Articles | Volume 29, issue 4
https://doi.org/10.5194/hess-29-983-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-29-983-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
25 Feb 2025
Research article |
| 25 Feb 2025
| 25 Feb 2025
Quantifying spatiotemporal and elevational precipitation gauge network uncertainty in the Canadian Rockies
André Bertoncini
CORRESPONDING AUTHOR
Centre for Hydrology, University of Saskatchewan, 200 – 50 Lincoln Park, Canmore, AB T1W 3E9, Canada
John W. Pomeroy
Centre for Hydrology, University of Saskatchewan, 200 – 50 Lincoln Park, Canmore, AB T1W 3E9, Canada
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Marlena Reil, Julia Kaltenborn, Donovan J. M. Allum, Francis Pelletier, Sebastian Roessler, Samip Shrestha, Zhibang Lv, John Truckenbrodt, Gabriele Schwaizer, Thomas Nagler, John W. Pomeroy, Christopher B. Marsh, Benoit Montpetit, Tobias Jonas, Gabriel Tseng, David Rolnick, Andreas J. Dietz, and Celia A. Baumhoer
EGUsphere, https://doi.org/10.5194/egusphere-2026-3833, https://doi.org/10.5194/egusphere-2026-3833, 2026
This preprint is open for discussion and under review for The Cryosphere (TC).
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Many communities rely on snowmelt from the mountains for their water supply. However, monitoring snow from space is challenging because clouds and other factors can obscure satellite observations. We present SnowGalileo, an AI model that combines data from multiple satellites to produce snow maps. The model can produce accurate maps even when clouds are present and high-resolution data are missing. This helps to improve our understanding of snow conditions and their impact on water resources.
Jonas Stankevicius, Alain Pietroniro, Qi Zhou, Mohamed Elshamy, and John W. Pomeroy
EGUsphere, https://doi.org/10.5194/egusphere-2026-3559, https://doi.org/10.5194/egusphere-2026-3559, 2026
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
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We built a three-dimensional computer model of Great Slave Lake, the deepest lake in North America, to understand how large northern lakes warm, mix, and freeze. Compared with temperature, ice, and evaporation measurements from 1998 to 2001, it reproduced water temperatures well, timed ice freeze-up and break-up to within one or two days, and matched summer evaporation closely. Wind most strongly controlled mixing. The methods can be reused on other remote ice-covered lakes for climate studies.
Kevin R. Shook, Paul H. Whitfield, Christopher Spence, and John W. Pomeroy
Hydrol. Earth Syst. Sci., 28, 5173–5192, https://doi.org/10.5194/hess-28-5173-2024, https://doi.org/10.5194/hess-28-5173-2024, 2024
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Recent studies suggest that the velocities of water running off landscapes in the Canadian Prairies may be much smaller than generally assumed. Analyses of historical flows for 23 basins in central Alberta show that many of the rivers responded more slowly and that the flows are much slower than would be estimated from equations developed elsewhere. The effects of slow flow velocities on the development of hydrological models of the region are discussed, as are the possible causes.
Phillip Harder, Warren D. Helgason, and John W. Pomeroy
The Cryosphere, 18, 3277–3295, https://doi.org/10.5194/tc-18-3277-2024, https://doi.org/10.5194/tc-18-3277-2024, 2024
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Remote sensing the amount of water in snow (SWE) at high spatial resolutions is an unresolved challenge. In this work, we tested a drone-mounted passive gamma spectrometer to quantify SWE. We found that the gamma observations could resolve the average and spatial variability of SWE down to 22.5 m resolutions. Further, by combining drone gamma SWE and lidar snow depth we could estimate SWE at sub-metre resolutions which is a new opportunity to improve the measurement of shallow snowpacks.
Mazda Kompanizare, Diogo Costa, Merrin L. Macrae, John W. Pomeroy, and Richard M. Petrone
Hydrol. Earth Syst. Sci., 28, 2785–2807, https://doi.org/10.5194/hess-28-2785-2024, https://doi.org/10.5194/hess-28-2785-2024, 2024
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A new agricultural tile drainage module was developed in the Cold Region Hydrological Model platform. Tile flow and water levels are simulated by considering the effect of capillary fringe thickness, drainable water and seasonal regional groundwater dynamics. The model was applied to a small well-instrumented farm in southern Ontario, Canada, where there are concerns about the impacts of agricultural drainage into Lake Erie.
Zhihua He, Kevin Shook, Christopher Spence, John W. Pomeroy, and Colin Whitfield
Hydrol. Earth Syst. Sci., 27, 3525–3546, https://doi.org/10.5194/hess-27-3525-2023, https://doi.org/10.5194/hess-27-3525-2023, 2023
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This study evaluated the impacts of climate change on snowmelt, soil moisture, and streamflow over the Canadian Prairies. The entire prairie region was divided into seven basin types. We found strong variations of hydrological sensitivity to precipitation and temperature changes in different land covers and basins, which suggests 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.
Marcos R. C. Cordeiro, Kang Liang, Henry F. Wilson, Jason Vanrobaeys, David A. Lobb, Xing Fang, and John W. Pomeroy
Hydrol. Earth Syst. Sci., 26, 5917–5931, https://doi.org/10.5194/hess-26-5917-2022, https://doi.org/10.5194/hess-26-5917-2022, 2022
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This study addresses the issue of increasing interest in the hydrological impacts of converting cropland to perennial forage cover in the Canadian Prairies. By developing customized models using the Cold Regions Hydrological Modelling (CRHM) platform, this long-term (1992–2013) modelling study is expected to provide stakeholders with science-based information regarding the hydrological impacts of land use conversion from annual crop to perennial forage cover in the Canadian Prairies.
Christopher Spence, Zhihua He, Kevin R. Shook, John W. Pomeroy, Colin J. Whitfield, and Jared D. Wolfe
Hydrol. Earth Syst. Sci., 26, 5555–5575, https://doi.org/10.5194/hess-26-5555-2022, https://doi.org/10.5194/hess-26-5555-2022, 2022
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We learnt how streamflow from small creeks could be altered by wetland removal in the Canadian Prairies, where this practice is pervasive. Every creek basin in the region was placed into one of seven groups. We selected one of these groups and used its traits to simulate streamflow. The model worked well enough so that we could trust the results even if we removed the wetlands. Wetland removal did not change low flow amounts very much, but it doubled high flow and tripled average flow.
Dhiraj Pradhananga and John W. Pomeroy
Hydrol. Earth Syst. Sci., 26, 2605–2616, https://doi.org/10.5194/hess-26-2605-2022, https://doi.org/10.5194/hess-26-2605-2022, 2022
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This study considers the combined impacts of climate and glacier changes due to recession on the hydrology and water balance of two high-elevation glaciers. Peyto and Athabasca glacier basins in the Canadian Rockies have undergone continuous glacier loss over the last 3 to 5 decades, leading to an increase in ice exposure and changes to the elevation and slope of the glacier surfaces. Streamflow from these glaciers continues to increase more due to climate warming than glacier recession.
Christopher Spence, Zhihua He, Kevin R. Shook, Balew A. Mekonnen, John W. Pomeroy, Colin J. Whitfield, and Jared D. Wolfe
Hydrol. Earth Syst. Sci., 26, 1801–1819, https://doi.org/10.5194/hess-26-1801-2022, https://doi.org/10.5194/hess-26-1801-2022, 2022
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We determined how snow and flow in small creeks change with temperature and precipitation in the Canadian Prairie, a region where water resources are often under stress. We tried something new. Every watershed in the region was placed in one of seven groups based on their landscape traits. We selected one of these groups and used its traits to build a model of snow and streamflow. It worked well, and by the 2040s there may be 20 %–40 % less snow and 30 % less streamflow than the 1980s.
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Short summary
Rainfall and snowfall spatial estimation for hydrological purposes is often compromised in cold mountain regions due to inaccessibility, creating sparse gauge networks with few high-elevation gauges. This study developed a framework for quantifying gauge network uncertainty, considering elevation to aid in future gauge placement in mountain regions. Results show that gauge placement above 2000 m is the most cost-effective measure to decrease gauge network uncertainty in the Canadian Rockies.
Rainfall and snowfall spatial estimation for hydrological purposes is often compromised in cold...
