Analysis of seasonal snowmelt contribution using a distributed energy balance model for a river basin in the Altai Mountains of northwestern China

Snowmelt water is a vital freshwater resource in the Altai Mountains of northwestern China. Yet its seasonal hydrological cycle characteristics could change under a warming climate and more rapid spring snowmelt. Here, we simulated snowmelt runoff dynamics in the Kayiertesi River catchment, from 2000 to 2016, by using an improved hydrological distribution model that relied on high-resolution meteorological data acquired from the National Centers for Environmental Prediction (Fnl-NCEP) that were downscaled using the Weather Research Forecasting model. Its predictions were compared to observed runoff data, which confirmed the simulations' reliability. Our results show the model performed well, in general, given its daily validation Nash–Sutcliffe efficiency (NSE) of 0.62 (from 2013 to 2015) and a monthly NSE score of 0.68 (from 2000 to 2010) for the studied river basin of the Altai Mountains. In this river basin catchment, snowfall accounted for 64.1% of its precipitation and snow evaporation for 49.8% of its total evaporation, while snowmelt runoff constituted 29.3% of the annual runoff volume. Snowmelt's contribution to runoff in the Altai Mountains can extend into non-snow days because of the snowmelt water retained in soils. From 2000 to 2016, the snow-to-rain ratio decreased rapidly, however, the snowmelt contribution remained relatively stable in the study region. Our findings provide a sound basis for making snowmelt runoff predictions, which could be used prevent snowmelt-induced flooding, as well as a generalizable approach applicable to other remote, high-elevation locations where high-density, long-term observational data are currently lacking. How snowmelt contributes to water dynamics and resources in cold regions is garnering greater attention. Our proposed model is thus timely perhaps, enabling more comprehensive assessments of snowmelt contributions to hydrological processes in those alpine regions characterized by seasonal snow cover.     

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.     

Snow cover and runoff modelling in a high mountain catchment with scarce data: effects of temperature and precipitation parameters

Snowmelt is an important source of runoff in high mountain catchments. Snowmelt modelling for alpine regions remains challenging with scarce gauges. This study simulates the snowmelt in the Karuxung River catchment in the south Tibetan Plateau using an altitude zone based temperature‐index model, calibrates the snow cover area and runoff simulation during 2003–2005 and validates the model performance via snow cover area and runoff simulation in 2006. In the snowmelt and runoff modelling, temperature and precipitation are the two most important inputs. Relevant parameters, such as critical snow fall temperature, temperature lapse rate and precipitation gradient, determine the form and amount of precipitation and distribution of temperature and precipitation in hydrological modelling of the sparsely gauged catchment. Sensitivity analyses show that accurate estimation of these parameters would greatly help in improving the snowmelt simulation accuracy, better describing the snow‐hydrological behaviours and dealing with the data scarcity at higher elevations. Specifically, correlation between the critical snow fall temperature and relative humidity and seasonal patterns of both the temperature lapse rate and the precipitation gradient should be considered in the modelling studies when precipitation form is not logged and meteorological observations are only available at low elevation. More accurate simulation of runoff involving snowmelt, glacier melt and rainfall runoff will improve our understanding of hydrological processes and help assess runoff impacts from a changing climate in high mountain catchments. Copyright © 2013 John Wiley & Sons, Ltd.     

Identifying run‐off contributions during melt‐induced run‐off events in a glacierized alpine catchment

We analysed contributions to run‐off using hourly stream water samples from seven individual melt‐induced run‐off events (plus one rainfall event) during 2011, 2012 and 2013 in two nested glacierized catchments in the Eastern Italian Alps. Electrical conductivity and stable isotopes of water were used for mixing analysis and two‐component and three‐component hydrograph separation. High‐elevation snowmelt, glacier melt and autumn groundwater were identified as major end‐members. Discharge and tracers in the stream followed the diurnal variations of air temperature but markedly reacted to rainfall inputs. Hysteresis patterns between discharge and electrical conductivity during the melt‐induced run‐off events revealed contrasting loop directions at the two monitored stream sections. Snowmelt contribution to run‐off was highest in June and July (up to 33%), whereas the maximum contribution of glacier melt was reached in August (up to 65%). The maximum groundwater and rainfall contributions were 62% and 11%, respectively. Run‐off events were generally characterized by decreasing snowmelt and increasing glacier melt fractions from the beginning to the end of the summer 2012, while run‐off events in 2013 showed less variable snowmelt and lower glacier melt contributions than in 2012. The results provided essential insights into the complex dynamics of melt‐induced run‐off events and may be of further use in the context of water resource management in alpine catchments. Copyright © 2015 John Wiley & Sons, Ltd.     

Melted snow volume control in the snowmelt runoff model using a snow water equivalent statistically based model

Snowmelt is an important component of the river discharge in mountain environments. In the past 40 years, the snowmelt dynamics has been mostly evaluated using degree‐day‐based models like the snowmelt runoff model (SRM). This model has no control on the volume of the melting snow, even if SRM includes as data input the snow‐covered area. This lack explains why the application of SRM may lead to inaccurate snowmelt volume estimations, even if the discharge volumes are accurately reproduced. Here we introduce in SRM the control on the melted snow volume and consider it in the determination of SRM parameters. The total snow volume, accumulated at the end of winter season, is evaluated by a snow water equivalent statistically based model, SWE‐SEM, and used as an estimate of the melting snow during the summer season. The benefit derived from the introduction of the control on the melting snow volume was investigated in the Mallero basin (northern Italy) for the 2003 and 2004 snow melting seasons. The analysis compares the model's results adopting different parameter sets, both considering and ignoring the control on the melting snow volume. Copyright © 2011 John Wiley & Sons, Ltd.     

Hydrological dynamics of snowmelt induced streamflow in a high mountain catchment of the Pyrenees under contrasting snow accumulation and duration years

Snowmelt drives a large portion of streamflow in many mountain areas of the world. However, the water paths from snowmelt to the arrival of the water in the streams are still largely unknown. This work analyzes for first time the influence of snowmelt on spring streamflow with different snow accumulation and duration, in an alpine catchment of the central Spanish Pyrenees. This study presents the water balance of the main melting months (May and June). Piezometric values, water temperature, electrical conductivity and isotope data (δ¹⁸O) allow a better understanding of the hydrological functioning of the basin during these months. Results of the water balance calculations showed that snow represented on average 73% of the water available for streamflow in May and June while precipitation during these months accounted for only 27%. However, rainfall during the melting period was important to determine the shape of the spring hydrographs. On average, 78% of the sum of both the snow water equivalent (SWE) accumulated at the beginning of May and the precipitation in May and June converted into runoff during the May–June melting period. The average evaporation-sublimation during the 2 months corresponded to 8.4% of the accumulated SWE and rainfall, so that only a small part of the water input was ultimately available for soil and groundwater storage. When snow cover disappeared from the catchment, soil water storage and streamflow showed a sharp decline. Consequently, streamflow electrical conductivity, temperature and δ¹⁸O showed a marked tipping point towards higher values. The fast hydrological response of the catchment to snow and meteorological fluctuations, as well as the marked diel fluctuations of streamflow δ¹⁸O during the melting period, strongly suggests short meltwater transit times. As a consequence of this hydrological behaviour, independently of the amount of snow accumulated and of melting date, summer streamflow remained always low, with only small runoff peaks driven by rainfall events.     

Model complexity and data requirements in snow hydrology: seeking a balance in practical applications

We investigate the problem of balancing model complexity and input data requirements in snow hydrology. For this purpose, we analyze the performance of two models of different complexity in estimating variables of interest in snow hydrology applications. These are snow depth, bulk snow density, snow water equivalent and snowmelt run‐off. We quantify the differences between data and model prediction using 18 years of measurements from an experimental site in the French Alps (Col de Porte, 1325 m AMSL). The models involved in this comparison are a one‐layer temperature‐index model (HyS) and a multilayer model (Crocus). Results show that the expected loss in performance in the one‐layer temperature‐index model with respect to the multilayer model is low when considering snow depth, snow water equivalent and bulk snow density. As for run‐off, the comparison returns less clear indications for identification of a balance. In particular, differences between the models' prediction and data with an hourly resolution are higher when considering the Crocus model than the HyS model. However, Crocus is better at reproducing sub‐daily cycles in this variable. In terms of daily run‐off, the multilayer physically based model seems to be a better choice, while results in terms of cumulative run‐off are comparable. The better reproduction of daily and sub‐daily variability of run‐off suggests that use of the multilayer model may be preferable for this purpose. Variation in performance is discussed as a function of both the calibration solution chosen and the time of year. Copyright © 2016 John Wiley & Sons, Ltd.     

Stable isotope‐based mean catchment altitudes of springs in the Lebanon Mountains

Stable isotopes of water are known to provide information on mean altitudes of spring recharge areas, which is an important parameter for groundwater resources management especially in karstic environments. Very often, a lack of precipitation input data limits the possibility for an appropriate estimation of mean catchment altitudes. In the Jeita spring catchment, Lebanon, a characterization of precipitation input was possible with samples collected at six stations at varying altitudes (88 amount‐weighted monthly samples). A local meteoric water line for the Jeita spring catchment was characterized as δ²H = 6.04 * δ¹⁸O + 8.45 (R ² = .92) for a 2‐year observation period between October 2012 and September 2014. Integral samples from the snow layer were collected at 22 sites at altitudes ranging from 1,000 to 2,300 m above sea level at the end of February 2012 and February 2013, when snow height reached a maximum of more than 6 m at the highest peak in the catchment. Water samples were continuously collected from six springs (Jeita, Kashkoush, Labbane, Assal, Afqa, and Rouaiss). Jeita spring water samples were collected additionally in daily time steps during the snowmelt season in 2012. Mean isotope values of the sampled springs range from ?6.8‰ to ?8.2‰, and from ?33‰ to ?44‰, for δ¹⁸O and δ²H, respectively. The stable isotope data show that input variability (space and time, snow cover, and rainfall) has direct impacts on mean altitude estimates of spring catchments. A more profound interpretation of spring response to rainfall for six local springs in the Lebanon Mountains was possible in comparison to four earlier described springs collected in the Anti‐Lebanon Mountains in Syria.     

Hydrological footprints of urban developments in the Lake Simcoe watershed,Canada: a combined paired‐catchment and change detection modelling approach

Urban sprawl and regional climate variability are major stresses on surface water resources in many places. The Lake Simcoe watershed (LSW) Ontario, Canada, is no exception. The LSW is predominantly agricultural but is experiencing rapid population growth because of its proximity to the Greater Toronto area. This has led to extensive land use changes that have impacted its water resources and altered run‐off patterns in some rivers draining to the lake. Here, we use a paired‐catchment approach, hydrological change detection modelling and remote sensing analysis of satellite images to evaluate the impacts of land use change on the hydrology of the LSW (1994 to 2008). Results show that urbanization increased up to 16% in Lovers Creek, the most urban‐impacted catchment. Annual run‐off from Lovers Creek increased from 239 to 442 mm/year in contrast to the reference catchment (Black River at Washago) where run‐off was relatively stable with an annual mean of 474 mm/year. Increased annual run‐off from Lovers Creek was not accompanied by an increase in annual precipitation. Discriminant function analysis suggests that early (1992–1997; pre‐major development) and late (2004–2009; fully urbanized) periods for Lovers Creek separated mainly based on model parameter sets related to run‐off flashiness and evapotranspiration. As a result, parameterization in either period cannot be used interchangeably to produce credible run‐off simulations in Lovers Creek because of greater scatter between the parameters in canonical space. Separation of early and late‐period parameter sets for the reference catchment was based on climate and snowmelt‐related processes. This suggests that regional climatic variability could be influencing hydrologic change in the reference catchment, whereas urbanization amplified the regional natural hydrologic changes in urbanizing catchments of the LSW. Copyright © 2014 John Wiley & Sons, Ltd.     

Use of a parsimonious rainfall–run‐off model for predicting hydrological response in ungauged basins

A new parameter parsimonious rainfall–run‐off model, the Distance Distribution Dynamics (DDD) model, is used to simulate hydrological time series at ungauged sites in the Lygne basin in Norway. The model parameters were estimated as functions of catchment characteristics determined by geographical information system. The multiple regression equations relating catchment characteristics and model parameters were trained from 84 calibrated catchments located all over Norway, and all model parameters showed significant correlations with catchment characteristics. The significant correlation coefficients (with p‐value < 0.05) ranged from 0.22 to 0.55. The suitability of DDD for predictions in ungauged basins was tested for 17 catchments not used to estimate the multiple regression equations. For ten of the 17 catchments, deviations in Nash–Sutcliffe efficiency (NSE) criteria between the calibrated and regionalised model were less than 0.1, and for two calibrated catchments within the Lygne basin, the deviations were less than 0.08. The median NSE for the regionalized DDD for the 17 catchments for two time series was 0.66 and 0.72. Deviations in NSE between calibrated and regionalised models are well explained by the deviations between calibrated and regressed parameters describing spatial snow distribution and snowmelt respectively. The quality of the simulated run‐off series for the ungauged sites in the Lygne basin was assessed by comparing flow indices describing high, medium and low flow estimated from observed run‐off at the 17 catchments and for the simulated run‐off series. The indices estimated for the simulated series were generally well within the ranges defined by the 17 observed series. Copyright © 2014 John Wiley & Sons, Ltd.     

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.     

Evaluating the SWAT's snow hydrology over a Northern Quebec watershed

The snow treatment becomes an important component of Soil and Water Assessment Tool (SWAT)’s hydrology when spring flows are dominated by snow melting. However, little is known about SWAT's snow hydrology performance because most studies using SWAT were conducted in rainfall‐driven catchments. To fill this gap, the present study aims to evaluate the ability of SWAT in simulating snow‐melting‐dominated streamflow in the Outardes Basin in Northern Quebec. SWAT performance in simulating snowmelt is evaluated against observed streamflow data and compared to simulations from the operationally used Streamflow Synthesis and Reservoir Regulation (SSARR) model over that catchment. The SWAT 5‐year calibration showed a satisfactory performance at the daily and seasonal time scales with low volume biases. The SWAT validation was conducted over two (17‐year and 15‐year) periods. Performances were similar to the calibration period in simulating the daily and seasonal streamflows again with low model biases. The spring‐snowmelt‐generated peak flow was accurately simulated by SWAT both in magnitude and timing. When SWAT's results are compared to SSARR, similar performances in simulating the daily discharges were observed. SSARR simulates more accurately streamflow generated at the snowmelt onset whereas SWAT better predicts streamflow in summer, fall and winter. SWAT provided reasonable streamflow simulations for our snow‐covered catchment, but refinement of the process‐driven baseflow during the snowmelt onset could improve spring performances. Therefore, SWAT becomes an attractive tool for evaluating water resources management in Nordic environments when a distributed model is preferred or when water quality information (e.g. temperature) is required. Copyright © 2013 John Wiley & Sons, Ltd.     

Effect of climatic change on snowmelt runoffs in mountainous regions of inland rivers in Northwestern China

Snow is one of the most active natural elements of snow cover through its high albedo, variation of the the cryosphere on the earth surface. Its unique proper- snow cover distribution and frozen soils in regional ties, such as areal extent, surface albedo, and snow scales not only affect local climate and environments, depth are important parameters in global energy bal- but also feedback to large-scale, or even global cli- ance models. On global and terrestrial scales, a large matic change th…     

Modelling runoff using optical satellite remote sensing data in a high mountainous alpine catchment of Italy

Development of hydrological models for seasonal and real-time runoff forecast in rivers of high alpine catchments is useful for management of water resources. The conceptual models for this purpose are based on a temperature index and/or energy budget and can be either lumped or distributed over the catchment area. Remote sensing satellite data are most useful to acquire near real-time geophysical parameters in order to input to the distributed forecasting models. In the present study, integration of optical satellite remote sensing-derived information was made with ground meteorological and hydrological data, and predetermined catchment morphological parameters, to study the feasibility of application of a distributed temperature index snowmelt runoff model to one of the high mountainous catchments in the Italian Alps, known as Cordevole River Basin. Five sets of Landsat Multispectral Scanning System (MSS) and Thematic Mapper (TM) computer-compatible tapes (CCTs) were processed using digital image processing techniques in order to evaluate the snow cover variation quantitatively. Digital elevation model, slope and aspect parameters were developed and used during satellite data processing. The satellite scenes were classified as snow, snow under transition and snow free areas. A second-order polynomial fit has been attempted to approximate the snow depletion and to estimate daily snow cover areal extent for three elevation zones of the catchment separately. Model performance evaluation based on correlation coefficient, Nash–Sutcliffe coefficient and percentage volume deviation indicated very good simulation between measured and computed discharges for the entire snowmelt period. The use of average temperature values computed from the maximum and minimum temperatures into the model was studied and a suitable algorithm was proposed. © 1997 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.     

Using an inverse modelling approach with equifinality control to investigate the dominant controls on snowmelt nutrient export

There is great interest in modelling the export of nitrogen (N) and phosphorus (P) from agricultural fields because of ongoing challenges of eutrophication. However, the use of existing hydrochemistry models can be problematic in cold regions because models frequently employ incomplete or conceptually incorrect representations of the dominant cold regions hydrological processes and are overparameterized, often with insufficient data for validation. Here, a process‐based N model, WINTRA, which is coupled to a physically based cold regions hydrological model, was expanded to simulate P and account for overwinter soil nutrient biochemical cycling. An inverse modelling approach, using this model with consideration of parameter equifinality, was applied to an intensively monitored agricultural basin in Manitoba, Canada, to help identify the main climate, soil, and anthropogenic controls on nutrient export. Consistent with observations, the model results suggest that snow water equivalent, melt rate, snow cover depletion rate, and contributing area for run‐off generation determine the opportunity time and surface area for run‐off–soil interaction. These physical controls have not been addressed in existing models. Results also show that the time lag between the start of snowmelt and the arrival of peak nutrient concentration in run‐off increased with decreasing antecedent soil moisture content, highlighting potential implications of frozen soils on run‐off processes and hydrochemistry. The simulations showed TDP concentration peaks generally arriving earlier than NO₃ but also decreasing faster afterwards, which suggests a significant contribution of plant residue Total dissolved Phosphorus (TDP) to early snowmelt run‐off. Antecedent fall tillage and fertilizer application increased TDP concentrations in spring snowmelt run‐off but did not consistently affect NO₃ run‐off. In this case, the antecedent soil moisture content seemed to have had a dominant effect on overwinter soil N biogeochemical processes such as mineralization, which are often ignored in models. This work demonstrates both the need for better representation of cold regions processes in hydrochemical models and the model improvements that are possible if these are included.     

Run‐off formation in a humid,temperate headwater catchment using a combined hydrological,hydrochemical and isotopic approach (Jizera Mountains,Czech Republic)

The formation of baseflow and stormflow was examined in the 1.18 km² part of the headwater catchment Uhlí?ská, Jizera Mountains, Czech Republic, over the period 2007–2011, by means of run‐off data and environmental tracers ¹⁸O and SiO₂. The baseflow, computed using the digital filter approach BFLOW, contributes 67% to total streamflow and has a mean residence time of 12.3 months. It is formed by groundwater discharge from the valley deluviofluvial granitic sediments, in combination with soil water in weathered layers on hillslopes during rainfall and snowmelt periods. The prevailing source of the groundwater is the infiltration of snowmelt water. Analysis of 20 run‐off events and their hysteretic patterns demonstrated that the stormflow water has a residence time of about 4 months and is generated by preferential flow on hillslopes combined by soil matrix drainage. Because of slower flow in the soil matrix, the enrichment of pore water in SiO₂ is more pronounced. The stormflow and snowmelt water flowing via preferential pathways of upslope minerals soils pushes the pre‐event groundwater through the pathways in wetlands to the stream, and the wetland can be therefore considered as groundwater supplied. This mechanism has been found to be typical for the groundwater‐supplied headwater catchments of the Jizera Mountains and can be also assumed in other mountainous headwaters of the granitic massif in Central Europe. The main methodological contribution of this study are the residence time calculations stratified by baseflow and event flow, identifying run‐off components of different travel times to streams and linking them with geochemical run‐off sources. This achievement was possible because of a comprehensive dataset on hydrology, stable isotopes and silica hydrochemistry in all relevant run‐off generation components. This concept indicates that a possible long‐term change in snowmelt may affect the run‐off regime of headwater catchments to climate or land‐use changes. Copyright © 2013 John Wiley & Sons, Ltd.     

Dynamics of snow ablation in a small Alpine catchment observed by repeated terrestrial laser scans

The spatio‐temporal distribution of snow in a catchment during ablation reflects changes in the total amount of snow water equivalent and is thus a key parameter for the estimation of melt water run‐off. This study explores possible rules behind the spatial variability of snow depth during the ablation season in a small Alpine catchment with complex topography. The snow depth observations are based on more than 160 000 terrestrial laser scanner data points with a spatial resolution of 1 m, which were obtained from 11 scanning campaigns of two consecutive ablation seasons. The analysis suggests that for estimating cumulative snow melt dynamics from the catchment investigated, assessing the initial snow distribution prior to the melt season is more important than addressing spatial differences in the melt behaviour. Snow volume and snow‐covered area could be predicted well using a conceptual melt model assuming spatially uniform melt rates. However, accurate results were only obtained if the model was initialized with a pre‐melt snow distribution that reflected measured mean and standard deviation. Using stratified melt rates on the other hand did not improve the model results. At least for sites with similar meteorological and topographical conditions, the model approach presented here comprises an efficient way to estimate snow depletion dynamics, especially if persistent snow accumulation pattern between years facilitate the characterization of the initial snow distribution prior to the melt. Copyright © 2011 John Wiley & Sons, Ltd.     

Snow hydrology of a constructed watershed in the Athabasca oil sands region,Alberta, Canada

Wetlands are now being integrated into oil sands mining landscape closure design plans. These wetland ecosystems will be constructed within a regional sub‐humid climate where snowfall represents ~25% of annual precipitation. However, few studies focus on the distribution of snow and, hence, the storage of winter precipitation in reclaimed oil sands landscapes. In this study, the distribution, ablation and fate of snowmelt waters are quantified within a constructed watershed in a post‐mining oil sands environment. Basin‐averaged peak SWE was 106 mm, with no significant difference between reclaimed slopes with vegetation and those that were sparsely vegetated or bare. Snow depth was greatest and more variable near the toe of slopes and became progressively shallower towards the crest. Snow ablation started first on the vegetated slope, which also exhibited the maximum observed ablation rates. This enhanced melt was attributed to increased absorption of short‐wave radiation by vegetation stems and branches. Recharge to reclaimed slopes and a constructed aquifer during the snowmelt period was minimal, as the presence of ground frost minimized infiltration. Accordingly, substantial surface run‐off was observed from all reclaimed slopes, despite being designed to reduce run‐off and increase water storage. This could result in increased flashiness of downstream watercourses during the spring freshet that receive run‐off from post‐mining landscapes where large reclaimed slopes are prolific. Run‐off ratios for the reclaimed slopes were between 0.7 and 0.9. Thus, it is essential to consider snow dynamics when designing landscape‐scale constructed ecosystems. This research demonstrates that the snowmelt period hydrology within reclaimed landscapes is fundamentally different from that reported for natural settings and represents one of the first studies on snow dynamics in constructed watershed systems in the post‐mined oil sands landscape. Copyright © 2016 John Wiley & Sons, Ltd.     

Assessing the effects of precipitation and temperature changes on hydrological processes in a glacier‐dominated catchment

The processes by which climate change affects streamflow in alpine river basins are not entirely understood. This study evaluated the impacts of temperature and precipitation changes on runoff and streamflow using glacier‐enhanced Soil and Water Assessment Tool model. The study used observed and detrended historical meteorological data for recent decades (1961–2005) to analyse individual and combined effects of temperature and precipitation changes on snow and glacier melts and discharges in the Sary‐Djaz‐Kumaric River Basin (SRB), Tianshan Mountains. The results showed a 1.3% increase in annual snowmelt in the basin, mainly because of an increase in precipitation. Snowmelt in the basin varied seasonally, increasing from April through May because of increasing precipitation and decreasing from July through September because of rising temperature. Glacier melt increased by 5.4%, 5.0% of which was due to rising temperature and only 0.4% due to increasing precipitation. Annual streamflow increased by 4.4%, of which temperature and precipitation increases accounted for 2.5% and 1.9%, respectively. The impacts of temperature and precipitation changes on streamflow were especially significant after 1980 and even more so in September. Glacier melt, due to temperature rise, was the dominant driver of increasing streamflow in the glacier‐dominated SRB, Tianshan Mountains. Copyright © 2015 John Wiley & Sons, Ltd.