Cold Regions Hydrological Model Research Articles

Sensitivity of surface water and groundwater contributions to streamflow in a tropical glacierized basin under climate change scenarios

Abstract While mountain water faces threats posed by climate change, particularly in snow-dominated and glacierized systems, the role of groundwater in sustaining streamflow in these systems remains elusive. Changing mountain headwaters, marked by reduced snowpacks, retreating glaciers, shifting precipitation patterns, and rising temperatures, pose a crucial question: what is the resilience of streamflow in these mountains, and what role does groundwater play in this resilience? This is particularly uncertain in tropical high mountains where the seasonality of precipitation and glacier melt govern streamflow generation. A glacio-hydrological model was created using the Cold Regions Hydrological Modelling platform to investigate cryosphere-surface water-groundwater interactions in the Quilcayhuanca Basin, in Peru’s Cordillera Blanca. The model was forced by in-situ meteorological observations and parameterized using numerous data sources and process-based studies in the basin. Model results show that during the dry season, 37% of streamflow is generated from groundwater discharge, increasing to 56% during the lowest flows. Evapotranspiration is the largest mass flux from the basin at the peak of the dry season. Precipitation, temperature, and glacier change scenarios were used to assess the sensitivity of basin hydrology to climate change and glacier retreat. In a warmer, wetter, and nearly deglaciated future, Quilcayhuanca basin streamflow is expected to decrease by 4-19% annually, with a larger volumetric change in overland and vadose zone flow than in groundwater flow. The range in values is more closely linked to uncertainty in precipitation change than temperature change. Despite a strong reduction in snow and ice contribution to streamflow with warming and deglaciation, the concomitant increase in precipitation can limit the changes in streamflow and groundwater flow, showcasing the resilience of the system to shifts in climate and glacier cover.

Developing a tile drainage module for the Cold Regions Hydrological Model: lessons from a farm in southern Ontario, Canada

Abstract. Systematic tile drainage is used extensively in poorly drained agricultural lands to remove excess water and improve crop growth; however, tiles can also transfer nutrients from farmlands to downstream surface water bodies, leading to water quality problems. Thus, there is a need to simulate the hydrological behaviour of tile drains to understand the impacts of climate or land management change on agricultural surface and subsurface runoff. The Cold Regions Hydrological Model (CRHM) is a physically based, modular modelling system developed for cold regions. Here, a tile drainage module is developed for CRHM. A multi-variable, multi-criteria model performance evaluation strategy was deployed to examine the ability of the module to capture tile discharge under both winter and summer conditions (NSE > 0.29, RSR < 0.84 and PBias < 20 for tile flow and saturated storage simulations). Initial model simulations run at a 15 min interval did not satisfactorily represent tile discharge; however, model simulations improved when the time step was lengthened to hourly but also with the explicit representation of capillary rise for moisture interactions between the rooting zone and groundwater, demonstrating the significance of capillary rise above the saturated storage layer in the hydrology of tile drains in loam soils. Novel aspects of this module include the sub-daily time step, which is shorter than most existing models, and the use of field capacity and its corresponding pressure head to provide estimates of drainable water and the thickness of the capillary fringe, rather than using detailed soil retention curves that may not always be available. An additional novel aspect is the demonstration that flows in some tile drain systems can be better represented and simulated when related to shallow saturated storage dynamics.

Modelling the regional sensitivity of snowmelt, soil moisture, and streamflow generation to climate over the Canadian Prairies using a basin classification approach

Abstract. This study evaluated the effects of climate perturbations on snowmelt, soil moisture, and streamflow generation in small Canadian Prairies basins using a modelling approach based on classification of basin biophysical characteristics. Seven basin classes that encompass the entirety of the Prairies Ecozone in Canada were determined by cluster analysis of these characteristics. Individual semi-distributed virtual basin (VB) models representing these classes were parameterized in the Cold Regions Hydrological Model (CRHM) platform, which includes modules for snowmelt and sublimation, soil freezing and thawing, actual evapotranspiration (ET), soil moisture dynamics, groundwater recharge, and depressional storage dynamics including fill and spill runoff generation and variable connected areas. Precipitation (P) and temperature (T) perturbation scenarios covering the range of climate model predictions for the 21st century were used to evaluate climate sensitivity of hydrological processes in individual land cover and basin types across the Prairies Ecozone. Results indicated that snow accumulation in wetlands had a greater sensitivity to P and T than that in croplands and grasslands in all basin types. Wetland soil moisture was also more sensitive to T than the cropland and grassland soil moisture. Jointly influenced by land cover distribution and local climate, basin-average snow accumulation was more sensitive to T in the drier and grassland-characterized basins than in the wetter basins dominated by cropland, whilst basin-average soil moisture was most sensitive to T and P perturbations in basins typified by pothole depressions and broad river valleys. Annual streamflow had the greatest sensitivities to T and P in the dry and poorly connected Interior Grasslands (See Fig. 1) basins but the smallest in the wet and well-connected Southern Manitoba basins. The ability of P to compensate for warming-induced reductions in snow accumulation and streamflow was much higher in the wetter and cropland-dominated basins than in the drier and grassland-characterized basins, whilst decreases in cropland soil moisture induced by the maximum expected warming of 6 ∘C could be fully offset by a P increase of 11 % in all basins. These results can be used to (1) identify locations which had the largest hydrological sensitivities to changing climate and (2) diagnose underlying processes responsible for hydrological responses to expected climate change. Variations of hydrological sensitivity in land cover and basin types suggest that different water management and adaptation methods are needed to address enhanced water stress due to expected climate change in different regions of the Prairies Ecozone.

Simulation of the impact of future changes in climate on the hydrology of Bow River headwater basins in the Canadian Rockies

This study diagnoses the impact of projected changes in climate and glacier cover on the hydrology of several natural flowing Bow River headwater basins in the Canadian Rockies: the Bow River at Lake Louise (∼420.7 km2), the Pipestone River near Lake Louise (∼304.2 km2), the Bow River at Banff (∼2192.2 km2) all of which drain the high elevation, snowy, partially glaciated Central Range, and the Elbow River at Calgary (∼1191.9 km2), which drains the drier Front Ranges and foothills, using models created using the modular, flexible, physically based Cold Regions Hydrological Modelling platform (CRHM). Hydrological models were constructed and parameterised in CRHM from local research results to include relevant streamflow generation processes for Canadian Rockies headwater basins, such as blowing snow, avalanching, snow interception and sublimation, energy budget snow and glacier melt, infiltration to frozen and unfrozen soils, hillslope sub-surface water redistribution, wetlands, lakes, evapotranspiration, groundwater flow, surface runoff and open channel flow. Surface layer outputs from Weather Research and Forecasting (WRF) model simulations for the current climate and for the late 21st century climate under a “business-as-usual” scenario, Representative Concentration Pathway 8.5 (RCP8.5) at 4-km resolution, were used to force model simulations to examine the climate change impact. A projected glacier cover under a “business-as-usual” scenario (RCP8.5) was incorporated to assess the impact of concomitant glacier cover decline. Uncalibrated model simulations for the current climate and glacier coverage showed useful predictions of snow accumulation, snowmelt, and streamflow when compared to surface observations from 2000 to 2015. Under the RCP8.5 climate change scenario, the basins of the Bow River at Banff and Elbow River at Calgary will warm up by 4.7 and 4.5 °C respectively and receive 12% to 15% more precipitation annually, with both basins experiencing a greater proportion of precipitation as rainfall. Peak snow accumulation in Bow River Basin will slightly rise by 3 mm, whilst it will drop by 20 mm in Elbow River Basin, and annual snowmelt volume will increase by 43 mm in Bow River Basin but decrease by 55 mm in Elbow River Basin. Snowcovered periods will decline by 37 and 46 days in Bow and Elbow river basins respectively due to suppressed snow redistribution by wind and gravity and earlier melt. The shorter snowcovered period and warmer, wetter climate will increase evapotranspiration and glacier melt, if the glaciers were held constant, and decrease sublimation, lake levels, soil moisture and groundwater levels. The hydrological responses of the basins will differ despite similar climate changes because of differing biophysical characteristics, climates and hydrological processes generating runoff. Climate change with concomitant glacier decline is predicted to increase the peak discharge and mean annual water yield by 12.23 m3 s−1 (+11%) and 11% in the higher elevation basins of the Bow River but will decrease the mean annual peak discharge by 3.58 m3 s−1 (-9%) and increase the mean annual water yield by 18% in the lower elevation basin of the Elbow River. This shows complex and compensatory hydrological process responses to climate change with the reduced glacier contribution reducing the impact of higher precipitation in high elevation headwaters and drier soil conditions and lower spring snowpacks reducing peak discharges despite increased precipitation during spring runoff in the Front Range and foothills headwaters under a warmer climate.

Simulating the hydrological impacts of land use conversion from annual crop to perennial forage in the Canadian Prairies using the Cold Regions Hydrological Modelling platform

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.

The cold regions hydrological modelling platform for hydrological diagnosis and prediction based on process understanding

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.

Landscape and climate conditions influence the hydrological sensitivity to climate change in eastern Canada

Hydrological conditions in cold regions have been shown to be sensitive to climate change. However, a detailed understanding of how regional climate and basin landscape conditions independently influence the current hydrology and its climate sensitivity is currently lacking. This study, therefore, compares the climate sensitivity of the hydrology of two basins with contrasted landscape and meteorological characteristics typical of eastern Canada: a forested boreal climate basin (Montmorency) versus an agricultural hemiboreal climate basin (Acadie). The physically based Cold Regions Hydrological Modelling (CRHM) platform was used to simulate the current and future hydrological processes. Both basin landscape and regional climate drove differences in hydrological sensitivities to climate change. Projected peak SWE were highly sensitive to warming, particularly for milder baseline climate conditions and moderately influenced by differences in landscape conditions. Landscape conditions mediated a wide range of differing hydrological processes and streamflow responses to climate change. The effective precipitation was more sensitive to warming in the forested basin than in the agricultural one, due to reductions in forest canopy interception losses with warming. Under present climate, precipitation and discharge were found to be more synchronized in the greater relief and slopes of the forested basin, whereas under climate change, they are more synchronized in the agricultural basin due to reduced infiltration and storage capacities. Flow through and over agricultural soils translated the increase in water availability under a warmer and wetter climate into higher peak discharges, whereas the porous forest soils dampened the response of peak discharge to increased available water. These findings help diagnose the mechanisms controlling hydrological response to climate change in cold regions forested and agricultural basins.

Recent hydrological response of glaciers in the Canadian Rockies to changing climate and glacier configuration

Abstract. Mountain snow and ice greatly influence the hydrological cycle of alpine regions by regulating both the quantity of and seasonal variations in water availability downstream. This study considers the combined impacts of climate and glacier changes due to recession on the hydrology and water balance of two high-elevation basins in the Canadian Rockies. A distributed, physically based, uncalibrated glacier hydrology model developed in the Cold Regions Hydrological Modelling platform (CRHM) was used to simulate the glacier mass balance and basin hydrology of the Peyto and Athabasca glacier basins in Alberta, Canada. Bias-corrected reanalysis data were used to drive the model. The model calculates the water balance of glacierized basins, influenced by the surface energy and mass balance, and considers the redistribution of snow by wind and avalanches. It was set up using hydrological response units based on elevation bands, surface slope, and aspect, as well as changing land cover. Aerial photos, satellite images and digital elevation models (DEMs) were assimilated to represent the changing configurations of glacier area and the exposure of ice and firn. Observations of glacier mass balance, snow, and glacier ice surface elevation changes at glacier and alpine tundra meteorological stations and streamflow discharge at the glacier outlets were used to evaluate the model performance. Basin hydrology was simulated over two periods, 1965–1975 and 2008–2018, using the observed glacier configurations for those time periods. Both basins have undergone continuous glacier loss over the last 3 to 5 decades, leading to a 6 %–31 % reduction in glacierized area, a 78 %–109 % increase in ice exposure, and changes to the elevation and slope of the glacier surfaces. Air temperatures are increasing, mainly due to increasing winter maximum and summer minimum daily temperatures. Annual precipitation has increased by less than 11 %, but rainfall ratios have increased by 29 %–44 %. The results show that changes in both climate and glacier configuration have influenced the melt rates and runoff and a shift of peak flows in the Peyto Glacier basin from August to July. Glacier melt contributions increased/decreased from 27 %–61 % to 43 %–59 % of the annual discharges. Recent discharges were 3 %–19 % higher than in the 1960s and 1970s. The results suggest that increased exposure of glacier ice and lower surface elevation due to glacier thinning were less influential than climate warming in increasing streamflow. Streamflow from these glaciers continues to increase.

Diagnosing changes in glacier hydrology from physical principles using a hydrological model with snow redistribution, sublimation, firnification and energy balance ablation algorithms

A comprehensive glacier hydrology model was developed within the Cold Regions Hydrological Modelling platform (CRHM) to include modules representing wind flow over complex terrain, blowing snow redistribution and sublimation by wind, snow redistribution by avalanches, solar irradiance to sloping surfaces, surface sublimation, glacier mass balance and runoff, meltwater and streamflow routing. The physically based glacier hydrology model created from these modules in CRHM was applied to simulate the hydrology of the instrumented, glacierized and rapidly deglaciating Peyto and Athabasca glacier research basins in the Canadian Rockies without calibration of parameters from streamflow. It was tested against observed albedo, point and aggregated glacier mass balance, and streamflow and found to successfully simulate surface albedo, snow redistribution, snow and glacier accumulation and ablation, mass balance and streamflow discharge, both when driven by in-situ observations and reanalysis forcing data. Long term modelling results indicate that the increases in discharge from the 1960s to the present are due to increased glacier ice melt contributions, despite declining precipitation and snow melt.

The sensitivity of snow hydrology to changes in air temperature and precipitation in three North American headwater basins

Whether or not the impact of warming on mountain snow and runoff can be offset by precipitation increases has not been well examined, but it is crucially important for future downstream water supply. Using the physically based Cold Regions Hydrological Modelling Platform (CRHM), elasticity (percent change in runoff divided by change in a climate forcing) and the sensitivity of snow regimes to perturbations were investigated in three well-instrumented mountain research basins spanning the northern North American Cordillera. Hourly meteorological observations were perturbed using air temperature and precipitation changes and were then used to force hydrological models for each basin. In all three basins, lower temperature sensitivities of annual runoff volume (≤ 6% °C−1) and higher sensitivities of peak snowpack (−17% °C−1) showed that annual runoff was far less sensitive to temperature than the snow regime. Higher and lower precipitation elasticities of annual runoff (1.5 – 2.1) and peak snowpack (0.7 – 1.1) indicated that the runoff change is primarily attributed to precipitation change and, secondarily, to warming. A low discrepancy between observed and simulated precipitation elasticities showed that the model results are reliable, and one can conduct sensitivity analysis. The air temperature elasticities, however, must be interpreted with care as the projected warmings range beyond the observed temperatures and, hence, it is not possible to test their reliability. Simulations using multiple elevations showed that the timing of peak snowpack was most sensitive to temperature. For the range of warming expected from North American climate model simulations, the impacts of warming on annual runoff, but not on peak snowpack, can be offset by the size of precipitation increases projected for the near-future period 2041–2070. To offset the impact of 2 °C warming on annual runoff, precipitation would need to increase by less than 5% in all three basins. To offset the impact of 2 °C warming on peak snowpack, however, precipitation would need to increase by 12% in Wolf Creek in Yukon Territory, 18% in Marmot Creek in the Canadian Rockies, and an amount greater than the maximum projected at Reynolds Mountain in Idaho. The role of increased precipitation as a compensator for the impact of warming on snowpack is more effective at the highest elevations and higher latitudes. Increased precipitation leads to resilient and strongly coupled snow and runoff regimes, contrasting sharply with the sensitive and weakly coupled regimes at low elevations and in temperate climate zones.

Sensitivity of forest–snow interactions to climate forcing: Local variability in a Pyrenean valley

Mountain forests affect spatial and temporal variability of snow processes through snow interception and by modifying the energy balance of snowpack. The high sensitivity of snow cover to seasonal temperatures in mid–latitude mountains is well known and is of particular interest with regard to a future warmer climate. The snowpack in the Pyrenees is expected to be the most impacted by climate change in the Mediterranean mountains, where future climate trends project rising temperatures and decreasing precipitation. This study analyzes how changes in temperature and precipitation can affect current forest–snow interactions in four forests, located near each other but under contrasting topographic settings, in the Spanish Pyrenees. This understanding will allow us to anticipate the future hydrological responses of Pyrenean forested mountain basins. The research was accomplished by performing a sensitivity analysis using simulations from the Cold Regions Hydrological Model (CRHM) and by comparing forest canopy sites (F) vs. openings (O). The CRHM platform focuses on the incorporation of physically based descriptions of snow–dominated regions hydrological processes. It was found that forest cover induced different snowpack sensibility to climatic change conditions in the studied forests. Delayed onset of snow accumulation (F: 13 days·°C−1; O: 5 days·°C−1) and reduced snowpack duration (F: 28 %·°C−1; O: 23 %·°C−1) under warmer temperatures were more intense in areas beneath the forest canopy compared to openings. A lower annual peak of snow water equivalent (SWE) (F: 81 mm·°C−1; O: 129 mm·°C−1), earlier melt-out date (F: 8 days·°C−1; O: 10 days·°C−1) and slower melting rates (F: 0.4 mm·day−1·°C−1; O: 0.5 mm·day−1·°C−1) with increasing temperatures were more intense in forest openings. The forest–driven reduction in snowpack duration (40%) was significantly enhanced with warming (10% per °C). Lower precipitation (20% precipitation reduction) could increase the response of this forest effect to warming (32%), while higher precipitation (20% precipitation increment) could reduce it (−26%). There was relevant topographic variability in the forest−snow interactions in response to climate change among the study stands, despite their proximity.

Advances in the simulation of nutrient dynamics in cold climate agricultural basins: Developing new nitrogen and phosphorus modules for the Cold Regions Hydrological Modelling Platform

Excess nutrients in aquatic ecosystems is a major water quality problem globally. Worsening eutrophication issues are notable in cold temperate areas, with pervasive problems in many agriculturally dominated catchments. Predicting nutrient export to rivers and lakes is particularly difficult in cold agricultural environments because of challenges in modelling snow, soil, frozen ground, climate, and anthropogenic controls. Previous research has shown that the use of many popular small basin nutrient models can be problematic in cold regions due to poor representation of cold region hydrology. In this study, the Cold Regions Hydrological Modelling Platform (CRHM), a modular modelling system, which has been widely deployed across Canada and cold regions worldwide, was used to address this problem. CRHM was extended to simulate biogeochemical and transport processes for nitrogen and phosphorus through a complex of new process-based modules that represent physicochemical processes in snow, soil and freshwater. Agricultural practices such as tillage and fertilizer application, which strongly impact the availability and release of soil nutrients, can be explicitly represented in the model. A test case in an agricultural basin draining towards Lake Winnipeg shows that the model can capture the extreme hydrology and nutrient load variability of small agricultural basins at hourly time steps. It was demonstrated that fine temporal resolutions are an essential modelling requisite to capture strong concentration changes in agricultural tributaries in cold agricultural environments. Within these ephemeral and intermittent streams, on average, 30%, 31%, 20%, and 16% of the total annual load of nitrate (NO3), ammonium (NH4), soluble reactive phosphorus (SRP), and particulate phosphorous (partP)NO3, NH4, SRP and partP occurred during the episodic snowmelt freshet (∼9 days, accounting for 21% of the annual flow), but shows extreme temporal variation. The new nutrient modules are critical tools for predicting nutrient export from small agricultural drainage basins in cold climates via better representation of key hydrological processes, and a temporal resolution more suited to capture dynamics of ephemeral and intermittent streams.

Simulating site-scale permafrost hydrology: Sensitivity to modelling decisions and air temperature

To predict future hydrological cycling in permafrost-dominated regions requires consideration of complex hydrological interactions that involve cryospheric states and fluxes, and hence thermodynamics. This challenges many hydrological models, particularly those applied in the Arctic. This study presents the implementation and validation of set of algorithms representing permafrost and frozen ground dynamics, coupled into a physically based, modular, cold regions hydrological model at two tundra sites in northern Yukon Territory, Canada. Hydrological processes represented in the model include evapotranspiration, soil moisture dynamics, flow through organic and mineral terrain, ground freeze–thaw, infiltration to frozen and unfrozen soils, snowpack energy balance, and the accumulation, wind redistribution, sublimation, and canopy interception of snow. The model was able to successfully represent observed ground surface temperature, ground thaw and snow accumulation at the two sites without calibration. A sensitivity analysis of simulated ground thaw revealed that the soil properties of the upper organic layer dominated the model response; however, its performance was robust for a range of realistic physical parameters. Different modelling decisions were assessed by removing the physically based algorithms for snowpack dynamics and ground surface temperature and replacing them with empirical approaches. Results demonstrate that more physically based approaches should be pursued to reduce uncertainties in poorly monitored environments. Finally, the model was driven by three climate warming scenarios to assess the sensitivity of snow redistribution and ablation processes and ground thaw to warming temperatures. This showed great sensitivity of snow regime and soil thaw to warming, even in the cold continental climate of the northwestern Canadian Arctic. The results are pertinent to transportation infrastructure and water management in this remote, cold, sparsely gauged region where traditional approaches to hydrological prediction are not possible.

Sensitivity analysis of hydrological processes to perturbed climate in a southern boreal forest basin

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 evaluation of the potential of global data products for snow hydrological modelling in ungauged high-alpine catchments

Abstract. For many ungauged mountain regions, global datasets of different meteorological and land surface parameters are the only data sources available. However, their applicability in modelling high-alpine regions has been insufficiently investigated so far. Therefore, we tested a suite of globally available datasets by applying the physically based Cold Regions Hydrological Model (CRHM) for a 10-year (September 2000–August 2010) period in the gauged high-alpine Research Catchment Zugspitze (RCZ), which is 12 km2 and located in the European Alps. Besides meteorological data, snow depth is measured at two stations. We ran CRHM with a reference run with in situ-measured meteorological data and a 2.5 m high-resolution digital elevation model (DEM) for the parameterization of the surface characteristics. Regarding different meteorological setups, we used 10 different globally available datasets (including versions of ERA, GLDAS, CFSR, CHIRPS) and additionally one transferred dataset from a similar station in the vicinity. Regarding the different DEMs, we used ALOS (Advanced Land Observing Satellite) and SRTM (Shuttle Radar Topography Mission) (both 30 m) as well as GTOPO30 (1 km). The following two main goals were investigated: (a) the reliability of simulations of snow depth, specific snow hydrological parameters and runoff with global meteorological products and (b) the influence of different global DEMs on snow hydrological simulations in such a topographically complex terrain. The range between all setups in mean decadal temperature is high at 3.5 ∘C and for the mean decadal precipitation sum at 1510 mm, which subsequently leads to large offsets in the snow hydrological results. Only three meteorological setups, the reference, the transferred in situ dataset and the CHIRPS dataset, substituting precipitation only, showed agreeable results when comparing modelled to measured snow depth. Nevertheless, those setups showed obvious differences in the catchment's runoff regime and in snow depth, snow cover, ablation period, the date, and quantity of maximum snow water equivalent in the entire catchment and in specific parts. All other globally available meteorological datasets performed worse. In contrast, all globally available DEM setups reproduced snow depth, the snow hydrological parameters and runoff quite well. Differences occurred mainly due to differences in radiation model input due to different spatial realizations. Even though SRTM and ALOS have the same spatial resolution, they showed considerable differences due to their different product origins. Despite the fact that the very coarse GTOPO30 DEM performed relatively well on the catchment mean, we advise against using this product in such heterogeneous high-alpine terrain since small-scale topographic characteristics cannot be captured. While global meteorological data are not suitable for sound snow hydrological modelling in the RCZ, the choice of the DEM with resolutions in the decametre level is less critical. Nevertheless, global meteorological data can be a valuable source to substitute single missing variables. For the future, however, we expect an increasing role of global data in modelling ungauged high-alpine basins due to further product improvements, spatial refinements and further steps regarding assimilation with remote sensing data.

Summary and synthesis of Changing Cold Regions Network (CCRN) research in the interior of western Canada – Part 2: Future change in cryosphere, vegetation, and hydrology

Abstract. The interior of western Canada, like many similar cold mid- to high-latitude regions worldwide, is undergoing extensive and rapid climate and environmental change, which may accelerate in the coming decades. Understanding and predicting changes in coupled climate–land–hydrological systems are crucial to society yet limited by lack of understanding of changes in cold-region process responses and interactions, along with their representation in most current-generation land-surface and hydrological models. It is essential to consider the underlying processes and base predictive models on the proper physics, especially under conditions of non-stationarity where the past is no longer a reliable guide to the future and system trajectories can be unexpected. These challenges were forefront in the recently completed Changing Cold Regions Network (CCRN), which assembled and focused a wide range of multi-disciplinary expertise to improve the understanding, diagnosis, and prediction of change over the cold interior of western Canada. CCRN advanced knowledge of fundamental cold-region ecological and hydrological processes through observation and experimentation across a network of highly instrumented research basins and other sites. Significant efforts were made to improve the functionality and process representation, based on this improved understanding, within the fine-scale Cold Regions Hydrological Modelling (CRHM) platform and the large-scale Modélisation Environmentale Communautaire (MEC) – Surface and Hydrology (MESH) model. These models were, and continue to be, applied under past and projected future climates and under current and expected future land and vegetation cover configurations to diagnose historical change and predict possible future hydrological responses. This second of two articles synthesizes the nature and understanding of cold-region processes and Earth system responses to future climate, as advanced by CCRN. These include changing precipitation and moisture feedbacks to the atmosphere; altered snow regimes, changing balance of snowfall and rainfall, and glacier loss; vegetation responses to climate and the loss of ecosystem resilience to wildfire and disturbance; thawing permafrost and its influence on landscapes and hydrology; groundwater storage and cycling and its connections to surface water; and stream and river discharge as influenced by the various drivers of hydrological change. Collective insights, expert elicitation, and model application are used to provide a synthesis of this change over the CCRN region for the late 21st century.

A Review of Hydrological Models Applied in the Permafrost-Dominated Arctic Region

The Arctic region is the most sensitive region to climate change. Hydrological models are fundamental tools for climate change impact assessment. However, due to the extreme weather conditions, specific hydrological process, and data acquisition challenges in the Arctic, it is crucial to select suitable hydrological model(s) for this region. In this paper, a comprehensive review and comparison of different models is conducted based on recently available studies. The functionality, limitations, and suitability of the potential hydrological models for the Arctic hydrological process are analyzed, including: (1) The surface hydrological models Topoflow, DMHS (deterministic modeling hydrological system), HBV (Hydrologiska Byråns Vattenbalansavdelning), SWAT (soil and water assessment tool), WaSiM (water balance simulation model), ECOMAG (ecological model for applied geophysics), and CRHM (cold regions hydrological model); and (2) the cryo-hydrogeological models ATS (arctic terrestrial simulator), CryoGrid 3, GEOtop, SUTRA-ICE (ice variant of the existing saturated/unsaturated transport model), and PFLOTRAN-ICE (ice variant of the existing massively parallel subsurface flow and reactive transport model). The review finds that Topoflow, HBV, SWAT, ECOMAG, and CRHM are suitable for studying surface hydrology rather than other processes in permafrost environments, whereas DMHS, WaSiM, and the cryo-hydrogeological models have higher capacities for subsurface hydrology, since they take into account the three phase changes of water in the near-surface soil. Of the cryo-hydrogeological models reviewed here, GEOtop, SUTRA-ICE, and PFLOTRAN-ICE are found to be suitable for small-scale catchments, whereas ATS and CryoGrid 3 are potentially suitable for large-scale catchments. Especially, ATS and GEOtop are the first tools that couple surface/subsurface permafrost thermal hydrology. If the accuracy of simulating the active layer dynamics is targeted, DMHS, ATS, GEOtop, and PFLOTRAN-ICE are potential tools compared to the other models. Further, data acquisition is a challenging task for cryo-hydrogeological models due to the complex boundary conditions when compared to the surface hydrological models HBV, SWAT, and CRHM, and the cryo-hydrogeological models are more difficult for non-expert users and more expensive to run compared to other models.

Diagnosis of future changes in hydrology for a Canadian Rockies headwater basin

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.

On the Ability of LIDAR Snow Depth Measurements to Determine or Evaluate the HRU Discretization in a Land Surface Model

To find the adequate spatial model discretization scheme, which balances the models capabilities and the demand for representing key features in reality, is a challenging task. It becomes even more challenging in high alpine catchments, where the variability of topography and meteorology over short distances strongly influences the distribution of snow cover, the dominant component in the alpine water cycle. For the high alpine Research Catchment Zugspitze (RCZ) a new method for objective delineation of hydrological response units (HRUs) using a time series of high resolution LIDAR derived snow depth maps and the physiographic properties of the RCZ is introduced. Via principle component analysis (PCA) of these maps, a dominant snow depth pattern, that turned out to be largely defined during the (winter) accumulation period was identified. This dominant pattern serves as a reference for HRU delineations on the basis of cluster analyses of the catchment’s physiographic properties. The method guarantees for an appropriate, objective, spatial discretization scheme, which allows for a reliable and meaningful reproduction of snow cover variability with the Cold Regions Hydrological Model—at the same time avoiding significant increase of computational demands. Different HRU schemes were evaluated with measured snow depth and the comparison of their model results identified significant differences in model output and best performance of the scheme which best represents measured snow depth distribution.

Assimilating snow observations to snow interception process simulations

AbstractSnow interception is a crucial hydrological process in cold regions needleleaf forests, but is rarely measured directly. Indirect estimates of snow interception can be made by measuring the difference in the increase in snow accumulation between the forest floor and a nearby clearing over the course of a storm. Pairs of automatic weather stations with acoustic snow depth sensors provide an opportunity to estimate this, if snow density can be estimated reliably. Three approaches for estimating fresh snow density were investigated: weighted post‐storm density increments from the physically based Snobal model, fresh snow density estimated empirically from air temperature (Hedstrom, N. R., et al. [1998]. Hydrological Processes, 12, 1611–1625), and fresh snow density estimated empirically from air temperature and wind speed (Jordan, R. E., et al. [1999]. Journal of Geophysical Research, 104, 7785–7806). Automated snow depth observations from adjacent forest and clearing sites and estimated snow densities were used to determine snowstorm snow interception in a subalpine forest in the Canadian Rockies, Alberta, Canada. Then the estimated snow interception and measured interception information from a weighed, suspended tree and a time‐lapse camera were assimilated into a model, which was created using the Cold Regions Hydrological Modelling platform (CRHM), using Ensemble Kalman Filter or a simple rule‐based direct insertion method. Interception determined using density estimates from the Hedstrom‐Pomeroy fresh snow density equation agreed best with observations. Assimilating snow interception information from automatic snow depth measurements improved modelled snow interception timing by 7% and magnitude by 13%, compared to an open loop simulation driven by a numerical weather model; its accuracy was close to that simulated using locally observed meteorological data. Assimilation of tree‐measured snow interception improved the snow interception simulation timing and magnitude by 18 and 19%, respectively. Time‐lapse camera snow interception information assimilation improved the snow interception simulation timing by 32% and magnitude by 7%. The benefits of assimilation were greatly influenced by assimilation frequency and quality of the forcing data.