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Item An integrated assessment of impacts to ecosystem services associated with prairie pothole wetland drainage quantifying wide-ranging losses(Canadian Science Publishing, 2024-06-20) Whitfield, Colin; Cavaliere, Emily; Baulch, Helen; Clark, Robert; Spence, Christopher; Shook, Kevin; He, Zhihua; Pomeroy, John W.; Wolfe, JaredIn many regions, a tradeoff exists between draining wetlands to support the expansion of agricultural land, and conserving wetlands to maintain their valuable ecosystem services. Decisions about wetland drainage are often made without identifying the impacts on the services these systems provide. We address this gap through a novel assessment of impacts on ecosystem services via wetland drainage in the Canadian prairie landscape. Draining pothole wetlands has large impacts, but sensitivity varies among the indicators considered. Loss of water storage increased the magnitude of median annual flows, but absolute increases with drainage were higher for larger, less frequent events. Total phosphorus exports increased in concert with streamflow. Our analysis suggested disproportionate riparian habitat losses with the first 30% of wetland area drained. Dabbling ducks and wetland-associated bird abundances respond strongly to the loss of small wetland ponds; abundances were predicted to decrease by half with the loss of only 20%–40% of wetland area. This approach to evaluating changes to key wetland ecosystem services in a large region where wetland drainage is ongoing can be used with an economic valuation of the drainage impacts, which should be weighed against the benefits associated with agricultural expansion.Item Assessing hydrological sensitivity of grassland basins in the Canadian Prairies to climate using a basin classification-based virtual modelling approach(Copernicus Publications on behalf of the European Geosciences Union, 2022) Spence, Christopher; He, Zhihua; Shook, Kevin R.; Mekonnen, Balew A.; Pomeroy, John; Whitfield, Colin; Wolfe, JaredSignificant challenges from changes in climate and land use face sustainable water use in the Canadian Prairies ecozone. The region has experienced significant warming since the mid-20th century, and continued warming of an additional 2 _C by 2050 is expected. This paper aims to enhance understanding of climate controls on Prairie basin hydrology through numerical model experiments. It approaches this by developing a basin-classification-based virtual modelling framework for a portion of the Prairie region and applying the modelling framework to investigate the hydrological sensitivity of one Prairie basin class (High Elevation Grasslands) to changes in climate. High Elevation Grasslands dominate much of central and southern Alberta and parts of south-western Saskatchewan, with outliers in eastern Saskatchewan and western Manitoba. The experiments revealed that High Elevation Grassland snowpacks are highly sensitive to changes in climate but that this varies geographically. Spring maximum snow water equivalent in grasslands decreases 8% °C-1 of warming. Climate scenario simulations indicated that a 2 °C increase in temperature requires at least an increase of 20% in mean annual precipitation for there to be enough additional snowfall to compensate for enhanced melt losses. The sensitivity in runoff is less linear and varies substantially across the study domain: simulations using 6 °C of warming, and a 30% increase in mean annual precipitation yields simulated decreases in annual runoff of 40%in climates of the western Prairie but 55% increases in climates of eastern portions. These results can be used to identify those areas of the region that are most sensitive to climate change and highlight focus areas for monitoring and adaptation. The results also demonstrate how a basin classification based virtual modelling framework can be applied to evaluate regional-scale impacts of climate change with relatively high spatial resolution in a robust, effective and efficient manner.Item Assessing runoff sensitivity of North American Prairie Pothole Region basins to wetland drainage using a basin classification-based virtual modelling approach(Copernicus Publications on behalf of the European Geosciences Union, 2022) Spence, Christopher; He, Zhihua; Shook, Kevin R.; Pomeroy, John; Whitfield, Colin; Wolfe, JaredWetland drainage has been pervasive in the North American Prairie Pothole Region. There is strong evidence that this drainage increases the hydrological connectivity of previously isolated wetlands and, in turn, runoff response to snowmelt and rainfall. It can be hard to disentangle the role of climate from the influence of wetland drainage in observed records. In this study, a basin-classification-based virtual modelling approach is described that can isolate these effects on runoff regimes. The basin class which was examined, entitled Pothole Till, extends throughout much of Canada’s portion of the Prairie Pothole Region. Three knowledge gaps were addressed. First, it was determined that the spatial pattern in which wetlands are drained has little influence on how much the runoff regime was altered. Second, no threshold could be identified below which wetland drainage has no effect on the runoff regime, with drainage thresholds as low as 10 % in the area being evaluated. Third, wetter regions were less sensitive to drainage as they tend to be better hydrologically connected, even in the absence of drainage. Low flows were the least affected by drainage. Conversely, during extremely wet years, runoff depths could double as the result of complete wetland removal. Simulated median annual runoff depths were the most responsive, potentially tripling under typical conditions with high degrees of wet- land drainage. As storage capacity is removed from the landscape through wetland drainage, the size of the storage deficit of median years begins to decrease and to converge on those of the extreme wet years. Model simulations of flood frequency suggest that, because of these changes in antecedent conditions, precipitation that once could generate a median event with wetland drainage can generate what would have been a maximum event without wetland drainage. The advantage of the basin-classification-based virtual modelling approach employed here is that it simulated a long period that included a wide variety of precipitation and antecedent storage conditions across a diversity of wetland complexes. This has allowed seemingly disparate results of past research to be put into context and finds that conflicting results are often only because of differences in spatial scale and temporal scope of investigation. A conceptual framework is provided that shows, in general, how annual runoff in different climatic and drainage situations will likely respond to wetland drainage in the Prairie Pothole Region.Item Changes in the frequency of global high mountain rain-on-snow events due to climate warming(IOP Publishing Ltd, 2021) López-Moreno, Juan Ignacio; Pomeroy, John; Morán-Tejeda, Enrique; Revuelto, Jesús; Navarro-Serrano, Francisco; Vidaller, Ixeia; Alonso González, EstebanRain-on-snow (ROS) events can trigger severe floods in mountain regions. There is high uncertainty about how the frequency of ROS events (ROS) and associated floods will change as climate warms. Previous research has found considerable spatial variability in ROS responses to climate change. Detailed global assessments have not been conducted. Here, atmospheric reanalysis data was used to drive a physically based snow hydrology model to simulate the snowpack and the streamflow response to climate warming of a 5.25 km2 virtual basin (VB) applied to different high mountain climates around the world. Results confirm that the sensitivity of ROS to climate warming is highly variable among sites, and also with different elevations, aspects and slopes in each basin. The hydrological model predicts a decrease in the frequency of ROS with warming in 30 out 40 of the VBs analyzed; the rest have increasing ROS. The dominant phase of precipitation, duration of snow cover and average temperature of each basin are the main factors that explain this variation in the sensitivity of ROS to climate warming. Within each basin, the largest decreases in ROS were predicted to be at lower elevations and on slopes with sunward aspects. Although the overall frequency of ROS drops, the hydrological importance of ROS is not expected to decline. Peak streamflows due to ROS are predicted to increase due to more rapid melting from enhanced energy inputs, and warmer snowpacks during future ROS.Item The cold regions hydrological modelling platform for hydrological diagnosis and prediction based on process understanding(Elsevier B.V., 2022) Pomeroy, John; Brown, Tom; Fang, Xing; Shook, Kevin R.; Pradhananga, Dhiraj; Armstrong, Robert; Harder, Phillip; Marsh, Christopher; Costa, Diogo; Krogh, Sebastian; Aubry-Wake, Caroline; Annand, Holly; Lawford, Peter; He, Zhihua; Kompanizare, Mazda; Lopez-Moreno, IgnacioCold regions involve hydrological processes that are not often addressed appropriately in hydrological models. The Cold Regions Hydrological Modelling platform (CRHM) was initially developed in 1998 to assemble and explore the hydrological understanding developed from a series of research basins spanning Canada and international cold regions. Hydrological processes and basin response in cold regions are simulated in a flexible, modular, object-oriented, multiphysics platform. The CRHM platform allows for multiple representations of forcing data interpolation and extrapolation, hydrological model spatial and physical process structures, and parameter values. It is well suited for model falsification, algorithm intercomparison and benchmarking, and has been deployed for basin hydrology diagnosis, prediction, land use change and water quality analysis, climate impact analysis and flood forecasting around the world. This paper describes CRHM’s capabilities, and the insights derived by applying the model in concert with process hydrology research and using the combined information and understanding from research basins to predict hydrological variables, diagnose hydrological change and determine the appropriateness of model structure and parameterisations.Item Crop water use efficiency from eddy covariance methods in cold(Agricultural and Forest Meteorology, 2023-08) Harder, Phillip; Helgason, Warren; Johnson, Bruce; Pomeroy, JohnCrop–water interactions define productivity in water-limited dryland agricultural production systems in cold regions. Despite the agronomic and economic importance of this relationship there are challenges in quantifying crop water use efficiency (WUE). To understand dynamics driving crop water use and agricultural productivity in these environments, observations of evapotranspiration, carbon assimilation, meteorology, and crop growth were collected over 17 site-years at 5 agricultural sites in the sub-humid continental Canadian Prairies. Eddy-covariance (EC) derived water and carbon fluxes provided a means to comprehensively assess the WUE of current agricultural practices by both physiological (WUEP: g C kg−1 H2O) and agronomic (WUEY): kg yield mm H2O−1 hectare−1) approaches. Mean field scale WUEY for grain yields were 10.4 (Barley), 10.2 (Wheat), 6.0 (Canola), 19.3 (Peas), 12.2 (Lentils) and for silage/forage crops were 23.0 (Barley), 11.9 (Forage), and 20.7 (Corn) (kg yield mm H2O−1 hectare−1). An assessment of environmental factors and their covariance with WUE, utilising a conditional inference tree approach, demonstrated that WUE decreased when crops were under greater evapotranspiration demands. EC-based areal WUE approaches, measuring fluxes over footprints of hundreds of square metres, were compared with more commonly reported point-scale water balance residual approaches (WUEWB) and demonstrated consistently smaller magnitudes. WUEWB was greater than EC-estimated WUEY by an average of 52% and 65% for grain and forage/silage crops respectively. WUEWB also had greater variability than EC estimates, with standard deviations 188% and 128% greater than Barley and Wheat crops, respectively. This comparison highlights the scale dependency of WUE estimation methods, demonstrates considerable uncertainty in point scale water balance approaches due to spatial variability in crop–water interactions, and shows how this variability can be accounted for by EC observations. This improves the understanding of WUE and quantifies its variability in cold continental water-limited climates and provides a means to diagnose improved agricultural water management.Item Developing a tile drainage module for the Cold Regions Hydrological Model: lessons from a farm in southern Ontario, Canada(European Geosciences Union, 2024-07-04) Kompanizare, Mazda; Costa, Diogo; Macrae, Merrin; Pomeroy, John W.; Petrone, RichardSystematic tile drainage is used extensively in poorly drained agricultural lands to remove excess water and improve crop growth; however, tiles can also transfer nutrients from farmlands to downstream surface water bodies, leading to water quality problems. Thus, there is a need to simulate the hydrological behaviour of tile drains to understand the impacts of climate or land management change on agricultural surface and subsurface runoff. The Cold Regions Hydrological Model (CRHM) is a physically based, modular modelling system developed for cold regions. Here, a tile drainage module is developed for CRHM. A multi-variable, multi-criteria model performance evaluation strategy was deployed to examine the ability of the module to capture tile discharge under both winter and summer conditions (NSE > 0.29, RSR < 0.84 and PBias < 20 for tile flow and saturated storage simulations). Initial model simulations run at a 15 min interval did not satisfactorily represent tile discharge; however, model simulations improved when the time step was lengthened to hourly but also with the explicit representation of capillary rise for moisture interactions between the rooting zone and groundwater, demonstrating the significance of capillary rise above the saturated storage layer in the hydrology of tile drains in loam soils. Novel aspects of this module include the sub-daily time step, which is shorter than most existing models, and the use of field capacity and its corresponding pressure head to provide estimates of drainable water and the thickness of the capillary fringe, rather than using detailed soil retention curves that may not always be available. An additional novel aspect is the demonstration that flows in some tile drain systems can be better represented and simulated when related to shallow saturated storage dynamics.Item Fire and Ice: The Impact of Wildfire-Affected Albedo and Irradiance on Glacier Melt(Wiley Open Access [Commercial Publisher], American Geophysical Union [Society Publisher], 2022) Aubry-Wake, Caroline; Bertoncini, André; Pomeroy, JohnWildfire occurrence and severity is predicted to increase in the upcoming decades with severe negative impacts on human societies. The impacts of upwind wildfire activity on glacier melt, a critical source of freshwater for downstream environments, were investigated through analysis of field and remote sensing observations and modeling experiments for the 2015–2020 melt seasons at the well-instrumented Athabasca Glacier in the Canadian Rockies. Upwind wildfire activity influenced surface glacier melt through both a decrease in the surface albedo from deposition of soot on the glacier and through the impact of smoke on atmospheric conditions above the glacier. Athabasca Glacier on-ice weather station observations show days with dense smoke were warmer than clear, non-smoky days, and sustained a reduction in surface shortwave irradiance of 103 W m-2 during peak shortwave irradiance and an increase in longwave irradiance of 10 W m-2, producing an average 15 W m-2 decrease in net radiation. Albedo observed on-ice gradually decreased after the wildfires started, from a summer average of 0.29 in 2015 before the wildfires to as low as 0.16 in 2018 after extensive wildfires and remained low for two more melt seasons without substantial upwind wildfires. Reduced all-wave irradiance partly compensated for the increase in melt due to lowered albedo in those seasons when smoke was detected above Athabasca Glacier. In melt seasons without smoke, the suppressed albedo increased melt by slightly more than 10% compared to the simulations without fire-impacted albedo, increasing melt by 0.42 m. w.e. in 2019 and 0.37 m. w.e. in 2020.Item High-Resolution Large-Eddy Simulations of Flow in the Complex Terrain of the Canadian Rockies(Earth and Space Science, 10/25/2023) Rohanizadegan, Mina; Petrone, Richard; Pomeroy, John W.; Kosovic, Branko; Muñoz-Esparza, Domingo; Helgason, WarrenImproving the calculation of land-atmosphere fluxes of heat and water vapor in mountain terrain requires better resolution of thermally driven diurnal winds (i.e., valley, slope winds) due to differential heating by terrain and radiative fluxes. In this study, the Weather Research and Forecasting model is used to simulate flow in large-eddy simulation (LES) mode over the complex terrain of the Fortress Mountain and Marmot Creek research basins, Kananaskis Valley, Canadian Rockies, Alberta in mid-summer. The model was used to examine the temporal and spatial evolution of local winds and near-surface boundary layer processes with variability in topography and elevation. Numerically resolving complex terrain wind flow effects require smaller grid cell size. However, the use of terrain-following coordinates in most numerical weather prediction models results in large numerical errors when flow over steep terrain is simulated. These errors propagate through the domain and can result in numerical instability. To avoid this issue when simulating flow over steep terrain a local smoothing approach was used, where smoothing is applied only where slope exceeds some predetermined threshold. LES results from local smoothing were compared with a mesoscale model and LES with global smoothing. Simulations are evaluated using sounding data and meteorological stations. The differences in flow patterns and reversals in two mountain basins suggest that valley geometry and volume is relevant to the break up of inversion layers, removal of cold-air pools, and strength of thermally driven winds.Item Hydrometeorological data from Marmot Creek Research Basin, Canadian Rockies(Copernicus Publications, 2019) Fang, Xing; Pomeroy, John; DeBeer, Chris; Harder, Philip; Siemens, EvanMeteorological, snow survey, streamflow, and groundwater data are presented from Marmot Creek Research Basin, Alberta, Canada. The basin is a 9.4 km2, alpine–montane forest headwater catchment of the Saskatchewan River basin that provides vital water supplies to the Prairie Provinces of Canada. It was heavily instrumented, experimented upon, and operated by several federal government agencies between 1962 and 1986, during which time its main and sub-basin streams were gauged, automated meteorological stations at multiple elevations were installed, groundwater observation wells were dug and automated, and frequent manual measurements of snow accumulation and ablation and other weather and water variables were made. Over this period, mature evergreen forests were harvested in two sub-basins, leaving large clear cuts in one basin and a “honeycomb” of small forest clearings in another basin. Whilst meteorological measurements and sub-basin streamflow discharge weirs in the basin were removed in the late 1980s, the federal government maintained the outlet streamflow discharge measurements and a nearby high-elevation meteorological station, and the Alberta provincial government maintained observation wells and a nearby fire weather station. Marmot Creek Research Basin was intensively re-instrumented with 12 automated meteorological stations, four sub-basin hydrometric sites, and seven snow survey transects starting in 2004 by the University of Saskatchewan Centre for Hydrology. The observations provide detailed information on meteorology, precipitation, soil moisture, snowpack, streamflow, and groundwater during the historical period from 1962 to 1987 and the modern period from 2005 to the present time. These data are ideal for monitoring climate change, developing hydrological process understanding, evaluating process algorithms and hydrological, cryospheric, or atmospheric models, and examining the response of basin hydrological cycling to changes in climate, extreme weather, and land cover through hydrological modelling and statistical analyses. The data presented are publicly available from Federated Research Data Repository (https://doi.org/10.20383/101.09, Fang et al., 2018).Item Hydrometeorological, glaciological and geospatial research data from the Peyto Glacier Research Basin in the Canadian Rockies(Copernicus Publications, 2021) Pradhananga, Dhiraj; Pomeroy, John; Aubry-Wake, Caroline; Munro, D. Scott; Shea, Joseph; Demuth, Michael N.; Kirat, Nammy Hang; Menounos, Brian; Mukherjee, KritiThis paper presents hydrometeorological, glaciological and geospatial data from the Peyto Glacier Research Basin (PGRB) in the Canadian Rockies. Peyto Glacier has been of interest to glaciological and hydrological researchers since the 1960s, when it was chosen as one of five glacier basins in Canada for the study of mass and water balance during the International Hydrological Decade (IHD, 1965–1974). Intensive studies of the glacier and observations of the glacier mass balance continued after the IHD, when the initial seasonal meteorological stations were discontinued, then restarted as continuous stations in the late 1980s. The corresponding hydrometric observations were discontinued in 1977 and restarted in 2013. Datasets presented in this paper include high-resolution, co-registered digital elevation models (DEMs) derived from original air photos and lidar surveys; hourly off-glacier meteorological data recorded from 1987 to the present; precipitation data from the nearby Bow Summit weather station; and long-term hydrological and glaciological model forcing datasets derived from bias-corrected reanalysis products. These data are crucial for studying climate change and variability in the basin and understanding the hydrological responses of the basin to both glacier and climate change. The comprehensive dataset for the PGRB is a valuable and exceptionally long-standing testament to the impacts of climate change on the cryosphere in the high-mountain environment. The dataset is publicly available from Federated Research Data Repository at https://doi.org/10.20383/101.0259 (Pradhananga et al., 2020).Item Icefield Breezes: Mesoscale Diurnal Circulation in the Atmospheric Boundary Layer Over an Outlet of the Columbia Icefield, Canadian Rockies(Wiley [Commercial Publisher]; American Geophysical Union [Society Publisher], 2021) Conway, Jonathan; Helgason, Warren D.; Pomeroy, John; sicart, jeanAtmospheric boundary layer (ABL) dynamics over glaciers mediate the response of glacier mass balance to large-scale climate forcing. Despite this, very few ABL observations are available over mountain glaciers in complex terrain. An intensive field campaign was conducted in June 2015 at the Athabasca Glacier outlet of Columbia Icefield in the Canadian Rockies. Observations of wind and temperature profiles with novel kite and radio-acoustic sounding systems showed a well-defined mesoscale circulation developed between the glacier and snow-free valley in fair weather. The typical vertical ABL structure above the glacier differed from that expected for “glacier winds”; strong daytime down-glacier winds extended through the lowest 200 m with no up-valley return flow aloft. This structure suggests external forcing at mesoscale scales or greater and is provisionally termed an “icefield breeze.” A wind speed maximum near the surface, characteristic of a “glacier wind,” was only observed during nighttime and one afternoon. Lapse rates of air temperature down the glacier centerline show the interaction of down-glacier cooling driven by sensible heat loss into the ice, entrainment and periodic disruption and warming. Down-glacier cooling was weaker in “icefield breeze” conditions, while in “glacier wind” conditions, stronger down-glacier cooling enabled large increases in near-surface temperature on the lower glacier during periods of surface boundary layer (SBL) disruption. These results raise several questions, including the impact of Columbia Icefield on the ABL and melt of Athabasca Glacier. Future work should use these observations as a testbed for modeling spatio-temporal variations in the ABL and SBL within complex glaciated terrain.Item Implementing a parsimonious variable contributing area algorithm for the prairie pothole region in the HYPE modelling framework(Environmental Modelling and Software, 2023-09) Ahmed, Mohamed Ismaiel; Shook, Kevin; Pietroniro, Alain; Stadnyk, Tricia; Pomeroy, John W.; Pers, Charlotta; Gustafsson, DavidThe North American prairie region is known for its poorly defined drainage system with numerous surface depressions that lead to variable contributing areas for streamflow generation. Current approaches of representing surface depressions are either simplistic or computationally demanding. In this study, a variable contributing area algorithm is implemented in the HYdrological Predictions for the Environment (HYPE) model and evaluated in the Canadian prairies. HYPE's local lake module is replaced with a Hysteretic Depressional Storage (HDS) algorithm to estimate the variable contributing fractions of subbasins. The modified model shows significant improvements in simulating the streamflows of two prairie basins in Saskatchewan, Canada. The modified model can replicate the hysteretic relationships between the water volume and contributing area of the basins. With the inclusion of the HDS algorithm in HYPE, the global HYPE modelling community can now simulate an important hydrological phenomenon, previously unavailable in the model.Item Improving sub-canopy snow depth mapping with unmanned aerial vehicles: lidar versus structure-from-motion techniques(Copernicus Publications [Commercial Publisher]; European Geosciences Union [Society Publisher], 2020) Harder, Philip; Pomeroy, John; Helgason, Warren D.Vegetation has a tremendous influence on snow processes and snowpack dynamics, yet remote sensing techniques to resolve the spatial variability of sub-canopy snow depth are not always available and are difficult from space-based platforms. Unmanned aerial vehicles (UAVs) have had recent widespread application to capture high-resolution information on snow processes and are herein applied to the sub-canopy snow depth challenge. Previous demonstrations of snow depth mapping with UAV structure from motion (SfM) and airborne lidar have focussed on non-vegetated surfaces or reported large errors in the presence of vegetation. In contrast, UAV-lidar systems have high-density point clouds and measure returns from a wide range of scan angles, increasing the likelihood of successfully sensing the sub-canopy snow depth. The effectiveness of UAV lidar and UAV SfM in mapping snow depth in both open and forested terrain was tested in a 2019 field campaign at the Canadian Rockies Hydrological Observatory, Alberta, and at Canadian prairie sites near Saskatoon, Saskatchewan, Canada. Only UAV lidar could successfully measure the sub-canopy snow surface with reliable sub-canopy point coverage and consistent error metrics (root mean square error (RMSE) <0.17 m and bias −0.03 to −0.13 m). Relative to UAV lidar, UAV SfM did not consistently sense the sub-canopy snow surface, the interpolation needed to account for point cloud gaps introduced interpolation artefacts, and error metrics demonstrated relatively large variability (RMSE<0.33 m and bias 0.08 to −0.14 m). With the demonstration of sub-canopy snow depth mapping capabilities, a number of early applications are presented to showcase the ability of UAV lidar to effectively quantify the many multiscale snow processes defining snowpack dynamics in mountain and prairie environments.Item The influence of roads on depressional storage capacity estimates from high-resolution LiDAR DEMs in a Canadian Prairie agricultural basin(Canadian Water Resources Journal, 2023-07) Annand, Holly; wheater, howard; Pomeroy, John W.The Canadian Prairies are a post-glacial agricultural landscape, where millions of small depressions store surface water, form wetlands and control runoff contributing area. Their management is key to flood and drought hydrology, groundwater recharge, ecological integrity, migratory bird habitat and agricultural productivity. Depression drainage and infilling is common in the region, where it is often used to increase cropped area. The regularly spaced, rural ‘grid-road‘ network also impedes drainage, but associated culvert drainage can mitigate those effects. Management of depressions can be informed by hydrological modelling, but accurate surface water storage capacity estimates are needed to ensure accurate model results. Simple representation of road embankments in digital elevation models (DEMs) neglects the effects of culvert drainage. Here, a raster-based depression-filling algorithm was used to delineate depressions from three LiDAR-derived DEMs: a 10-m DEM with roads intact, a 2-m DEM with roads intact, and a 2-m DEM with roads breached at culvert locations. Road breaching was conducted manually in the 2-m DEM to remove artifact depressions that form alongside roads where culverts exist. Results indicated that increasing DEM resolution from 10-m to 2-m in a 393.5 km2 basin did not significantly change depression area or storage capacity estimates; however, breaching roads in the 2-m DEM decreased depression area by 29% (from 98.5 km2 to 69.8 km2) and estimated storage capacity by 48% (from 47.4 × 106 m3 to 23.8 × 106 m3), compared to leaving roads intact in the 2-m DEM. Depressions delineated from the 2-m roads-breached DEM also covered 48% more area and offered 53% more storage capacity than Canadian Wetland Inventory (CWI) aerial-photograph delineated wetlands, which occupied 47.1 km2 with an estimated storage capacity of 15.5 × 106 m3. The implications of these results for the ability of hydrological models to calculate runoff contributing areas and streamflow are discussed.Item Measuring prairie snow water equivalent with combined UAV-borne gamma spectrometry and lidar(European Geosciences Union, 2024) Harder, Philip; Helgason, Warren; Pomeroy, John W.Despite decades of effort, there remains an inability to measure snow water equivalent (SWE) at high spatial resolutions using remote sensing. Passive gamma ray spectrometry is one of the only well-established methods to reliably remotely sense SWE, but airborne applications to date have been limited to observing kilometre-scale areal averages. Noting the increasing capabilities of unoccupied aerial vehicles (UAVs) and miniaturization of passive gamma ray spectrometers, this study tested the ability of a UAV-borne gamma spectrometer and concomitant UAV-borne lidar to quantify the spatial variability of SWE at high spatial resolutions. Gamma and lidar observations from a UAV (UAV-gamma and UAV-lidar) were collected over two seasons from shallow, wind-blown, prairie snowpacks in Saskatchewan, Canada, with validation data collected from manual snow depth and density observations. A fine-resolution (0.25 m) reference dataset of SWE, to test UAV-gamma methods, was developed from UAV-lidar snow depth and snow survey snow density observations. The ability of UAV-gamma to resolve the areal average and spatial variability of SWE was promising with appropriate flight characteristics. Survey flights flown at a velocity of 5 m s−1, altitude of 15 m, and line spacing of 15 m were unable to capture the average or spatial variability of SWE within the uncertainty of the reference dataset. Slower, lower, and denser flight lines at a velocity of 4 m s−1, altitude of 8 m, and line spacing of 8 m were able to successfully observe areal average SWE and its variability at spatial resolutions greater than 22.5 m. Using a combination of UAV-based gamma SWE and UAV-based lidar snow depth improved the spatial representation of SWE substantially and permitted estimation of SWE at a spatial resolution 0.25 m with a ± 14.3 mm error relative to the reference SWE dataset. UAV-borne gamma spectrometry to estimate SWE is a promising and novel technique that has the potential to improve the measurement of shallow prairie snowpacks, and when combined with UAV-borne lidar snow depths, can provide fine-resolution, high-accuracy estimates of prairie SWE. Research on optimal hardware, data processing, and interpolation techniques is called for to further improve this remote sensing product and explore its application in other environments.Item Meteorological observations collected during the Storms and Precipitation Across the continental Divide Experiment (SPADE), April–June 2019(Copernicus Publications, 2021) Thériault, Julie M.; Déry, Stephen J.; Pomeroy, John; Smith, Hilary; Almonte, Juris; Bertoncini, André; Crawford, Robert W.; Desroches-Lapointe, Aurélie; Lachapelle, Mathieu; Mariani, Zen; Mitchell, Selina; Morris, Jeremy E.; Hébert-Pinard, Charlie; Rodriguez, Peter; Thompson, HadleighThe continental divide along the spine of the Canadian Rockies in southwestern Canada is a critical headwater region for hydrological drainages to the Pacific, Arctic, and Atlantic oceans. Major flooding events are typically attributed to heavy precipitation on its eastern side due to upslope (easterly) flows. Precipitation can also occur on the western side of the divide when moisture originating from the Pacific Ocean encounters the west-facing slopes of the Canadian Rockies. Often, storms propagating across the divide result in significant precipitation on both sides. Meteorological data over this critical region are sparse, with few stations located at high elevations. Given the importance of all these types of events, the Storms and Precipitation Across the continental Divide Experiment (SPADE) was initiated to enhance our knowledge of the atmospheric processes leading to storms and precipitation on either side of the continental divide. This was accomplished by installing specialized meteorological instrumentation on both sides of the continental divide and carrying out manual observations during an intensive field campaign from 24 April–26 June 2019. On the eastern side, there were two field sites: (i) at Fortress Mountain Powerline (2076ma.s.l.) and (ii) at Fortress Junction Service, located in a high-elevation valley (1580ma.s.l.). On the western side, Nipika Mountain Resort, also located in a valley (1087ma.s.l.), was chosen as a field site. Various meteorological instruments were deployed including two Doppler light detection and ranging instruments (lidars), three vertically pointing micro rain radars, and three optical disdrometers. The three main sites were nearly identically instrumented, and observers were on site at Fortress Mountain Powerline and Nipika Mountain Resort during precipitation events to take manual observations of precipitation type and microphotographs of solid particles. The objective of the field campaign was to gather high-temporal-frequency meteorological data and to compare the different conditions on either side of the divide to study the precipitation processes that can lead to catastrophic flooding in the region. Details on field sites, instrumentation used, and collection methods are discussed. Data from the study are publicly accessible from the Federated Research Data Repository at https://doi.org/10.20383/101.0221 (Thériault et al., 2020). This dataset will be used to study atmospheric conditions associated with precipitation events documented simultaneously on either side of a continental divide. This paper also provides a sample of the data gathered during a precipitation event.Item Modelling the regional sensitivity of snowmelt, soil moisture, and streamflow generation to climate over the Canadian Prairies using a basin classification approach(Hydrology and Earth System Sciences, 10/9/2023) He, Zhihua; Shook, Kevin; Spence, Christopher; Pomeroy, John W.; Whitfield, ColinThis study evaluated the effects of climate perturbations on snowmelt, soil moisture, and streamflow generation in small Canadian Prairies basins using a modelling approach based on classification of basin biophysical characteristics. Seven basin classes that encompass the entirety of the Prairies Ecozone in Canada were determined by cluster analysis of these characteristics. Individual semi-distributed virtual basin (VB) models representing these classes were parameterized in the Cold Regions Hydrological Model (CRHM) platform, which includes modules for snowmelt and sublimation, soil freezing and thawing, actual evapotranspiration (ET), soil moisture dynamics, groundwater recharge, and depressional storage dynamics including fill and spill runoff generation and variable connected areas. Precipitation (P) and temperature (T) perturbation scenarios covering the range of climate model predictions for the 21st century were used to evaluate climate sensitivity of hydrological processes in individual land cover and basin types across the Prairies Ecozone. Results indicated that snow accumulation in wetlands had a greater sensitivity to P and T than that in croplands and grasslands in all basin types. Wetland soil moisture was also more sensitive to T than the cropland and grassland soil moisture. Jointly influenced by land cover distribution and local climate, basin-average snow accumulation was more sensitive to T in the drier and grassland-characterized basins than in the wetter basins dominated by cropland, whilst basin-average soil moisture was most sensitive to T and P perturbations in basins typified by pothole depressions and broad river valleys. Annual streamflow had the greatest sensitivities to T and P in the dry and poorly connected Interior Grasslands (See Fig. 1) basins but the smallest in the wet and well-connected Southern Manitoba basins. The ability of P to compensate for warming-induced reductions in snow accumulation and streamflow was much higher in the wetter and cropland-dominated basins than in the drier and grassland-characterized basins, whilst decreases in cropland soil moisture induced by the maximum expected warming of 6 ∘C could be fully offset by a P increase of 11 % in all basins. These results can be used to (1) identify locations which had the largest hydrological sensitivities to changing climate and (2) diagnose underlying processes responsible for hydrological responses to expected climate change. Variations of hydrological sensitivity in land cover and basin types suggest that different water management and adaptation methods are needed to address enhanced water stress due to expected climate change in different regions of the Prairies EcozoneItem Multi-scale snowdrift-permitting modelling of mountain snowpack(Copernicus Publications on behalf of the European Geosciences Union, 2021) Vionnet, Vincent; Marsh, Christopher; Menounos, Brian; Gascoin, Simon; Wayand, Nicholas; Shea, Joseph; Mukherjee, Kriti; Pomeroy, JohnThe interaction of mountain terrain with meteorological processes causes substantial temporal and spatial variability in snow accumulation and ablation. Processes impacted by complex terrain include large-scale orographic enhancement of snowfall, small-scale processes such as gravitational and wind-induced transport of snow, and variability in the radiative balance such as through terrain shadowing. In this study, a multi-scale modelling approach is proposed to simulate the temporal and spatial evolution of high-mountain snowpacks. The multi-scale approach combines atmospheric data from a numerical weather prediction system at the kilometre scale with process-based downscaling techniques to drive the Canadian Hydrological Model (CHM) at spatial resolutions allowing for explicit snow redistribution modelling. CHM permits a variable spatial resolution by using the efficient terrain representation by unstructured triangular meshes. The model simulates processes such as radiation shadowing and irradiance to slopes, blowing-snow transport (saltation and suspension) and sublimation, avalanching, forest canopy interception and sublimation, and snowpack melt. Short-term, kilometre-scale atmospheric forecasts from Environment and Climate Change Canada’s Global Environmental Multiscale Model through its High Resolution Deterministic Prediction System (HRDPS) drive CHM and are downscaled to the unstructured mesh scale. In particular, a new wind-downscaling strategy uses pre-computed wind fields from a mass-conserving wind model at 50m resolution to perturb the mesoscale HRDPS wind and to account for the influence of topographic features on wind direction and speed. HRDPS-CHM was applied to simulate snow conditions down to 50m resolution during winter 2017/2018 in a domain around the Kananaskis Valley (~1000km2) in the Canadian Rockies. Simulations were evaluated using high-resolution airborne light detection and ranging (lidar) snow depth data and snow persistence indexes derived from remotely sensed imagery. Results included model falsifications and showed that both wind-induced and gravitational snow redistribution need to be simulated to capture the snowpack variability and the evolution of snow depth and persistence with elevation across the region. Accumulation of windblown snow on leeward slopes and associated snow cover persistence were underestimated in a CHM simulation driven by wind fields that did not capture lee-side flow recirculation and associated wind speed decreases. A terrain-based metric helped to identify these lee-side areas and improved the wind field and the associated snow redistribution. An overestimation of snow redistribution from windward to leeward slopes and subsequent avalanching was still found. The results of this study highlight the need for further improvements of snowdrift-permitting models for large-scale applications, in particular the representation of subgrid topographic effects on snow transport.Item The Perils of Regridding: Examples Using a Global Precipitation Dataset(American Meteorological Society (AMS), 2021) Rajulapati, Chandra Rupa; Papalexiou, Simon Michael; Clark, Martyn P.; Pomeroy, JohnGridded precipitation datasets are used in many applications such as the analysis of climate variability/change and hydrological modeling. Regridding precipitation datasets is common for model coupling (e.g., coupling atmospheric and hydrological models) or comparing different models and datasets. However, regridding can considerably alter precipitation statistics. In this global analysis, the effects of regridding a precipitation dataset are emphasized using three regridding methods (first-order conservative, bilinear, and distance-weighted averaging). The differences between the original and regridded dataset are substantial and greatest at high quantiles. Differences of 46 and 0.13 mm are noted in high (0.95) and low (0.05) quantiles, respectively. The impacts of regridding vary spatially for land and oceanic regions; there are substantial differences at high quantiles in tropical land regions, and at low quantiles in polar regions. These impacts are approximately the same for different regridding methods. The differences increase with the size of the grid at higher quantiles and vice versa for low quantiles. As the grid resolution increases, the difference between original and regridded data declines, yet the shift size dominates for high quantiles for which the differences are higher. While regridding is often necessary to use gridded precipitation datasets, it should be used with great caution for fine resolutions (e.g., daily and subdaily), because it can severely alter the statistical properties of precipitation, specifically at high and low quantiles.