A simple method to combine snow height and meteorological observations to estimate winter precipitation at sub-daily resolution

ABSTRACT

Measuring winter solid and liquid precipitation with high temporal resolution in remote or higher elevation regions is a challenging task because of undercatch and power supply issues. However, the number of micro-meteorological stations and ultrasonic height sensors in mountain regions is steadily increasing. To gain more benefit from such stations, a new simple approach for EStimating SOlid and LIquid Precipitation (ESOLIP) is presented. The method consists of three main steps: (1) definition of precipitation events using micro-meteorological data, (2) quantification of solid and liquid precipitation using wet-bulb temperature and filtered snow height and (3) calculation of fresh snow density. ESOLIP performance was validated using data from a heated rain gauge, snow pillow and daily manual observations both for single precipitation events and over three winter seasons. Results proved ESOLIP as an effective approach for precipitation quantification, where snow height observations and basic meteorological measurements (air temperature, solar radiation, wind speed, relative humidity), but no reliable rain gauges are available.     

Modelling snow water equivalent and spring runoff in a boreal watershed,James Bay,Canada

The hydrology of boreal regions is strongly influenced by seasonal snow accumulation and melt. In this study, we compare simulations of snow water equivalent (SWE) and streamflow by using the hydrological model HYDROTEL with two contrasting approaches for snow modelling: a mixed degree‐day/energy balance model (small number of inputs, but several calibration parameters needed) and the thermodynamic model CROCUS (large number of inputs, but no calibration parameter needed). The study site, in Northern Quebec, Canada was equipped with a ground‐based gamma ray sensor measuring the SWE continuously for 5 years in a small forest clearing. The first simulation of CROCUS showed a tendency to underestimate SWE, attributable to bias in the meteorological inputs. We found that it was appropriate to use a threshold of 2 °C to separate rain and snow. We also applied a correction to account for snowfall undercatch by the precipitation gauge. After these modifications to the input dataset, we noticed that CROCUS clearly overestimated the SWE, likely as a result of not including loss in SWE because of blowing snow sublimation and relocation. To correct this, we included into CROCUS a simple parameterisation effective after a certain wind speed threshold, after which the thermodynamic model performed much better than the traditional mixed degree‐day/energy balance model. HYDROTEL was then used to simulate streamflow with both snow models. With CROCUS, the main peak flow could be captured, but the second peak because of delayed snowmelt from forested areas could not be reproduced due to a lack of sub‐canopy radiation data to feed CROCUS. Despite the relative homogeneity of the boreal landscape, data inputs from each land cover type are needed to generate satisfying simulation of the spring runoff. Copyright © 2013 John Wiley & Sons, Ltd.     

Application of a distributed blowing snow model to the Arctic

Transportation, sublimation and accumulation of snow dominate snow cover development in the Arctic and produce episodic high evaporative fluxes. Unfortunately, blowing snow processes are not presently incorporated in any hydrological or meteorological models. To demonstrate the application of simple algorithms that represent blowing snow processes, monthly snow accumulation, relocation and sublimation fluxes were calculated and applied in a spatially distributed manner to a 68-km² catchment in the low Arctic of north-western Canada. The model uses a Landsat-derived vegetation classification and a digital elevation model to segregate the basin into snow ‘sources’ and ‘sinks’. The model then relocates snow from sources to sinks and calculates in-transit sublimation loss. The resulting annual snow accumulation in specific landscape types was compared with the result of intensive surveys of snow depth and density. On an annual basis, 28% of annual snowfall sublimated from tundra surfaces whilst 18% was transported to sink areas. Annual blowing snow transport to sink areas amounted to an additional 16% of annual snowfall to shrub–tundra and an additional 182% to drifts. For the catchment, 19·5% of annual snowfall sublimated from blowing snow, 5·8% was transported into the catchment and 86·5% accumulated on the ground. The model overestimated snow accumulation in the catchment by 6%. The application demonstrates that winter precipitation alone is insufficient to calculate snow accumulation and that blowing snow processes and landscape patterns govern the spatial distribution and total accumulation of snow water equivalent over the winter. These processes can be modelled by relatively simple algorithms, and, when distributed by landscape type over the catchment, produce reasonable estimates of snow accumulation and loss in wind-swept regions. © 1997 John Wiley & Sons, Ltd.     

Estimating surface sublimation losses from snowpacks in a mountain catchment using eddy covariance and turbulent transfer calculations

Sublimation is a critical component of the snow cover mass balance. Although sublimation can be directly measured using eddy covariance (EC), such measurements are relatively uncommon in complex mountainous environments. The EC measurements of surface snowpack sublimation from three consecutive winter seasons (2004, 2005 and 2006) at a wind‐exposed and wind‐sheltered site were analysed to characterise sublimation in mountainous terrain. During the 2006 snow season, snow surface and near‐surface air temperature, humidity and wind were also measured, permitting the calculation of sublimation rates and a comparison with EC measurements. This comparison showed that measured and simulated sublimation was very similar at the exposed site but less so at the sheltered site. Wind speeds at the exposed site were nearly four times than that at the sheltered site, and the exposed site yielded measured sublimation that was two times the magnitude of that at the sheltered site. The time variation of measured sublimation showed diurnal increases in the early afternoon and increased rates overall as the snow season progressed. Measured mean daily sublimation rates were 0.39 and 0.15 mm day^?1 at the exposed and sheltered sites, respectively. At the exposed site, measured sublimation accounted for 16% and 41% of the maximum snow accumulation in 2006 and 2005, respectively. At the sheltered site, measured seasonal sublimation was approximately 4% in 2004 and 2006 and 8% in 2005 of the maximum snow water equivalent. Simulated sublimation was only available for 2006 and suggested smaller but comparable percentages to the sublimation estimated from observations. At the exposed site, a total of 42 mm sublimated for the snow season, which constituted 12% of the maximum accumulation. At the sheltered site, 17 mm (2.2% of maximum accumulation) was sublimated over the snow season. Copyright © 2011 John Wiley & Sons, Ltd.     

Response of snow processes to climate change: spatial variability in a small basin in the Spanish Pyrenees

In this study, the Cold Regions Hydrological Modelling platform was used to create an alpine snow model including wind redistribution of snow and energy balance snowmelt to simulate the snowpack over the period 1996–2009 in a small (33 ha) snow‐dominated basin in the Spanish Pyrenees. The basin was divided into three hydrological response units (HRUs), based on contrasting physiographic and aerodynamic characteristics. A sensitivity analysis was conducted to calculate the snow water equivalent regime for various combinations of temperature and precipitation that differed from observed conditions. The results show that there was large inter‐annual variability in the snowpack in this region of the Pyrenees because of its marked sensitivity to climatic conditions. Although the basin is small and quite homogeneous, snowpack seasonality and inter‐annual evolution of the snowpack varied in each HRU. Snow accumulation change in relation to temperature change was approximately 20% for every 1 °C, and the duration of the snowpack was reduced by 20–30 days per °C. Melting rates decreased with increased temperature, and wind redistribution of snow was higher with decreased temperature. The magnitude and sign of changes in precipitation may markedly affect the response of the snowpack to changes in temperature. There was a non‐linear response of snow to individual and combined changes in temperature and precipitation, with respect to both the magnitude and sign of the change. This was a consequence of the complex interactions among climate, topography and blowing snow in the study basin. Copyright © 2012 John Wiley & Sons, Ltd.     

Estimating sublimation of intercepted and sub‐canopy snow using eddy covariance systems

Direct measurements of winter water loss due to sublimation were made in a sub‐alpine forest in the Rocky Mountains of Colorado. Above‐and below‐canopy eddy covariance systems indicated substantial losses of winter‐season snow accumulation in the form of snowpack (0·41 mm d^?1) and intercepted snow (0·71 mm d^?1) sublimation. The partitioning between these over and under story components of water loss was highly dependent on atmospheric conditions and near‐surface conditions at and below the snow/atmosphere interface. High above‐canopy sensible heat fluxes lead to strong temperature gradients between vegetation and the snow‐surface, driving substantial specific humidity gradients at the snow surface and high sublimation rates. Intercepted snowfall resulted in rapid response of above‐canopy latent heat fluxes, high within‐canopy sublimation rates (maximum = 3·7 mm d^?1), and diminished sub‐canopy snowpack sublimation. These results indicate that sublimation losses from the sub‐canopy snowpack are strongly dependent on the partitioning of sensible and latent heat fluxes in the canopy. This compels comprehensive studies of snow sublimation in forested regions that integrate sub‐canopy and over‐story processes. Copyright © 2007 John Wiley & Sons, Ltd.     

Sublimation over seasonal snowpack at the southeastern edge of a desert in central Eurasia

The Gurbantonggut Desert, China, is an ideal site for study of sublimation from the snowpack because there are sparse vegetation and simple topography, and the wind speed is not large enough to blow snow into the atmosphere from the snowpack. Daily sublimation was measured by manual snow lysimeters at 8:00, and an automatic weather station was deployed at the top of a stout longitudinal dune chain at the southeastern edge of the desert. It is shown that on a daily scale, there was an extremely significant no‐intercept linear relationship between the measured sublimation and that calculated by the bulk aerodynamic method, although the former was only 83.8% of the latter. It is also demonstrated that ?10°C and 2 m/s were the thresholds where the sublimation varied with the air temperature and the wind speed. When these two thresholds were exceeded, the sublimation accelerated. However, the air temperature and the wind speed at 2 m above the ground averaged ?17.2°C and 1.3 m/s, respectively, and the percentages of the time when the air temperature was below ?10 °C and the wind speed was below 2 m/s were 76.9% and 85.1%, respectively. As a result, the rate of sublimation was quite low most of the time, and the thin snowpack remained in a quasi‐static state until the melt stage started. Copyright © 2011 John Wiley & Sons, Ltd.     

Role of temporal resolution of meteorological inputs for process‐based snow modelling

Accurate snow accumulation and melt simulations are crucial for understanding and predicting hydrological dynamics in mountainous settings. As snow models require temporally varying meteorological inputs, time resolution of these inputs is likely to play an important role on the model accuracy. Because meteorological data at a fine temporal resolution (~1 hr) are generally not available in many snow‐dominated settings, it is important to evaluate the role of meteorological inputs temporal resolution on the performance of process‐based snow models. The objective of this work is to assess the loss in model accuracy with temporal resolution of meteorological inputs, for a range of climatic conditions and topographic elevations. To this end, a process‐based snow model was run using 1‐, 3‐, and 6‐hourly inputs for wet, average, and dry years over Boise River Basin (6,963 km²), which spans rain dominated (≤1,400 m), rain–snow transition (>1,400 and ≤1,900 m), snow dominated below tree line (>1,900 and ≤2,400 m), and above tree line (>2,400 m) elevations. The results show that sensitivity of the model accuracy to the inputs time step generally decreases with increasing elevation from rain dominated to snow dominated above tree line. Using longer than hourly inputs causes substantial underestimation of snow cover area (SCA) and snow water equivalent (SWE) in rain‐dominated and rain–snow transition elevations, due to the precipitation phase mischaracterization. In snow‐dominated elevations, the melt rate is underestimated due to errors in estimation of net snow cover energy input. In addition, the errors in SCA and SWE estimates generally decrease toward years with low snow mass, that is, dry years. The results indicate significant increases in errors in estimates of SCA and SWE as the temporal resolution of meteorological inputs becomes coarser than an hour. However, use of 3‐hourly inputs can provide accurate estimates at snow‐dominated elevations. The study underscores the need to record meteorological variables at an hourly time step for accurate process‐based snow modelling.     

Sublimation from thin snow cover at the edge of the Eurasian cryosphere in Mongolia

Sublimation from thin snow cover at the edge of the Eurasian cryosphere in Mongolia was calculated using the aerodynamic profile method and verified by eddy covariance observations using multiple‐level meteorological data from three sites representing a variety of geographic and vegetative conditions in Mongolia. Data were collected in the winter and analysed from three sites. Intense sublimation events, defined by daily sublimation levels of more than 0·4 mm, were predominant in their effect on the temporal variability of sublimation. The dominant meteorological elements affecting sublimation were wind speed and air temperature, with the latter affecting sublimation indirectly through the vapour deficit. Seasonal and interannual variations in sublimation were investigated using long‐interval estimations for 19 years at a mountainous‐area meteorological station and for 24 years at a flat‐plain meteorological station. The general seasonal pattern indicated higher rates of sublimation in both the beginning and ending of the snow‐covered period, when the wind speed and vapour deficit were higher. Annual sublimation averaged 11·7 mm at the flat‐plain meteorological station, or 20·3% of the annual snowfall, and 15·7 mm at the site in the mountains, or 21·6% of snowfall. The sum of snow sublimation and snowmelt evaporation represented 17 to 20% of annual evapotranspiration in a couple observation years. Copyright © 2008 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.     

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.     

Increasing water losses from snow captured in the canopy of boreal forests: A case study using a 30 year data set

Water losses from snow intercepted by forest canopy can significantly influence the hydrological cycle in seasonally snow‐covered regions, yet how snow interception losses (SIL) are influenced by a changing climate are poorly understood. In this study, we used a unique 30 year record (1986–2015) of snow accumulation and snow water equivalent measurements in a mature mixed coniferous (Picea abies and Pinus sylvestris ) forest stand and an adjacent open area to assess how changes in weather conditions influence SIL. Given little change in canopy cover during this study, the 20% increase in SIL was likely the result of changes in winter weather conditions. However, there was no significant change in average wintertime precipitation and temperature during the study period. Instead, mean monthly temperature values increased during the early winter months (i.e., November and December), whereas there was a significant decrease in precipitation in March. We also assessed how daily variation in meteorological variables influenced SIL and found that about 50% of the variation in SIL was correlated to the amount of precipitation that occurred when temperatures were lower than ?3 °C and to the proportion of days with mean daily temperatures higher than +0.4 °C. Taken together, this study highlights the importance of understanding the appropriate time scale and thresholds in which weather conditions influence SIL in order to better predict how projected climate change will influence snow accumulation and hydrology in boreal forests in the future.     

A precise monitoring of snow surface height in the region of Lambert Glacier basin-Amery Ice Shelf,East Antarctica

The net surface snow accumulation on the Antarctic ice sheet is determined by a combination of precipitation, sublimation and wind redistribution. We present a one-year record of hourly snow-height measurements at LGB69 (70°50'S, 77°04'E, 1850 m a.s.l.). east side of Lambert Glacier basin (LGB), and 4 year record at G3 (70°53'S, 69°52'E, 84 m a.s.l.), Amery Ice Shelf (AIS). The measurements were made with ultrasonic sensors mounted on automatic weather stations installed at two sites. The snow accumulation at LGB69 is approximately 70 cm. Throughout the winter, between April and September, there was little change in surface snow height (SSH) at the two sites. The negative SSH change is due to densification at LGB69, and is due to both ablation and densification at G3. The strongest accumulation at two sites occurred during the period between October and March (accounting for 101.6% at LGB69), with four episodic increasing events occurring during 2002 for LGB69, and eight events during 1999-2002 for G     

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.     

Variable effects of forest canopies on snow processes in a valley of the central Spanish Pyrenees

Snowpacks and forests have complex interactions throughout the large range of altitudes where they co-occur. However, there are no reliable data on the spatial and temporal interactions of forests with snowpacks, such as those that occur in nearby areas that have different environmental conditions and those that occur during different snow seasons. This study monitored the interactions of forests with snowpacks in four forest stands in a single valley of the central Spanish Pyrenees during three consecutive snow seasons (2015/2016, 2016/2017 and 2017/2018). Daily snow depth data from time-lapse cameras were compared with snow data from field surveys that were performed every 10–15 days. These data thus provided information on the spatial and temporal changes of snow–water equivalent (SWE). The results indicated that forest had the same general effects on snowpack in each forest stand and during each snow season. On average, forest cover reduced the duration of snowpack by 17 days, reduced the cumulative SWE of the snowpack by about 60% and increased the spatial heterogeneity of snowpack by 190%. Overall, forest cover reduced SWE total accumulation by 40% and the rate of SWE accumulation by 25%. The forest-mediated reduction of the accumulation rate, in combination with the occasional forest-mediated enhancement of melting rate, explained the reduced duration of snowpacks beneath forest canopies. However, the magnitude and timing of certain forest effects on snowpack had significant spatial and temporal variations. This variability must be considered when selecting the location of an experimental site in a mountainous area, because the study site should be representative of surrounding areas. The same considerations apply when selecting a time period for study.     

II: Wind related errors in different methods of solid precipitation measurement

Using data sets assembled within the WMO Solid Precipitation Measurement Intercomparison, the paper deals with the wind related losses in national methods of solid precipitation measurement. Fourteen different types of precipitation gauges are included in the Harzgerode/GDR intercomparison field. Initial results of the comparisons between the Valdai double fence reference method and the other gauges in terms of dependence on wind speed and type of precipitation are presented. These results reveal that the national unsheltered HELLMANN gauge catches only 24 per cent to 70 per cent of the daily totals of solid precipitation as compared with the reference gauge. Results of the analysis of monthly totals and individual events reveal a similar dependence of gauge deficiencies on wind speed and type of precipitation. Case studies of single snow falls and the wind field conditions around and within the double fence reference are also described.     

Occurrence of blowing snow events at an alpine site over a 10-year period: Observations and modelling

Blowing snow events control the evolution of the snow pack in mountainous areas and cause inhomogeneous snow distribution. The goal of this study is to identify the main features of blowing snow events at an alpine site and assess the ability of the detailed snowpack model Crocus to reproduce the occurrence of these events in a 1D configuration. We created a database of blowing snow events observed over 10 years at our experimental site. Occurrences of blowing snow events were divided into cases with and without concurrent falling snow. Overall, snow transport is observed during 10.5% of the time in winter and occurs with concurrent falling snow 37.3% of the time. Wind speed and snow age control the frequency of occurrence. Model results illustrate the necessity of taking the wind-dependence of falling snow grain characteristics into account to simulate periods of snow transport and mass fluxes satisfactorily during those periods. The high rate of false alarms produced by the model is investigated in detail for winter 2010/2011 using measurements from snow particle counters.     

Temporal observations of a seasonal snowpack using upward‐looking GPR

An increase of the spatial and temporal resolution of snowpack measurements in Alpine or Arctic regions will improve the predictability of flood and avalanche hazards and increase the spatial validity of snowpack simulation models. In the winter season 2009, we installed a ground‐penetrating radar (GPR) system beneath the snowpack to measure snowpack conditions above the antennas. In comparison with modulated frequency systems, GPR systems consist of a much simpler technology, are commercially available and therefore are cheaper. The radar observed the temporal alternation of the snow height over more than 2·5 months. The presented data showed that with moved antennas, it is possible to record the snow height with an uncertainty of less than 8% in comparison with the probed snow depth. Three persistent melt crusts, which formed at the snow surface and were buried by further new snow events, were used as reflecting tracers to follow the snow cover evolution and to determine the strain rates of underlaying layers between adjacent measurements. The height in two‐way travel time of each layer changed over time, which is a cumulative effect of settlement and variation of wave speed in response to densification and liquid water content. The infiltration of liquid water with depth during melt processes was clearly observed during one event. All recorded reflections appeared in concordance with the physical principles (e.g. in phase structure), and one can assume that distinct density steps above a certain threshold result in reflections in the radargram. The accuracy of the used impulse radar system in determining the snow water equivalent is in good agreement with previous studies, which used continuous wave radar systems. The results of this pilot study encourage further investigations with radar measurements using the described test arrangement on a daily basis for continuous destruction‐free monitoring of the snow cover. Copyright © 2010 John Wiley & Sons, Ltd.     

A Downscaling Approach Toward High-Resolution Surface Mass Balance Over Antarctica

The Antarctic ice sheet surface mass balance shows high spatial variability over the coastal area. As state-of-the-art climate models usually require coarse resolutions to keep computational costs to a moderate level, they miss some local features that can be captured by field measurements. The downscaling approach adopted here consists of using a cascade of atmospheric models from large scale to meso-?? scale. A regional climate model (Modèle Atmosphérique Régional) forced by meteorological reanalyses provides a diagnostic physically-based rain- and snowfall downscaling model with meteorological fields at the regional scale. Although the parameterizations invoked by the downscaling model are fairly simple, the knowledge of small-scale topography significantly improves the representation of spatial variability of precipitation and therefore that of the surface mass balance. Model evaluation is carried out with the help of shallow firn cores and snow height measurements provided by automatic weather stations. Although downscaling of blowing snow still needs to be implemented in the model, the net accumulation gradient across Law Dome summit is shown to be induced mostly by orographic effects on precipitation.     

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.