Browsing by Author "Pomeroy, John"
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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 hydrological sensitivity to future climate change in the Canadian southern boreal forest(2023) He, Zhihua; Pomeroy, JohnItem 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 Development of the Prairie Hydrology Design and Analysis Product (PHyDAP)(2023) Shook, Kevin; He, Zhihua; Spence, Christopher; Whitfield, Colin; Pomeroy, JohnCurrently, there are no tools which account for the complexities of prairie hydrology and hydrography available to hydrological practitioners for calculating return-period flows and flooding at small scales on the Canadian Prairies. The need for such tools is especially great due to non-stationarity from the effects of climate change and surface drainage. The Prairie Hydrology Design and Analysis Product (PHyDAP) uses the research results of the Global Water Futures Prairie Water Project to produce a spatial dataset which will allow practitioners to determine return-period flows and flooded areas in a scientifically defensible manner, while incorporating changes in the local climate and land use.Item Diagnosing Hydrological Process Controls in Streamflow Generation and Variability in a 1 Glacierized Alpine Headwater Basin(Wiley Online Library, 2022) Aubry-Wake, Caroline; Pradhananga, Dhiraj; Pomeroy, JohnMountain glacierized headwaters are currently witnessing a transient shift in their hydrological and glaciological systems in response to rapid climate change. To characterize these changes, a robust understanding of the hydrological processes operating in the basin and their interactions is needed. Such an investigation was undertaken in the Peyto Glacier Research Basin, Canadian Rockies over 32 years (1988–2020). A distributed, physically based, uncalibrated glacier hydrology model was developed using the modular, object-oriented Cold Region Hydrological Modelling Platform to simulate both on and off-glacier high mountain processes and streamflow generation. The hydrological processes that generate streamflow from this alpine basin are characterized by substantial inter-annual variability over the 32 years. Snowmelt runoff always provided the largest fraction of annual streamflow (44% to 89%), with smaller fractional contributions occurring in higher streamflow years. Ice melt runoff provided 10% to 45% of annual streamflow volume, with higher fractions associated with higher flow years. Both rainfall and firn melt runoff contributed less than 13% of annual streamflow. Years with high streamflow were on average 1.43°C warmer than low streamflow years, and higher streamflow years had lower seasonal snow accumulation, earlier snowmelt and higher summer rainfall than years with lower streamflow. Greater ice exposure in warmer, low snowfall (high rainfall) years led to greater streamflow generation. The understanding gained here provides insight into how future climate and increased meteorological variability may impact glacier meltwater contributions to streamflow and downstream water availability as alpine glaciers continue to retreat.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 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 Impacts of Climate Change on Saskatchewan’s Water Resources(Centre for Hydrology, University Saskatchewan, Saskatoon, Saskatchewan, 2009) Pomeroy, John; Fang, Xing; Williams, BrandonThe purposes of this report are two-fold, i) documenting the expected impacts of climate change on Saskatchewan's water resources, ii) outlining the options for adaptation of water resource management practices, policies and infrastructure to minimize the risk associated with the impacts of climate change. Prairie province hydrology is dominated by cold regions processes so that snowmelt is the primary hydrological event of the year for both the major rivers that derive from the Rocky Mountains and small streams and rivers that arise in Saskatchewan. Climate change impacts on water resources are therefore focussed on changes to snow accumulation, snowmelt and infiltration to frozen soils. Climate change scenarios suggest generally warmer and wetter winters for Saskatchewan. Large scale hydrological models that take these scenarios into account suggest changes in the annual streamflow of the South Saskatchewan River ranging from an 8% increase to a 22% decrease, with an 8.5% decrease being an average prediction. Small scale hydrological models for prairie streams suggest a 24% increase in spring runoff by 2050 followed by a 37% decrease by 2080 is possible as the winter snowcover becomes discontinuous. Both model results suggest that there is not a dramatic drying of the prairies to be anticipated under climate change and that in some cases streamflow will increase for certain scenarios and under moderate degrees of climate change. For the major rivers draining from Alberta into Saskatchewan, more efficient water use for irrigation or a reduction in irrigated acreage in Alberta could compensate for the reduced water availability, which is due mainly to reduced mountain snowmelt. Current minimum tillage and continuous cropping systems are resilient for most climate changes to agricultural water resources. Initially there will be increases in prairie runoff but as climate change progresses later in the 21st C there will be dramatic drops in runoff and the flow of small streams to wetlands and depressions and to small prairie rivers. Infrastructure will have difficulty keeping up with this level of change unless agricultural land management is used to compensate for changes in hydrology. New crop varieties and tillage methods which are able to leave some water for runoff to natural ecosystems will need to be devised. Drainage of wetlands may have to be reversed to limit high spring streamflows and wetland/lake levels. Integrated basin management of the South Saskatchewan River across both Alberta and Saskatchewan and for smaller watersheds in Saskatchewan is the preferred adaptation method for dealing with these uncertainties. Integrated basin management plans with apportionment powers, enforceable land use controls and agricultural management incentives will need to be 2 implemented to deal with rapid changes and increased uncertainties in water management designs. In all cases the uncertainties in the model outputs and driving hydrometeorological data for current simulations make recommending adaptation measures very difficult as the range of predictions is from a decrease to an increase in available streamflow compared to current estimates. It is imperative that the scientific basis of these hydrological models be improved so that there is reduced uncertainty in model predictions. The current climate and water resources available in the headwater basins are themselves uncertain and need to be better quantified to permit more reliable comparisons of future climate and water resource predictions with the current situation.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 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 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.Item Physically based cold regions river flood prediction in data-sparse regions: The Yukon River Basin flow forecasting system(Chartered Institution of Water and Environmental Management and John Wiley & Sons Ltd., 2022) Elshamy, Mohamed; Loukili, Youssef; Pomeroy, John; Pietroniro, Alain; Richard, Dominique; Princz, DanielThe Yukon River Basin (YRB) is one of the most important river networks shared between Canada and The United States, and is one of the largest river basins in the subarctic region of North America. The Canadian part of the YRB is characterized by steeply sloped, partly glaciated mountain headwaters that generate considerable runoff during melt of glaciers and seasonal snow-cover. Snow redistribution, snowmelt, glacier melt and freezing–thawing soil processes in winter and spring along with summertime rainfall-runoff and evapotranspiration processes are thus key components of streamflow generation in the basin, making conceptual rainfall-runoff models unsuitable for this cold region. Due to the remote high latitudes and high altitudes of the basin, there is a paucity of observational data, making heavily calibrated conceptual modeling approaches infeasible. At the request of the Yukon Government, this project developed and operationalized a streamflow forecasting system for the Yukon River and several of its tributary rivers using a distributed land surface modeling approach developed for large-scale implementation in cold regions. This represents a substantial advance in bringing operational hydrological forecasting to the Canadian subarctic for the first time. This experience will inform future research to operation improvements as Canada develops a nationally coordinated flood forecast system.Item Recent hydrological response of glaciers in the Canadian Rockies to changing climate and glacier configuration(Copernicus Publications on behalf of the European Geosciences Union, 2022) Pradhananga, Dhiraj; Pomeroy, JohnMountain snow and ice greatly influence the hydrological cycle of alpine regions by regulating both the quantity of and seasonal variations in water availability downstream. This study considers the combined impacts of climate and glacier changes due to recession on the hydrology and water balance of two high-elevation basins in the Canadian Rockies. A distributed, physically based, uncalibrated glacier hydrology model developed in the Cold Regions Hydrological Modelling platform (CRHM) was used to simulate the glacier mass balance and basin hydrology of the Peyto and Athabasca glacier basins in Alberta, Canada. Bias-corrected reanalysis data were used to drive the model. The model calculates the water balance of glacierized basins, influenced by the surface energy and mass balance, and considers the redistribution of snow by wind and avalanches. It was set up using hydrological response units based on elevation bands, surface slope, and aspect, as well as changing land cover. Aerial photos, satellite images and digital elevation models (DEMs) were assimilated to represent the changing configurations of glacier area and the exposure of ice and firn. Observations of glacier mass balance, snow, and glacier ice surface elevation changes at glacier and alpine tundra meteorological stations and streamflow discharge at the glacier outlets were used to evaluate the model performance. Basin hydrology was simulated over two periods, 1965–1975 and2008–2018, using the observed glacier configurations for those time periods. Both basins have undergone continuous glacier loss over the last 3 to 5 decades, leading to a 6 %–31% reduction in glacierized area, a 78 %–109% increase in ice exposure, and changes to the elevation and slope of the glacier surfaces. Air temperatures are increasing, mainly due to increasing winter maximum and summer minimum daily temperatures. Annual precipitation has increased by less than 11 %, but rainfall ratios have increased by 29 %–44 %. The results show that changes in both climate and glacier configuration have influenced the melt rates and runoff and a shift of peak flows in the Peyto Glacier basin from August to July. Glacier melt contributions increased/decreased from 27 %–61% to 43 %–59% of the annual discharges. Recent discharges were 3 %–19% higher than in the 1960s and 1970s.The results suggest that increased exposure of glacier ice and lower surface elevation due to glacier thinning were less influential than climate warming in increasing streamflow. Streamflow from these glaciers continues to increase.Item The Role of Basin Geometry in Mountain Snowpack Responses to Climate Change(Frontiers Media, 2021) Shea, Joseph; Whitfield, Paul; Fang, Xing; Pomeroy, JohnSnowmelt contributions to streamflow in mid-latitude mountain basins typically dominate other runoff sources on annual and seasonal timescales. Future increases in temperature and changes in precipitation will affect both snow accumulation and seasonal runoff timing and magnitude, but the underlying and fundamental roles of mountain basin geometry and hypsometry on snowmelt sensitivity have received little attention. To investigate the role of basin geometry in snowmelt sensitivity, a linear snow accumulation model and the Cold Regions Hydrological Modeling (CRHM) platform driven are used to estimate how hypsometry affects basin-wide snow volumes and snowmelt runoff. Area-elevation distributions for fifty basins in western Canada were extracted, normalized according to their elevation statistics, and classified into three clusters that represent top-heavy, middle, and bottom-heavy basins. Prescribed changes in air temperature alter both the snow accumulation gradient and the total snowmelt energy, leading to snowpack volume reductions (10–40%), earlier melt onsets (1–4 weeks) and end of melt season (3 weeks), increases in early spring melt rates and reductions in seasonal areal melt rates (up to 50%). Basin hypsometry controls the magnitude of the basin response. The most sensitive basins are bottom-heavy, and have a greater proportion of their area at low elevations. The least sensitive basins are top-heavy, and have a greater proportion of their area at high elevations. Basins with similar proportional areas at high and low elevations fall in between the others in terms of sensitivity and other metrics. This work provides context for anticipating the impacts of ongoing hydrological change due to climate change, and provides guidance for both monitoring networks and distributed modeling efforts.Item Scientific and Human Errors in a Snow Model Intercomparison(American Meteorological Society (AMS), 2021) Menard, Cecile; Essery, Richard; Krinner, Gerhard; Arduini, Gabriele; Bartlett, Paul; boone, aaron; Brutel-Vuilmet, Claire; Burke, Eleanor; Cuntz, Matthias; Dai, Yongjiu; Decharme, Bertrand; Dutra, Emanuel; Fang, Xing; Fierz, Charles; Yeugeniy, Gusev; Hagemann, Stefan; Haverd, Vanessa; Kim, Hyungjun; Lafaysse, Matthieu; Marke, Thomas; Nasonova, Olga; Nitta, Tomoko; Niwano, Masashi; Pomeroy, John; Schädler, Gerd; Semenov, Vladimir A.; Smirnova, Tatiana; Strasser, Ulrich; Swenson, Sean; Turkov, Dmitry; Wever, Nander; Yuan, HuaTwenty-seven models participated in the Earth System Model–Snow Model Intercomparison Project (ESM-SnowMIP), the most data-rich MIP dedicated to snow modeling. Our findings do not support the hypothesis advanced by previous snow MIPs: evaluating models against more variables and providing evaluation datasets extended temporally and spatially does not facilitate identification of key new processes requiring improvement to model snow mass and energy budgets, even at point scales. In fact, the same modeling issues identified by previous snow MIPs arose: albedo is a major source of uncertainty, surface exchange parameterizations are problematic, and individual model performance is inconsistent. This lack of progress is attributed partly to the large number of human errors that led to anomalous model behavior and to numerous resubmissions. It is unclear how widespread such errors are in our field and others; dedicated time and resources will be needed to tackle this issue to prevent highly sophisticated models and their research outputs from being vulnerable because of avoidable human mistakes. The design of and the data available to successive snow MIPs were also questioned. Evaluation of models against bulk snow properties was found to be sufficient for some but inappropriate for more complex snow models whose skills at simulating internal snow properties remained untested. Discussions between the authors of this paper on the purpose of MIPs revealed varied, and sometimes contradictory, motivations behind their participation. These findings started a collaborative effort to adapt future snow MIPs to respond to the diverse needs of the community.Item A simple model for local-scale sensible and latent heat advection contributions to snowmelt(Copernicus Publications [Commercial Publisher]; European Geosciences Union [Society Publisher], 2019) Harder, Phillip; Pomeroy, John; Helgason, Warren D.Local-scale advection of energy from warm snow-free surfaces to cold snow-covered surfaces is an important component of the energy balance during snow-cover depletion. Unfortunately, this process is difficult to quantify in one-dimensional snowmelt models. This paper proposes a simple sensible and latent heat advection model for snowmelt situations that can be readily coupled to one-dimensional energy balance snowmelt models. An existing advection parameterization was coupled to a conceptual frozen soil infiltration surface water retention model to estimate the areal average sensible and latent heat advection contributions to snowmelt. The proposed model compared well with observations of latent and sensible heat advection, providing confidence in the process parameterizations and the assumptions applied. Snow-covered area observations from unmanned aerial vehicle imagery were used to update and evaluate the scaling properties of snow patch area distribution and lengths. Model dynamics and snowmelt implications were explored within an idealized modelling experiment, by coupling to a one-dimensional energy balance snowmelt model. Dry, snow-free surfaces were associated with advection of dry air that compensated for positive sensible heat advection fluxes and so limited the net influence of advection on snowmelt. Latent and sensible heat advection fluxes both contributed positive fluxes to snow when snow-free surfaces were wet and enhanced net advection contributions to snowmelt. The increased net advection fluxes from wet surfaces typically develop towards the end of snowmelt and offset decreases in the one-dimensional areal average melt energy that declines with snow-covered area. The new model can be readily incorporated into existing one-dimensional snowmelt hydrology and land surface scheme models and will foster improvements in snowmelt understanding and predictions.Item Simulating the hydrological impacts of land use conversion from annual crop to perennial forage in the Canadian Prairies using the Cold Regions Hydrological Modelling platform(Copernicus Publications on behalf of the European Geosciences Union, 2022) Cordeiro, Marcos; Liang, Kang; Wilson, Henry; Vanrobaeys, Jason; Lobb, David; Fang, Xing; Pomeroy, JohnThe Red River is one of the largest contributing sources of discharge and nutrients to the world’s 10th largest freshwater lake, Lake Winnipeg. Conversion of large areas of annual cropland to perennial forage has been proposed as a strategy to reduce both flooding and nutrient export to Lake Winnipeg. Such reductions could occur either via a reduction in the concentration of nutrients in runoff or through changes in the basin-scale hydrology, resulting in a lower water yield and the concomitant export of nutrients. This study assessed the latter mechanism by using the physically based Cold Regions Hydrological Modelling platform to examine the hydrological impacts of land use conversion from annual crops to perennial forage in a subbasin of the La Salle River basin in Canada. This basin is a typical agricultural subbasin in the Red River Valley, characterised by flat topography, clay soils, and a cold subhumid, continental climate. Long-term simulations (1992–2013) of the major components of water balance were compared between canola and smooth bromegrass, representing a conversion from annual cropping systems to perennial forage. An uncertainty framework was used to represent a range of fall soil saturation status (0% to 70 %), which governs the infiltration to frozen soil in the subsequent spring. The model simulations indicated that, on average, there was a 36.5±6.6% (36.5±7.2 mm) reduction in annual cumulative discharge and a 29.9±16.3% (2.6±1.6m3 s-1/ reduction in annual peak discharge due to forage conversion over the assessed period. These reductions were driven by reduced overland flow 52.9±12.8% (28.8±10.1 mm), increased peak snowpack (8.1±1.5 %, 7.8±1.6 mm), and enhanced infiltration to frozen soils (66.7±7.7 %, 141.5±15.2 mm). Higher cumulative evapotranspiration (ET) from perennial forage (34.5±0.9 %, 94.1±2.5 mm) was also predicted by the simulations. Overall, daily soil moisture under perennial forage was 18.0% (57.2±1.2 mm) higher than that of crop simulation, likely due to the higher snow water equivalent (SWE) and enhanced infiltration. However, the impact of forage conversion on daily soil moisture varied interannually. Soil moisture under perennial forage stands could be either higher or lower than that of annual crops, depending on antecedent spring snowmelt infiltration volumes.