Spatio‐temporal controls of snowmelt and runoff generation during rain‐on‐snow events in a mid‐latitude mountain catchment

A network of 30 standalone snow monitoring stations was used to investigate the snow cover distribution, snowmelt dynamics, and runoff generation during two rain‐on‐snow (ROS) events in a 40 km² montane catchment in the Black Forest region of southwestern Germany. A multiple linear regression analysis using elevation, aspect, and land cover as predictors for the snow water equivalent (SWE) distribution within the catchment was applied on an hourly basis for two significant ROS flood events that occurred in December 2012. The available snowmelt water, liquid precipitation, as well as the total retention storage of the snow cover were considered in order to estimate the amount of water potentially available for the runoff generation. The study provides a spatially and temporally distributed picture of how the two observed ROS floods developed in the catchment. It became evident that the retention capacity of the snow cover is a crucial mechanism during ROS. It took several hours before water was released from the snowpack during the first ROS event, while retention storage was exceeded within 1 h from the start of the second event. Elevation was the most important terrain feature. South‐facing terrain contributed more water for runoff than north‐facing slopes, and only slightly more runoff was generated at open compared to forested areas. The results highlight the importance of snowmelt together with liquid precipitation for the generation of flood runoff during ROS and the large temporal and spatial variability of the relevant processes. Copyright © 2015 John Wiley & Sons, Ltd.     

Analysis of snowpack dynamics during the spring melt season for a sub‐alpine site using point measurements and numerical modeling

Snowpack dynamics through October 2014–June 2017 were described for a forested, sub‐alpine field site in southeastern Wyoming. Point measurements of wetness and density were combined with numerical modeling and continuous time series of snow depth, snow temperature, and snowpack outflow to identify 5 major classes of distinct snowpack conditions. Class (i) is characterized by no snowpack outflow and variable average snowpack temperature and density. Class (ii) is characterized by short durations of liquid water in the upper snowpack, snowpack outflow values of 0.0008–0.005 cm hr^?1, an increase in snowpack temperature, and average snow density between 0.25–0.35 g cm^?3. Class (iii) is characterized by a partially saturated wetness profile, snowpack outflow values of 0.005–0.25 cm hr^?1, snowpack temperature near 0 °C, and average snow density between 0.25–0.40 g cm^?3. Class (iv) is characterized by strong diurnal snowpack outflow pattern with values as high as 0.75 cm hr^?1, stable snowpack temperature near 0 °C, and stable average snow density between 0.35–0.45 g cm^?3. Class (v) occurs intermittently between Classes (ii)–(iv) and displays low snowpack outflow values between 0.0008–0.04 cm hr^?1, a slight decrease in temperature relative to the preceding class, and similar densities to the preceding class. Numerical modeling of snowpack properties with SNOWPACK using both the Storage Threshold scheme and Richards' equation was used to quantify the effect of snowpack capillarity on predictions of snowpack outflow and other snowpack properties. Results indicate that both simulations are able to predict snow depth, snow temperature, and snow density reasonably well with little difference between the 2 water transport schemes. Richards' equation more accurately simulates the timing of snowpack outflow over the Storage Threshold scheme, especially early in the melt season and at diurnal timescales.     

A modelling framework to simulate field‐scale nitrate response and transport during snowmelt: The WINTRA model

Modelling nutrient transport during snowmelt in cold regions remains a major scientific challenge. A key limitation of existing nutrient models for application in cold regions is the inadequate representation of snowmelt, including hydrological and biogeochemical processes. This brief period can account for more than 80% of the total annual surface runoff in the Canadian Prairies and Northern Canada and processes such as atmospheric deposition, overwinter redistribution of snow, ion exclusion from snow crystals, frozen soils, and snow‐covered area depletion during melt influence the distribution and release of snow and soil nutrients, thus affecting the timing and magnitude of snowmelt runoff nutrient concentrations. Research in cold regions suggests that nitrate (NO₃) runoff at the field‐scale can be divided into 5 phases during snowmelt. In the first phase, water and ions originating from ion‐rich snow layers travel and diffuse through the snowpack. This process causes ion concentrations in runoff to gradually increase. The second phase occurs when this snow ion meltwater front has reached the bottom of the snowpack and forms runoff to the edge‐of‐the‐field. During the third and fourth phases, the main source of NO₃ transitions from the snowpack to the soil. Finally, the fifth and last phase occurs when the snow has completely melted, and the thawing soil becomes the main source of NO₃ to the stream. In this research, a process‐based model was developed to simulate hourly export based on this 5‐phase approach. Results from an application in the Red River Basin of southern Manitoba, Canada, shows that the model can adequately capture the dynamics and rapid changes of NO₃ concentrations during this period at relevant temporal resolutions. This is a significant achievement to advance the current nutrient modelling paradigm in cold climates, which is generally limited to satisfactory results at monthly or annual resolutions. The approach can inform catchment‐scale nutrient models to improve simulation of this critical snowmelt period.     

One‐year‐long runoff forecast by a single snowpack evaluation

A degree‐day‐based model is presented for a 1 year ahead runoff forecast, with 1 day time steps. The input information is a single snowpack evaluation collected at the beginning of the snowmelt season. The snow‐cover dynamics, the key information for long‐term snowmelt forecast, are described by the snow‐line dynamics, i.e. by the movements of the downhill snowpack limit. The snowmelt volume, estimated by the snow‐line dynamics, is the exogenous input of an autoregressive transformation model. The model is calibrated by a least‐squares procedure on the basis of observed daily runoff data and the corresponding measurements of the snowpack volume (one measurement per year). A real‐world case study on the Alto Tunuyan River basin (2380 km², Argentinean Andes) is presented. The 1 year ahead Alto Tunuyan River runoff patterns, computed for both calibration and validation periods, reveal high agreement with observed streamflows. Copyright © 2004 John Wiley & Sons, Ltd.     

Seasonal snowpack dynamics and runoff in a cool temperate forest: lysimeter experiment in Niigata,Japan

Seasonal snowpack dynamics are described through field measurements under contrasting canopy conditions for a mountainous catchment in the Japan Sea region. Microclimatic data, snow accumulation, albedo and lysimeter runoff are given through the complete winter season 2002–03 in (1) a mature cedar stand, (2) a larch stand, and (3) a regenerating cedar stand or opening. The accumulation and melt of seasonal snowpack strongly influences streamflow runoff during December to May, including winter baseflow, mid‐winter melt, rain on snow, and diurnal peaks driven by radiation melt in spring. Lysimeter runoff at all sites is characterized by constant ground melt of 0·8–1·0 mm day⁻¹. Rapid response to mid‐winter melt or rainfall shows that the snowpack remains in a ripe or near‐ripe condition throughout the snow‐cover season. Hourly and daily lysimeter discharge was greatest during rain on snow (e.g. 7 mm h⁻¹ and 53 mm day⁻¹ on 17 December) with the majority of runoff due to rainfall passing through the snowpack as opposed to snowmelt. For both rain‐on‐snow and radiation melt events lysimeter discharge was generally greatest at the open site, although there were exceptions such as during interception melt events. During radiation melt instantaneous discharge was up to 4·0 times greater in the opening compared with the mature cedar, and 48 h discharge was up to 2·5 times greater. Perhaps characteristic of maritime climates, forest interception melt is shown to be important in addition to sublimation in reducing snow accumulation beneath dense canopies. While sublimation represents a loss from the catchment water balance, interception melt percolates through the snowpack and contributes to soil moisture during the winter season. Strong differences in microclimate and snowpack albedo persisted between cedar, larch and open sites, and it is suggested further work is needed to account for this in hydrological simulation models. Copyright © 2005 John Wiley & Sons, Ltd.     

Modelling the spatial–temporal variability of spring snowmelt in an arctic catchment

Arctic spring landscapes are usually characterized by a mosaic of coexisting snow‐covered and bare ground patches. This phenomenon has major implications for hydrological processes, including meltwater production and runoff. Furthermore, as indicated by aircraft observations, it affects land‐surface–atmosphere exchanges, leading to a high degree of variability in surface energy terms during melt. The heterogeneity and related differences when certain parts of the landscape become snow free also affects the length of the growing season and the carbon cycle. Small‐scale variability in arctic snowmelt is addressed here by combining a spatially distributed end‐of‐winter snow cover with simulations of variable snowmelt energy balance factors for the small arctic catchment of Trail Valley Creek (63 km²). Throughout the winter, snow in arctic tundra basins is redistributed by frequent blowing snow events. Areas of above‐ or below‐average end‐of‐winter snow water equivalents were determined from land‐cover classifications, topography, land‐cover‐based snow surveys, and distributed surface wind‐field simulations. Topographic influences on major snowmelt energy balance factors (solar radiation and turbulent fluxes of sensible and latent heat) were modelled on a small‐scale (40 m) basis. A spatially variable complete snowmelt energy balance was subsequently computed and applied to the distributed snow cover, allowing the simulation of the progress of melt throughout the basin. The emerging patterns compared very well visually to snow cover observations from satellite images and aerial photographs. Results show the relative importance of variable end‐of‐winter snow cover, spatially distributed melt energy fluxes, and local advection processes for the development of a patchy snow cover. This illustrates that the consideration of these processes is crucial for an accurate determination of snow‐covered areas, as well as the location, timing, and amount of meltwater release from arctic catchments, and should, therefore, be included in hydrological models. Furthermore, the study shows the need for a subgrid parameterization of these factors in the land surface schemes of larger scale climate models. Copyright © 2005 John Wiley & Sons, Ltd.     

A temperature‐precipitation‐based model of thirty‐year mean snowpack accumulation and melt in Oregon,USA

High‐resolution, spatially extensive climate grids can be useful in regional hydrologic applications. However, in regions where precipitation is dominated by snow, snowmelt models are often used to account for timing and magnitude of water delivery. We developed an empirical, nonlinear model to estimate 30‐year means of monthly snowpack and snowmelt throughout Oregon. Precipitation and temperature for the period 1971–2000, derived from 400‐m resolution PRISM data, and potential evapotranspiration (estimated from temperature and day length) drive the model. The model was calibrated using mean monthly data from 45 SNOTEL sites and accurately estimated snowpack at 25 validation sites: R² = 0·76, Nash‐Sutcliffe Efficiency (NSE) = 0·80. Calibrating it with data from all 70 SNOTEL sites gave somewhat better results (R² = 0·84, NSE = 0·85). We separately applied the model to SNOTEL stations located < 200 and ≥ 200 km from the Oregon coast, since they have different climatic conditions. The model performed equally well for both areas. We used the model to modify moisture surplus (precipitation minus potential evapotranspiration) to account for snowpack accumulation and snowmelt. The resulting values accurately reflect the shape and magnitude of runoff at a snow‐dominated basin, with low winter values and a June peak. Our findings suggest that the model is robust with respect to different climatic conditions, and that it can be used to estimate potential runoff in snow‐dominated basins. The model may allow high‐resolution, regional hydrologic comparisons to be made across basins that are differentially affected by snowpack, and may prove useful for investigating regional hydrologic response to climate change. Published in 2011 by John Wiley & Sons, Ltd.     

Applicability of isotopic hydrograph separation in a suburban basin during snowmelt

C. H. TAYLOR Methodological issues associated with isotopic hydrograph separations (IHSs) in built-up environments are explored using results from the 1990 spring melt in a suburban basin in Peterborough, Ontario, Canada. The hetrogeneous nature of suburban environments complicates the selection of appropriate isotopic signatures for event and pre-event waters. Near-stream groundwater δ¹⁸O sampled from wells was poorly mixed, such that the pre-event water signature was best characterized by δ¹⁸O in pre-melt baseflow or discharge from a headwater spring. The event water signature during snowmelt can be characterized using δ¹⁸O in the pre-melt snowpack, surface runoff samples or meltwater from lysimeters. However, the use of snowpack δ¹⁸O may be inappropriate in suburban basins where meltwater from thin snowcover may exhibit pronounced responses to δ¹⁸O in rainfall contributions. Intensive sampling of the spatial variability of runoff or meltwater δ¹⁸O may be required to characterize the average event water signature adequately. Rainfall δ¹⁸O provided an appropriate event water signal during a large rain on snow event, and differences between this IHS and one generated using an event water signature that included meltwater contributions from snow-covered surfaces were within the uncertainty attributable to the analytical error in δ¹⁸O values. Event water supplied 55-63% of the peak discharge and 48-58% of total runoff from the basin during the melt, which is consistent with the fraction of the basin that has been developed. These results contrast with IHSs conducted in forested basins that suggest that stormflow is dominated by pre-event water contributions.     

Modified passive capillary samplers for collecting samples of snowmelt infiltration for stable isotope analysis in remote,seasonally inaccessible watersheds 2: field evaluation

Twelve modified passive capillary samplers (M‐PCAPS) were installed in remote locations within a large, alpine watershed located in the southern Rocky Mountains of Colorado to collect samples of infiltration during the snowmelt and summer rainfall seasons. These samples were collected in order to provide better constraints on the isotopic composition of soil‐water endmembers in the watershed. The seasonally integrated stable isotope composition (δ¹⁸O and δ²H) of soil‐meltwater collected with M‐PCAPS installed at shallow soil depths < 10 cm was similar to the seasonally integrated isotopic composition of bulk snow taken at the soil surface. However, meltwater which infiltrated to depths > 20 cm evolved along an isotopic enrichment line similar to the trendline described by the evolution of fresh snow to surface runoff from snowmelt in the watershed. Coincident changes in geochemistry were also observed at depth suggesting that the isotopic and geochemical composition of deep infiltration may be very different from that obtained by surface and/or shallow‐subsurface measurements. The M‐PCAPS design was also used to estimate downward fluxes of meltwater during the snowmelt season. Shallow and deep infiltration averaged 8·4 and 4·7 cm of event water or 54 and 33% of the measured snow water equivalent (SWE), respectively. Finally, dominant shallow‐subsurface runoff processes occurring during snowmelt could be identified using geochemical data obtained with the M‐PCAPS design. One soil regime was dominated by a combination of slow matrix flow in the shallow soil profile and fast preferential flow at depth through a layer of platy, volcanic rocks. The other soil regime lacked the rock layer and was dominated by slow matrix flow. Based on these results, the M‐PCAPS design appears to be a useful, robust methodology to quantify soil‐water fluxes during the snowmelt season and to sample the stable isotopic and geochemical composition of soil‐meltwater endmembers in remote watersheds. Copyright © 2009 John Wiley & Sons, Ltd.     

Using stable isotopes to estimate travel times in a data‐sparse Arctic catchment: Challenges and possible solutions

Use of isotopes to quantify the temporal dynamics of the transformation of precipitation into run‐off has revealed fundamental new insights into catchment flow paths and mixing processes that influence biogeochemical transport. However, catchments underlain by permafrost have received little attention in isotope‐based studies, despite their global importance in terms of rapid environmental change. These high‐latitude regions offer limited access for data collection during critical periods (e.g., early phases of snowmelt). Additionally, spatio‐temporal variable freeze–thaw cycles, together with the development of an active layer, have a time variant influence on catchment hydrology. All of these characteristics make the application of traditional transit time estimation approaches challenging. We describe an isotope‐based study undertaken to provide a preliminary assessment of travel times at Siksik Creek in the western Canadian Arctic. We adopted a model–data fusion approach to estimate the volumes and isotopic characteristics of snowpack and meltwater. Using samples collected in the spring/summer, we characterize the isotopic composition of summer rainfall, melt from snow, soil water, and stream water. In addition, soil moisture dynamics and the temporal evolution of the active layer profile were monitored. First approximations of transit times were estimated for soil and streamwater compositions using lumped convolution integral models and temporally variable inputs including snowmelt, ice thaw, and summer rainfall. Comparing transit time estimates using a variety of inputs revealed that transit time was best estimated using all available inflows (i.e., snowmelt, soil ice thaw, and rainfall). Early spring transit times were short, dominated by snowmelt and soil ice thaw and limited catchment storage when soils are predominantly frozen. However, significant and increasing mixing with water in the active layer during the summer resulted in more damped steam water variation and longer mean travel times (~1.5 years). The study has also highlighted key data needs to better constrain travel time estimates in permafrost catchments.     

Seasonal transition of hydrological processes in a slow‐moving landslide in a snowy region

A comprehensive understanding of seasonal hydrological dynamics is required to describe the influence of pore‐water pressure on the stability of landslides in snowy regions. This study reports on the results of continuous meteorological and hydrological observations over 2 years on a landslide body comprising Neogene sedimentary rocks in northern Japan, where a thick (3–5 m) seasonal snowpack covers the land surface. Monitoring of the volumetric water content in shallow unsaturated zones (<0.8 m depth) and pore‐water pressure in saturated bedrock at depths of 2.0 and 5.2 m revealed clear seasonality in hydrological responses to rainfall and meltwater supply. During snow‐free periods, both the shallow soil moisture and deep pore‐water pressure responded rapidly to intense rainwater infiltration. In contrast, during snowmelt, the deep pore pressure fluctuated in accordance with the daily cycle of meltwater input, without notable changes in shallow moisture conditions. During occasional foehn events that cause intense snow melting in midwinter, meltwater flows preferentially through the layered snowpack, converging to produce a localized water supply at the ground surface. This episodically triggers a significant rise in pore‐water pressure. The seasonal differences in hydrological responses were characterized by a set of newly proposed indices for the magnitude and quickness of increases in the pressure head near the sliding surface. Under snow‐covered conditions, the magnitude of the pressure increase tends to be suppressed, probably owing to a reduction in infiltration caused by a seasonal decrease in the permeability of surface soils, and effective pore‐water drainage through the highly conductive colluvial layer. Deep groundwater flow within bedrock remained in a steady upwelling state, enhanced by increasing moisture in shallow soils under snow cover, reflecting the convergence of subsurface water from surrounding hillslopes.     

Modification and testing of a one‐dimensional energy and mass balance model for supraglacial snowpacks

A one‐dimensional energy and mass balance snow model (SNTHERM) has been modified for use with supraglacial snowpacks and applied to a point on Haut Glacier d'Arolla, Switzerland. It has been adapted to incorporate the underlying glacier ice and a site‐specific, empirically derived albedo routine. Model performance was tested against continuous measurements of snow depth and meltwater outflow from the base of the snowpack, and intermittent measurements of surface albedo and snowpack density profiles collected during the 1993 and 2000 melt seasons. Snow and ice ablation was simulated accurately. The timing of the daily pattern of meltwater outflow was well reproduced, although magnitudes were generally underestimated, possibly indicating preferential flow into the snowpack lysimeter. The model was used to assess the quantity of meltwater stored temporally within the unsaturated snowpack and meltwater percolation rates, which were found to be in agreement with dye tracer experiments undertaken on this glacier. As with other energy balance studies on alpine valley glaciers, the energy available for melt was dominated by net radiation (64%), with a sizable contribution from sensible heat flux (36%) and with a negligible latent heat flux overall, although there was more complex temporal variation on diurnal timescales. A basic sensitivity analysis indicated that melt rates were most sensitive to radiation, air temperature and snowpack density, indicating the need to accurately extrapolate/interpolate these variables when developing a spatially distributed framework for this model. Copyright © 2008 John Wiley & Sons, Ltd.     

Seasonal evolution of meltwater generation,storage and discharge at a non‐temperate glacier in Svalbard

In glacierized catchments, meteorological inputs driving surface melting are translated into runoff outputs mediated by the glacier hydrological system: analysis of the relationship between meteorology and diurnal and seasonal patterns of runoff should reflect the functioning of that system, with the role of meltwater storage likely to be of particular importance. Daily meltwater storage is determined for a glacier at 78 °N in the Svalbard archipelago, by comparing inputs calculated from a surface energy balance model with measured outputs (proglacial discharge). Solar radiation, air temperature, wind speed and proglacial discharge are then analysed by regression and time‐series methods, in order to assess the meteorology–discharge relationship and its variation at diurnal and seasonal time‐scales. The recorded discharge time‐series can be divided into two contrasting intervals: up to early August, proglacial discharge was high and variable, mean hydrographs showed little indication of diurnal cycling, ARIMA models of discharge indicated a non‐seasonal, moving‐average generating process, and there was a net loss of meltwater from storage; from early August, proglacial discharge was low and relatively invariable, but with clearer diurnal cycles, regression models of discharge showed substantially improved correlations with air temperature and solar radiation, ARIMA models indicated a non‐seasonal, autoregressive generating process, and eventually a seasonal component, and there was a net gain in meltwater storage. The transition between the two periods is brief compared with the duration of the melt season. The runoff response to meteorology therefore lacks the strongly progressive element previously identified in mid‐latitude glacierized catchments. In particular, the glacier hydrological system only appears responsive to diurnal forcing following the depletion of the seasonal snowpack meltwater store. Copyright © 2001 John Wiley & Sons, Ltd.     

Hydroclimate controls over seasonal sediment yield in two adjacent High Arctic watersheds

Interannual variations in seasonal sediment transfer in two High Arctic non‐glacial watersheds were evaluated through three summers of field observations (2003–2005). Total seasonal discharge, controlled by initial watershed snow water equivalence (SWE) was the most important factor in total seasonal suspended sediment transfer. Secondary factors included melt energy, snow distribution and sediment supply. The largest pre‐melt SWE of the three years studied (2004) generated the largest seasonal runoff and disproportionately greater suspended sediment yield than the other years. In contrast, 2003 and 2005 had similar SWE and total runoff, but reduced runoff intensity resulted in lower suspended sediment concentrations and lower total suspended sediment yield in 2005. Lower air temperatures at the beginning of the snowmelt period in 2003 prolonged the melt period and increased meltwater storage within the snowpack. Subsequently, peak discharge and instantaneous suspended sediment concentrations were more intense than in the otherwise warmer 2005 season. The results for this study will aid in model development for sediment yield estimation from cold regions and will contribute to the interpretation of paleoenvironmental records obtained from sedimentary deposits in lakes. Copyright © 2007 John Wiley & Sons, Ltd.     

The nutrient cycle through snow and ice, a review

This paper reviews the merging of the nutrient cycle with the water cycle in the seasonal alpine snow cover, emphasizing physical processes at the snowpack and snow grain scale. Nutrients are incorporated into snowflakes growing in the atmosphere, they are part of the dry deposition from the atmosphere to the snowpack and they reach the snow as plant litter. The physical processes of the accumulation of nutrients and their redistribution in and on the snow grains and in the pore space of the snow matrix are described.¶The first flush of meltwater that reaches the soil carries a solution of nutrients and acids in a concentration several times higher than bulk values, an effect that increases with the age of the snow and the number of melt/freeze cycles and is more pronounced for sulfate than for chloride. Species that are attached to insoluble particles will be concentrated near the snow surface and will display peak concentrations in the final fraction of meltwater.     

Quantifying the role of the snowpack in generating water available for run‐off during rain‐on‐snow events from snow pillow records

Rain‐on‐snow events have generated major floods around the world, particularly in coastal, mountainous regions. Most previous studies focused on a limited number of major rain‐on‐snow events or were based primarily on model results, largely due to a lack of long‐term records from lysimeters or other instrumentation for quantifying event water balances. In this analysis, we used records from five automated snow pillow sites in south coastal British Columbia, Canada, to reconstruct event water balances for 286 rain‐on‐snow events over a 10‐year period. For large rain‐on‐snow events (event rainfall >40 mm), snowmelt enhanced the production of water available for run‐off (WAR) by approximately 25% over rainfall alone. For smaller events, a range of antecedent and meteorological factors influenced WAR generation, particularly the antecedent liquid water content of the snowpack. Most large events were associated with atmospheric rivers. Rainfall dominated WAR generation during autumn and winter events, whereas snowmelt dominated during spring and summer events. In the majority of events, the sensible heat of rain contributed less than 10% of the total energy consumed by snowmelt. This analysis illustrated the importance of understanding the amount of rainfall occurring at high elevations during rain‐on‐snow events in mountainous regions.     

The cold rain‐on‐snow event of June 2013 in the Canadian Rockies — characteristics and diagnosis

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.     

Estimating source regions for snowmelt runoff in a Rocky Mountain basin: tests of a data‐based conceptual modeling approach

In many mountain basins, river discharge measurements are located far away from runoff source areas. This study tests whether a basic snowmelt runoff conceptual model can be used to estimate relative contributions of different elevation zones to basin‐scale discharge in the Cache la Poudre, a snowmelt‐dominated Rocky Mountain river. Model tests evaluate scenarios that vary model configuration, input variables, and parameter values to determine how these factors affect discharge simulation and the distribution of runoff generation with elevation. Results show that the model simulates basin discharge well (NSCE and R >0.90) when input precipitation and temperature are distributed with different lapse rates, with a rain‐snow threshold parameter between 0 and 3.3 °C, and with a melt rate parameter between 2 and 4 mm °C^?1 d^?1 because these variables and parameters can have compensating interactions with each other and with the runoff coefficient parameter. Only the hydrograph recession parameter can be uniquely defined with this model structure. These non‐unique model scenarios with different configurations, input variables, and parameter values all indicate that the majority of basin discharge comes from elevations above 2900 m, or less than 25% of the basin total area, with a steep increase in runoff generation above 2600 m. However, the simulations produce unrealistically low runoff ratios for elevations above 3000 m, highlighting the need for additional measurements of snow and discharge at under‐sampled elevations to evaluate the accuracy of simulated snow and runoff patterns. Copyright © 2013 John Wiley & Sons, Ltd.     

Infiltration into frozen soil: From core‐scale dynamics to hillslope‐scale connectivity

Infiltration into frozen soil is a key hydrological process in cold regions. Although the mechanisms behind point‐scale infiltration into frozen soil are relatively well understood, questions remain about upscaling point‐scale results to estimate hillslope‐scale run‐off generation. Here, we tackle this question by combining laboratory, field, and modelling experiments. Six large (0.30‐m diameter by 0.35‐m deep) soil cores were extracted from an experimental hillslope on the Canadian Prairies. In the laboratory, we measured run‐off and infiltration rates of the cores for two antecedent moisture conditions under snowmelt rates and diurnal freeze–thaw conditions observed on the same hillslope. We combined the infiltration data with spatially variable data from the hillslope, to parameterise a surface run‐off redistribution model. We used the model to determine how spatial patterns of soil water content, snowpack water equivalent (SWE), and snowmelt rates affect the spatial variability of infiltration and hydrological connectivity over frozen soil. Our experiments showed that antecedent moisture conditions of the frozen soil affected infiltration rates by limiting the initial soil storage capacity and infiltration front penetration depth. However, shallow depths of infiltration and refreezing created saturated conditions at the surface for dry and wet antecedent conditions, resulting in similar final infiltration rates (0.3 mm hr^?1). On the hillslope‐scale, the spatial variability of snowmelt rates controlled the development of hydrological connectivity during the 2014 spring melt, whereas SWE and antecedent soil moisture were unimportant. Geostatistical analysis showed that this was because SWE variability and antecedent moisture variability occurred at distances shorter than that of topographic variability, whereas melt variability occurred at distances longer than that of topographic variability. The importance of spatial controls will shift for differing locations and winter conditions. Overall, our results suggest that run‐off connectivity is determined by (a) a pre‐fill phase, during which a thin surface soil layer wets up, refreezes, and saturates, before infiltration excess run‐off is generated and (b) a subsequent fill‐and‐spill phase on the surface that drives hillslope‐scale run‐off.     

Testing a spatially distributed tracer‐aided runoff model in a snow‐influenced catchment: Effects of multicriteria calibration on streamwater ages

Integrating stable isotope tracers into rainfall‐runoff models allows investigation of water partitioning and direct estimation of travel times and water ages. Tracer data have valuable information content that can be used to constrain models and, in integration with hydrometric observations, test the conceptualization of catchment processes in model structure and parameterization. There is great potential in using tracer‐aided modelling in snow‐influenced catchments to improve understanding of these catchments' dynamics and sensitivity to environmental change. We used the spatially distributed tracer‐aided rainfall‐runoff (STARR) model to simulate the interactions between water storage, flux, and isotope dynamics in a snow‐influenced, long‐term monitored catchment in Ontario, Canada. Multiple realizations of the model were achieved using a combination of single and multiple objectives as calibration targets. Although good simulations of hydrometric targets such as discharge and snow water equivalent could be achieved by local calibration alone, adequate capture of the stream isotope dynamics was predicated on the inclusion of isotope data in the calibration. Parameter sensitivity was highest, and most local, for single calibration targets. With multiple calibration targets, key sensitive parameters were still identifiable in snow and runoff generation routines. Water ages derived from flux tracking subroutines in the model indicated a catchment where runoff is dominated by younger waters, particularly during spring snowmelt. However, resulting water ages were most sensitive to the partitioning of runoff sources from soil and groundwater sources, which was most realistically achieved when isotopes were included in the calibration. Given the paucity of studies where hydrological models explicitly incorporate tracers in snow‐influenced regions, this study using STARR is an important contribution to satisfactorily simulating snowpack dynamics and runoff generation processes, while simultaneously capturing stable isotope variability in snow‐influenced catchments.