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
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
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Hydrol. Earth Syst. Sci., 26, 1801–1819, https://doi.org/10.5194/hess-26-1801-2022, https://doi.org/10.5194/hess-26-1801-2022, 2022
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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
Synergy between satellite observations of soil moisture and water storage anomalies for runoff estimation
A physically based distributed karst hydrological model (QMG model-V1.0) for flood simulations
Modular Assessment of Rainfall–Runoff Models Toolbox (MARRMoT) v2.1: an object-oriented implementation of 47 established hydrological models for improved speed and readability
CREST-VEC: a framework towards more accurate and realistic flood simulation across scales
Rad-cGAN v1.0: Radar-based precipitation nowcasting model with conditional generative adversarial networks for multiple dam domains
The eWaterCycle platform for open and FAIR hydrological collaboration
Evaluating the Atibaia River hydrology using JULES6.1
A framework for ensemble modelling of climate change impacts on lakes worldwide: the ISIMIP Lake Sector
CLIMFILL v0.9: a framework for intelligently gap filling Earth observations
Modeling subgrid lake energy balance in ORCHIDEE terrestrial scheme using the FLake lake model
Evaluating a reservoir parametrization in the vector-based global routing model mizuRoute (v2.0.1) for Earth system model coupling
Improved runoff simulations for a highly varying soil depth and complex terrain watershed in the Loess Plateau with the Community Land Model version 5
GSTools v1.3: a toolbox for geostatistical modelling in Python
AI4Water v1.0: an open-source python package for modeling hydrological time series using data-driven methods
Modeling of streamflow in a 30 km long reach spanning 5 years using OpenFOAM 5.x
Tree hydrodynamic modelling of the soil–plant–atmosphere continuum using FETCH3
Effects of dimensionality on the performance of hydrodynamic models for stratified lakes and reservoirs
Computation of backwater effects in surface waters of lowland catchments including control structures – an efficient and re-usable method implemented in the hydrological open-source model Kalypso-NA (4.0)
Inishell 2.0: semantically driven automatic GUI generation for scientific models
Irrigation quality and management determine salinization in Israeli olive orchards
Implementing the Water, HEat and Transport model in GEOframe (WHETGEO-1D v.1.0): algorithms, informatics, design patterns, open science features, and 1D deployment
HydroPy (v1.0): a new global hydrology model written in Python
How to perform global sensitivity analysis of a catchment-scale, distributed pesticide transfer model? Application to the PESHMELBA model
GMD perspective: The quest to improve the evaluation of groundwater representation in continental- to global-scale models
SELF v1.0: a minimal physical model for predicting time of freeze-up in lakes
POET (v0.1): speedup of many-core parallel reactive transport simulations with fast DHT lookups
Assessment of the ParFlow–CLM CONUS 1.0 integrated hydrologic model: evaluation of hyper-resolution water balance components across the contiguous United States
Cosmic-Ray neutron Sensor PYthon tool (crspy 1.2.1): an open-source tool for the processing of cosmic-ray neutron and soil moisture data
SuperflexPy 1.3.0: an open-source Python framework for building, testing, and improving conceptual hydrological models
DRYP 1.0: a parsimonious hydrological model of DRYland Partitioning of the water balance
HydroBlocks v0.2: enabling a field-scale two-way coupling between the land surface and river networks in Earth system models
GP-SWAT (v1.0): a two-level graph-based parallel simulation tool for the SWAT model
Development of a coupled simulation framework representing the lake and river continuum of mass and energy (TCHOIR v1.0)
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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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.
Stefania Camici, Gabriele Giuliani, Luca Brocca, Christian Massari, Angelica Tarpanelli, Hassan Hashemi Farahani, Nico Sneeuw, Marco Restano, and Jérôme Benveniste
Geosci. Model Dev., 15, 6935–6956, https://doi.org/10.5194/gmd-15-6935-2022, https://doi.org/10.5194/gmd-15-6935-2022, 2022
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This paper presents an innovative approach, STREAM (SaTellite-based Runoff Evaluation And Mapping), to derive daily river discharge and runoff estimates from satellite observations of soil moisture, precipitation, and terrestrial total water storage anomalies. Potentially useful for multiple operational and scientific applications, the added value of the STREAM approach is the ability to increase knowledge on the natural processes, human activities, and their interactions on the land.
Ji Li, Daoxian Yuan, Fuxi Zhang, Jiao Liu, and Mingguo Ma
Geosci. Model Dev., 15, 6581–6600, https://doi.org/10.5194/gmd-15-6581-2022, https://doi.org/10.5194/gmd-15-6581-2022, 2022
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A new karst hydrological model (the QMG model) is developed to simulate and predict the floods in karst trough valley basins. Unlike the complex structure and parameters of current karst groundwater models, this model has a simple double-layered structure with few parameters and decreases the demand for modeling data in karst areas. The flood simulation results based on the QMG model of the Qingmuguan karst trough valley basin are satisfactory, indicating the suitability of the model simulation.
Luca Trotter, Wouter J. M. Knoben, Keirnan J. A. Fowler, Margarita Saft, and Murray C. Peel
Geosci. Model Dev., 15, 6359–6369, https://doi.org/10.5194/gmd-15-6359-2022, https://doi.org/10.5194/gmd-15-6359-2022, 2022
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MARRMoT is a piece of software that emulates 47 common models for hydrological simulations. It can be used to run and calibrate these models within a common environment as well as to easily modify them. We restructured and recoded MARRMoT in order to make the models run faster and to simplify their use, while also providing some new features. This new MARRMoT version runs models on average 3.6 times faster while maintaining very strong consistency in their outputs to the previous version.
Zhi Li, Shang Gao, Mengye Chen, Jonathan Gourley, Naoki Mizukami, and Yang Hong
Geosci. Model Dev., 15, 6181–6196, https://doi.org/10.5194/gmd-15-6181-2022, https://doi.org/10.5194/gmd-15-6181-2022, 2022
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Operational streamflow prediction at a continental scale is critical for national water resources management. However, limited computational resources often impede such processes, with streamflow routing being one of the most time-consuming parts. This study presents a recent development of a hydrologic system that incorporates a vector-based routing scheme with a lake module that markedly speeds up streamflow prediction. Moreover, accuracy is improved and flood false alarms are mitigated.
Suyeon Choi and Yeonjoo Kim
Geosci. Model Dev., 15, 5967–5985, https://doi.org/10.5194/gmd-15-5967-2022, https://doi.org/10.5194/gmd-15-5967-2022, 2022
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Here we present the cGAN-based precipitation nowcasting model, named Rad-cGAN, trained to predict a radar reflectivity map with a lead time of 10 min. Rad-cGAN showed superior performance at a lead time of up to 90 min compared with the reference models. Furthermore, we demonstrate the successful implementation of the transfer learning strategies using pre-trained Rad-cGAN to develop the models for different dam domains.
Rolf Hut, Niels Drost, Nick van de Giesen, Ben van Werkhoven, Banafsheh Abdollahi, Jerom Aerts, Thomas Albers, Fakhereh Alidoost, Bouwe Andela, Jaro Camphuijsen, Yifat Dzigan, Ronald van Haren, Eric Hutton, Peter Kalverla, Maarten van Meersbergen, Gijs van den Oord, Inti Pelupessy, Stef Smeets, Stefan Verhoeven, Martine de Vos, and Berend Weel
Geosci. Model Dev., 15, 5371–5390, https://doi.org/10.5194/gmd-15-5371-2022, https://doi.org/10.5194/gmd-15-5371-2022, 2022
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With the eWaterCycle platform, we are providing the hydrological community with a platform to conduct their research that is fully compatible with the principles of both open science and FAIR science. The eWatercyle platform gives easy access to well-known hydrological models, big datasets and example experiments. Using eWaterCycle hydrologists can easily compare the results from different models, couple models and do more complex hydrological computational research.
Hsi-Kai Chou, Ana Maria Heuminski de Avila, and Michaela Bray
Geosci. Model Dev., 15, 5233–5240, https://doi.org/10.5194/gmd-15-5233-2022, https://doi.org/10.5194/gmd-15-5233-2022, 2022
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Land surface models allow us to understand and investigate the cause and effect of environmental process changes. Therefore, this type of model is increasingly used for hydrological assessments. Here we explore the possibility of this approach using a case study in the Atibaia River basin, which serves as a major water supply for the metropolitan regions of Campinas and São Paulo, Brazil. We evaluated the model performance and use the model to simulate the basin hydrology.
Malgorzata Golub, Wim Thiery, Rafael Marcé, Don Pierson, Inne Vanderkelen, Daniel Mercado-Bettin, R. Iestyn Woolway, Luke Grant, Eleanor Jennings, Benjamin M. Kraemer, Jacob Schewe, Fang Zhao, Katja Frieler, Matthias Mengel, Vasiliy Y. Bogomolov, Damien Bouffard, Marianne Côté, Raoul-Marie Couture, Andrey V. Debolskiy, Bram Droppers, Gideon Gal, Mingyang Guo, Annette B. G. Janssen, Georgiy Kirillin, Robert Ladwig, Madeline Magee, Tadhg Moore, Marjorie Perroud, Sebastiano Piccolroaz, Love Raaman Vinnaa, Martin Schmid, Tom Shatwell, Victor M. Stepanenko, Zeli Tan, Bronwyn Woodward, Huaxia Yao, Rita Adrian, Mathew Allan, Orlane Anneville, Lauri Arvola, Karen Atkins, Leon Boegman, Cayelan Carey, Kyle Christianson, Elvira de Eyto, Curtis DeGasperi, Maria Grechushnikova, Josef Hejzlar, Klaus Joehnk, Ian D. Jones, Alo Laas, Eleanor B. Mackay, Ivan Mammarella, Hampus Markensten, Chris McBride, Deniz Özkundakci, Miguel Potes, Karsten Rinke, Dale Robertson, James A. Rusak, Rui Salgado, Leon van der Linden, Piet Verburg, Danielle Wain, Nicole K. Ward, Sabine Wollrab, and Galina Zdorovennova
Geosci. Model Dev., 15, 4597–4623, https://doi.org/10.5194/gmd-15-4597-2022, https://doi.org/10.5194/gmd-15-4597-2022, 2022
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Lakes and reservoirs are warming across the globe. To better understand how lakes are changing and to project their future behavior amidst various sources of uncertainty, simulations with a range of lake models are required. This in turn requires international coordination across different lake modelling teams worldwide. Here we present a protocol for and results from coordinated simulations of climate change impacts on lakes worldwide.
Verena Bessenbacher, Sonia Isabelle Seneviratne, and Lukas Gudmundsson
Geosci. Model Dev., 15, 4569–4596, https://doi.org/10.5194/gmd-15-4569-2022, https://doi.org/10.5194/gmd-15-4569-2022, 2022
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Earth observations have many missing values. They are often filled using information from spatial and temporal contexts that mostly ignore information from related observed variables. We propose the gap-filling method CLIMFILL that additionally uses information from related variables. We test CLIMFILL using gap-free reanalysis data of variables related to soil–moisture climate interactions. CLIMFILL creates estimates for the missing values that recover the original dependence structure.
Anthony Bernus and Catherine Ottlé
Geosci. Model Dev., 15, 4275–4295, https://doi.org/10.5194/gmd-15-4275-2022, https://doi.org/10.5194/gmd-15-4275-2022, 2022
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The lake model FLake was coupled to the ORCHIDEE land surface model to simulate lake energy balance at global scale with a multi-tile approach. Several simulations were performed with various atmospheric reanalyses and different lake depth parameterizations. The simulated lake surface temperature showed good agreement with observations (RMSEs of the order of 3 °C). We showed the large impact of the atmospheric forcing on lake temperature. We highlighted systematic errors on ice cover phenology.
Inne Vanderkelen, Shervan Gharari, Naoki Mizukami, Martyn P. Clark, David M. Lawrence, Sean Swenson, Yadu Pokhrel, Naota Hanasaki, Ann van Griensven, and Wim Thiery
Geosci. Model Dev., 15, 4163–4192, https://doi.org/10.5194/gmd-15-4163-2022, https://doi.org/10.5194/gmd-15-4163-2022, 2022
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Human-controlled reservoirs have a large influence on the global water cycle. However, dam operations are rarely represented in Earth system models. We implement and evaluate a widely used reservoir parametrization in a global river-routing model. Using observations of individual reservoirs, the reservoir scheme outperforms the natural lake scheme. However, both schemes show a similar performance due to biases in runoff timing and magnitude when using simulated runoff.
Jiming Jin, Lei Wang, Jie Yang, Bingcheng Si, and Guo-Yue Niu
Geosci. Model Dev., 15, 3405–3416, https://doi.org/10.5194/gmd-15-3405-2022, https://doi.org/10.5194/gmd-15-3405-2022, 2022
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This study aimed to improve runoff simulations and explore deep soil hydrological processes for a highly varying soil depth and complex terrain watershed in the Loess Plateau, China. The actual soil depths and river channels were incorporated into the model to better simulate the runoff in this watershed. The soil evaporation scheme was modified to better describe the evaporation processes. Our results showed that the model significantly improved the runoff simulations.
Sebastian Müller, Lennart Schüler, Alraune Zech, and Falk Heße
Geosci. Model Dev., 15, 3161–3182, https://doi.org/10.5194/gmd-15-3161-2022, https://doi.org/10.5194/gmd-15-3161-2022, 2022
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The GSTools package provides a Python-based platform for geoostatistical applications. Salient features of GSTools are its random field generation, its kriging capabilities and its versatile covariance model. It is furthermore integrated with other Python packages, like PyKrige, ogs5py or scikit-gstat, and provides interfaces to meshio and PyVista. Four presented workflows showcase the abilities of GSTools.
Ather Abbas, Laurie Boithias, Yakov Pachepsky, Kyunghyun Kim, Jong Ahn Chun, and Kyung Hwa Cho
Geosci. Model Dev., 15, 3021–3039, https://doi.org/10.5194/gmd-15-3021-2022, https://doi.org/10.5194/gmd-15-3021-2022, 2022
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The field of artificial intelligence has shown promising results in a wide variety of fields including hydrological modeling. However, developing and testing hydrological models with artificial intelligence techniques require expertise from diverse fields. In this study, we developed an open-source framework based upon the python programming language to simplify the process of the development of hydrological models of time series data using machine learning.
Yunxiang Chen, Jie Bao, Yilin Fang, William A. Perkins, Huiying Ren, Xuehang Song, Zhuoran Duan, Zhangshuan Hou, Xiaoliang He, and Timothy D. Scheibe
Geosci. Model Dev., 15, 2917–2947, https://doi.org/10.5194/gmd-15-2917-2022, https://doi.org/10.5194/gmd-15-2917-2022, 2022
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Climate change affects river discharge variations that alter streamflow. By integrating multi-type survey data with a computational fluid dynamics tool, OpenFOAM, we show a workflow that enables accurate and efficient streamflow modeling at 30 km and 5-year scales. The model accuracy for water stage and depth average velocity is −16–9 cm and 0.71–0.83 in terms of mean error and correlation coefficients. This accuracy indicates the model's reliability for evaluating climate impact on rivers.
Marcela Silva, Ashley M. Matheny, Valentijn R. N. Pauwels, Dimetre Triadis, Justine E. Missik, Gil Bohrer, and Edoardo Daly
Geosci. Model Dev., 15, 2619–2634, https://doi.org/10.5194/gmd-15-2619-2022, https://doi.org/10.5194/gmd-15-2619-2022, 2022
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Our study introduces FETCH3, a ready-to-use, open-access model that simulates the water fluxes across the soil, roots, and stem. To test the model capabilities, we tested it against exact solutions and a case study. The model presented considerably small errors when compared to the exact solutions and was able to correctly represent transpiration patterns when compared to experimental data. The results show that FETCH3 can correctly simulate above- and below-ground water transport.
Mayra Ishikawa, Wendy Gonzalez, Orides Golyjeswski, Gabriela Sales, J. Andreza Rigotti, Tobias Bleninger, Michael Mannich, and Andreas Lorke
Geosci. Model Dev., 15, 2197–2220, https://doi.org/10.5194/gmd-15-2197-2022, https://doi.org/10.5194/gmd-15-2197-2022, 2022
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Reservoir hydrodynamics is often described in numerical models differing in dimensionality. 1D and 2D models assume homogeneity along the unresolved dimension. We compare the performance of models with 1 to 3 dimensions. All models presented reasonable results for seasonal temperature dynamics. Neglecting longitudinal transport resulted in the largest deviations in temperature. Flow velocity could only be reproduced by the 3D model. Results support the selection of models and their assessment.
Sandra Hellmers and Peter Fröhle
Geosci. Model Dev., 15, 1061–1077, https://doi.org/10.5194/gmd-15-1061-2022, https://doi.org/10.5194/gmd-15-1061-2022, 2022
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A hydrological method to compute backwater effects in surface water streams and on adjacent lowlands caused by mostly complex flow control systems is presented. It enables transfer of discharges to water levels and calculation of backwater volume routing along streams and lowland areas by balancing water level slopes. The developed, implemented and evaluated method extends the application range of hydrological models significantly for flood-routing simulation in backwater-affected catchments.
Mathias Bavay, Michael Reisecker, Thomas Egger, and Daniela Korhammer
Geosci. Model Dev., 15, 365–378, https://doi.org/10.5194/gmd-15-365-2022, https://doi.org/10.5194/gmd-15-365-2022, 2022
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Most users struggle with the configuration of numerical models. This can be improved by relying on a GUI, but this requires a significant investment and a specific skill set and does not fit with the daily duties of model developers, leading to major maintenance burdens. Inishell generates a GUI on the fly based on an XML description of the required configuration elements, making maintenance very simple. This concept has been shown to work very well in our context.
Vladimir Mirlas, Yaakov Anker, Asher Aizenkod, and Naftali Goldshleger
Geosci. Model Dev., 15, 129–143, https://doi.org/10.5194/gmd-15-129-2022, https://doi.org/10.5194/gmd-15-129-2022, 2022
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Salinization owing to irrigation water quality causes soil degradation and soil fertility reduction that with poor drainage conditions impede plant development and manifest in economic damage. This study provided a soil salting process evaluation procedure through a combination of soil salinity monitoring, field experiments, remote sensing, and unsaturated soil profile saline water movement modeling. The modeling results validated the soil salinization danger from using brackish irrigation.
Niccolò Tubini and Riccardo Rigon
Geosci. Model Dev., 15, 75–104, https://doi.org/10.5194/gmd-15-75-2022, https://doi.org/10.5194/gmd-15-75-2022, 2022
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This paper presents WHETGEO and its 1D deployment: a new physically based model simulating the water and energy budgets in a soil column. WHETGEO-1D is intended to be the first building block of a new customisable land-surface model that is integrated with process-based hydrology. WHETGEO is developed as an open-source code and is fully integrated into the GEOframe/OMS3 system, allowing the use of the many ancillary tools it provides.
Tobias Stacke and Stefan Hagemann
Geosci. Model Dev., 14, 7795–7816, https://doi.org/10.5194/gmd-14-7795-2021, https://doi.org/10.5194/gmd-14-7795-2021, 2021
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HydroPy is a new version of an established global hydrology model. It was rewritten from scratch and adapted to a modern object-oriented infrastructure to facilitate its future development and application. With this study, we provide a thorough documentation and evaluation of our new model. At the same time, we open our code base and publish the model's source code in a public software repository. In this way, we aim to contribute to increasing transparency and reproducibility in science.
Emilie Rouzies, Claire Lauvernet, Bruno Sudret, and Arthur Vidard
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2021-425, https://doi.org/10.5194/gmd-2021-425, 2021
Revised manuscript accepted for GMD
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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 selecting the most influential input parameters but it has to be adapted to spatial modelling. This study will (i) identify relevant methods that can be transposed to any hydrological and water quality models, (ii) improve the fate of pesticides knowledge.
Tom Gleeson, Thorsten Wagener, Petra Döll, Samuel C. Zipper, Charles West, Yoshihide Wada, Richard Taylor, Bridget Scanlon, Rafael Rosolem, Shams Rahman, Nurudeen Oshinlaja, Reed Maxwell, Min-Hui Lo, Hyungjun Kim, Mary Hill, Andreas Hartmann, Graham Fogg, James S. Famiglietti, Agnès Ducharne, Inge de Graaf, Mark Cuthbert, Laura Condon, Etienne Bresciani, and Marc F. P. Bierkens
Geosci. Model Dev., 14, 7545–7571, https://doi.org/10.5194/gmd-14-7545-2021, https://doi.org/10.5194/gmd-14-7545-2021, 2021
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Groundwater is increasingly being included in large-scale (continental to global) land surface and hydrologic simulations. However, it is challenging to evaluate these simulations because groundwater is
hiddenunderground and thus hard to measure. We suggest using multiple complementary strategies to assess the performance of a model (
model evaluation).
Marco Toffolon, Luca Cortese, and Damien Bouffard
Geosci. Model Dev., 14, 7527–7543, https://doi.org/10.5194/gmd-14-7527-2021, https://doi.org/10.5194/gmd-14-7527-2021, 2021
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The time when lakes freeze varies considerably from year to year. A common way to predict it is to use negative degree days, i.e., the sum of air temperatures below 0 °C, a proxy for the heat lost to the atmosphere. Here, we show that this is insufficient as the mixing of the surface layer induced by wind tends to delay the formation of ice. To do so, we developed a minimal model based on a simplified energy balance, which can be used both for large-scale analyses and short-term predictions.
Marco De Lucia, Michael Kühn, Alexander Lindemann, Max Lübke, and Bettina Schnor
Geosci. Model Dev., 14, 7391–7409, https://doi.org/10.5194/gmd-14-7391-2021, https://doi.org/10.5194/gmd-14-7391-2021, 2021
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POET is a parallel reactive transport simulator which implements a mechanism to store and reuse previous results of geochemical simulations through distributed hash tables. POET parallelizes chemistry using a master/worker design with noncontiguous grid partitions to maximize its efficiency and load balance on shared-memory machines and compute clusters.
Mary M. F. O'Neill, Danielle T. Tijerina, Laura E. Condon, and Reed M. Maxwell
Geosci. Model Dev., 14, 7223–7254, https://doi.org/10.5194/gmd-14-7223-2021, https://doi.org/10.5194/gmd-14-7223-2021, 2021
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Modeling the hydrologic cycle at high resolution and at large spatial scales is an incredible opportunity and challenge for hydrologists. In this paper, we present the results of a high-resolution hydrologic simulation configured over the contiguous United States. We discuss simulated water fluxes through groundwater, soil, plants, and over land, and we compare model results to in situ observations and satellite products in order to build confidence and guide future model development.
Daniel Power, Miguel Angel Rico-Ramirez, Sharon Desilets, Darin Desilets, and Rafael Rosolem
Geosci. Model Dev., 14, 7287–7307, https://doi.org/10.5194/gmd-14-7287-2021, https://doi.org/10.5194/gmd-14-7287-2021, 2021
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Cosmic-ray neutron sensors estimate root-zone soil moisture at sub-kilometre scales. There are national-scale networks of these sensors across the globe; however, methods for converting neutron signals to soil moisture values are inconsistent. This paper describes our open-source Python tool that processes raw sensor data into soil moisture estimates. The aim is to allow a user to ensure they have a harmonized data set, along with informative metadata, to facilitate both research and teaching.
Marco Dal Molin, Dmitri Kavetski, and Fabrizio Fenicia
Geosci. Model Dev., 14, 7047–7072, https://doi.org/10.5194/gmd-14-7047-2021, https://doi.org/10.5194/gmd-14-7047-2021, 2021
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This paper introduces SuperflexPy, an open-source Python framework for building flexible conceptual hydrological models. SuperflexPy is available as open-source code and can be used by the hydrological community to investigate improved process representations, for model comparison, and for operational work.
E. Andrés Quichimbo, Michael Bliss Singer, Katerina Michaelides, Daniel E. J. Hobley, Rafael Rosolem, and Mark O. Cuthbert
Geosci. Model Dev., 14, 6893–6917, https://doi.org/10.5194/gmd-14-6893-2021, https://doi.org/10.5194/gmd-14-6893-2021, 2021
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Understanding and quantifying water partitioning in dryland regions are of key importance to anticipate the future impacts of climate change in water resources and dryland ecosystems. Here, we have developed a simple hydrological model (DRYP) that incorporates the key processes of water partitioning in drylands. DRYP is a modular, versatile, and parsimonious model that can be used to anticipate and plan for climatic and anthropogenic changes to water fluxes and storage in dryland regions.
Nathaniel W. Chaney, Laura Torres-Rojas, Noemi Vergopolan, and Colby K. Fisher
Geosci. Model Dev., 14, 6813–6832, https://doi.org/10.5194/gmd-14-6813-2021, https://doi.org/10.5194/gmd-14-6813-2021, 2021
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Although there have been significant advances in river routing and sub-grid heterogeneity (i.e., tiling) schemes in Earth system models over the past decades, there has yet to be a concerted effort to couple these two concepts. This paper aims to bridge this gap through the development of a two-way coupling between tiling schemes and river networks in the HydroBlocks land surface model. The scheme is implemented and tested over a 1 arc degree domain in Oklahoma, United States.
Dejian Zhang, Bingqing Lin, Jiefeng Wu, and Qiaoying Lin
Geosci. Model Dev., 14, 5915–5925, https://doi.org/10.5194/gmd-14-5915-2021, https://doi.org/10.5194/gmd-14-5915-2021, 2021
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GP-SWAT is a two-layer model parallelization tool for a SWAT model based on the graph-parallel Pregel algorithm. It can be employed to perform both individual and iterative model parallelization, endowing it with a range of possible applications and great flexibility in maximizing performance. As a flexible and scalable tool, it can run in diverse environments, ranging from a commodity computer with a Microsoft Windows, Mac or Linux OS to a Spark cluster consisting of a large number of nodes.
Daisuke Tokuda, Hyungjun Kim, Dai Yamazaki, and Taikan Oki
Geosci. Model Dev., 14, 5669–5693, https://doi.org/10.5194/gmd-14-5669-2021, https://doi.org/10.5194/gmd-14-5669-2021, 2021
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We developed TCHOIR, a hydrologic simulation framework, to solve fluvial- and thermodynamics of the river–lake continuum. This provides an algorithm for upscaling high-resolution topography as well, which enables the representation of those interactions at the global scale. Validation against in situ and satellite observations shows that the coupled mode outperforms river- or lake-only modes. TCHOIR will contribute to elucidating the role of surface hydrology in Earth’s energy and water cycle.
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...
