2023
2022
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The cold regions hydrological modelling platform for hydrological diagnosis and prediction based on process understanding
John W. Pomeroy,
Thomas A. Brown,
Xing Fang,
Kevin Shook,
Dhiraj Pradhananga,
Robert Armstrong,
Phillip Harder,
Christopher B. Marsh,
Diogo Costa,
Sebastian A. Krogh,
Caroline Aubry‐Wake,
Holly Annand,
P. Lawford,
Zhihua He,
Mazda Kompanizare,
Jimmy Moreno
Journal of Hydrology, Volume 615
• Snow, glaciers, wetlands, frozen ground and permafrost needed in hydrological models. • Water quality export by coupling biochemical transformations to cold regions processes. • Hydrological sensitivity to land use depends on cold regions processes. • Strong cold regions hydrological sensitivity to climate warming. Cold regions involve hydrological processes that are not often addressed appropriately in hydrological models. The Cold Regions Hydrological Modelling platform (CRHM) was initially developed in 1998 to assemble and explore the hydrological understanding developed from a series of research basins spanning Canada and international cold regions. Hydrological processes and basin response in cold regions are simulated in a flexible, modular, object-oriented, multiphysics platform. The CRHM platform allows for multiple representations of forcing data interpolation and extrapolation, hydrological model spatial and physical process structures, and parameter values. It is well suited for model falsification, algorithm intercomparison and benchmarking, and has been deployed for basin hydrology diagnosis, prediction, land use change and water quality analysis, climate impact analysis and flood forecasting around the world. This paper describes CRHM’s capabilities, and the insights derived by applying the model in concert with process hydrology research and using the combined information and understanding from research basins to predict hydrological variables, diagnose hydrological change and determine the appropriateness of model structure and parameterisations.
Abstract. The Red River is one of the largest contributing sources of discharge and nutrients to the world's 10th largest freshwater lake, Lake Winnipeg. Conversion of large areas of annual cropland to perennial forage has been proposed as a strategy to reduce both flooding and nutrient export to Lake Winnipeg. Such reductions could occur either via a reduction in the concentration of nutrients in runoff or through changes in the basin-scale hydrology, resulting in a lower water yield and the concomitant export of nutrients. This study assessed the latter mechanism by using the physically based Cold Regions Hydrological Modelling platform to examine the hydrological impacts of land use conversion from annual crops to perennial forage in a subbasin of the La Salle River basin in Canada. This basin is a typical agricultural subbasin in the Red River Valley, characterised by flat topography, clay soils, and a cold subhumid, continental climate. Long-term simulations (1992–2013) of the major components of water balance were compared between canola and smooth bromegrass, representing a conversion from annual cropping systems to perennial forage. An uncertainty framework was used to represent a range of fall soil saturation status (0 % to 70 %), which governs the infiltration to frozen soil in the subsequent spring. The model simulations indicated that, on average, there was a 36.5 ± 6.6 % (36.5 ± 7.2 mm) reduction in annual cumulative discharge and a 29.9 ± 16.3 % (2.6 ± 1.6 m3 s−1) reduction in annual peak discharge due to forage conversion over the assessed period. These reductions were driven by reduced overland flow 52.9 ± 12.8 % (28.8 ± 10.1 mm), increased peak snowpack (8.1 ± 1.5 %, 7.8 ± 1.6 mm), and enhanced infiltration to frozen soils (66.7 ± 7.7 %, 141.5 ± 15.2 mm). Higher cumulative evapotranspiration (ET) from perennial forage (34.5 ± 0.9 %, 94.1 ± 2.5 mm) was also predicted by the simulations. Overall, daily soil moisture under perennial forage was 18.0 % (57.2 ± 1.2 mm) higher than that of crop simulation, likely due to the higher snow water equivalent (SWE) and enhanced infiltration. However, the impact of forage conversion on daily soil moisture varied interannually. Soil moisture under perennial forage stands could be either higher or lower than that of annual crops, depending on antecedent spring snowmelt infiltration volumes.
2021
• The CRHM-created Boreal Hydrology Model performed quite well on simultaneously simulating runoff, snow water equivalent, soil liquid water content and evapotranspiration (ET) with minor parameter calibration. • The basin hydrological variables showed quite different sensitivities to perturbations of precipitation (P) and temperature (T). Annual runoff was more sensitive to rising P than warming T, but annual ET was more sensitive to warming T. • Perturbed P and T had distinctively different influences on the streamflow regime. Increased P enhanced the intra- and inter-annual variabilities of basin runoff, whilst rising T resulted in the inverse changes. • Effects of warming on annual runoff and snow processes could be compensated for to varying degrees by the effects of increases in P. Hydrological processes over and through frozen and unfrozen ground were simulated in the well instrumented boreal forest basin of White Gull Creek, Saskatchewan, Canada using a model created using the flexible Cold Regions Hydrological Modelling (CRHM) platform. The CRHM-created Boreal Hydrology Model was structured and initially parameterized using decades of process hydrology research in the southern boreal forest with minor parameter calibration, and generally produced quite good performance on simultaneously reproducing the measurements of runoff, snow water equivalent (SWE), soil liquid water content and eddy correlation flux tower observations of evapotranspiration (ET) over two decades. To examine the sensitivity of basin hydrology to perturbed climate inputs, air temperature (T) inputs were set up by linear increments in the reference observation of up to +6 ℃, and precipitation (P) inputs were generated by multiplying the reference observed P from 70% to 130%. The model results showed that the basin hydrological variables showed quite different sensitivities to perturbations of P and T. The volume of annual runoff and the annual runoff coefficient increased more rapidly with rising P, at rates of 31% and 16% per 10% increase in P, but decreased by only 3.8% and 4.7% per 1 ℃ of warming. Annual ET increased rapidly with temperature, by 7% per 1 ℃ of warming and therefore drove the streamflow volumetric changes with warming, but increased only 1% per 10% increase in P. Perturbations of P and T had distinctively different influences on the streamflow regime. Increased P enhanced the intra- and inter-annual variabilities of basin runoff, reduced the relative contribution of winter runoff to annual runoff and increased the relative contribution of summer runoff; whilst rising T resulted in the inverse changes in the streamflow regime. Effects of warming on some hydrological processes could be compensated for to varying degrees by the effects of increases in P. Reductions in the annual runoff volume and runoff coefficient caused by warming up to 6 ℃ could be compensated for by increases of <20% in P. However, the maximum increase in P (+30%) examined could only compensate for the changes in snow processes caused by warming of less than 4 ℃ and snow-cover duration decreases with 1 ℃ warming could not be compensated for by any precipitation increase considered. These results inform the vulnerability of boreal forest hydrology to the first-order changes in P and T and provide guidance for further climate impact assessments for hydrology in the southern boreal forest in Canada.
• The CRHM-created Boreal Hydrology Model performed quite well on simultaneously simulating runoff, snow water equivalent, soil liquid water content and evapotranspiration (ET) with minor parameter calibration. • The basin hydrological variables showed quite different sensitivities to perturbations of precipitation (P) and temperature (T). Annual runoff was more sensitive to rising P than warming T, but annual ET was more sensitive to warming T. • Perturbed P and T had distinctively different influences on the streamflow regime. Increased P enhanced the intra- and inter-annual variabilities of basin runoff, whilst rising T resulted in the inverse changes. • Effects of warming on annual runoff and snow processes could be compensated for to varying degrees by the effects of increases in P. Hydrological processes over and through frozen and unfrozen ground were simulated in the well instrumented boreal forest basin of White Gull Creek, Saskatchewan, Canada using a model created using the flexible Cold Regions Hydrological Modelling (CRHM) platform. The CRHM-created Boreal Hydrology Model was structured and initially parameterized using decades of process hydrology research in the southern boreal forest with minor parameter calibration, and generally produced quite good performance on simultaneously reproducing the measurements of runoff, snow water equivalent (SWE), soil liquid water content and eddy correlation flux tower observations of evapotranspiration (ET) over two decades. To examine the sensitivity of basin hydrology to perturbed climate inputs, air temperature (T) inputs were set up by linear increments in the reference observation of up to +6 ℃, and precipitation (P) inputs were generated by multiplying the reference observed P from 70% to 130%. The model results showed that the basin hydrological variables showed quite different sensitivities to perturbations of P and T. The volume of annual runoff and the annual runoff coefficient increased more rapidly with rising P, at rates of 31% and 16% per 10% increase in P, but decreased by only 3.8% and 4.7% per 1 ℃ of warming. Annual ET increased rapidly with temperature, by 7% per 1 ℃ of warming and therefore drove the streamflow volumetric changes with warming, but increased only 1% per 10% increase in P. Perturbations of P and T had distinctively different influences on the streamflow regime. Increased P enhanced the intra- and inter-annual variabilities of basin runoff, reduced the relative contribution of winter runoff to annual runoff and increased the relative contribution of summer runoff; whilst rising T resulted in the inverse changes in the streamflow regime. Effects of warming on some hydrological processes could be compensated for to varying degrees by the effects of increases in P. Reductions in the annual runoff volume and runoff coefficient caused by warming up to 6 ℃ could be compensated for by increases of <20% in P. However, the maximum increase in P (+30%) examined could only compensate for the changes in snow processes caused by warming of less than 4 ℃ and snow-cover duration decreases with 1 ℃ warming could not be compensated for by any precipitation increase considered. These results inform the vulnerability of boreal forest hydrology to the first-order changes in P and T and provide guidance for further climate impact assessments for hydrology in the southern boreal forest in Canada.
Snowmelt contributions to streamflow in mid-latitude mountain basins typically dominate other runoff sources on annual and seasonal timescales. Future increases in temperature and changes in precipitation will affect both snow accumulation and seasonal runoff timing and magnitude, but the underlying and fundamental roles of mountain basin geometry and hypsometry on snowmelt sensitivity have received little attention. To investigate the role of basin geometry in snowmelt sensitivity, a linear snow accumulation model and the Cold Regions Hydrological Modeling (CRHM) platform driven are used to estimate how hypsometry affects basin-wide snow volumes and snowmelt runoff. Area-elevation distributions for fifty basins in western Canada were extracted, normalized according to their elevation statistics, and classified into three clusters that represent top-heavy, middle, and bottom-heavy basins. Prescribed changes in air temperature alter both the snow accumulation gradient and the total snowmelt energy, leading to snowpack volume reductions (10–40%), earlier melt onsets (1–4 weeks) and end of melt season (3 weeks), increases in early spring melt rates and reductions in seasonal areal melt rates (up to 50%). Basin hypsometry controls the magnitude of the basin response. The most sensitive basins are bottom-heavy, and have a greater proportion of their area at low elevations. The least sensitive basins are top-heavy, and have a greater proportion of their area at high elevations. Basins with similar proportional areas at high and low elevations fall in between the others in terms of sensitivity and other metrics. This work provides context for anticipating the impacts of ongoing hydrological change due to climate change, and provides guidance for both monitoring networks and distributed modeling efforts.
Snowmelt contributions to streamflow in mid-latitude mountain basins typically dominate other runoff sources on annual and seasonal timescales. Future increases in temperature and changes in precipitation will affect both snow accumulation and seasonal runoff timing and magnitude, but the underlying and fundamental roles of mountain basin geometry and hypsometry on snowmelt sensitivity have received little attention. To investigate the role of basin geometry in snowmelt sensitivity, a linear snow accumulation model and the Cold Regions Hydrological Modeling (CRHM) platform driven are used to estimate how hypsometry affects basin-wide snow volumes and snowmelt runoff. Area-elevation distributions for fifty basins in western Canada were extracted, normalized according to their elevation statistics, and classified into three clusters that represent top-heavy, middle, and bottom-heavy basins. Prescribed changes in air temperature alter both the snow accumulation gradient and the total snowmelt energy, leading to snowpack volume reductions (10–40%), earlier melt onsets (1–4 weeks) and end of melt season (3 weeks), increases in early spring melt rates and reductions in seasonal areal melt rates (up to 50%). Basin hypsometry controls the magnitude of the basin response. The most sensitive basins are bottom-heavy, and have a greater proportion of their area at low elevations. The least sensitive basins are top-heavy, and have a greater proportion of their area at high elevations. Basins with similar proportional areas at high and low elevations fall in between the others in terms of sensitivity and other metrics. This work provides context for anticipating the impacts of ongoing hydrological change due to climate change, and provides guidance for both monitoring networks and distributed modeling efforts.
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Scientific and Human Errors in a Snow Model Intercomparison
Cécile B. Ménard,
Richard Essery,
Gerhard Krinner,
Gabriele Arduini,
Paul Bartlett,
Aaron Boone,
Claire Brutel-Vuilmet,
Eleanor Burke,
Matthias Cuntz,
Yongjiu Dai,
Bertrand Decharme,
Emanuel Dutra,
Xing Fang,
Charles Fierz,
Yeugeniy M. Gusev,
Stefan Hagemann,
Vanessa Haverd,
Hyungjun Kim,
Matthieu Lafaysse,
Thomas Marke,
О. Н. Насонова,
Tomoko Nitta,
Masashi Niwano,
John W. Pomeroy,
Gerd Schädler,
В. А. Семенов,
Tatiana G. Smirnova,
Ulrich Strasser,
Sean Swenson,
Dmitry Turkov,
Nander Wever,
Hua Yuan
Bulletin of the American Meteorological Society, Volume 102, Issue 1
Abstract Twenty-seven models participated in the Earth System Model–Snow Model Intercomparison Project (ESM-SnowMIP), the most data-rich MIP dedicated to snow modeling. Our findings do not support the hypothesis advanced by previous snow MIPs: evaluating models against more variables and providing evaluation datasets extended temporally and spatially does not facilitate identification of key new processes requiring improvement to model snow mass and energy budgets, even at point scales. In fact, the same modeling issues identified by previous snow MIPs arose: albedo is a major source of uncertainty, surface exchange parameterizations are problematic, and individual model performance is inconsistent. This lack of progress is attributed partly to the large number of human errors that led to anomalous model behavior and to numerous resubmissions. It is unclear how widespread such errors are in our field and others; dedicated time and resources will be needed to tackle this issue to prevent highly sophisticated models and their research outputs from being vulnerable because of avoidable human mistakes. The design of and the data available to successive snow MIPs were also questioned. Evaluation of models against bulk snow properties was found to be sufficient for some but inappropriate for more complex snow models whose skills at simulating internal snow properties remained untested. Discussions between the authors of this paper on the purpose of MIPs revealed varied, and sometimes contradictory, motivations behind their participation. These findings started a collaborative effort to adapt future snow MIPs to respond to the diverse needs of the community.
2020
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Snow cover duration trends observed at sites and predicted bymultiple models
Richard Essery,
Hyungjun Kim,
Libo Wang,
Paul Bartlett,
Aaron Boone,
Claire Brutel-Vuilmet,
Eleanor Burke,
Matthias Cuntz,
Bertrand Decharme,
Emanuel Dutra,
Xing Fang,
Yeugeniy M. Gusev,
Stefan Hagemann,
Vanessa Haverd,
Anna Kontu,
Gerhard Krinner,
Matthieu Lafaysse,
Yves Lejeune,
Thomas Marke,
Danny Marks,
Christoph Marty,
Cécile B. Ménard,
О. Н. Насонова,
Tomoko Nitta,
John W. Pomeroy,
Gerd Schaedler,
В. А. Семенов,
Tatiana G. Smirnova,
Sean Swenson,
Dmitry Turkov,
Nander Wever,
Hua Yuan
Abstract. Thirty-year simulations of seasonal snow cover in 22 physically based models driven with bias-corrected meteorological reanalyses are examined at four sites with long records of snow observations. Annual snow cover durations differ widely between models but interannual variations are strongly correlated because of the common driving data. No significant trends are observed in starting dates for seasonal snow cover, but there are significant trends towards snow cover ending earlier at two of the sites in observations and most of the models. A simplified model with just two parameters controlling solar radiation and sensible heat contributions to snowmelt spans the ranges of snow cover durations and trends. This model predicts that sites where snow persists beyond annual peaks in solar radiation and air temperature will experience rapid decreases in snow cover duration with warming as snow begins to melt earlier and at times of year with more energy available for melting.
Abstract. Climate change is anticipated to impact the hydrology of the Saskatchewan River, which originates in the Canadian Rockies mountain range. To better understand the climate change impacts in the mountain headwaters of this basin, a physically based hydrological model was developed for this basin using the Cold Regions Hydrological Modelling platform (CRHM) for Marmot Creek Research Basin (∼9.4 km2), located in the Front Ranges of the Canadian Rockies. Marmot Creek is composed of ecozones ranging from montane forests to alpine tundra and alpine exposed rock and includes both large and small clearcuts. The model included blowing and intercepted snow redistribution, sublimation, energy-balance snowmelt, slope and canopy effects on melt, Penman–Monteith evapotranspiration, infiltration to frozen and unfrozen soils, hillslope hydrology, streamflow routing, and groundwater components and was parameterised without calibration from streamflow. Near-surface outputs from the 4 km Weather Research and Forecasting (WRF) model were bias-corrected using the quantile delta mapping method with respect to meteorological data from five stations located from low-elevation montane forests to alpine ridgetops and running over October 2005–September 2013. The bias-corrected WRF outputs during a current period (2005–2013) and a future pseudo global warming period (PGW, 2091–2099) were used to drive model simulations to assess changes in Marmot Creek's hydrology. Under a “business-as-usual” forcing scenario, Representative Concentration Pathway 8.5 (RCP8.5) in PGW, the basin will warm up by 4.7 ∘C and receive 16 % more precipitation, which will lead to a 40 mm decline in seasonal peak snowpack, 84 mm decrease in snowmelt volume, 0.2 mm d−1 slower melt rate, and 49 d shorter snow-cover duration. The alpine snow season will be shortened by almost 1.5 months, but at some lower elevations there will be large decreases in peak snowpack (∼45 %) in addition to a shorter snow season. Declines in the peak snowpack will be much greater in clearcuts than under mature forest canopies. In alpine and treeline ecozones, blowing snow transport and sublimation will be suppressed by higher-threshold wind speeds for transport, in forest ecozones, sublimation losses from intercepted snow will decrease due to faster unloading and drip, and throughout the basin, evapotranspiration will increase due to a longer snow-free season and more rainfall. Runoff will begin earlier in all ecozones, but, as a result of variability in surface and subsurface hydrology, forested and alpine ecozones will generate the greatest runoff volumetric increases, ranging from 12 % to 25 %, whereas the treeline ecozone will have a small (2 %) decrease in runoff volume due to decreased melt volumes from smaller snowdrifts. The shift in timing in streamflow will be notable, with 236 % higher flows in spring months and 12 % lower flows in summer and 13 % higher flows in early fall. Overall, Marmot Creek's annual streamflow discharge will increase by 18 % with PGW, without a change in its streamflow generation efficiency, despite its basin shifting from primarily snowmelt runoff towards rainfall-dominated runoff generation.
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Snow cover duration trends observed at sites and predicted by multiple models
Richard Essery,
Hyungjun Kim,
Libo Wang,
Paul Bartlett,
Aaron Boone,
Claire Brutel-Vuilmet,
Eleanor Burke,
Matthias Cuntz,
Bertrand Decharme,
Emanuel Dutra,
Xing Fang,
Yeugeniy M. Gusev,
Stefan Hagemann,
Vanessa Haverd,
Anna Kontu,
Gerhard Krinner,
Matthieu Lafaysse,
Yves Lejeune,
Thomas Marke,
Danny Marks,
Christoph Marty,
Cécile B. Ménard,
О. Н. Насонова,
Tomoko Nitta,
John W. Pomeroy,
Gerd Schädler,
В. А. Семенов,
Tatiana G. Smirnova,
Sean Swenson,
Dmitry Turkov,
Nander Wever,
Hua Yuan
The Cryosphere, Volume 14, Issue 12
Abstract. The 30-year simulations of seasonal snow cover in 22 physically based models driven with bias-corrected meteorological reanalyses are examined at four sites with long records of snow observations. Annual snow cover durations differ widely between models, but interannual variations are strongly correlated because of the common driving data. No significant trends are observed in starting dates for seasonal snow cover, but there are significant trends towards snow cover ending earlier at two of the sites in observations and most of the models. A simplified model with just two parameters controlling solar radiation and sensible heat contributions to snowmelt spans the ranges of snow cover durations and trends. This model predicts that sites where snow persists beyond annual peaks in solar radiation and air temperature will experience rapid decreases in snow cover duration with warming as snow begins to melt earlier and at times of year with more energy available for melting.
2019
Snow water equivalent (SWE) is one of the most hydrologically important physical properties of a snowpack. The U.S. National Weather Service's Snow Data Assimilation System (SNODAS) provides snow products at high spatial (~1 km2) and temporal (daily) resolution for the contiguous United States and southern Canada. This study evaluated the SNODAS SWE product in the boreal forest, prairie, and Canadian Rockies of western Canada against extensive snow survey measurements. SNODAS was found to work well in sheltered environments, to overestimate SWE under needle‐leaf forests, and to be unable to capture the spatial variation of SWE in windswept prairie and alpine environments. Results indicate that SNODAS SWE accuracy is strongly influenced by the missing blowing snow redistribution and canopy energetics and snow interception and sublimation processes in the mass balance calculations of the SNODAS model and by erroneous precipitation data forcing the model. To demonstrate how errors caused by missing processes can be corrected in areas with low assimilation frequency, SNODAS data were assimilated into a physically based hydrological model created using the modular Cold Region Hydrological Modelling (CRHM) platform that includes blowing and intercepted snow redistribution and subcanopy melt energetic processes. This approach decreased the overestimation of SWE compared to SNODAS from 135 to 79% in the study area and suggests that snow assimilation modeled SWE quality can be improved if snow redistribution, sublimation, and subcanopy melt processes are incorporated.
Abstract. Meteorological, snow survey, streamflow, and groundwater data are presented from Marmot Creek Research Basin, Alberta, Canada. The basin is a 9.4 km2, alpine–montane forest headwater catchment of the Saskatchewan River basin that provides vital water supplies to the Prairie Provinces of Canada. It was heavily instrumented, experimented upon, and operated by several federal government agencies between 1962 and 1986, during which time its main and sub-basin streams were gauged, automated meteorological stations at multiple elevations were installed, groundwater observation wells were dug and automated, and frequent manual measurements of snow accumulation and ablation and other weather and water variables were made. Over this period, mature evergreen forests were harvested in two sub-basins, leaving large clear cuts in one basin and a “honeycomb” of small forest clearings in another basin. Whilst meteorological measurements and sub-basin streamflow discharge weirs in the basin were removed in the late 1980s, the federal government maintained the outlet streamflow discharge measurements and a nearby high-elevation meteorological station, and the Alberta provincial government maintained observation wells and a nearby fire weather station. Marmot Creek Research Basin was intensively re-instrumented with 12 automated meteorological stations, four sub-basin hydrometric sites, and seven snow survey transects starting in 2004 by the University of Saskatchewan Centre for Hydrology. The observations provide detailed information on meteorology, precipitation, soil moisture, snowpack, streamflow, and groundwater during the historical period from 1962 to 1987 and the modern period from 2005 to the present time. These data are ideal for monitoring climate change, developing hydrological process understanding, evaluating process algorithms and hydrological, cryospheric, or atmospheric models, and examining the response of basin hydrological cycling to changes in climate, extreme weather, and land cover through hydrological modelling and statistical analyses. The data presented are publicly available from Federated Research Data Repository (https://doi.org/10.20383/101.09, Fang et al., 2018).
Permafrost degradation in the peat‐rich southern fringe of the discontinuous permafrost zone is catalysing substantial changes to land cover with expansion of permafrost‐free wetlands (bogs and fens) and shrinkage of forest‐dominated permafrost peat plateaux. Predicting discharge from headwater basins in this region depends upon understanding and numerically representing the interactions between storage and discharge within and between the major land cover types and how these interactions are changing. To better understand the implications of advanced permafrost thaw‐induced land cover change on wetland discharge, with all landscape features capable of contributing to drainage networks, the hydrological behaviour of a channel fen sub‐basin in the headwaters of Scotty Creek, Northwest Territories, Canada, dominated by peat plateau–bog complexes, was modelled using the Cold Regions Hydrological Modelling platform for the period of 2009 to 2015. The model construction was based on field water balance observations, and performance was deemed adequate when evaluated against measured water balance components. A sensitivity analysis was conducted to assess the impact of progressive permafrost loss on discharge from the sub‐basin, in which all units of the sub‐basin have the potential to contribute to the drainage network, by incrementally reducing the ratio of wetland to plateau in the modelled sub‐basin. Simulated reductions in permafrost extent decreased total annual discharge from the channel fen by 2.5% for every 10% decrease in permafrost area due to increased surface storage capacity, reduced run‐off efficiency, and increased landscape evapotranspiration. Runoff ratios for the fen hydrological response unit dropped from 0.54 to 0.48 after the simulated 50% permafrost area loss with a substantial reduction of 0.47 to 0.31 during the snowmelt season. The reduction in peat plateau area resulted in decreased seasonal variability in discharge due to changes in the flow path routing, with amplified low flows associated with small increases in subsurface discharge, and decreased peak discharge with large reductions in surface run‐off.
2018
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ESM-SnowMIP: assessing snow models and quantifying snow-related climate feedbacks
Gerhard Krinner,
Chris Derksen,
Richard Essery,
M. Flanner,
Stefan Hagemann,
Martyn Clark,
Alex Hall,
Helmut Rott,
Claire Brutel-Vuilmet,
Hyungjun Kim,
Cécile B. Ménard,
Lawrence Mudryk,
Chad W. Thackeray,
Libo Wang,
Gabriele Arduini,
Gianpaolo Balsamo,
Paul Bartlett,
Julia Boike,
Aaron Boone,
F. Chéruy,
Jeanne Colin,
Matthias Cuntz,
Yongjiu Dai,
Bertrand Decharme,
Jeff Derry,
Agnès Ducharne,
Emanuel Dutra,
Xing Fang,
Charles Fierz,
Josephine Ghattas,
Yeugeniy M. Gusev,
Vanessa Haverd,
Anna Kontu,
Matthieu Lafaysse,
R. M. Law,
David M. Lawrence,
Weiping Li,
Thomas Marke,
Danny Marks,
Martin Ménégoz,
О. Н. Насонова,
Tomoko Nitta,
Masashi Niwano,
John W. Pomeroy,
Mark S. Raleigh,
Gerd Schaedler,
В. А. Семенов,
Tatiana G. Smirnova,
Tobias Stacke,
Ulrich Strasser,
Sean Svenson,
Dmitry Turkov,
Tao Wang,
Nander Wever,
Hua Yuan,
Wenyan Zhou,
Dan Zhu
Geoscientific Model Development, Volume 11, Issue 12
Abstract. This paper describes ESM-SnowMIP, an international coordinated modelling effort to evaluate current snow schemes, including snow schemes that are included in Earth system models, in a wide variety of settings against local and global observations. The project aims to identify crucial processes and characteristics that need to be improved in snow models in the context of local- and global-scale modelling. A further objective of ESM-SnowMIP is to better quantify snow-related feedbacks in the Earth system. Although it is not part of the sixth phase of the Coupled Model Intercomparison Project (CMIP6), ESM-SnowMIP is tightly linked to the CMIP6-endorsed Land Surface, Snow and Soil Moisture Model Intercomparison (LS3MIP).
2016
The June 2013 flood in the Canadian Rockies featured rain‐on‐snow (ROS) runoff generation at alpine elevations that contributed to the high streamflows observed during the event. Such a mid‐summer ROS event has not been diagnosed in detail, and a diagnosis may help to understand future high discharge‐producing hydrometeorological events in mountainous cold regions. The alpine hydrology of the flood was simulated using a physically based model created with the modular cold regions hydrological modelling platform. The event was distinctive in that, although at first, relatively warm rain fell onto existing snowdrifts inducing ROS melt; the rainfall turned to snowfall as the air mass cooled and so increased snowcover and snowpacks in alpine regions, which then melted rapidly from ground heat fluxes in the latter part of the event. Melt rates of existing snowpacks were substantially lower during the ROS than during the relatively sunny periods preceding and following the event as a result of low wind speeds, cloud cover and cool temperatures. However, at the basin scale, melt volumes increased during the event as a result of increased snowcover from the fresh snowfall and consequent large ground heat contributions to melt energy, causing snowmelt to enhance rainfall–runoff by one fifth. Flow pathways also shifted during the event from relatively slow sub‐surface flow prior to the flood to an even contribution from sub‐surface and fast overland flow during and immediately after the event. This early summer, high precipitation ROS event was distinctive for the impact of decreased solar irradiance in suppressing melt rates, the contribution of ground heat flux to basin scale snowmelt after precipitation turned to snowfall, the transition from slow sub‐surface to fast overland flow runoff as the sub‐surface storage saturated and streamflow volumes that exceeded precipitation. These distinctions show that summer, mountain ROS events should be considered quite distinct from winter ROS and can be important contributors to catastrophic events. Copyright © 2016 John Wiley & Sons, Ltd.
A devastating flood struck Southern Alberta in late June 2013, with much of its streamflow generation in the Front Ranges of the Rocky Mountains, west of Calgary. To better understand streamflow generation processes and their sensitivity to initial conditions, a physically based hydrological model was developed using the Cold Regions Hydrological Modelling platform (CRHM) to simulate the flood for the Marmot Creek Research Basin (~9.4 km2). The modular model includes major cold and warm season hydrological processes including snow redistribution, sublimation, melt, runoff over frozen and unfrozen soils, evapotranspiration, subsurface runoff on hillslopes, groundwater recharge and discharge and streamflow routing. Uncalibrated simulations were conducted for eight hydrological years and generally matched streamflow observations well, with a NRMSD of 52%, small model bias (−3%) and a Nash–Sutcliffe efficiency (NSE) of 0.71. The model was then used to diagnose the responses of hydrological processes in 2013 flood from different ecozones in Marmot Creek: alpine, treeline, montane forest and large and small forest clearings to better understand spatial variations in the flood runoff generation mechanisms. To examine the sensitivity to antecedent conditions, ‘virtual’ flood simulations were conducted using a week (17 to 24 June 2013) of flood meteorology imposed on the meteorology of the same period in other years (2005 to 2012), or switched with the meteorology of one week in different months (May to July) of 2013. Sensitivity to changing precipitation and land cover was assessed by varying the precipitation amount during the flood and forest cover and soil storage capacity in forest ecozone. The results show that runoff efficiency increases rapidly with antecedent snowpack and soil moisture storage with the highest runoff response to rainfall from locations in the basin where there are recently melted or actively melting snowpacks and resulting high soil moisture or frozen soils. The impact of forest canopy on flooding is negligible, but flood peak doubles if forest canopy removal is accompanied by 50% reduction in water storage capacity in the basin. Copyright © 2016 John Wiley & Sons, Ltd.
Snow cover dynamics in alpine regions play a crucial role in view of the water balance of head water catchments. The temporal storage of water in form of snow and ice leads to a decoupling of precipitation and runoff. Changes in the volume and the temporal dynamics of the snow storage lead to modified runoff regimes and can influence the frequency of low flow events and floods. For a better estimation of the possible range and direction of future changes, projection runs can be realized by using process-based models. In this study, the Cold Regions Hydrological Modelling platform (CRHM) is used to compile such a model for simulating the snow cover development within research catchment Zugspitze (RCZ; 11.4 km2/Germany). Therefore, the catchment is divided into four hydrological response units (HRUs), able to cover the physiographic characteristics in four elevation zones. The model is evaluated over snow depth measurements. The range of variability within and differences between the HRUs are analyzed, and future projections (2001–2100) are performed on the basis of three different WETTREG realizations. It could be shown that CRHM is able to reproduce the snow cover dynamics very well and that the ongoing climate change does have an identifiable influence on the average extent and size of the snow storage. Furthermore, it could be shown that variations in snow cover dynamics within the RCZ are strongly connected to NAO.