffusion, volatilization, sorption, as well as a reaction network of 14 biogeochemical processes. The model successfully simulates the soil porewater and headspace concentration time series data by representing the temperature dependencies of microbial reaction and gas diffusion rates during FTCs. According to the model results, the observed increases in the headspace concentrations of CH4 and CO2 by 87% and 136%, respectively, following toluene addition are explained by toluene fermentation and subsequent methanogenesis reactions. The experimental results and numerical simulations both confirm that methanogenic degradation in anoxic soil is the dominant toluene attenuation mechanism, representing 74% of the attenuation, with sorption contributing to 11%, and evaporation contributing to 15%. Also, the model-predicted contribution of acetate-based methanogenesis to total produced CH4 agrees with that derived from the 13C isotope data. The freezing-induced soil matrix organic carbon release is considered as an important process causing DOC increase following each freezing period according to the calculations of carbon balance and SUVA index. The simulation results of a no FTC scenario indicate that, in the absence of FTCs, CO2 and CH4 emissions decrease by 29% and 26%, respectively, and that toluene is biodegraded 23% faster than in FTC scenario. Given its ability to represent the dominant processes controlling CH4 and CO2 fluxes and porewater chemical changes, our modelling approach can be used to simulate the sensitivity of soil biodegradation processes to FTC frequency and duration driven by temperature fluctuations.


Identifying methanogenic pathways using isothermal microcalorimetry

First Author: Christina Lam, Ecohydrology Research Group, Department of Earth and Environmental Sciences, University of Waterloo, Canada


Additional Author(s): Steph Slowinski (1), Saraswati Saraswati (1), Christina Smeaton (2), Philippe Van Cappellen (1); (1) Ecohydrology Research Group, Department of Earth and Environmental Sciences, University of Waterloo, Canada; (2) School of Science and the Environment, Grenfell Campus, Memorial University of Newfoundland, Canada

Abstract: Petroleum hydrocarbons (PHCs) are major environmental contaminants which can leach from contaminated soils to surrounding surface water or groundwater sources. Methanogenesis generates methane (CH4) and represents a key process involved in PHC biodegradation at contaminated sites under anoxic and electron acceptor-limited conditions. Hydrocarbon fermentation precedes methanogenesis, producing mainly hydrogen and acetate, which then act as reactants for the two main methanogenic pathways: hydrogen-based methanogenesis (HBM) and acetate-based methanogenesis (ABM). It has been proposed that acetate buildup may inhibit PHC biodegradation at contaminated sites by causing the ABM and hydrocarbon fermentation reactions to become thermodynamically unfavorable. That is, high acetate concentrations result in Gibbs reaction energies > 0. We conducted soil batch experiments with commercial peat amended with two acetate concentrations, 0.1 mM and 1 mM. An isothermal microcalorimeter was used to measure heat fluxes released during the incubations of peat amended with two acetate concentrations. These heat fluxes are related to the reaction enthalpies with opposite signs for HBM (endergonic) and ABM (exergonic). The heat fluxes and the gas phase concentrations of CO2 and CH4 suggested that ABM switched to HBM over the course of the experiment. As expected, the relative differences in the heat fluxes in the soils amended with two different acetate concentrations imply that the higher acetate concentration (1 mM) results in lower ABM rates overall. These experimental results provide preliminary evidence of the hypothesized thermodynamic inhibition of ABM by acetate buildup. They also demonstrate the potential for microcalorimetry as a tool for identifying methanogenic reaction pathways at contaminated sites. In this presentation, we will show our experimental results and discuss the implications of our study for the natural attenuation of PHCs at contaminated soil sites.


Investigating Small-Scale Lake Ice Growth and Temperature Dynamics in two Canadian Subarctic Lakes

First Author: Arash Rafat, Department of Geography and Environmental Studies, Wilfrid Laurier University, Waterloo, ON;


Additional Author(s): Homa Kheyrollah Pour, Department of Geography and Environmental Studies, Wilfrid Laurier University, Waterloo, ON; Christopher Spence, Environment and Climate Change Canada, Saskatoon, SK; Michael J. Palmer, North Slave Research Centre, Aurora Research Institute, Aurora College, Yellowknife, NT; Alex MacLean, Department of Geography and Environmental Studies, Wilfrid Laurier University, Waterloo, ON


Abstract: Lake ice has hydrologic and climatic significance as an indicator of climate change and variability. Extensive research conducted on the phenology of lake ice has found that ice is forming later, melting earlier, and is becoming thinner across subarctic and arctic regions due to climate change. However, it is unclear how climate, and weather variability on short time scales (e.g. hourly, daily, weekly), are playing a role in influencing the formation, growth, and decay of lake ice covers (i.e lake ice evolution). This is particularly the case in Canada where the study of small-scale lake ice processes using high temporal resolution in-situ measurements is lacking. Here, we investigate lake ice growth and temperature dynamics at 15-minute intervals over a 4-month period (December 2021-March 2022) through installing two autonomous lake ice sensors (Snow and Ice Mass Balance Apparatuses; SIMBAs) near Yellowknife, Northwest Territories, Canada. Each SIMBA consists of 145 temperature sensors spaced at 2 cm intervals which are used to measure the seasonal temperature dynamics of air, snow, ice, and water. As the start to a broader network of autonomous ice sensors, two SIMBAs were installed in two subarctic lakes near Yellowknife, Northwest Territories with different physical characteristics: Ryan Lake (1 km2, 90 m deep) and Landing Lake (1 km2, 3 m deep). Results from this study highlight: 1) the importance of snow accumulation on reducing heat fluxes and thermal gradients through ice, 2) the differences in lake ice evolution between a shallow and a deep subarctic lake, and 3) the role of air temperature variability in influencing snow and ice temperature profiles and growth. Knowledge obtained from this study can be used to directly improve community ice safety under future climate change and variability.


Accuracy of snow depth estimation on Canadian sub-Arctic lakes using Ground-Penetrating Radar

First Author: Alicia Pouw, Wilfrid Laurier University (WLU)


Additional Author(s): Homa Kheyrollah Pour - WLU, Alex MacLean - WLU


Abstract: As high latitude regions are experiencing warming disproportionately; snow is increasingly vulnerable to the changing climate. Slight changes in the surface-atmosphere energy balance could alter snowpack dynamics and have a profound impact on lake ice thickness and formation. The presence and depth of snow overlying lake ice affects both lake ice growth and timing of melt due to snow's highly insulative and reflective properties. An accurate representation of the depth and distribution of snow on lake ice is important for hydrological modeling, as well as thermodynamic lake ice modeling. The spatial distribution of snow over lake ice varies and is driven by wind redistribution and snowpack metamorphism making it challenging to quantify. Currently, snow depth observations on lake ice are sparse and mostly restricted to point measurements. In this study, ground penetrating radar (GPR) acquisitions took place over four small subarctic freshwater lakes (Landing Lake, Long Lake, Finger Lake, Vee Lake), located north of Yellowknife, Northwest Territories. High spatial resolution (~9 cm) two-way travel-time (TWT) observations along transects totaling ~38km were acquired using a 1 GHz sensor. We estimated the snow depth by automatically picking the GPR TWT of the snow-ice interface. The accuracy of the derived snow depth is assessed using in-situ observations collected using a snow depth probe. We compared the in-situ snow depth observations to those derived from the GPR TWT and reported a root mean square error of 1.72 cm, a -0.33cm bias, and R2 of 0.62 on average between the four lakes. The results showed that this method can improve the accuracy of snow depth and distribution data retrieval on lake ice which is essential for hydrologic and lake ice modeling communities.


Impact of different precipitation phase estimation methods around 0C on snowpack evolution.

First Author: Nicolas R. Leroux, UQAM


Additional Author(s): Vincent Vionnet, ECCC; Julie M. Thériault, UQAM; Hadleigh D. Thompson, UQAM; Dominique Boisvert, UQAM; Lisa Rickard, UNBC; Stephen J. Déry, UNBC; Ronald Stewart, University of Manitoba


Abstract: "Accurate estimation of precipitation phase at the surface is critical for hydrological modelling in cold regions. The current precipitation phase partioning methods (PPM) differ in their abilities to estimate precipitation phase around 0oC. This can have significant impacts on estimations of snow accumulation and melt, particularly as the climate is warming and near 0oC conditions become more frequent during the cold seasons (Mekis et al., 2020). The goal of this study is to evaluate PPMs of varying complexity using high-quality observations of precipitation phase and to assess the impact on simulated snowpack evolution over a winter season. To do so, we used meteorological data including air temperature, relative humidity, wind speed, and precipitation amount collected at Edmundston, New Brunswick, during the Saint John River Experiment on Cold Season Storms field campaign. These data were combined with observations of snow depth and snow water equivalent. The reference precipitation phase was derived from measurements with a laser-optical disdrometer operating during SAJESS and was evaluated using Doppler velocity and reflectivity measurements from a micro rain radar. The snowpack evolution during the 2020-2021 winter was simulated using the model Crocus. The impact of the different PPMs on snow depth estimation during 16 accumulation periods across the winter season, as well as uncertainties related to compaction and snowfall density models was investigated. The results show that the snow accumulation from the different PPMs differed significantly when the temperature was close to 0oC and that precipitation phase estimated from disdrometer data was the most accurate when simulating snow accumulation, followed by the PPM using the wet-bulb temperature with a constant threshold. Snow events accumulation were more sensitive to the snowfall density model chosen than to the compaction algorithm. However, the impact of the snowfall density models on snow accumulation was insensitive to the PPM chosen, while the performance of the compaction models was slightly influenced by the selected PPM. Overall, this study highlights the difficulty in estimating precipitation phase at the surface during near 0oC conditions and its impact on snow modelling.


Mekis, E., Stewart, R. E., Theriault, J. M., Kochtubajda, B., Bonsal, B. R., & Liu, Z. (2020). Near-0°C surface temperature and precipitation type patterns across Canada. Hydrology and Earth System Sciences, 24(4), 1741–1761. https://doi.org/10.5194/hess-24-1741-2020"


Do bioretention cells reduce urban stormwater phosphorus and nitrogen loads? Insights from International Stormwater Best Management Practices Database

First Author: Bowen Zhou, University of Waterloo


Additional Author(s): Mahyar Shafii, University of Waterloo; Chris Parsons, Environment and Climate Change Canada; Elodie Passeport, University of Toronto; Fereidoun Rezanezhad, University of Waterloo; Philippe Van Cappellen, University of Waterloo


Abstract: Bioretention cells are a Low Impact Development (LID) technology, widely promoted as a green solution to attenuate the loadings of the limiting macronutrients phosphorus (P) and nitrogen (N) exported through urban stormwater runoff. Despite the broad implementation of this LID approach in North America, their reported P and N reduction efficiencies are highly variable. We conducted an analysis of total P (TP), soluble reactive P (SRP), total N (TN), and dissolved inorganic N (DIN) data available in the International Stormwater Best Management Practice (BMP) Database to assess trends in nutrient reduction, including seasonal and long-term trends. We further applied decision tree and random forest machine learning models to identify the watershed properties and climate conditions that most affect the reduction efficiencies of TP, SRP, TN, and DIN. Unlike previous studies that mostly focus on the differences in concentration between the inflow and outflow of bioretention cells, our analysis incorporates flow data to quantify P and N reduction performance both in terms of concentration and load reductions. Our results show that, on average, bioretention cells are actually SRP exporters: outlet concentrations and loads are higher at the outlet than the inlet. By contrast, TP, TN and DIN outflow loadings are reduced, relative to the inflow. However, the TP, TN and DIN outlet concentrations are generally higher than their inlet counterparts. Thus, surface flow reduction is the main mechanism that reduces the outflow loadings of TP, TN and DIN. Because the surface flow reduction is largely due to recharge to the underlying groundwater, bioretention cells may represent an important pathway of nutrient enrichment of urban aquifers. Most bioretention cells analyzed further show deteriorating long-term performance in mitigating the loadings of SRP and DIN, with potential negative consequences for the receiving surface waters. Key variables modulating the relative changes in SRP and DIN loadings caused by bioretention cells include the average rainfall intensity, the inflow concentrations, and the watershed imperviousness. Overall, our findings bring into question the effectiveness of existing bioretention cells for controlling loads. This is particularly true for SRP, which is recognized as a major driver of eutrophication.