Articles | Volume 13, issue 1
https://doi.org/10.5194/gmd-13-225-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-13-225-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
29 Jan 2020
Model description paper |
| 29 Jan 2020
| 29 Jan 2020
The Canadian Hydrological Model (CHM) v1.0: a multi-scale, multi-extent, variable-complexity hydrological model – design and overview
Christopher B. Marsh
CORRESPONDING AUTHOR
Centre for Hydrology, University of
Saskatchewan, Canada
Global Institute for Water Security,
University of Saskatchewan, Canada
John W. Pomeroy
Centre for Hydrology, University of
Saskatchewan, Canada
Global Institute for Water Security,
University of Saskatchewan, Canada
Howard S. Wheater
Global Institute for Water Security,
University of Saskatchewan, Canada
Centre for Hydrology, University of
Saskatchewan, Canada
Related authors
Vincent Vionnet, Christopher B. Marsh, Brian Menounos, Simon Gascoin, Nicholas E. Wayand, Joseph Shea, Kriti Mukherjee, and John W. Pomeroy
The Cryosphere, 15, 743–769, https://doi.org/10.5194/tc-15-743-2021, https://doi.org/10.5194/tc-15-743-2021, 2021
Short summary
Short summary
Mountain snow cover provides critical supplies of fresh water to downstream users. Its accurate prediction requires inclusion of often-ignored processes. A multi-scale modelling strategy is presented that efficiently accounts for snow redistribution. Model accuracy is assessed via airborne lidar and optical satellite imagery. With redistribution the model captures the elevation–snow depth relation. Redistribution processes are required to reproduce spatial variability, such as around ridges.
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
Short summary
Short summary
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
Short summary
Short summary
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.
André Bertoncini and John W. Pomeroy
EGUsphere, https://doi.org/10.5194/egusphere-2024-288, https://doi.org/10.5194/egusphere-2024-288, 2024
Short summary
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 to quantify gauge network uncertainty, considering elevation to aid in future gauge placement in mountain regions. Results show that gauge placement above 2000 m was the most cost-effective measure to decrease gauge network uncertainty in the Canadian Rockies.
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
Short summary
Short summary
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.
Mohamed S. Abdelhamed, Mohamed E. Elshamy, Saman Razavi, and Howard S. Wheater
The Cryosphere Discuss., https://doi.org/10.5194/tc-2023-20, https://doi.org/10.5194/tc-2023-20, 2023
Preprint withdrawn
Short summary
Short summary
Prior to any climate change assessment, it is necessary to assess the ability of available models to reliably reproduce observed permafrost and hydrology. Following a progressive approach, various model set-ups were developed and evaluated against different data sources. The study shows that different model set-ups favour different sources of data and it is challenging to configure a model faithful to all data sources, which are at times inconsistent with each other.
Kevin Robert Shook, Paul H. Whitfield, Christopher Spence, and John Willard Pomeroy
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2023-51, https://doi.org/10.5194/hess-2023-51, 2023
Preprint under review for HESS
Short summary
Short summary
Recent studies suggest that the velocities of water running off landscapes in the Canadian Prairies may be much smaller than are generally assumed. Analyses of historical flows for 23 basins in central Alberta, showed 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.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
Dhiraj Pradhananga, John W. Pomeroy, Caroline Aubry-Wake, D. Scott Munro, Joseph Shea, Michael N. Demuth, Nammy Hang Kirat, Brian Menounos, and Kriti Mukherjee
Earth Syst. Sci. Data, 13, 2875–2894, https://doi.org/10.5194/essd-13-2875-2021, https://doi.org/10.5194/essd-13-2875-2021, 2021
Short summary
Short summary
This paper presents hydrological, meteorological, glaciological and geospatial data of Peyto Glacier Basin in the Canadian Rockies. They include high-resolution DEMs derived from air photos and lidar surveys 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.
Paul H. Whitfield, Philip D. A. Kraaijenbrink, Kevin R. Shook, and John W. Pomeroy
Hydrol. Earth Syst. Sci., 25, 2513–2541, https://doi.org/10.5194/hess-25-2513-2021, https://doi.org/10.5194/hess-25-2513-2021, 2021
Short summary
Short summary
Using only warm season streamflow records, regime and change classifications were produced for ~ 400 watersheds in the Nelson and Mackenzie River basins, and trends in water storage and vegetation were detected from satellite imagery. Three areas show consistent changes: north of 60° (increased streamflow and basin greenness), in the western Boreal Plains (decreased streamflow and basin greenness), and across the Prairies (three different patterns of increased streamflow and basin wetness).
Chris M. DeBeer, Howard S. Wheater, John W. Pomeroy, Alan G. Barr, Jennifer L. Baltzer, Jill F. Johnstone, Merritt R. Turetsky, Ronald E. Stewart, Masaki Hayashi, Garth van der Kamp, Shawn Marshall, Elizabeth Campbell, Philip Marsh, Sean K. Carey, William L. Quinton, Yanping Li, Saman Razavi, Aaron Berg, Jeffrey J. McDonnell, Christopher Spence, Warren D. Helgason, Andrew M. Ireson, T. Andrew Black, Mohamed Elshamy, Fuad Yassin, Bruce Davison, Allan Howard, Julie M. Thériault, Kevin Shook, Michael N. Demuth, and Alain Pietroniro
Hydrol. Earth Syst. Sci., 25, 1849–1882, https://doi.org/10.5194/hess-25-1849-2021, https://doi.org/10.5194/hess-25-1849-2021, 2021
Short summary
Short summary
This article examines future changes in land cover and hydrological cycling across the interior of western Canada under climate conditions projected for the 21st century. Key insights into the mechanisms and interactions of Earth system and hydrological process responses are presented, and this understanding is used together with model application to provide a synthesis of future change. This has allowed more scientifically informed projections than have hitherto been available.
Julie M. Thériault, Stephen J. Déry, John W. Pomeroy, Hilary M. Smith, Juris Almonte, André Bertoncini, Robert W. Crawford, Aurélie Desroches-Lapointe, Mathieu Lachapelle, Zen Mariani, Selina Mitchell, Jeremy E. Morris, Charlie Hébert-Pinard, Peter Rodriguez, and Hadleigh D. Thompson
Earth Syst. Sci. Data, 13, 1233–1249, https://doi.org/10.5194/essd-13-1233-2021, https://doi.org/10.5194/essd-13-1233-2021, 2021
Short summary
Short summary
This article discusses the data that were collected during the Storms and Precipitation Across the continental Divide (SPADE) field campaign in spring 2019 in the Canadian Rockies, along the Alberta and British Columbia border. Various instruments were installed at five field sites to gather information about atmospheric conditions focussing on precipitation. Details about the field sites, the instrumentation used, the variables collected, and the collection methods and intervals are presented.
Vincent Vionnet, Christopher B. Marsh, Brian Menounos, Simon Gascoin, Nicholas E. Wayand, Joseph Shea, Kriti Mukherjee, and John W. Pomeroy
The Cryosphere, 15, 743–769, https://doi.org/10.5194/tc-15-743-2021, https://doi.org/10.5194/tc-15-743-2021, 2021
Short summary
Short summary
Mountain snow cover provides critical supplies of fresh water to downstream users. Its accurate prediction requires inclusion of often-ignored processes. A multi-scale modelling strategy is presented that efficiently accounts for snow redistribution. Model accuracy is assessed via airborne lidar and optical satellite imagery. With redistribution the model captures the elevation–snow depth relation. Redistribution processes are required to reproduce spatial variability, such as around ridges.
Richard Essery, Hyungjun Kim, Libo Wang, Paul Bartlett, Aaron Boone, Claire Brutel-Vuilmet, Eleanor Burke, Matthias Cuntz, Bertrand Decharme, Emanuel Dutra, Xing Fang, Yeugeniy Gusev, Stefan Hagemann, Vanessa Haverd, Anna Kontu, Gerhard Krinner, Matthieu Lafaysse, Yves Lejeune, Thomas Marke, Danny Marks, Christoph Marty, Cecile B. Menard, Olga Nasonova, Tomoko Nitta, John Pomeroy, Gerd Schädler, Vladimir Semenov, Tatiana Smirnova, Sean Swenson, Dmitry Turkov, Nander Wever, and Hua Yuan
The Cryosphere, 14, 4687–4698, https://doi.org/10.5194/tc-14-4687-2020, https://doi.org/10.5194/tc-14-4687-2020, 2020
Short summary
Short summary
Climate models are uncertain in predicting how warming changes snow cover. This paper compares 22 snow models with the same meteorological inputs. Predicted trends agree with observations at four snow research sites: winter snow cover does not start later, but snow now melts earlier in spring than in the 1980s at two of the sites. Cold regions where snow can last until late summer are predicted to be particularly sensitive to warming because the snow then melts faster at warmer times of year.
Nikolas O. Aksamit and John W. Pomeroy
The Cryosphere, 14, 2795–2807, https://doi.org/10.5194/tc-14-2795-2020, https://doi.org/10.5194/tc-14-2795-2020, 2020
Short summary
Short summary
In cold regions, it is increasingly important to quantify the amount of water stored as snow at the end of winter. Current models are inconsistent in their estimates of snow sublimation due to atmospheric turbulence. Specific wind structures have been identified that amplify potential rates of surface and blowing snow sublimation during blowing snow storms. The recurrence of these motions has been modeled by a simple scaling argument that has its foundation in turbulent boundary layer theory.
Nicholas J. Kinar, John W. Pomeroy, and Bing Si
Geosci. Instrum. Method. Data Syst., 9, 293–315, https://doi.org/10.5194/gi-9-293-2020, https://doi.org/10.5194/gi-9-293-2020, 2020
Short summary
Short summary
Heat pulse probes are widely used to monitor soil thermal and physical properties for agricultural and hydrological monitoring related to crop productivity, drought, snowmelt, and evapotranspiration. Changes in the effective probe spacing distance can cause measurement inaccuracy. This paper uses a novel heat pulse probe and theory to compensate for changes in effective distance, thereby enabling more accurate sensor outputs useful for forecasts and predictions of drought and flooding.
Phillip Harder, John W. Pomeroy, and Warren D. Helgason
The Cryosphere, 14, 1919–1935, https://doi.org/10.5194/tc-14-1919-2020, https://doi.org/10.5194/tc-14-1919-2020, 2020
Short summary
Short summary
Unmanned-aerial-vehicle-based (UAV) structure-from-motion (SfM) techniques have the ability to map snow depths in open areas. Here UAV lidar and SfM are compared to map sub-canopy snowpacks. Snow depth accuracy was assessed with data from sites in western Canada collected in 2019. It is demonstrated that UAV lidar can measure the sub-canopy snow depth at a high accuracy, while UAV-SfM cannot. UAV lidar promises to quantify snow–vegetation interactions at unprecedented accuracy and resolution.
Xing Fang and John W. Pomeroy
Hydrol. Earth Syst. Sci., 24, 2731–2754, https://doi.org/10.5194/hess-24-2731-2020, https://doi.org/10.5194/hess-24-2731-2020, 2020
Short summary
Short summary
High-resolution Weather Research and Forecasting model near-surface outputs from control and future periods were bias-corrected by downscaling outputs with respect to meteorological stations in Marmot Creek Research Basin, Canadian Rocky Mountains. A hydrological model simulation driven by the bias-corrected outputs showed declined seasonal peak snowpack, shorter snow-cover duration, higher evapotranspiration, and increased streamflow discharge in Marmot Creek for the warmer and wetter future.
Vincent Vionnet, Vincent Fortin, Etienne Gaborit, Guy Roy, Maria Abrahamowicz, Nicolas Gasset, and John W. Pomeroy
Hydrol. Earth Syst. Sci., 24, 2141–2165, https://doi.org/10.5194/hess-24-2141-2020, https://doi.org/10.5194/hess-24-2141-2020, 2020
Short summary
Short summary
The 2013 Alberta flood in Canada was typical of late-spring floods in mountain basins combining intense precipitation with rapid melting of late-lying snowpack. Hydrological simulations of this event are mainly influenced by (i) the spatial resolution of the atmospheric forcing due to the best estimate of precipitation at the kilometer scale and changes in turbulent fluxes contributing to snowmelt and (ii) uncertainties in initial snow conditions at high elevations. Soil texture has less impact.
Zilefac Elvis Asong, Mohamed Ezzat Elshamy, Daniel Princz, Howard Simon Wheater, John Willard Pomeroy, Alain Pietroniro, and Alex Cannon
Earth Syst. Sci. Data, 12, 629–645, https://doi.org/10.5194/essd-12-629-2020, https://doi.org/10.5194/essd-12-629-2020, 2020
Short summary
Short summary
This dataset provides an improved set of forcing data for large-scale hydrological models for climate change impact assessment in the Mackenzie River Basin (MRB). Here, the strengths of two historical datasets were blended to produce a less-biased long-record product for hydrological modelling and climate change impact assessment over the MRB. This product is then used to bias-correct climate projections from the Canadian Regional Climate Model under RCP8.5.
Paul H. Whitfield, Philip D. A. Kraaijenbrink, Kevin R. Shook, and John W. Pomeroy
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2019-671, https://doi.org/10.5194/hess-2019-671, 2020
Revised manuscript not accepted
Short summary
Short summary
Using partial year streamflow records a regime and change classification were produced for ~ 400 watersheds in the Saskatchewan and Mackenzie River basins, and trends in water storage and vegetation were detected from satellite imagery. Three areas show consistent changes; north of 60° [increased streamflow and basin greenness], in the western Boreal Plains [decreased streamflow and basin greenness], and across the Prairies [three different patterns of increased streamflow and basin wetness].
Mohamed E. Elshamy, Daniel Princz, Gonzalo Sapriza-Azuri, Mohamed S. Abdelhamed, Al Pietroniro, Howard S. Wheater, and Saman Razavi
Hydrol. Earth Syst. Sci., 24, 349–379, https://doi.org/10.5194/hess-24-349-2020, https://doi.org/10.5194/hess-24-349-2020, 2020
Short summary
Short summary
Permafrost is an important feature of cold-region hydrology and needs to be properly represented in hydrological and land surface models (H-LSMs), especially under the observed and expected climate warming trends. This study aims to devise a robust, yet computationally efficient, initialization and parameterization approach for permafrost. We used permafrost observations from three sites along the Mackenzie River valley spanning different permafrost classes to test the validity of the approach.
Michael Schirmer and John W. Pomeroy
Hydrol. Earth Syst. Sci., 24, 143–157, https://doi.org/10.5194/hess-24-143-2020, https://doi.org/10.5194/hess-24-143-2020, 2020
Short summary
Short summary
The spatial distribution of snow water equivalent (SWE) and melt are important for hydrological applications in alpine terrain. We measured the spatial distribution of melt using a drone in very high resolution and could relate melt to topographic characteristics. Interestingly, melt and SWE were not related spatially, which influences the speed of areal melt out. We could explain this by melt varying over larger distances than SWE.
Kabir Rasouli, John W. Pomeroy, and Paul H. Whitfield
Hydrol. Earth Syst. Sci., 23, 4933–4954, https://doi.org/10.5194/hess-23-4933-2019, https://doi.org/10.5194/hess-23-4933-2019, 2019
Short summary
Short summary
The combined effects of changes in climate, vegetation, and soils on mountain hydrology were modeled in three mountain basins. In the Yukon, an insignificant increasing effect of vegetation change on snow was found to be important enough to offset the climate change effect. In the Canadian Rockies, a combined effect of soil and climate change on runoff became significant, whereas their individual effects were not significant. Only vegetation change decreased runoff in the basin in Idaho.
Robert N. Armstrong, John W. Pomeroy, and Lawrence W. Martz
Hydrol. Earth Syst. Sci., 23, 4891–4907, https://doi.org/10.5194/hess-23-4891-2019, https://doi.org/10.5194/hess-23-4891-2019, 2019
Short summary
Short summary
Digital and thermal images taken near midday were used to scale daily point observations of key factors driving actual-evaporation estimates across a complex Canadian Prairie landscape. Point estimates of actual evaporation agreed well with observed values via eddy covariance. Impacts of spatial variations on areal estimates were minor, and no covariance was found between model parameters driving the energy term. The methods can be applied further to improve land surface parameterisations.
Fuad Yassin, Saman Razavi, Mohamed Elshamy, Bruce Davison, Gonzalo Sapriza-Azuri, and Howard Wheater
Hydrol. Earth Syst. Sci., 23, 3735–3764, https://doi.org/10.5194/hess-23-3735-2019, https://doi.org/10.5194/hess-23-3735-2019, 2019
Zilefac Elvis Asong, Mohamed Elshamy, Daniel Princz, Howard Wheater, John Pomeroy, Alain Pietroniro, and Alex Cannon
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2019-249, https://doi.org/10.5194/hess-2019-249, 2019
Publication in HESS not foreseen
Fuad Yassin, Saman Razavi, Jefferson S. Wong, Alain Pietroniro, and Howard Wheater
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2019-207, https://doi.org/10.5194/hess-2019-207, 2019
Preprint withdrawn
Xing Fang, John W. Pomeroy, Chris M. DeBeer, Phillip Harder, and Evan Siemens
Earth Syst. Sci. Data, 11, 455–471, https://doi.org/10.5194/essd-11-455-2019, https://doi.org/10.5194/essd-11-455-2019, 2019
Short summary
Short summary
Meteorological, snow survey, streamflow, and groundwater data are presented from Marmot Creek Research Basin, a small alpine-montane forest headwater catchment in the Alberta Rockies. It was heavily instrumented, experimented upon, and operated by several federal government agencies between 1962 and 1986 and was re-established starting in 2004 by the University of Saskatchewan Centre for Hydrology. These long-term legacy data serve to advance our knowledge of hydrology of the Canadian Rockies.
Kabir Rasouli, John W. Pomeroy, J. Richard Janowicz, Tyler J. Williams, and Sean K. Carey
Earth Syst. Sci. Data, 11, 89–100, https://doi.org/10.5194/essd-11-89-2019, https://doi.org/10.5194/essd-11-89-2019, 2019
Short summary
Short summary
A set of hydrometeorological data including daily precipitation, hourly air temperature, humidity, wind, solar and net radiation, soil temperature, soil moisture, snow depth and snow water equivalent, streamflow and water level in a groundwater well, and geographical information system data are presented in this paper. This dataset was recorded at different elevation bands in Wolf Creek Research Basin, near Whitehorse, Yukon Territory, Canada.
Phillip Harder, John W. Pomeroy, and Warren D. Helgason
Hydrol. Earth Syst. Sci., 23, 1–17, https://doi.org/10.5194/hess-23-1-2019, https://doi.org/10.5194/hess-23-1-2019, 2019
Short summary
Short summary
As snow cover becomes patchy during snowmelt, energy is advected from warm snow-free surfaces to cold snow-covered surfaces. This paper proposes a simple sensible and latent heat advection model for snowmelt situations that can be coupled to one-dimensional energy balance snowmelt models. The model demonstrates that sensible and latent heat advection fluxes can compensate for one another, especially in early melt periods.
Gerhard Krinner, Chris Derksen, Richard Essery, Mark Flanner, Stefan Hagemann, Martyn Clark, Alex Hall, Helmut Rott, Claire Brutel-Vuilmet, Hyungjun Kim, Cécile B. Ménard, Lawrence Mudryk, Chad Thackeray, Libo Wang, Gabriele Arduini, Gianpaolo Balsamo, Paul Bartlett, Julia Boike, Aaron Boone, Frédérique Chéruy, Jeanne Colin, Matthias Cuntz, Yongjiu Dai, Bertrand Decharme, Jeff Derry, Agnès Ducharne, Emanuel Dutra, Xing Fang, Charles Fierz, Josephine Ghattas, Yeugeniy Gusev, Vanessa Haverd, Anna Kontu, Matthieu Lafaysse, Rachel Law, Dave Lawrence, Weiping Li, Thomas Marke, Danny Marks, Martin Ménégoz, Olga Nasonova, Tomoko Nitta, Masashi Niwano, John Pomeroy, Mark S. Raleigh, Gerd Schaedler, Vladimir Semenov, Tanya G. Smirnova, Tobias Stacke, Ulrich Strasser, Sean Svenson, Dmitry Turkov, Tao Wang, Nander Wever, Hua Yuan, Wenyan Zhou, and Dan Zhu
Geosci. Model Dev., 11, 5027–5049, https://doi.org/10.5194/gmd-11-5027-2018, https://doi.org/10.5194/gmd-11-5027-2018, 2018
Short summary
Short summary
This paper provides an overview of a coordinated international experiment to determine the strengths and weaknesses in how climate models treat snow. The models will be assessed at point locations using high-quality reference measurements and globally using satellite-derived datasets. How well climate models simulate snow-related processes is important because changing snow cover is an important part of the global climate system and provides an important freshwater resource for human use.
Zilefac Elvis Asong, Howard Simon Wheater, John Willard Pomeroy, Alain Pietroniro, Mohamed Ezzat Elshamy, Daniel Princz, and Alex Cannon
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2018-128, https://doi.org/10.5194/essd-2018-128, 2018
Preprint withdrawn
Short summary
Short summary
Cold regions hydrology is very sensitive to the impacts of climate warming. We need better hydrological models driven by reliable climate data in order to assess hydrologic responses to climate change. Cold regions often have sparse surface observations, particularly at high elevations that generate a major amount of runoff. We produce a long-term dataset that can be used to better understand and represent the seasonal/inter-annual variability of hydrological fluxes and the the timing of runoff.
Julie M. Thériault, Ida Hung, Paul Vaquer, Ronald E. Stewart, and John W. Pomeroy
Hydrol. Earth Syst. Sci., 22, 4491–4512, https://doi.org/10.5194/hess-22-4491-2018, https://doi.org/10.5194/hess-22-4491-2018, 2018
Short summary
Short summary
Precipitation events associated with rain and snow on the eastern slopes of the Rocky Mountains, Canada, are a critical aspect of the regional water cycle. The goal is to characterize the precipitation and weather conditions in the Kananaskis Valley, Alberta, during a field experiment. Mainly dense solid precipitation reached the surface and occurred during downslope and upslope conditions. The precipitation phase has critical implications on the severity of flooding events in the area.
Sebastian A. Krogh and John W. Pomeroy
Hydrol. Earth Syst. Sci., 22, 3993–4014, https://doi.org/10.5194/hess-22-3993-2018, https://doi.org/10.5194/hess-22-3993-2018, 2018
Short summary
Short summary
The Arctic has warmed and vegetation has expanded; however, impacts on hydrology are poorly understood. This study used observed meteorology from the last 56 years and changes in vegetation to simulate the water cycle of an Arctic headwater basin. Several changes were found: decreased snow cover duration, deeper permafrost and earlier peak flows. Most changes are from climate change; however, vegetation impacts blowing snow, partially compensating the impact of climate change on streamflow.
Gonzalo Sapriza-Azuri, Pablo Gamazo, Saman Razavi, and Howard S. Wheater
Hydrol. Earth Syst. Sci., 22, 3295–3309, https://doi.org/10.5194/hess-22-3295-2018, https://doi.org/10.5194/hess-22-3295-2018, 2018
Short summary
Short summary
Arctic and subarctic regions are amongst the most susceptible regions on Earth to climate change. There, models require a proper representation of the interactions between climate and hydrology. Typically these model represent the soil with shallow depths, whereas for cold regions, deep soil is needed. To address this, we run model experiments to characterize the effect of soil depth and temperature soil initialization. Our results demonstrate that 20 m of soil profile is essential.
Zilefac Elvis Asong, Howard Simon Wheater, Barrie Bonsal, Saman Razavi, and Sopan Kurkute
Hydrol. Earth Syst. Sci., 22, 3105–3124, https://doi.org/10.5194/hess-22-3105-2018, https://doi.org/10.5194/hess-22-3105-2018, 2018
Short summary
Short summary
Canada is very susceptible to recurrent droughts, which have damaging impacts on regional water resources and agriculture. However, nationwide drought assessments are currently lacking and impacted by limited ground-based observations. We delineate two major drought regions (Prairies and northern central) over Canada and link drought characteristics to external factors of climate variability. This study helps to determine when the drought events occur, their duration, and how often they occur.
José-Luis Guerrero, Patricia Pernica, Howard Wheater, Murray Mackay, and Chris Spence
Hydrol. Earth Syst. Sci., 21, 6345–6362, https://doi.org/10.5194/hess-21-6345-2017, https://doi.org/10.5194/hess-21-6345-2017, 2017
Short summary
Short summary
Lakes are sentinels of climate change, and an adequate characterization of their feedbacks to the atmosphere could improve climate modeling. These feedbacks, as heat fluxes, can be simulated but are seldom measured, casting doubt on modeling results. Measurements from a small lake in Canada established that the model parameter modulating how much light penetrates the lake dominates model response. This parameter is measurable: improved monitoring could lead to more robust modeling.
Xicai Pan, Warren Helgason, Andrew Ireson, and Howard Wheater
Hydrol. Earth Syst. Sci., 21, 5401–5413, https://doi.org/10.5194/hess-21-5401-2017, https://doi.org/10.5194/hess-21-5401-2017, 2017
Short summary
Short summary
In this paper we present a case study from a heterogeneous pasture site in the Canadian prairies, where we have quantified the various components of the water balance on the field scale, and critically examine some of the simplifying assumptions which are often invoked when applying water budget approaches in applied hydrology. We highlight challenges caused by lateral fluxes of blowing snow and ambiguous partitioning of snow melt water into runoff and infiltration.
Yoshihide Wada, Marc F. P. Bierkens, Ad de Roo, Paul A. Dirmeyer, James S. Famiglietti, Naota Hanasaki, Megan Konar, Junguo Liu, Hannes Müller Schmied, Taikan Oki, Yadu Pokhrel, Murugesu Sivapalan, Tara J. Troy, Albert I. J. M. van Dijk, Tim van Emmerik, Marjolein H. J. Van Huijgevoort, Henny A. J. Van Lanen, Charles J. Vörösmarty, Niko Wanders, and Howard Wheater
Hydrol. Earth Syst. Sci., 21, 4169–4193, https://doi.org/10.5194/hess-21-4169-2017, https://doi.org/10.5194/hess-21-4169-2017, 2017
Short summary
Short summary
Rapidly increasing population and human activities have altered terrestrial water fluxes on an unprecedented scale. Awareness of potential water scarcity led to first global water resource assessments; however, few hydrological models considered the interaction between terrestrial water fluxes and human activities. Our contribution highlights the importance of human activities transforming the Earth's water cycle, and how hydrological models can include such influences in an integrated manner.
Marcos R. C. Cordeiro, Henry F. Wilson, Jason Vanrobaeys, John W. Pomeroy, Xing Fang, and The Red-Assiniboine Project Biophysical Modelling Team
Hydrol. Earth Syst. Sci., 21, 3483–3506, https://doi.org/10.5194/hess-21-3483-2017, https://doi.org/10.5194/hess-21-3483-2017, 2017
Short summary
Short summary
The physically based Cold Regions Hydrological Model (CRHM) was utilized to simulate runoff in the La Salle River, located in the northern Great Plains with flat topography, clay soils, and surface drainage. Snow sublimation and transport as well as infiltration to frozen soils were identified as critical in defining snowmelt. Challenges in representing infiltration into frozen but dry clay soils and flow routing under both dry and flooded conditions indicate the need for further study.
Jefferson S. Wong, Saman Razavi, Barrie R. Bonsal, Howard S. Wheater, and Zilefac E. Asong
Hydrol. Earth Syst. Sci., 21, 2163–2185, https://doi.org/10.5194/hess-21-2163-2017, https://doi.org/10.5194/hess-21-2163-2017, 2017
Short summary
Short summary
This study was conducted to quantify the spatial and temporal variability of the errors associated with various gridded precipitation products in Canada. Overall, WFDEI [GPCC] and CaPA performed best with respect to different performance measures, followed by ANUSPLIN and WEDEI [CRU]. Princeton and NARR demonstrated the lowest quality. Comparing the climate model-simulated products, PCIC ensembles generally performed better than NA-CORDEX ensembles in terms of reliability in four seasons.
Craig D. Smith, Anna Kontu, Richard Laffin, and John W. Pomeroy
The Cryosphere, 11, 101–116, https://doi.org/10.5194/tc-11-101-2017, https://doi.org/10.5194/tc-11-101-2017, 2017
Short summary
Short summary
One of the objectives of the WMO Solid Precipitation Intercomparison Experiment (SPICE) was to assess the performance of automated instruments that measure snow water equivalent and make recommendations on the best measurement practices and data interpretation. This study assesses the Campbell Scientific CS725 and the Sommer SSG100 for measuring SWE. Different measurement principals of the instruments as well as site characteristics influence the way that the SWE data should be interpreted.
Nikolas O. Aksamit and John W. Pomeroy
The Cryosphere, 10, 3043–3062, https://doi.org/10.5194/tc-10-3043-2016, https://doi.org/10.5194/tc-10-3043-2016, 2016
Short summary
Short summary
The first implementation of particle tracking velocimetry in outdoor alpine blowing snow has both provided new insight on intermittent snow particle transport initiation and entrainment in the dense near-surface "creep" layer whilst also confirming some wind tunnel observations. Environmental PTV has shown to be a viable avenue for furthering our understanding of the coupling of the atmospheric boundary layer turbulence and blowing snow transport.
Phillip Harder, Michael Schirmer, John Pomeroy, and Warren Helgason
The Cryosphere, 10, 2559–2571, https://doi.org/10.5194/tc-10-2559-2016, https://doi.org/10.5194/tc-10-2559-2016, 2016
Short summary
Short summary
This paper assesses the accuracy of high-resolution snow depth maps generated from unmanned aerial vehicle imagery. Snow depth maps are generated from differencing snow-covered and snow-free digital surface models produced from structure from motion techniques. On average, the estimated snow depth error was 10 cm. This technique is therefore useful for observing snow accumulation and melt in deep snow but is restricted to observing peak snow accumulation in shallow snow.
Xicai Pan, Daqing Yang, Yanping Li, Alan Barr, Warren Helgason, Masaki Hayashi, Philip Marsh, John Pomeroy, and Richard J. Janowicz
The Cryosphere, 10, 2347–2360, https://doi.org/10.5194/tc-10-2347-2016, https://doi.org/10.5194/tc-10-2347-2016, 2016
Short summary
Short summary
This study demonstrates a robust procedure for accumulating precipitation gauge measurements and provides an analysis of bias corrections of precipitation measurements across experimental sites in different ecoclimatic regions of western Canada. It highlights the need for and importance of precipitation bias corrections at both research sites and operational networks for water balance assessment and the validation of global/regional climate–hydrology models.
Chris M. DeBeer, Howard S. Wheater, Sean K. Carey, and Kwok P. Chun
Hydrol. Earth Syst. Sci., 20, 1573–1598, https://doi.org/10.5194/hess-20-1573-2016, https://doi.org/10.5194/hess-20-1573-2016, 2016
Short summary
Short summary
This paper provides a comprehensive review and up-to-date synthesis of the observed changes in air temperature, precipitation, seasonal snow cover, mountain glaciers, permafrost, freshwater ice cover, and river discharge over the interior of western Canada since the mid- or late 20th century. Important long-term observational networks and data sets are described, and qualitative linkages among the changing Earth system components are highlighted.
Nicolas R. Leroux and John W. Pomeroy
The Cryosphere Discuss., https://doi.org/10.5194/tc-2016-55, https://doi.org/10.5194/tc-2016-55, 2016
Revised manuscript not accepted
Short summary
Short summary
Snowmelt runoff reaches our rivers and is critical for water management and consumption in cold regions. Preferential flow paths form while snow is melting and accelerate the timing at which meltwater reaches the base of the snowpack and has great impact on basin hydrology. A novel 2D numerical model that simulates water and heat fluxes through a melting snowpack is presented. Its ability to simulate formation and flow through preferential flow paths and impacts on snowmelt runoff are discussed.
A. Nazemi and H. S. Wheater
Hydrol. Earth Syst. Sci., 19, 33–61, https://doi.org/10.5194/hess-19-33-2015, https://doi.org/10.5194/hess-19-33-2015, 2015
Short summary
Short summary
Activities related to water resource management perturb terrestrial water cycle with hydrologic and land-atmospheric implications. By defining water resource management as the integration of water demand with water supply and allocation, this paper critically reviews current schemes for representing human water demands in models relevant to Earth system modelling. We conclude that current representations are limited due to uncertainties in data support, demand algorithms and large-scale models.
A. Nazemi and H. S. Wheater
Hydrol. Earth Syst. Sci., 19, 63–90, https://doi.org/10.5194/hess-19-63-2015, https://doi.org/10.5194/hess-19-63-2015, 2015
Short summary
Short summary
Human water supply and allocation are major drivers of change in terrestrial water cycle. Considering current schemes for representing water supply and allocation in large-scale models, we review the state of the art and highlight various sources of uncertainty. Considering the opportunities for improving available schemes, we argue that the time is right for a global initiative based on a set of regional case studies to improve the inclusion of water resource management in large-scale models.
C. B. Ménard, R. Essery, and J. Pomeroy
Hydrol. Earth Syst. Sci., 18, 2375–2392, https://doi.org/10.5194/hess-18-2375-2014, https://doi.org/10.5194/hess-18-2375-2014, 2014
X. Fang, J. W. Pomeroy, C. R. Ellis, M. K. MacDonald, C. M. DeBeer, and T. Brown
Hydrol. Earth Syst. Sci., 17, 1635–1659, https://doi.org/10.5194/hess-17-1635-2013, https://doi.org/10.5194/hess-17-1635-2013, 2013
Related subject area
Hydrology
STORM v.2: A simple, stochastic rainfall model for exploring the impacts of climate and climate change at and near the land surface in gauged watersheds
Fluvial flood inundation and socio-economic impact model based on open data
RoGeR v3.0.5 – a process-based hydrological toolbox model in Python
Coupling a large-scale glacier and hydrological model (OGGM v1.5.3 and CWatM V1.08) – towards an improved representation of mountain water resources in global assessments
An open-source refactoring of the Canadian Small Lakes Model for estimates of evaporation from medium-sized reservoirs
EvalHyd v0.1.2: a polyglot tool for the evaluation of deterministic and probabilistic streamflow predictions
Modelling water quantity and quality for integrated water cycle management with the Water Systems Integrated Modelling framework (WSIMOD) software
HGS-PDAF (version 1.0): a modular data assimilation framework for an integrated surface and subsurface hydrological model
Wflow_sbm v0.7.3, a spatially distributed hydrological model: from global data to local applications
Reservoir Assessment Tool version 3.0: a scalable and user-friendly software platform to mobilize the global water management community
HydroFATE (v1): a high-resolution contaminant fate model for the global river system
Validation of a new global irrigation scheme in the land surface model ORCHIDEE v2.2
GPEP v1.0: the Geospatial Probabilistic Estimation Package to support Earth science applications
GEMS v1.0: Generalizable Empirical Model of Snow Accumulation and Melt, based on daily snow mass changes in response to climate and topographic drivers
mesas.py v1.0: a flexible Python package for modeling solute transport and transit times using StorAge Selection functions
rSHUD v2.0: advancing the Simulator for Hydrologic Unstructured Domains and unstructured hydrological modeling in the R environment
GLOBGM v1.0: a parallel implementation of a 30 arcsec PCR-GLOBWB-MODFLOW global-scale groundwater model
Development of inter-grid-cell lateral unsaturated and saturated flow model in the E3SM Land Model (v2.0)
pyESDv1.0.1: an open-source Python framework for empirical-statistical downscaling of climate information
Representing the impact of Rhizophora mangroves on flow in a hydrodynamic model (COAWST_rh v1.0): the importance of three-dimensional root system structures
Dynamically weighted ensemble of geoscientific models via automated machine-learning-based classification
Deep Dive into Global Hydrologic Simulations: Harnessing the Power of Deep Learning and Physics-informed Differentiable Models (δHBV-globe1.0-hydroDL)
Enhancing the representation of water management in global hydrological models
NEOPRENE v1.0.1: a Python library for generating spatial rainfall based on the Neyman–Scott process
Uncertainty estimation for a new exponential-filter-based long-term root-zone soil moisture dataset from Copernicus Climate Change Service (C3S) surface observations
Validating the Nernst–Planck transport model under reaction-driven flow conditions using RetroPy v1.0
DynQual v1.0: a high-resolution global surface water quality model
Data space inversion for efficient uncertainty quantification using an integrated surface and sub-surface hydrologic model
Simulation of crop yield using the global hydrological model H08 (crp.v1)
How is a global sensitivity analysis of a catchment-scale, distributed pesticide transfer model performed? Application to the PESHMELBA model
iHydroSlide3D v1.0: an advanced hydrological–geotechnical model for hydrological simulation and three-dimensional landslide prediction
GEB v0.1: a large-scale agent-based socio-hydrological model – simulating 10 million individual farming households in a fully distributed hydrological model
Tracing and visualisation of contributing water sources in the LISFLOOD-FP model of flood inundation (within CAESAR-Lisflood version 1.9j-WS)
Continental-scale evaluation of a fully distributed coupled land surface and groundwater model, ParFlow-CLM (v3.6.0), over Europe
Evaluating a global soil moisture dataset from a multitask model (GSM3 v1.0) with potential applications for crop threats
SERGHEI (SERGHEI-SWE) v1.0: a performance-portable high-performance parallel-computing shallow-water solver for hydrology and environmental hydraulics
A simple, efficient, mass-conservative approach to solving Richards' equation (openRE, v1.0)
Customized deep learning for precipitation bias correction and downscaling
Implementation and sensitivity analysis of the Dam-Reservoir OPeration model (DROP v1.0) over Spain
Regional coupled surface–subsurface hydrological model fitting based on a spatially distributed minimalist reduction of frequency domain discharge data
Operational water forecast ability of the HRRR-iSnobal combination: an evaluation to adapt into production environments
Prediction of algal blooms via data-driven machine learning models: an evaluation using data from a well-monitored mesotrophic lake
UniFHy v0.1.1: a community modelling framework for the terrestrial water cycle in Python
Basin-scale gyres and mesoscale eddies in large lakes: a novel procedure for their detection and characterization, assessed in Lake Geneva
SIMO v1.0: simplified model of the vertical temperature profile in a small, warm, monomictic lake
Thermal modeling of three lakes within the continuous permafrost zone in Alaska using the LAKE 2.0 model
Water balance model (WBM) v.1.0.0: a scalable gridded global hydrologic model with water-tracking functionality
Coupling a large-scale hydrological model (CWatM v1.1) with a high-resolution groundwater flow model (MODFLOW 6) to assess the impact of irrigation at regional scale
RavenR v2.1.4: an open-source R package to support flexible hydrologic modelling
Developing a parsimonious canopy model (PCM v1.0) to predict forest gross primary productivity and leaf area index of deciduous broad-leaved forest
Manuel F. Rios Gaona, Katerina Michaelides, and Michael Bliss Singer
Geosci. Model Dev., 17, 5387–5412, https://doi.org/10.5194/gmd-17-5387-2024, https://doi.org/10.5194/gmd-17-5387-2024, 2024
Short summary
Short summary
STORM v.2 (short for STOchastic Rainfall Model version 2.0) is an open-source and user-friendly modelling framework for simulating rainfall fields over a basin. It also allows simulating the impact of plausible climate change either on the total seasonal rainfall or the storm’s maximum intensity.
Lukas Riedel, Thomas Röösli, Thomas Vogt, and David N. Bresch
Geosci. Model Dev., 17, 5291–5308, https://doi.org/10.5194/gmd-17-5291-2024, https://doi.org/10.5194/gmd-17-5291-2024, 2024
Short summary
Short summary
River floods are among the most devastating natural hazards. We propose a flood model with a statistical approach based on openly available data. The model is integrated in a framework for estimating impacts of physical hazards. Although the model only agrees moderately with satellite-detected flood extents, we show that it can be used for forecasting the magnitude of flood events in terms of socio-economic impacts and for comparing these with past events.
Robin Schwemmle, Hannes Leistert, Andreas Steinbrich, and Markus Weiler
Geosci. Model Dev., 17, 5249–5262, https://doi.org/10.5194/gmd-17-5249-2024, https://doi.org/10.5194/gmd-17-5249-2024, 2024
Short summary
Short summary
The new process-based hydrological toolbox model, RoGeR (https://roger.readthedocs.io/), can be used to estimate the components of the hydrological cycle and the related travel times of pollutants through parts of the hydrological cycle. These estimations may contribute to effective water resources management. This paper presents the toolbox concept and provides a simple example of providing estimations to water resources management.
Sarah Hanus, Lilian Schuster, Peter Burek, Fabien Maussion, Yoshihide Wada, and Daniel Viviroli
Geosci. Model Dev., 17, 5123–5144, https://doi.org/10.5194/gmd-17-5123-2024, https://doi.org/10.5194/gmd-17-5123-2024, 2024
Short summary
Short summary
This study presents a coupling of the large-scale glacier model OGGM and the hydrological model CWatM. Projected future increase in discharge is less strong while future decrease in discharge is stronger when glacier runoff is explicitly included in the large-scale hydrological model. This is because glacier runoff is projected to decrease in nearly all basins. We conclude that an improved glacier representation can prevent underestimating future discharge changes in large river basins.
M. Graham Clark and Sean K. Carey
Geosci. Model Dev., 17, 4911–4922, https://doi.org/10.5194/gmd-17-4911-2024, https://doi.org/10.5194/gmd-17-4911-2024, 2024
Short summary
Short summary
This paper provides validation of the Canadian Small Lakes Model (CSLM) for estimating evaporation rates from reservoirs and a refactoring of the original FORTRAN code into MATLAB and Python, which are now stored in GitHub repositories. Here we provide direct observations of the surface energy exchange obtained with an eddy covariance system to validate the CSLM. There was good agreement between observations and estimations except under specific atmospheric conditions when evaporation is low.
Thibault Hallouin, François Bourgin, Charles Perrin, Maria-Helena Ramos, and Vazken Andréassian
Geosci. Model Dev., 17, 4561–4578, https://doi.org/10.5194/gmd-17-4561-2024, https://doi.org/10.5194/gmd-17-4561-2024, 2024
Short summary
Short summary
The evaluation of the quality of hydrological model outputs against streamflow observations is widespread in the hydrological literature. In order to improve on the reproducibility of published studies, a new evaluation tool dedicated to hydrological applications is presented. It is open source and usable in a variety of programming languages to make it as accessible as possible to the community. Thus, authors and readers alike can use the same tool to produce and reproduce the results.
Barnaby Dobson, Leyang Liu, and Ana Mijic
Geosci. Model Dev., 17, 4495–4513, https://doi.org/10.5194/gmd-17-4495-2024, https://doi.org/10.5194/gmd-17-4495-2024, 2024
Short summary
Short summary
Water management is challenging when models don't capture the entire water cycle. We propose that using integrated models facilitates management and improves understanding. We introduce a software tool designed for this task. We discuss its foundation, how it simulates water system components and their interactions, and its customisation. We provide a flexible way to represent water systems, and we hope it will inspire more research and practical applications for sustainable water management.
Qi Tang, Hugo Delottier, Wolfgang Kurtz, Lars Nerger, Oliver S. Schilling, and Philip Brunner
Geosci. Model Dev., 17, 3559–3578, https://doi.org/10.5194/gmd-17-3559-2024, https://doi.org/10.5194/gmd-17-3559-2024, 2024
Short summary
Short summary
We have developed a new data assimilation framework by coupling an integrated hydrological model HydroGeoSphere with the data assimilation software PDAF. Compared to existing hydrological data assimilation systems, the advantage of our newly developed framework lies in its consideration of the physically based model; its large selection of different assimilation algorithms; and its modularity with respect to the combination of different types of observations, states and parameters.
Willem J. van Verseveld, Albrecht H. Weerts, Martijn Visser, Joost Buitink, Ruben O. Imhoff, Hélène Boisgontier, Laurène Bouaziz, Dirk Eilander, Mark Hegnauer, Corine ten Velden, and Bobby Russell
Geosci. Model Dev., 17, 3199–3234, https://doi.org/10.5194/gmd-17-3199-2024, https://doi.org/10.5194/gmd-17-3199-2024, 2024
Short summary
Short summary
We present the wflow_sbm distributed hydrological model, recently released by Deltares, as part of the Wflow.jl open-source modelling framework in the programming language Julia. Wflow_sbm has a fast runtime, making it suitable for large-scale modelling. Wflow_sbm models can be set a priori for any catchment with the Python tool HydroMT-Wflow based on globally available datasets, which results in satisfactory to good performance (without much tuning). We show this for a number of specific cases.
Sanchit Minocha, Faisal Hossain, Pritam Das, Sarath Suresh, Shahzaib Khan, George Darkwah, Hyongki Lee, Stefano Galelli, Konstantinos Andreadis, and Perry Oddo
Geosci. Model Dev., 17, 3137–3156, https://doi.org/10.5194/gmd-17-3137-2024, https://doi.org/10.5194/gmd-17-3137-2024, 2024
Short summary
Short summary
The Reservoir Assessment Tool (RAT) merges satellite data with hydrological models, enabling robust estimation of reservoir parameters like inflow, outflow, surface area, and storage changes around the world. Version 3.0 of RAT lowers the barrier of entry for new users and achieves scalability and computational efficiency. RAT 3.0 also facilitates open-source development of functions for continuous improvement to mobilize and empower the global water management community.
Heloisa Ehalt Macedo, Bernhard Lehner, Jim Nicell, and Günther Grill
Geosci. Model Dev., 17, 2877–2899, https://doi.org/10.5194/gmd-17-2877-2024, https://doi.org/10.5194/gmd-17-2877-2024, 2024
Short summary
Short summary
Treated and untreated wastewaters are sources of contaminants of emerging concern. HydroFATE, a new global model, estimates their concentrations in surface waters, identifying streams that are most at risk and guiding monitoring/mitigation efforts to safeguard aquatic ecosystems and human health. Model predictions were validated against field measurements of the antibiotic sulfamethoxazole, with predicted concentrations exceeding ecological thresholds in more than 400 000 km of rivers worldwide.
Pedro Felipe Arboleda-Obando, Agnès Ducharne, Zun Yin, and Philippe Ciais
Geosci. Model Dev., 17, 2141–2164, https://doi.org/10.5194/gmd-17-2141-2024, https://doi.org/10.5194/gmd-17-2141-2024, 2024
Short summary
Short summary
We show a new irrigation scheme included in the ORCHIDEE land surface model. The new irrigation scheme restrains irrigation due to water shortage, includes water adduction, and represents environmental limits and facilities to access water, due to representing infrastructure in a simple way. Our results show that the new irrigation scheme helps simulate acceptable land surface conditions and fluxes in irrigated areas, even if there are difficulties due to shortcomings and limited information.
Guoqiang Tang, Andrew W. Wood, Andrew J. Newman, Martyn P. Clark, and Simon Michael Papalexiou
Geosci. Model Dev., 17, 1153–1173, https://doi.org/10.5194/gmd-17-1153-2024, https://doi.org/10.5194/gmd-17-1153-2024, 2024
Short summary
Short summary
Ensemble geophysical datasets are crucial for understanding uncertainties and supporting probabilistic estimation/prediction. However, open-access tools for creating these datasets are limited. We have developed the Python-based Geospatial Probabilistic Estimation Package (GPEP). Through several experiments, we demonstrate GPEP's ability to estimate precipitation, temperature, and snow water equivalent. GPEP will be a useful tool to support uncertainty analysis in Earth science applications.
Atabek Umirbekov, Richard Essery, and Daniel Müller
Geosci. Model Dev., 17, 911–929, https://doi.org/10.5194/gmd-17-911-2024, https://doi.org/10.5194/gmd-17-911-2024, 2024
Short summary
Short summary
We present a parsimonious snow model which simulates snow mass without the need for extensive calibration. The model is based on a machine learning algorithm that has been trained on diverse set of daily observations of snow accumulation or melt, along with corresponding climate and topography data. We validated the model using in situ data from numerous new locations. The model provides a promising solution for accurate snow mass estimation across regions where in situ data are limited.
Ciaran J. Harman and Esther Xu Fei
Geosci. Model Dev., 17, 477–495, https://doi.org/10.5194/gmd-17-477-2024, https://doi.org/10.5194/gmd-17-477-2024, 2024
Short summary
Short summary
Over the last 10 years, scientists have developed StorAge Selection: a new way of modeling how material is transported through complex systems. Here, we present some new, easy-to-use, flexible, and very accurate code for implementing this method. We show that, in cases where we know exactly what the answer should be, our code gets the right answer. We also show that our code is closer than some other codes to the right answer in an important way: it conserves mass.
Lele Shu, Paul Ullrich, Xianhong Meng, Christopher Duffy, Hao Chen, and Zhaoguo Li
Geosci. Model Dev., 17, 497–527, https://doi.org/10.5194/gmd-17-497-2024, https://doi.org/10.5194/gmd-17-497-2024, 2024
Short summary
Short summary
Our team developed rSHUD v2.0, a toolkit that simplifies the use of the SHUD, a model simulating water movement in the environment. We demonstrated its effectiveness in two watersheds, one in the USA and one in China. The toolkit also facilitated the creation of the Global Hydrological Data Cloud, a platform for automatic data processing and model deployment, marking a significant advancement in hydrological research.
Jarno Verkaik, Edwin H. Sutanudjaja, Gualbert H. P. Oude Essink, Hai Xiang Lin, and Marc F. P. Bierkens
Geosci. Model Dev., 17, 275–300, https://doi.org/10.5194/gmd-17-275-2024, https://doi.org/10.5194/gmd-17-275-2024, 2024
Short summary
Short summary
This paper presents the parallel PCR-GLOBWB global-scale groundwater model at 30 arcsec resolution (~1 km at the Equator). Named GLOBGM v1.0, this model is a follow-up of the 5 arcmin (~10 km) model, aiming for a higher-resolution simulation of worldwide fresh groundwater reserves under climate change and excessive pumping. For a long transient simulation using a parallel prototype of MODFLOW 6, we show that our implementation is efficient for a relatively low number of processor cores.
Han Qiu, Gautam Bisht, Lingcheng Li, Dalei Hao, and Donghui Xu
Geosci. Model Dev., 17, 143–167, https://doi.org/10.5194/gmd-17-143-2024, https://doi.org/10.5194/gmd-17-143-2024, 2024
Short summary
Short summary
We developed and validated an inter-grid-cell lateral groundwater flow model for both saturated and unsaturated zone in the ELMv2.0 framework. The developed model was benchmarked against PFLOTRAN, a 3D subsurface flow and transport model and showed comparable performance with PFLOTRAN. The developed model was also applied to the Little Washita experimental watershed. The spatial pattern of simulated groundwater table depth agreed well with the global groundwater table benchmark dataset.
Daniel Boateng and Sebastian G. Mutz
Geosci. Model Dev., 16, 6479–6514, https://doi.org/10.5194/gmd-16-6479-2023, https://doi.org/10.5194/gmd-16-6479-2023, 2023
Short summary
Short summary
We present an open-source Python framework for performing empirical-statistical downscaling of climate information, such as precipitation. The user-friendly package comprises all the downscaling cycles including data preparation, model selection, training, and evaluation, designed in an efficient and flexible manner, allowing for quick and reproducible downscaling products. The framework would contribute to climate change impact assessments by generating accurate high-resolution climate data.
Masaya Yoshikai, Takashi Nakamura, Eugene C. Herrera, Rempei Suwa, Rene Rollon, Raghab Ray, Keita Furukawa, and Kazuo Nadaoka
Geosci. Model Dev., 16, 5847–5863, https://doi.org/10.5194/gmd-16-5847-2023, https://doi.org/10.5194/gmd-16-5847-2023, 2023
Short summary
Short summary
Due to complex root system structures, representing the impacts of Rhizophora mangroves on flow in hydrodynamic models has been challenging. This study presents a new drag and turbulence model that leverages an empirical model for root systems. The model can be applied without rigorous measurements of root structures and showed high performance in flow simulations; this may provide a better understanding of hydrodynamics and related transport processes in Rhizophora mangrove forests.
Hao Chen, Tiejun Wang, Yonggen Zhang, Yun Bai, and Xi Chen
Geosci. Model Dev., 16, 5685–5701, https://doi.org/10.5194/gmd-16-5685-2023, https://doi.org/10.5194/gmd-16-5685-2023, 2023
Short summary
Short summary
Effectively assembling multiple models for approaching a benchmark solution remains a long-standing issue for various geoscience domains. We here propose an automated machine learning-assisted ensemble framework (AutoML-Ens) that attempts to resolve this challenge. Results demonstrate the great potential of AutoML-Ens for improving estimations due to its two unique features, i.e., assigning dynamic weights for candidate models and taking full advantage of AutoML-assisted workflow.
Dapeng Feng, Hylke Beck, Jens de Bruijn, Reetik Kumar Sahu, Yusuke Satoh, Yoshihide Wada, Jiangtao Liu, Ming Pan, Kathryn Lawson, and Chaopeng Shen
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-190, https://doi.org/10.5194/gmd-2023-190, 2023
Revised manuscript accepted for GMD
Short summary
Short summary
Accurate hydrological modeling is vital to characterizing water cycle responses to climate change. For the first time at this scale, we use differentiable physics-informed machine learning hydrologic models to simulate rainfall-runoff processes for 3753 basins around the world and compare them with purely data-driven and traditional approaches. This sets a benchmark for hydrologic estimates around the world and builds foundations for improving global hydrologic simulations.
Guta Wakbulcho Abeshu, Fuqiang Tian, Thomas Wild, Mengqi Zhao, Sean Turner, A. F. M. Kamal Chowdhury, Chris R. Vernon, Hongchang Hu, Yuan Zhuang, Mohamad Hejazi, and Hong-Yi Li
Geosci. Model Dev., 16, 5449–5472, https://doi.org/10.5194/gmd-16-5449-2023, https://doi.org/10.5194/gmd-16-5449-2023, 2023
Short summary
Short summary
Most existing global hydrologic models do not explicitly represent hydropower reservoirs. We are introducing a new water management module to Xanthos that distinguishes between the operational characteristics of irrigation, hydropower, and flood control reservoirs. We show that this explicit representation of hydropower reservoirs can lead to a significantly more realistic simulation of reservoir storage and releases in over 44 % of the hydropower reservoirs included in this study.
Javier Diez-Sierra, Salvador Navas, and Manuel del Jesus
Geosci. Model Dev., 16, 5035–5048, https://doi.org/10.5194/gmd-16-5035-2023, https://doi.org/10.5194/gmd-16-5035-2023, 2023
Short summary
Short summary
NEOPRENE is an open-source, freely available library allowing scientists and practitioners to generate synthetic time series and maps of rainfall. These outputs will help to explore plausible events that were never observed in the past but may occur in the near future and to generate possible future events under climate change conditions. The paper shows how to use the library to downscale daily precipitation and how to use synthetic generation to improve our characterization of extreme events.
Adam Pasik, Alexander Gruber, Wolfgang Preimesberger, Domenico De Santis, and Wouter Dorigo
Geosci. Model Dev., 16, 4957–4976, https://doi.org/10.5194/gmd-16-4957-2023, https://doi.org/10.5194/gmd-16-4957-2023, 2023
Short summary
Short summary
We apply the exponential filter (EF) method to satellite soil moisture retrievals to estimate the water content in the unobserved root zone globally from 2002–2020. Quality assessment against an independent dataset shows satisfactory results. Error characterization is carried out using the standard uncertainty propagation law and empirically estimated values of EF model structural uncertainty and parameter uncertainty. This is followed by analysis of temporal uncertainty variations.
Po-Wei Huang, Bernd Flemisch, Chao-Zhong Qin, Martin O. Saar, and Anozie Ebigbo
Geosci. Model Dev., 16, 4767–4791, https://doi.org/10.5194/gmd-16-4767-2023, https://doi.org/10.5194/gmd-16-4767-2023, 2023
Short summary
Short summary
Water in natural environments consists of many ions. Ions are electrically charged and exert electric forces on each other. We discuss whether the electric forces are relevant in describing mixing and reaction processes in natural environments. By comparing our computer simulations to lab experiments in literature, we show that the electric interactions between ions can play an essential role in mixing and reaction processes, in which case they should not be neglected in numerical modeling.
Edward R. Jones, Marc F. P. Bierkens, Niko Wanders, Edwin H. Sutanudjaja, Ludovicus P. H. van Beek, and Michelle T. H. van Vliet
Geosci. Model Dev., 16, 4481–4500, https://doi.org/10.5194/gmd-16-4481-2023, https://doi.org/10.5194/gmd-16-4481-2023, 2023
Short summary
Short summary
DynQual is a new high-resolution global water quality model for simulating total dissolved solids, biological oxygen demand and fecal coliform as indicators of salinity, organic pollution and pathogen pollution, respectively. Output data from DynQual can supplement the observational record of water quality data, which is highly fragmented across space and time, and has the potential to inform assessments in a broad range of fields including ecological, human health and water scarcity studies.
Hugo Delottier, John Doherty, and Philip Brunner
Geosci. Model Dev., 16, 4213–4231, https://doi.org/10.5194/gmd-16-4213-2023, https://doi.org/10.5194/gmd-16-4213-2023, 2023
Short summary
Short summary
Long run times are usually a barrier to the quantification and reduction of predictive uncertainty with complex hydrological models. Data space inversion (DSI) provides an alternative and highly model-run-efficient method for uncertainty quantification. This paper demonstrates DSI's ability to robustly quantify predictive uncertainty and extend the methodology to provide practical metrics that can guide data acquisition and analysis to achieve goals of decision-support modelling.
Zhipin Ai and Naota Hanasaki
Geosci. Model Dev., 16, 3275–3290, https://doi.org/10.5194/gmd-16-3275-2023, https://doi.org/10.5194/gmd-16-3275-2023, 2023
Short summary
Short summary
Simultaneously simulating food production and the requirements and availability of water resources in a spatially explicit manner within a single framework remains challenging on a global scale. Here, we successfully enhanced the global hydrological model H08 that considers human water use and management to simulate the yields of four major staple crops: maize, wheat, rice, and soybean. Our improved model will be beneficial for advancing global food–water nexus studies in the future.
Emilie Rouzies, Claire Lauvernet, Bruno Sudret, and Arthur Vidard
Geosci. Model Dev., 16, 3137–3163, https://doi.org/10.5194/gmd-16-3137-2023, https://doi.org/10.5194/gmd-16-3137-2023, 2023
Short summary
Short summary
Water and pesticide transfer models are complex and should be simplified to be used in decision support. Indeed, these models simulate many spatial processes in interaction, involving a large number of parameters. Sensitivity analysis allows us to select the most influential input parameters, but it has to be adapted to spatial modelling. This study will identify relevant methods that can be transposed to any hydrological and water quality model and improve the fate of pesticide knowledge.
Guoding Chen, Ke Zhang, Sheng Wang, Yi Xia, and Lijun Chao
Geosci. Model Dev., 16, 2915–2937, https://doi.org/10.5194/gmd-16-2915-2023, https://doi.org/10.5194/gmd-16-2915-2023, 2023
Short summary
Short summary
In this study, we developed a novel modeling system called iHydroSlide3D v1.0 by coupling a modified a 3D landslide model with a distributed hydrology model. The model is able to apply flexibly different simulating resolutions for hydrological and slope stability submodules and gain a high computational efficiency through parallel computation. The test results in the Yuehe River basin, China, show a good predicative capability for cascading flood–landslide events.
Jens A. de Bruijn, Mikhail Smilovic, Peter Burek, Luca Guillaumot, Yoshihide Wada, and Jeroen C. J. H. Aerts
Geosci. Model Dev., 16, 2437–2454, https://doi.org/10.5194/gmd-16-2437-2023, https://doi.org/10.5194/gmd-16-2437-2023, 2023
Short summary
Short summary
We present a computer simulation model of the hydrological system and human system, which can simulate the behaviour of individual farmers and their interactions with the water system at basin scale to assess how the systems have evolved and are projected to evolve in the future. For example, we can simulate the effect of subsidies provided on investment in adaptation measures and subsequent effects in the hydrological system, such as a lowering of the groundwater table or reservoir level.
Matthew D. Wilson and Thomas J. Coulthard
Geosci. Model Dev., 16, 2415–2436, https://doi.org/10.5194/gmd-16-2415-2023, https://doi.org/10.5194/gmd-16-2415-2023, 2023
Short summary
Short summary
During flooding, the sources of water that inundate a location can influence impacts such as pollution. However, methods to trace water sources in flood events are currently only available in complex, computationally expensive hydraulic models. We propose a simplified method which can be added to efficient, reduced-complexity model codes, enabling an improved understanding of flood dynamics and its impacts. We demonstrate its application for three sites at a range of spatial and temporal scales.
Bibi S. Naz, Wendy Sharples, Yueling Ma, Klaus Goergen, and Stefan Kollet
Geosci. Model Dev., 16, 1617–1639, https://doi.org/10.5194/gmd-16-1617-2023, https://doi.org/10.5194/gmd-16-1617-2023, 2023
Short summary
Short summary
It is challenging to apply a high-resolution integrated land surface and groundwater model over large spatial scales. In this paper, we demonstrate the application of such a model over a pan-European domain at 3 km resolution and perform an extensive evaluation of simulated water states and fluxes by comparing with in situ and satellite data. This study can serve as a benchmark and baseline for future studies of climate change impact projections and for hydrological forecasting.
Jiangtao Liu, David Hughes, Farshid Rahmani, Kathryn Lawson, and Chaopeng Shen
Geosci. Model Dev., 16, 1553–1567, https://doi.org/10.5194/gmd-16-1553-2023, https://doi.org/10.5194/gmd-16-1553-2023, 2023
Short summary
Short summary
Under-monitored regions like Africa need high-quality soil moisture predictions to help with food production, but it is not clear if soil moisture processes are similar enough around the world for data-driven models to maintain accuracy. We present a deep-learning-based soil moisture model that learns from both in situ data and satellite data and performs better than satellite products at the global scale. These results help us apply our model globally while better understanding its limitations.
Daniel Caviedes-Voullième, Mario Morales-Hernández, Matthew R. Norman, and Ilhan Özgen-Xian
Geosci. Model Dev., 16, 977–1008, https://doi.org/10.5194/gmd-16-977-2023, https://doi.org/10.5194/gmd-16-977-2023, 2023
Short summary
Short summary
This paper introduces the SERGHEI framework and a solver for shallow-water problems. Such models, often used for surface flow and flood modelling, are computationally intense. In recent years the trends to increase computational power have changed, requiring models to adapt to new hardware and new software paradigms. SERGHEI addresses these challenges, allowing surface flow simulation to be enabled on the newest and upcoming consumer hardware and supercomputers very efficiently.
Andrew M. Ireson, Raymond J. Spiteri, Martyn P. Clark, and Simon A. Mathias
Geosci. Model Dev., 16, 659–677, https://doi.org/10.5194/gmd-16-659-2023, https://doi.org/10.5194/gmd-16-659-2023, 2023
Short summary
Short summary
Richards' equation (RE) is used to describe the movement and storage of water in a soil profile and is a component of many hydrological and earth-system models. Solving RE numerically is challenging due to the non-linearities in the properties. Here, we present a simple but effective and mass-conservative solution to solving RE, which is ideal for teaching/learning purposes but also useful in prototype models that are used to explore alternative process representations.
Fang Wang, Di Tian, and Mark Carroll
Geosci. Model Dev., 16, 535–556, https://doi.org/10.5194/gmd-16-535-2023, https://doi.org/10.5194/gmd-16-535-2023, 2023
Short summary
Short summary
Gridded precipitation datasets suffer from biases and coarse resolutions. We developed a customized deep learning (DL) model to bias-correct and downscale gridded precipitation data using radar observations. The results showed that the customized DL model can generate improved precipitation at fine resolutions where regular DL and statistical methods experience challenges. The new model can be used to improve precipitation estimates, especially for capturing extremes at smaller scales.
Malak Sadki, Simon Munier, Aaron Boone, and Sophie Ricci
Geosci. Model Dev., 16, 427–448, https://doi.org/10.5194/gmd-16-427-2023, https://doi.org/10.5194/gmd-16-427-2023, 2023
Short summary
Short summary
Predicting water resource evolution is a key challenge for the coming century.
Anthropogenic impacts on water resources, and particularly the effects of dams and reservoirs on river flows, are still poorly known and generally neglected in global hydrological studies. A parameterized reservoir model is reproduced to compute monthly releases in Spanish anthropized river basins. For global application, an exhaustive sensitivity analysis of the model parameters is performed on flows and volumes.
Nicolas Flipo, Nicolas Gallois, and Jonathan Schuite
Geosci. Model Dev., 16, 353–381, https://doi.org/10.5194/gmd-16-353-2023, https://doi.org/10.5194/gmd-16-353-2023, 2023
Short summary
Short summary
A new approach is proposed to fit hydrological or land surface models, which suffer from large uncertainties in terms of water partitioning between fast runoff and slow infiltration from small watersheds to regional or continental river basins. It is based on the analysis of hydrosystem behavior in the frequency domain, which serves as a basis for estimating water flows in the time domain with a physically based model. It opens the way to significant breakthroughs in hydrological modeling.
Joachim Meyer, John Horel, Patrick Kormos, Andrew Hedrick, Ernesto Trujillo, and S. McKenzie Skiles
Geosci. Model Dev., 16, 233–250, https://doi.org/10.5194/gmd-16-233-2023, https://doi.org/10.5194/gmd-16-233-2023, 2023
Short summary
Short summary
Freshwater resupply from seasonal snow in the mountains is changing. Current water prediction methods from snow rely on historical data excluding the change and can lead to errors. This work presented and evaluated an alternative snow-physics-based approach. The results in a test watershed were promising, and future improvements were identified. Adaptation to current forecast environments would improve resilience to the seasonal snow changes and helps ensure the accuracy of resupply forecasts.
Shuqi Lin, Donald C. Pierson, and Jorrit P. Mesman
Geosci. Model Dev., 16, 35–46, https://doi.org/10.5194/gmd-16-35-2023, https://doi.org/10.5194/gmd-16-35-2023, 2023
Short summary
Short summary
The risks brought by the proliferation of algal blooms motivate the improvement of bloom forecasting tools, but algal blooms are complexly controlled and difficult to predict. Given rapid growth of monitoring data and advances in computation, machine learning offers an alternative prediction methodology. This study tested various machine learning workflows in a dimictic mesotrophic lake and gave promising predictions of the seasonal variations and the timing of algal blooms.
Thibault Hallouin, Richard J. Ellis, Douglas B. Clark, Simon J. Dadson, Andrew G. Hughes, Bryan N. Lawrence, Grenville M. S. Lister, and Jan Polcher
Geosci. Model Dev., 15, 9177–9196, https://doi.org/10.5194/gmd-15-9177-2022, https://doi.org/10.5194/gmd-15-9177-2022, 2022
Short summary
Short summary
A new framework for modelling the water cycle in the land system has been implemented. It considers the hydrological cycle as three interconnected components, bringing flexibility in the choice of the physical processes and their spatio-temporal resolutions. It is designed to foster collaborations between land surface, hydrological, and groundwater modelling communities to develop the next-generation of land system models for integration in Earth system models.
Seyed Mahmood Hamze-Ziabari, Ulrich Lemmin, Frédéric Soulignac, Mehrshad Foroughan, and David Andrew Barry
Geosci. Model Dev., 15, 8785–8807, https://doi.org/10.5194/gmd-15-8785-2022, https://doi.org/10.5194/gmd-15-8785-2022, 2022
Short summary
Short summary
A procedure combining numerical simulations, remote sensing, and statistical analyses is developed to detect large-scale current systems in large lakes. By applying this novel procedure in Lake Geneva, strategies for detailed transect field studies of the gyres and eddies were developed. Unambiguous field evidence of 3D gyre/eddy structures in full agreement with predictions confirmed the robustness of the proposed procedure.
Kristina Šarović, Melita Burić, and Zvjezdana B. Klaić
Geosci. Model Dev., 15, 8349–8375, https://doi.org/10.5194/gmd-15-8349-2022, https://doi.org/10.5194/gmd-15-8349-2022, 2022
Short summary
Short summary
We develop a simple 1-D model for the prediction of the vertical temperature profiles in small, warm lakes. The model uses routinely measured meteorological variables as well as UVB radiation and yearly mean temperature data. It can be used for the assessment of the onset and duration of lake stratification periods when water temperature data are unavailable, which can be useful for various lake studies performed in other scientific fields, such as biology, geochemistry, and sedimentology.
Jason A. Clark, Elchin E. Jafarov, Ken D. Tape, Benjamin M. Jones, and Victor Stepanenko
Geosci. Model Dev., 15, 7421–7448, https://doi.org/10.5194/gmd-15-7421-2022, https://doi.org/10.5194/gmd-15-7421-2022, 2022
Short summary
Short summary
Lakes in the Arctic are important reservoirs of heat. Under climate warming scenarios, we expect Arctic lakes to warm the surrounding frozen ground. We simulate water temperatures in three Arctic lakes in northern Alaska over several years. Our results show that snow depth and lake ice strongly affect water temperatures during the frozen season and that more heat storage by lakes would enhance thawing of frozen ground.
Danielle S. Grogan, Shan Zuidema, Alex Prusevich, Wilfred M. Wollheim, Stanley Glidden, and Richard B. Lammers
Geosci. Model Dev., 15, 7287–7323, https://doi.org/10.5194/gmd-15-7287-2022, https://doi.org/10.5194/gmd-15-7287-2022, 2022
Short summary
Short summary
This paper describes the University of New Hampshire's water balance model (WBM). This model simulates the land surface components of the global water cycle and includes water extractions for use by humans for agricultural, domestic, and industrial purposes. A new feature is described that permits water source tracking through the water cycle, which has implications for water resource management. This paper was written to describe a long-used model and presents its first open-source version.
Luca Guillaumot, Mikhail Smilovic, Peter Burek, Jens de Bruijn, Peter Greve, Taher Kahil, and Yoshihide Wada
Geosci. Model Dev., 15, 7099–7120, https://doi.org/10.5194/gmd-15-7099-2022, https://doi.org/10.5194/gmd-15-7099-2022, 2022
Short summary
Short summary
We develop and test the first large-scale hydrological model at regional scale with a very high spatial resolution that includes a water management and groundwater flow model. This study infers the impact of surface and groundwater-based irrigation on groundwater recharge and on evapotranspiration in both irrigated and non-irrigated areas. We argue that water table recorded in boreholes can be used as validation data if water management is well implemented and spatial resolution is ≤ 100 m.
Robert Chlumsky, James R. Craig, Simon G. M. Lin, Sarah Grass, Leland Scantlebury, Genevieve Brown, and Rezgar Arabzadeh
Geosci. Model Dev., 15, 7017–7030, https://doi.org/10.5194/gmd-15-7017-2022, https://doi.org/10.5194/gmd-15-7017-2022, 2022
Short summary
Short summary
We introduce the open-source RavenR package, which has been built to support the use of the hydrologic modelling framework Raven. The R package contains many functions that may be useful in each step of the model-building process, including preparing model input files, running the model, and analyzing the outputs. We present six reproducible use cases of the RavenR package for the Liard River basin in Canada to demonstrate how it may be deployed.
Bahar Bahrami, Anke Hildebrandt, Stephan Thober, Corinna Rebmann, Rico Fischer, Luis Samaniego, Oldrich Rakovec, and Rohini Kumar
Geosci. Model Dev., 15, 6957–6984, https://doi.org/10.5194/gmd-15-6957-2022, https://doi.org/10.5194/gmd-15-6957-2022, 2022
Short summary
Short summary
Leaf area index (LAI) and gross primary productivity (GPP) are crucial components to carbon cycle, and are closely linked to water cycle in many ways. We develop a Parsimonious Canopy Model (PCM) to simulate GPP and LAI at stand scale, and show its applicability over a diverse range of deciduous broad-leaved forest biomes. With its modular structure, the PCM is able to adapt with existing data requirements, and run in either a stand-alone mode or as an interface linked to hydrologic models.
Cited articles
Ahrens, J., Geveci, B., and Law, C.: ParaView: An End-User Tool for Large
Data Visualization, in Visualization handbook, Elsevier, 2005.
Avanzi, F., Michele, C. D., Morin, S., Carmagnola, C. M., and Lejeune, Y.:
Model complexity and data requirements in snow hydrology : seeking a balance
in practical applications, Hydrol. Proc., 30, 2106–2118, https://doi.org/10.1002/hyp.10782, 2016.
Bahremand, A.: HESS Opinions: Advocating process modeling and de-emphasizing
parameter estimation, Hydrol. Earth Syst. Sci., 20, 1433–1445, https://doi.org/10.5194/hess-20-1433-2016, 2016.
Bartelt, P. and Lehning, M.: A physical SNOWPACK model for the Swiss
avalanche warning Part I: numerical model, Cold Reg. Sci.
Technol., 35, 123–145, https://doi.org/10.1016/s0165-232x(02)00074-5,
2002.
Bavay, M. and Egger, T.: MeteoIO 2.4.2: a preprocessing library for meteorological data, Geosci. Model Dev., 7, 3135–3151, https://doi.org/10.5194/gmd-7-3135-2014, 2014.
Bentley, J. L.: Multidimensional binary search trees used for associative
searching, Commun. ACM, 18, 509–517, https://doi.org/10.1145/361002.361007, 1975.
Bernhardt, M. and Schulz, K.: SnowSlide: A simple routine for calculating
gravitational snow transport, Geophys. Res. Lett., 37, 1–6,
https://doi.org/10.1029/2010gl043086, 2010.
Beven, K.: Changing ideas in hydrology – The case of physically-based
models, J. Hydrol., 105, 157–172, https://doi.org/10.1016/0022-1694(89)90101-7, 1989.
Beven, K.: Prophecy, reality and uncertainty in distributed hydrological
modelling, Adv. Water Resour., 16, 41–51, https://doi.org/10.1016/0309-1708(93)90028-e, 1993.
Beven, K.: A manifesto for the equifinality thesis, Water Resour.
Res., 320, 18–36, https://doi.org/10.1016/j.jhydrol.2005.07.007, 2006.
Beven, K. and Westerberg, I.: On red herrings and real herrings:
Disinformation and information in hydrological inference, Hydrol.
Proc., 25, 1676–1680, https://doi.org/10.1002/hyp.7963, 2011.
Binley, A., Elgy, J., and Beven, K.: A physically based model of
heterogeneous hillslopes: 1. Runoff production, Water Resour. Res.,
25, 1219–1226, https://doi.org/10.1029/wr025i006p01219, 1989.
Blöschl, G. and Sivapalan, M.: Scale issues in hydrological modelling: A
review, Hydrol. Proc., 9, 251–290, https://doi.org/10.1002/hyp.3360090305, 1995.
Bowling, L. C., Pomeroy, J. W., and Lettenmaier, D. P.: Parameterization of
Blowing-Snow Sublimation in a Macroscale Hydrology Model, J.
Hydrometeorol., 5, 745–762, https://doi.org/10.1175/1525-7541(2004)005<0745:pobsia>2.0.co;2,
2004.
Braun, J. and Sambridge, M.: Modelling landscape evolution on geological
time scales: a new method based on irregular spatial discretization, Basin
Res., 9, 27–52, https://doi.org/10.1046/j.1365-2117.1997.00030.x,
1997.
Brigode, P., Oudin, L., and Perrin, C.: Hydrological model parameter
instability: A source of additional uncertainty in estimating the
hydrological impacts of climate change?, Water Resour. Res., 476,
410–425, https://doi.org/10.1016/j.jhydrol.2012.11.012, 2013.
Bring, A., Fedorova, I., Dibike, Y., Hinzman, L., Mård, J., Mernild, S.
H., Prowse, T., Semenova, O., Stuefer, S. L., and Woo, M.: Arctic terrestrial
hydrology: A synthesis of processes, regional effects, and research
challenges, J. Geophys. Res.-Biogeo., 121, 621–649,
https://doi.org/10.1002/2015jg003131, 2016.
Burridge, D. M. and Gadd, A. J.: The Meteorological Office Operational
10-level Numerical Weather Prediction Model, Scientific paper –
Meteorological Office, (34), 39 pp., 1975.
Bühler, Y., Adams, M. S., Bösch, R., and Stoffel, A.: Mapping snow depth in alpine terrain with unmanned aerial systems (UASs): potential and limitations, The Cryosphere, 10, 1075–1088, https://doi.org/10.5194/tc-10-1075-2016, 2016.
Carey, S. K. and Woo, M.-k.: Snowmelt Hydrology of Two Subarctic Slopes,
Southern Yukon, CanadaPaper Presented at the 11th Northern Res. Basins
Symposium/Workshop (Prudhoe Bay to Fairbanks, Alaska, USA, 18–22 August 1997), Hydrol. Res., 29, 331–346, https://doi.org/10.2166/nh.1998.0022, 1998.
Chang, K.-T.: Introduction to Geographic Information Systems, McGraw-Hill,
New York, New York, 2008.
Cherkauer, K. a, Bowling, L. C., and Lettenmaier, D. P.: Variable
infiltration capacity cold land process model updates, Global Planet.
Change, 38, 151–159, https://doi.org/10.1016/s0921-8181(03)00025-0, 2003.
Clark, M. P., Slater, A. G., Rupp, D. E., Woods, R. A., Vrugt, J. A., Gupta,
H. V., Wagener, T., and Hay, L. E.: Framework for Understanding Structural
Errors (FUSE): A modular framework to diagnose differences between
hydrological models, Water Resour. Res., 44, 1–14, https://doi.org/10.1029/2007wr006735, 2008.
Clark, M. P., Kavetski, D., and Fenicia, F.: Pursuing the method of multiple
working hypotheses for hydrological modeling, Water Resour. Res., 47, W09301,
https://doi.org/10.1029/2010wr009827, 2011.
Clark, M. P., Nijssen, B., Lundquist, J. D., Kavetski, D., Rupp, D. E.,
Woods, R. A., Freer, J. E., Gutmann, E. D., Wood, A. W., Brekke, L. D.,
Arnold, J. R., Gochis, D. J., and Rasmussen, R. M.: A unified approach for
process-based hydrologic modeling: 1. Modeling concept, Water Resour.
Res., 51, 2498–2514, https://doi.org/10.1002/2015wr017198, 2015.
Clark, M. P., Bierkens, M. F. P., Samaniego, L., Woods, R. A., Uijlenhoet, R., Bennett, K. E., Pauwels, V. R. N., Cai, X., Wood, A. W., and Peters-Lidard, C. D.: The evolution of process-based hydrologic models: historical challenges and the collective quest for physical realism, Hydrol. Earth Syst. Sci., 21, 3427–3440, https://doi.org/10.5194/hess-21-3427-2017, 2017.
Corripio, J. G.: Snow surface albedo estimation using terrestrial
photography, Int. J. Remote Sens., 25, 5705–5729,
https://doi.org/10.1080/01431160410001709002, 2004.
Cullen, R. M. and Marshall, S. J.: Mesoscale Temperature Patterns in the
Rocky Mountains and Foothills Region of Southern Alberta, Atmos.-Ocean,
49, 189–205, https://doi.org/10.1080/07055900.2011.592130, 2011.
Das, T., Bárdossy, A., Zehe, E., and He, Y.: Comparison of conceptual
model performance using different representations of spatial variability,
Water Resour. Res., 356, 106–118, https://doi.org/10.1016/j.jhydrol.2008.04.008, 2008.
Davies, T. D., Brimblecombe, P., Tranter, M., Tsiouris, S., Vincent, C. E.,
Abrahams, P., and Blackwood, I. L.: Seasonal Snowcovers: Physics, Chemistry,
Hydrology, D. Reidel Publishing Company, 1987.
DeBeer, C. M. and Pomeroy, J. W.: Modelling snow melt and snowcover
depletion in a small alpine cirque, Canadian Rocky Mountains, Hydrol.
Proc., 23, 2584–2599, https://doi.org/10.1002/hyp.7346, 2009.
DeBeer, C. M., Wheater, H. S., Quinton, W. L., Carey, S. K., Stewart, R. E.,
MacKay, M. D., and Marsh, P.: The Changing Cold Regions Network: Observation,
diagnosis and prediction of environmental change in the Saskatchewan and
Mackenzie River Basins, Canada, Science China Earth Sciences, 58, 46–60,
https://doi.org/10.1007/s11430-014-5001-6, 2015.
Dodson, R. and Marks, D.: Daily air temperature interpolated at high spatial
resolution over a large mountainous region, Climate Res., 8, 1–20,
https://doi.org/10.3354/cr008001, 1997.
Dornes, P., Pomeroy, J. W., Pietroniro, A., and Verseghy, D. L.: Effects of
Spatial Aggregation of Initial Conditions and Forcing Data on Modeling
Snowmelt Using a Land Surface Scheme, J. Hydrometeorol., 9,
789–803, https://doi.org/10.1175/2007jhm958.1, 2008a.
Dornes, P. F., Pomeroy, J. W., Pietroniro, A., Carey, S. K., and Quinton, W.
L.: Influence of landscape aggregation in modelling snow-cover ablation and
snowmelt runoff in a sub-arctic mountainous environment, Hydrol.
Sci. J., 53, 725–740, https://doi.org/10.1623/hysj.53.4.725,
2008b.
Dozier, J. and Frew, J.: Rapid calculation of terrain parameters for
radiation modeling from digital elevation data, IEEE T.
Geosci. Remote, 28, 963–969, https://doi.org/10.1109/36.58986, 1990.
Duarte, C. M., Lenton, T. M., Wadhams, P., and Wassmann, P.: Abrupt climate
change in the Arctic, Nat. Clim. Change, 2, 60–62, https://doi.org/10.1038/nclimate1386, 2012.
Ellis, C. R., Pomeroy, J. W., Brown, T., and MacDonald, J.: Simulation of snow accumulation and melt in needleleaf forest environments, Hydrol. Earth Syst. Sci., 14, 925–940, https://doi.org/10.5194/hess-14-925-2010, 2010.
Ellis, C. R. and Pomeroy, J. W.: Estimating sub-canopy shortwave irradiance
to melting snow on forested slopes, Hydrol. Proc., 21, 2581–2593,
https://doi.org/10.1002/hyp.6794, 2007.
Endrizzi, S., Gruber, S., Dall'Amico, M., and Rigon, R.: GEOtop 2.0: simulating the combined energy and water balance at and below the land surface accounting for soil freezing, snow cover and terrain effects, Geosci. Model Dev., 7, 2831–2857, https://doi.org/10.5194/gmd-7-2831-2014, 2014.
Essery, R.: A factorial snowpack model (FSM 1.0), Geosci. Model Dev., 8, 3867–3876, https://doi.org/10.5194/gmd-8-3867-2015, 2015.
Essery, R., Li, L. and Pomeroy, J.: A distributed model of blowing snow over
complex terrain, Hydrol. Proc., 13, 2423–2438, https://doi.org/10.1002/(SICI)1099-1085(199910)13:14/15<2423::AID-HYP853>3.0.CO;2-U, 1999.
Essery, R., Rutter, N., Pomeroy, J., Baxter, R., Gustafsson, D., Barr, A.,
Bartlett, P., Elder, E., and Stahli, M.: SNOWMIP2: An evaluation of forest
snow process simulations, B. Am. Meteorol. Soc.,
90, 1120–1135, https://doi.org/10.1175/2009bams2629.1, 2009.
Essery, R., Morin, S., Lejeune, Y., and Ménard, C. B.: A comparison of
1701 snow models using observations from an alpine site, Adv. Water
Resour., 55, 131–148, https://doi.org/10.1016/j.advwatres.2012.07.013,
2013.
Etchevers, P., Martin, E., Brown, R., Fierz, C., Lejeune, Y., Bazile, E.,
Boone, A., Dai, Y.-J., Essery, R., Fernandez, A., Gusev, Y., Jordan, R.,
Koren, V., Kowalczyk, E., Nasonova, N. O., Pyles, R. D., Schlosser, A.,
Shmakin, A. B., Smirnova, T. G., Strasser, U., Verseghy, D., Yamazaki, T.,
and Yang, Z.-L.: Validation of the energy budget of an alpine snowpack
simulated by several snow models (SnowMIP project), Ann. Glaciol.,
38, 150–158, https://doi.org/10.3189/172756404781814825, 2004.
Fang, X., Pomeroy, J. W., Ellis, C. R., MacDonald, M. K., DeBeer, C. M., and Brown, T.: Multi-variable evaluation of hydrological model predictions for a headwater basin in the Canadian Rocky Mountains, Hydrol. Earth Syst. Sci., 17, 1635–1659, https://doi.org/10.5194/hess-17-1635-2013, 2013.
Fang, X., Pomeroy, J. W., DeBeer, C. M., Harder, P., and Siemens, E.: Hydrometeorological data from Marmot Creek Research Basin, Canadian Rockies, Earth Syst. Sci. Data, 11, 455–471, https://doi.org/10.5194/essd-11-455-2019, 2019.
Fatichi, S., Vivoni, E. R., Ogden, F. L., Ivanov, V. Y., Mirus, B., Gochis,
D., Downer, C. W., Camporese, M., Davison, J. H., Ebel, B., Jones, N., Kim,
J., Mascaro, G., Niswonger, R., Restrepo, P., Rigon, R., Shen, C., Sulis, M.,
and Tarboton, D.: An overview of current applications, challenges, and
future trends in distributed process-based models in hydrology, J. Hydrol.,
537, 45–60, https://doi.org/10.1016/j.jhydrol.2016.03.026, 2016.
Fenicia, F., Kavetski, D., and Savenije, H. H. G.: Elements of a flexible
approach for conceptual hydrological modeling: 1. Motivation and theoretical
development, Water Resour. Res., 47, 1–13, https://doi.org/10.1029/2010wr010174, 2011.
Fiddes, J. and Gruber, S.: TopoSCALE v.1.0: downscaling gridded climate data in complex terrain, Geosci. Model Dev., 7, 387–405, https://doi.org/10.5194/gmd-7-387-2014, 2014.
Freeze, R. A.: Streamflow generation, Rev. Geophys., 12, 627–647,
https://doi.org/10.1029/rg012i004p00627, 1974.
Freeze, R. A. and Harlan, R. L.: Blueprint for a physically-based,
digitally-simulated hydrologic response model, J. Hydrol., 9,
237–258, https://doi.org/10.1016/0022-1694(69)90020-1, 1969.
Fu, P. and Rich, P. M.: Design and implementation of the Solar Analyst: an
ArcView extension for modeling solar radiation at landscape scales, in
Proceedings of the 19th Annual ESRI User Conference, San Diego,
USA, 1–33, 1999.
Gelfan, A. N., Pomeroy, J. W., and Kuchment, L. S.: Modeling Forest Cover
Influences on Snow Accumulation, Sublimation, and Melt, J.
Hydrometeorol., 5, 785–803, https://doi.org/10.1175/1525-7541(2004)005<0785:mfcios>2.0.co;2,
2004.
Golding, D. L.: Research results from Marmot Creek experimental watershed,
Alberta, Canada, in IASH Unesco – Symposium on the results of
research on representative and experimental basins,
Wellington, New Zealand, 397–404, 1970.
Gray, D. M. and Male, D. H.: Handbook of Snow: Principles, Processes,
Management, and Use, Pergamon Press, 1981.
Gray, D. M., Toth, B., Zhao, L., Pomeroy, J. W., and Granger, R. J.:
Estimating areal snowmelt infiltration into frozen soils, Hydrol. Proc., 15, 3095–3111, https://doi.org/10.1002/hyp.320, 2001.
Hagen, S. C., Horstmann, O., and Bennett, R. J.: An Unstructured Mesh
Generation Algorithm for Shallow Water Modeling, Int. J. Comput. Fluid. D, 16, 83–91, https://doi.org/10.1080/10618560290017176, 2002.
Harder, P. and Pomeroy, J.: Estimating precipitation phase using a
psychrometric energy balance method, Hydrol. Proc., 27, 1901–1914,
https://doi.org/10.1002/hyp.9799, 2013.
Harder, P., Schirmer, M., Pomeroy, J., and Helgason, W.: Accuracy of snow depth estimation in mountain and prairie environments by an unmanned aerial vehicle, The Cryosphere, 10, 2559–2571, https://doi.org/10.5194/tc-10-2559-2016, 2016.
Harder, P., Pomeroy, J. W., and Helgason, W. D.: A simple model for local-scale sensible and latent heat advection contributions to snowmelt, Hydrol. Earth Syst. Sci., 23, 1–17, https://doi.org/10.5194/hess-23-1-2019, 2019.
Hedstrom, N. R. and Pomeroy, J. W.: Measurements and modelling of snow
interception in the boreal forest, Hydrol. Proc., 12, 1611–1625,
https://doi.org/10.1002/(sici)1099-1085(199808/09)12:10/11<1611::aid-hyp684>3.0.co;2-4, 1998.
Hopkinson, C., Crasto, N., Marsh, P., Forbes, D., and Lesack, L.:
Investigating the spatial distribution of water levels in the Mackenzie
Delta using airborne LiDAR, Hydrol. Proc., 25, 2995–3011,
https://doi.org/10.1002/hyp.8167, 2011.
Hopp, L., Fatichi, S., and Ivanov, V. Y.: Simulating water flow in variably
saturated soils: a comparison of a 3-D model with approximation-based
formulations, Hydrol. Res., 47, 274–290, https://doi.org/10.2166/nh.2015.126,
2016.
Horne, F. E. and Kavvas, M. L.: Physics of the spatially averaged snowmelt
process, J. Hydrol., 191, 179–207, https://doi.org/10.1016/s0022-1694(96)03063-6, 1997.
Hrachowitz, M. and Clark, M. P.: HESS Opinions: The complementary merits of competing modelling philosophies in hydrology, Hydrol. Earth Syst. Sci., 21, 3953–3973, https://doi.org/10.5194/hess-21-3953-2017, 2017.
Hubbard, S. S., Gangodagamage, C., Dafflon, B., Wainwright, H., Peterson,
J., Gusmeroli, A., Ulrich, C., Wu, Y., Wilson, C., Rowland, J., Tweedie, C.,
and Wullschleger, S. D.: Quantifying and relating land-surface and
subsurface variability in permafrost environments using LiDAR and surface
geophysical datasets, Hydrogeol. J., 21, 149–169, https://doi.org/10.1007/s10040-012-0939-y, 2013.
Iqbal, M.: Prediction of hourly diffuse solar radiation from measured hourly
global radiation on a horizontal surface, Solar Energy, 24, 491–503,
https://doi.org/10.1016/0038-092x(80)90317-5, 1980.
Ivanov, V., Vivoni, E., Bras, R., and Entekhabi, D.: Preserving
high-resolution surface and rainfall data in operational-scale basin
hydrology: a fully-distributed physically-based approach, Water Resour.
Res., 298, 80–111, https://doi.org/10.1016/j.jhydrol.2004.03.041,
2004.
Jones, E., Oliphant, T. and Peterson, P.: SciPy: Open Source Scientific
Tools for Python, availablet at: https://www.scipy.org/citing.html (last access: 8 November 2019), 2018.
Jordan, R.: A one-dimensional temperature model for a snow cover, Technical
documentation for SNTHERM.89, 1991.
Klemeš, V.: Conceptualization and scale in hydrology, J. Hydrol., 65, 1–23, https://doi.org/10.1016/0022-1694(83)90208-1, 1983.
Kuchment, L. and Gelfan, A.: Physicomathematical model of snow accumulation
and melt in a forest, Russ. Meteorol. Hydrol., 57–65, 2004.
Kumar, M., Duffy, C. J., and Salvage, K. M.: A Second-Order Accurate, Finite
Volume–Based, Integrated Hydrologic Modeling (FIHM) Framework for
Simulation of Surface and Subsurface Flow, Vadose Z. J., 8, 873–890,
https://doi.org/10.2136/vzj2009.0014, 2009.
Kumar, M., Marks, D., Dozier, J., Reba, M., and Winstral, A.: Evaluation of
distributed hydrologic impacts of temperature-index and energy-based snow
models, Adv. Water Resour., 56, 77–89, https://doi.org/10.1016/j.advwatres.2013.03.006, 2013.
Kunkel, K. E.: Simple procedures for extrapolation of humidity variables in
the mountainous western United States, J. Climate, 2, 656–669,
1989.
Lafaysse, M., Cluzet, B., Dumont, M., Lejeune, Y., Vionnet, V., and Morin, S.: A multiphysical ensemble system of numerical snow modelling, The Cryosphere, 11, 1173–1198, https://doi.org/10.5194/tc-11-1173-2017, 2017.
Latifovic, R. and Pouliot, D.: Analysis of climate change impacts on lake
ice phenology in Canada using the historical satellite data record, Remote
Sens. Environ., 106, 492–507, https://doi.org/10.1016/j.rse.2006.09.015, 2007.
Leavesley, G. H., Markstrom, S. L., Restrepo, P. J., and Viger, R. J.: A
modular approach to addressing model design, scale, and parameter estimation
issues in distributed hydrological modelling, Hydrol. Proc., 16,
173–187, https://doi.org/10.1002/hyp.344, 2002.
Lehning, M., Bartelt, P., Brown, B., Fierz, C., and Satyawali, P.: A physical
SNOWPACK model for the Swiss avalanche warning Part II. Snow microstructure,
Cold Reg. Sci. Technol., 35, 147–167, https://doi.org/10.1016/s0165-232x(02)00073-3, 2002.
Lehning, M., Völksch, I., Gustafsson, D., Nguyen, T. A., Stähli, M.,
and Zappa, M.: ALPINE3-D: a detailed model of mountain surface processes and
its application to snow hydrology, Hydrol. Proc., 20, 2111–2128,
https://doi.org/10.1002/hyp.6204, 2006.
Lehning, M., Löwe, H., Ryser, M., and Raderschall, N.: Inhomogeneous
precipitation distribution and snow transport in steep terrain, Water
Resour. Res., 44, W07404, https://doi.org/10.1029/2007wr006545, 2008.
Leroux, N. R. and Pomeroy, J. W.: Modelling capillary hysteresis effects on
preferential flow through melting and cold layered snowpacks, Adv.
Water Resour., 107, 250–264, https://doi.org/10.1016/j.advwatres.2017.06.024, 2017.
Li, L. and Pomeroy, J. W.: Estimates of Threshold Wind Speeds for Snow
Transport Using Meteorological Data, J. Appl. Meteorol., 36,
205–213, https://doi.org/10.1175/1520-0450(1997)036<0205:eotwsf>2.0.co;2, 1997.
Liston, G. E. and Elder, K.: A Meteorological Distribution System for
High-Resolution Terrestrial Modeling (MicroMet), J.
Hydrometeorol., 7, 217–234, https://doi.org/10.1175/jhm486.1, 2006.
Lundberg, A., Ala-Aho, P., Eklo, O., Klöve, B., Kværner, J., and
Stumpp, C.: Snow and frost: implications for spatiotemporal infiltration
patterns – a review, Hydrol. Proc., 30, 1230–1250, https://doi.org/10.1002/hyp.10703, 2016.
MacDonald, M. K., Pomeroy, J. W., and Pietroniro, A.: Parameterizing
redistribution and sublimation of blowing snow for hydrological models:
tests in a mountainous subarctic catchment, Hydrol. Proc., 23,
2570–2583, https://doi.org/10.1002/hyp.7356, 2009.
Marks, D., Dozier, J., and Davis, R. E.: Climate and energy exchange at the
snow surface in the Alpine Region of the Sierra Nevada: 1. Meteorological
measurements and monitoring, Water Resour. Res., 28, 3029–3042,
https://doi.org/10.1029/92wr01482, 1992.
Marks, D., Kimball, J., Tingey, D., and Link, T.: The sensitivity of snowmelt
processes to climate conditions and forest cover during rain-on-snow: a case
study of the 1996 Pacific Northwest flood, Hydrol. Proc., 12,
1569–1587, 1998.
Marks, D., Domingo, J., Susong, D., Link, T., and Garen, D.: A spatially
distributed energy balance snowmelt model for application in mountain
basins, Hydrol. Proc., 13, 1935–1959, https://doi.org/10.1002/(sici)1099-1085(199909)13:12/13<1935::aid-hyp868> 3.0.co;2-c, 1999.
Marks, D., Winstral, A., Reba, M., Pomeroy, J., and Kumar, M.: An evaluation
of methods for determining during-storm precipitation phase and the
rain/snow transition elevation at the surface in a mountain basin, Adv. Water Resour., 55, 98–110, https://doi.org/10.1016/j.advwatres.2012.11.012, 2013.
Marsh, C. B., Pomeroy, J. W., and Spiteri, R. J.: Implications of mountain
shading on calculating energy for snowmelt using unstructured triangular
meshes, Hydrol. Proc., 26, 1767–1778, https://doi.org/10.1002/hyp.9329, 2012.
Marsh, C. B., Spiteri, R. J., Pomeroy, J. W., and Wheater, H. S.:
Multi-objective unstructured triangular mesh generation for use in
hydrological and land surface models, Comput. Geosci., 119,
49–67, https://doi.org/10.1016/j.cageo.2018.06.009, 2018.
Marsh, C. B., Pomeroy, J. W., Spiteri, R. J., and Wheater, H. S.: A finite
volume blowing snow model for use with variable resolution meshes, Water
Resour. Res., 55, e24400, https://doi.org/10.1029/2019WR025307, 2020.
Marty, C., Philipona, R., Fröhlich, C., and Ohmura, A.: Altitude
dependence of surface radiation fluxes and cloud forcing in the alps:
results from the alpine surface radiation budget network, Theor. Appl. Climatol., 72, 137–155, https://doi.org/10.1007/s007040200019,
2002.
Mason, P. and Sykes, R.: Flow over an isolated hill of moderate slope,
Q. J. Roy. Meteor. Soc., 105, 383–395,
https://doi.org/10.1002/qj.49710544405, 1979.
Maxwell, R. M. and Kollet, S. J.: Interdependence of groundwater dynamics
and land-energy feedbacks under climate change, Nat. Geosci., 1,
665–669, https://doi.org/10.1038/ngeo315, 2008.
McCauley, C. A., White, D. M., Lilly, M. R., and Nyman, D. M.: A comparison
of hydraulic conductivities, permeabilities and infiltration rates in frozen
and unfrozen soils, Cold Reg. Sci. Technol., 34, 117–125,
https://doi.org/10.1016/s0165-232x(01)00064-7, 2002.
Mendoza, P. A., Clark, M. P., Barlage, M., Rajagopalan, B., Samaniego, L.,
Abramowitz, G., and Gupta, H.: Are we unnecessarily constraining the agility
of complex process-based models?, Water Resour. Res., 51, 716–728,
https://doi.org/10.1002/2014wr015820, 2015.
Michlmayr, G., Lehning, M., Koboltschnig, G., Holzmann, H., Zappa, M., Mott,
R., and Schöner, W.: Application of the Alpine 3-D model for glacier mass
balance and glacier runoff studies at Goldbergkees, Austria, Hydrol. Proc., 22, 3941–3949, https://doi.org/10.1002/hyp.7102, 2008.
Milly, P. C. D., Betancourt, J., Falkenmark, M., Hirsch, R. M., Kundzewicz,
Z., Lettenmaier, D. P., and Stouffer, R. J.: Stationarity Is Dead: Whither
Water Management?, Science, 319, 573–574, 2008.
Mohanty, B. P.: Soil Hydraulic Property Estimation Using Remote Sensing: A
Review, Vadose Z. J., 12, https://doi.org/10.2136/vzj2013.06.0100, 2013.
Mosier, T. M., Hill, D. F., and Sharp, K. V.: How much cryosphere model complexity is just right? Exploration using the conceptual cryosphere hydrology framework, The Cryosphere, 10, 2147–2171, https://doi.org/10.5194/tc-10-2147-2016, 2016.
Mote, P. W., Hamlet, A. F., Clark, M. P., and Lettenmaier, D. P.: Declining
Mountain Snowpack in Western North America, B. Am. Meteorol. Soc., 86, 39–49, https://doi.org/10.1175/bams-86-1-39,
2005.
Mott, R., Schirmer, M., Bavay, M., Grünewald, T., and Lehning, M.: Understanding snow-transport processes shaping the mountain snow-cover, The Cryosphere, 4, 545–559, https://doi.org/10.5194/tc-4-545-2010, 2010.
Mott, R., Gromke, C., Grünewald, T., and Lehning, M.: Relative importance
of advective heat transport and boundary layer decoupling in the melt
dynamics of a patchy snow cover, Adv. Water Resour., 55, 88–97,
https://doi.org/10.1016/j.advwatres.2012.03.001, 2013.
Munro, D. S. and Young, G. J.: An operational net shortwave radiation model
for glacier basins, Water Resour. Res., 18, 220–230, https://doi.org/10.1029/wr018i002p00220, 1982.
Musselman, K. N., Pomeroy, J. W., and Link, T. E.: Variability in shortwave
irradiance caused by forest gaps: Measurements, modelling, and implications
for snow energetics, Agr. Forest Meteorol., 207, 69–82,
https://doi.org/10.1016/j.agrformet.2015.03.014, 2015.
Musselman, K. N., Clark, M. P., Liu, C., Ikeda, K., and Rasmussen, R.: Slower
snowmelt in a warmer world, Nat. Clim. Change, 7, 214–219,
https://doi.org/10.1038/nclimate3225, 2017.
Nazemi, A., Wheater, H. S., Chun, K. P., and Elshorbagy, A.: A stochastic
reconstruction framework for analysis of water resource system vulnerability
to climate-induced changes in river flow regime, Water Resour. Res.,
49, 291–305, https://doi.org/10.1029/2012wr012755, 2013.
O'Callaghan, J. F. and Mark, D. M.: The extraction of drainage networks from
digital elevation data, Comput. Vision Graph., 28,
323–344, https://doi.org/10.1016/s0734-189x(84)80011-0, 1984.
Oliphant, T. E.: A guide to NumPy, Trelgol Publishing, USA, 2006.
Olyphant, G. A.: Longwave Radiation in Mountainous Areas and Its Influence
on the Energy Balance of Alpine Snowfields, Water Resour. Res., 22,
62–66, https://doi.org/10.1029/wr022i001p00062, 1986.
Or, D., Lehmann, P., and Assouline, S.: Natural length scales define the
range of applicability of the Richards equation for capillary flows, Water
Resour. Res., 51, 7130–7144, https://doi.org/10.1002/2015wr017034,
2015.
Painter, S. L., Coon, E. T., Atchley, A. L., Berndt, M., Garimella, R.,
Moulton, J. D., Svyatskiy, D., and Wilson, C. J.: Integrated
surface/subsurface permafrost thermal hydrology: Model formulation and
proof-of-concept simulations, Water Resour. Res., 52, 6062–6077,
https://doi.org/10.1002/2015wr018427, 2016.
Paniconi, C. and Putti, M.: Physically based modeling in catchment hydrology
at 50: Survey and outlook, Water Resour. Res., 51, 7090–7129,
https://doi.org/10.1002/2015wr017780, 2015.
Perrin, C., Michel, C., and Andréassian, V.: Does a large number of
parameters enhance model performance? Comparative assessment of common
catchment model structures on 429 catchments, J. Hydrol., 242,
275–301, https://doi.org/10.1016/s0022-1694(00)00393-0, 2001.
Pietroniro, A., Fortin, V., Kouwen, N., Neal, C., Turcotte, R., Davison, B., Verseghy, D., Soulis, E. D., Caldwell, R., Evora, N., and Pellerin, P.: Development of the MESH modelling system for hydrological ensemble forecasting of the Laurentian Great Lakes at the regional scale, Hydrol. Earth Syst. Sci., 11, 1279–1294, https://doi.org/10.5194/hess-11-1279-2007, 2007.
Pomeroy, J. and Bernhardt, M.: Project Report for the 2017 GEWEX GHP
Meeting, Kathmandu, Nepal, 2017.
Pomeroy, J. W. and Gray, D. M.: Saltation of snow, Water Resour. Res.,
26, 1583–1594, https://doi.org/10.1029/wr026i007p01583, 1990.
Pomeroy, J. W. and Li, L.: Prairie and arctic areal snow cover mass balance
using a blowing snow model, J. Geophys. Res.-Atmos.,
105, 26619–26634, https://doi.org/10.1029/2000jd900149, 2000.
Pomeroy, J. W. and Male, D. H.: Steady-state suspension of snow, J. Hydrol., 136, 275–301, https://doi.org/10.1016/0022-1694(92)90015-n,
1992.
Pomeroy, J. W., Gray, D. M., and Landine, P. G.: The Prairie Blowing Snow
Model: characteristics, validation, operation, J. Hydrol., 144,
165–192, https://doi.org/10.1016/0022-1694(93)90171-5, 1993.
Pomeroy, J. W., Gray, D. M., Shook, K. R., Toth, B., Essery, R.,
Pietroniro, A., and Hedstrom, N.: An evaluation of snow accumulation and
ablation processes for land surface modelling, Hydrol. Proc., 12,
2339–2367, https://doi.org/10.1002/(SICI)1099-1085(199812)12:15<2339::AID-HYP800>3.0.CO;2-L, 1998a.
Pomeroy, J. W., Parviainen, J., Hedstrom, N., and Gray, D. M.: Coupled
modelling of forest snow interception and sublimation, Hydrol. Proc., 12, 2317–2337, https://doi.org/10.1002/(sici)1099-1085(199812)12:15<2317::aid-hyp799>3.0.co;2-x, 1998b.
Pomeroy, J. W., Toth, B., Granger, R. J., Hedstrom, N. R., and Essery, R. L.
H.: Variation in surface energetics during snowmelt in a subarctic mountain
catchment, J. Hydrometeorol., 4, 702–719, https://doi.org/10.1175/1525-7541(2003)004<0702:viseds>2.0.co;2,
2003.
Pomeroy, J. W., Granger, R. J., Hedstrom, N. R., Gray, D. M., Elliott, J.,
Pietroniro, A., and Janowicz, J. R.: The Process Hydrology Approach to
Improving Prediction of Ungauged Basins in Canada, in Prediction in Ungauged
Basins: Approaches for Canada's Cold Regions, Environment
Canada, 67–100, 2004.
Pomeroy, J. W., Gray, D. M., Brown, T., Hedstrom, N. R., Quinton, W. L.,
Granger, R. J., and Carey, S. K.: The cold regions hydrological model: a
platform for basing process representation and model structure on physical
evidence, Hydrol. Proc., 21, 2650–2667, https://doi.org/10.1002/hyp.6787, 2007.
Pomeroy, J. W., Marks, D., Link, T., Ellis, C., Hardy, J., Rowlands, A., and
Granger, R.: The impact of coniferous forest temperature on incoming
longwave radiation to melting snow, Hydrol. Proc., 23, 2513–2525,
https://doi.org/10.1002/hyp.7325, 2009.
Pomeroy, J., Fang, X., and Ellis, C.: Sensitivity of snowmelt hydrology in
Marmot Creek, Alberta, to forest cover disturbance, Hydrol. Proc.,
26, 1891–1904, https://doi.org/10.1002/hyp.9248, 2012.
Pomeroy, J. W., Fang, X., Shook, K., and Whitfield, P. H.: Predicting in
ungauged basins using physical principles obtained using the deductive,
inductive, and abdyctive reasoning approach, in: Putting prediction in
ungauged basins into practice, Canadian Water Resources
Association, 41–62, 2013.
Qu, Y. and Duffy, C. J.: A semidiscrete finite volume formulation for
multiprocess watershed simulation, Water Resour. Res., 43, 1–18,
https://doi.org/10.1029/2006wr005752, 2007.
Raderschall, N., Lehning, M., and Schär, C.: Fine-scale modeling of the
boundary layer wind field over steep topography, Water Resour. Res.,
44, 1–18, https://doi.org/10.1029/2007wr006544, 2008.
Raleigh, M. S., Livneh, B., Lapo, K., and Lundquist, J. D.: How does
availability of meteorological forcing data impact physically-based snowpack
simulations?, J. Hydrometeorol., 99–120, https://doi.org/10.1175/jhm-d-14-0235.1, 2015.
Rasouli, K., Pomeroy, J. W., and Marks, D. G.: Snowpack sensitivity to
perturbed climate in a cool mid-latitude mountain catchment, Hydrol. Proc., 29, 3925–3940, https://doi.org/10.1002/hyp.10587, 2015.
Razavi, S. and Gupta, H. V.: A new framework for comprehensive, robust, and
efficient global sensitivity analysis: 1. Theory, Water Resour. Res.,
52, 423–439, https://doi.org/10.1002/2015wr017558, 2016.
Rew, R. and Davis, G.: NetCDF: An Interface for Scientific Data Access, IEEE
Comput. Graph., 10, 76–82, https://doi.org/10.1109/38.56302, 1990.
Rothwell, R., Hillman, G., and Pomeroy, J. W.: Marmot Creek Experimental
Watershed Study, Forestry Chron., 92, 32–36, https://doi.org/10.5558/tfc2016-010, 2016.
Rouse, W. R., Oswald, C. J., Binyamin, J., Spence, C., Schertzer, W. M.,
Blanken, P. D., Bussières, N., and Duguay, C. R.: The Role of Northern
Lakes in a Regional Energy Balance, J. Hydrometeorol., 6,
291–305, https://doi.org/10.1175/jhm421.1, 2005.
Samaniego, L., Kumar, R., Thober, S., Rakovec, O., Zink, M., Wanders, N., Eisner, S., Müller Schmied, H., Sutanudjaja, E. H., Warrach-Sagi, K., and Attinger, S.: Toward seamless hydrologic predictions across spatial scales, Hydrol. Earth Syst. Sci., 21, 4323–4346, https://doi.org/10.5194/hess-21-4323-2017, 2017.
Savenije, H. H. G.: HESS Opinions “The art of hydrology”, Hydrol. Earth Syst. Sci., 13, 157–161, https://doi.org/10.5194/hess-13-157-2009, 2009.
Schlögl, S., Lehning, M., Fierz, C., and Mott, R.: Representation of
Horizontal Transport Processes in Snowmelt Modeling by Applying a Footprint
Approach, Front. Earth Sci., 6, 120, https://doi.org/10.3389/feart.2018.00120, 2018.
Schroeder, W., Martin, K. and Lorensen, B.: The Visualization Toolkit, 4th
edn., Kitware, 2006.
Shewchuk, J.: Triangle: engineering a 2D quality mesh generator and Delaunay
triangulator, in Applied computational geometry towards geometric
engineering, Springer Berlin/Heidelberg, 203–222, 1996.
Shook, K. and Gray, D. M.: Small-scale Spatial Structure Of Shallow
Snowcovers, Hydrol. Proc., 10, 1283–1292, https://doi.org/10.1002/(sici)1099-1085(199610)10:10<1283::aid-hyp460>3.0.co;2-m, 1996.
Shook, K., Pomeroy, J., and van der Kamp, G.: The transformation of frequency
distributions of winter precipitation to spring streamflow probabilities in
cold regions; case studies from the Canadian Prairies, J. Hydrol.,
521, 395–409, https://doi.org/10.1016/j.jhydrol.2014.12.014, 2015.
Sicart, J. E., Pomeroy, J. W., Essery, R. L. H., and Bewley, D.: Incoming
longwave radiation to melting snow: observations, sensitivity and estimation
in Northern environments, Hydrol. Proc., 20, 3697–3708,
https://doi.org/10.1002/hyp.6383, 2006.
Sivapalan, M.: From engineering hydrology to Earth system science: milestones in the transformation of hydrologic science, Hydrol. Earth Syst. Sci., 22, 1665–1693, https://doi.org/10.5194/hess-22-1665-2018, 2018.
Slater, A. G., Barrett, A. P., Clark, M. P., Lundquist, J. D., and Raleigh,
M. S.: Uncertainty in seasonal snow reconstruction: Relative impacts of
model forcing and image availability, Adv. Water Resour., 55,
165–177, https://doi.org/10.1016/j.advwatres.2012.07.006, 2013.
Smith, C. D.: The relationship between snowfall catch efficiency and wind
speed for the Geonor T-200B precipitation gauge utilizing various wind
shield configurations, in: Proceedings of the 77th Annual Western Snow
Conference, Canmore, AB, 115–121, 2009.
Spence, C. and Mengistu, S.: Deployment of an unmanned aerial system to
assist in mapping an intermittent stream, Hydrol. Proc., 30,
493–500, https://doi.org/10.1002/hyp.10597, 2016.
Tangelder, H. and Fabri, A.: dD Spatial Searching, in: CGAL user and
reference manual, version 4.10, available at: https://doc.cgal.org/4.10.2/Spatial_searching/index.html, last access: Januray 2018.
Tarboton, D. G.: A new method for the determination of flow directions and
upslope areas in grid digital elevation models, Water Resour. Res.,
33, 309–319, https://doi.org/10.1029/96wr03137, 1997.
Thornton, P. E., Running, S. W., and White, M. A.: Generating surfaces of
daily meteorological variables over large regions of complex terrain, Water
Resour. Res., 190, 214–251, https://doi.org/10.1016/s0022-1694(96)03128-9, 1997.
Todini, E.: Rainfall-runoff modeling – Past, present and future, Water
Resour. Res., 100, 341–352, https://doi.org/10.1016/0022-1694(88)90191-6, 1988.
Tucker, G.: An object-oriented framework for distributed hydrologic and
geomorphic modeling using triangulated irregular networks, Comput.
Geosci., 27, 959–973, https://doi.org/10.1016/s0098-3004(00)00134-5,
2001.
Vaze, J., Post, D. A., Chiew, F. H. S., Perraud, J. M., Viney, N. R., and
Teng, J.: Climate non-stationarity – Validity of calibrated
rainfall–runoff models for use in climate change studies, Water Resour.
Res., 394, 447–457, https://doi.org/10.1016/j.jhydrol.2010.09.018,
2010.
Verseghy, D. L.: Class – A Canadian land surface scheme for GCMS, I. Soil
model, Int. J. Climatol., 11, 111–133, https://doi.org/10.1002/joc.3370110202, 1991.
Verseghy, D. L., McFarlane, N. A., and Lazare, M.: Class – A Canadian land
surface scheme for GCMS, II. Vegetation model and coupled runs,
Int. J. Climatol., 13, 347–370, https://doi.org/10.1002/joc.3370130402, 1993.
Vionnet, V., Brun, E., Morin, S., Boone, A., Faroux, S., Le Moigne, P., Martin, E., and Willemet, J.-M.: The detailed snowpack scheme Crocus and its implementation in SURFEX v7.2, Geosci. Model Dev., 5, 773–791, https://doi.org/10.5194/gmd-5-773-2012, 2012.
Viviroli, D., Dürr, H. H., Messerli, B., Meybeck, M., and Weingartner,
R.: Mountains of the world, water towers for humanity: Typology, mapping,
and global significance, Water Resour. Res., 43, W07447, https://doi.org/10.1029/2006wr005653, 2007.
Vrugt, J. A., ter Braak, C. J. F., Clark, M. P., Hyman, J. M., and Robinson,
B. A.: Treatment of input uncertainty in hydrologic modeling: Doing hydrology
backward with Markov chain Monte Carlo simulation, Water Resour. Res.,
44, W00B09, https://doi.org/10.1029/2007wr006720, 2008.
Wagener, T. and Montanari, A.: Convergence of approaches toward reduci ng
uncertainty in predictions in ungauged basins, Water Resour. Res., 47,
W06301, https://doi.org/10.1029/2010wr009469, 2011.
Walcek, C. J.: Cloud cover and its relationship to relative humidity during
a springtime midlatitude cyclone, Mon. Weather Rev., 122, 1021–1035,
1994.
Walvoord, M. A. and Kurylyk, B. L.: Hydrologic Impacts of Thawing
Permafrost – A Review, Vadose Z. J., 15, https://doi.org/10.2136/vzj2016.01.0010, 2016.
Wayand, N. E., Marsh, C. B., Shea, J. M., and Pomeroy, J. W.: Globally
scalable alpine snow metrics, Remote Sens. Environ., 213, 61–72,
https://doi.org/10.1016/j.rse.2018.05.012, 2018.
Wheater, H. S.: Water Security – science and management challenges, Proc. IAHS, 366, 23–30, https://doi.org/10.5194/piahs-366-23-2015, 2015.
Winstral, A., Elder, K., and Davis, R. E.: Spatial snow modeling of
wind-redistributed snow using terrain-based parameters, J.
Hydrometeorol., 3, 524–538, https://doi.org/10.1175/1525-7541(2002)003<0524:ssmowr>2.0.co;2,
2002.
Wood, E. F., Roundy, J. K., Troy, T. J., Beek, L. P. H. van, Bierkens, M. F.
P., Blyth, E., Roo, A. de, Döll, P., Ek, M., Famiglietti, J., Gochis,
D., Giesen, N. van de, Houser, P., Jaffé, P. R., Kollet, S., Lehner, B.,
Lettenmaier, D. P., Peters-Lidard, C., Sivapalan, M., Sheffield, J., Wade,
A., and Whitehead, P.: Hyperresolution global land surface modeling: Meeting
a grand challenge for monitoring Earth's terrestrial water, Water Resour.
Res., 47, W05301, https://doi.org/10.1029/2010wr010090, 2011.
Zhao, L. and Gray, D. M.: Estimating snowmelt infiltration into frozen
soils, Hydrol. Proc., 13, 1827–1842, https://doi.org/10.1002/(sici)1099-1085(199909)13:12/13<1827::aid-hyp896>3.0.co;2-d, 1999.
Short summary
The Canadian Hydrological Model (CHM) is a next-generation distributed model. Although designed to be applied generally, it has a focus for application where cold-region processes, such as snowpacks, play a role in hydrology. A key feature is that it uses a multi-scale surface representation, increasing efficiency. It also enables algorithm comparisons in a flexible structure. Model philosophy, design, and several cold-region-specific examples are described.
The Canadian Hydrological Model (CHM) is a next-generation distributed model. Although designed...
