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.     

Development of a rain‐on‐snow detection algorithm using passive microwave radiometry

Currently observed climate warming in the Arctic has numerous consequences. Of particular relevance, the precipitation regime is modified where mixed and liquid precipitation can occur during the winter season leading to rain‐on‐snow (ROS) events. This phenomenon is responsible for ice crust formation, which has a significant impact on ecosystems (such as biological, hydrological, ecological and physical processes). The spatially and temporally sporadic nature of ROS events makes the phenomenon difficult to monitor using meteorological observations. This paper focuses on the detection of ROS events using passive microwave (PMW) data from a modified brightness temperature (T_B) gradient approach at 19 and 37 GHz. The approach presented here was developed empirically for observed ROS events with coincident ground‐based PMW measurements in Sherbrooke, Quebec, Canada. It was then tested in Nunavik, Quebec, with the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR‐E). We obtained a detection accuracy of 57, 71 and 89% for ROS detection for three AMSR‐E grid cells with a maximum error of 7% when considering all omissions and commissions with regard to the total number of AMSR‐E passes throughout the winter period. Copyright © 2016 John Wiley & Sons, Ltd.     

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.     

Regional variability in dust‐on‐snow processes and impacts in the Upper Colorado River Basin

Dust deposition onto mountain snow cover in the Upper Colorado River Basin frequently occurs in the spring when wind speeds and dust emission peaks on the nearby Colorado Plateau. Dust loading has increased since the intensive settlement in the western USA in the mid 1880s. The effects of dust‐on‐snow have been well studied at Senator Beck Basin Study Area (SBBSA) in the San Juan Mountains, CO, the first high‐altitude area of contact for predominantly southwesterly winds transporting dust from the southern Colorado Plateau. To capture variability in dust transport from the broader Colorado Plateau and dust deposition across a larger area of the Colorado River water sources, an additional study plot was established in 2009 on Grand Mesa, 150 km to the north of SBBSA in west central, CO. Here, we compare the 4‐year (2010–2013) dust source, deposition, and radiative forcing records at Grand Mesa Study Plot (GMSP) and Swamp Angel Study Plot (SASP), SBBSA's subalpine study plot. The study plots have similar site elevations/environments and differ mainly in the amount of dust deposited and ensuing impacts. At SASP, end of year dust concentrations ranged from 0.83 mg g^?1 to 4.80 mg g^?1, and daily mean spring dust radiative forcing ranged from 50–65 W m^?2, advancing melt by 24–49 days. At GMSP, which received 1.0 mg g^?1 less dust per season on average, spring radiative forcings of 32–50 W m^?2 advanced melt by 15–30 days. Remote sensing imagery showed that observed dust events were frequently associated with dust emission from the southern Colorado Plateau. Dust from these sources generally passed south of GMSP, and back trajectory footprints modelled for observed dust events were commonly more westerly and northerly for GMSP relative to SASP. These factors suggest that although the southern Colorado Plateau contains important dust sources, dust contributions from other dust sources contribute to dust loading in this region, and likely account for the majority of dust loading at GMSP. Copyright © 2015 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.     

Diagnosing snow accumulation errors in a rain‐snow transitional environment with snow board observations

Diagnosing the source of errors in snow models requires intensive observations, a flexible model framework to test competing hypotheses, and a methodology to systematically test the dominant snow processes. We present a novel process‐based approach to diagnose model errors through an example that focuses on snow accumulation processes (precipitation partitioning, new snow density, and snow compaction). Twelve years of meteorological and snow board measurements were used to identify the main source of model error on each snow accumulation day. Results show that modeled values of new snow density were outside observational uncertainties in 52% of days available for evaluation, while precipitation partitioning and compaction were in error 45% and 16% of the time, respectively. Precipitation partitioning errors mattered more for total winter accumulation during the anomalously warm winter of 2014–2015, when a higher fraction of precipitation fell within the temperature range where partition methods had the largest error. These results demonstrate how isolating individual model processes can identify the primary source(s) of model error, which helps prioritize future research.     

Spatial and temporal diversity for debris‐flow meteorological control in subarctic oceanic periglacial environments in Iceland

Slopes in fjord environments of Iceland are prone to debris‐flow initiation, responding to a wide variety of meteorological triggering factors, such as rain on snow, rapid snowmelt, long‐lasting rainfall or intense rainfall. If all fjord regions have similar debris flows with regards to their magnitude, their meteorological control is diverse both in space and in time. Debris flows in Northwest Iceland are triggered mostly by rain‐on‐snow and long‐lasting rainfall, while snowmelt is more characteristic in North Iceland, and rainfall has a clear impact in East Iceland. Most debris‐flow events occur on a single slope, and only a few are recorded at the same time in different regions. Observations of the threshold values underline the diversity of debris‐flow initiation, occurring with huge amounts of sudden water supply as well as with very moderate ones. Copyright © 2007 John Wiley & Sons, Ltd.     

A comparison of snowmelt‐derived streamflow from temperature‐index and modified‐temperature‐index snow models

Reliable estimation of the volume and timing of snowmelt runoff is vital for water supply and flood forecasting in snow‐dominated regions. Snowmelt is often simulated using temperature‐index (TI) models due to their applicability in data‐sparse environments. Previous research has shown that a modified‐TI model, which uses a radiation‐derived proxy temperature instead of air temperature as its surrogate for available energy, can produce more accurate snow‐covered area (SCA) maps than a traditional TI model. However, it is unclear whether the improved SCA maps are associated with improved snow water equivalent (SWE) estimation across the watershed or improved snowmelt‐derived streamflow simulation. This paper evaluates whether a modified‐TI model produces better streamflow estimates than a TI model when they are used within a fully distributed hydrologic model. It further evaluates the performance of the two models when they are calibrated using either point SWE measurements or SCA maps. The Senator Beck Basin in Colorado is used as the study site because its surface is largely bedrock, which reduces the role of infiltration and emphasizes the role of the SWE pattern on streamflow generation. Streamflow is simulated using both models for 6 years. The modified‐TI model produces more accurate streamflow estimates (including flow volume and peak flow rate) than the TI model, likely because the modified‐TI model better reproduces the SWE pattern across the watershed. Both models also produce better performance when calibrated with SCA maps instead of point SWE data, likely because the SCA maps better constrain the space‐time pattern of SWE.     

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.     

Uncertainty of snow water equivalent retrieved from AMSR‐E brightness temperature in northeast Asia

Accurate estimation of snow water equivalent (SWE) has been significantly recognized to improve management and analyses of water resource in specific regions. Although several studies have focused on developing SWE values based on remotely sensed brightness temperatures obtained by microwave sensor systems, it is known that there are still a number of uncertainties in SWE values retrieved from microwave radiometers. Therefore, further research for improving remotely sensed SWE values including global validation should be conducted in unexplored regions such as Northeast Asia. In this regard, we evaluated SWE through comparison of values produced by the Advanced Microwave Scanning Radiometer Earth Observing System (AMSR‐E) from December 2002 to February 2011 with in situ SWE values converted from snow‐depth observation data from four regions in the South Korea. The results from three areas showed similarities which indicated that the AMSR‐E SWE values were overestimated when compared with in situ SWE values, and their Mean Absolute Errors (MAE) by month were relatively small (1.1 to 6.5 mm). Contrariwise, the AMSR‐E SWE values of one area were significantly underestimated when compared with in situ SWE values and the MAE were much greater (4.9 to 35.2 mm). These results were closely related to AMSR‐E algorithm‐related error sources, which we analyzed with respect to topographic characteristics and snow properties. In particular, we found that snow density data used in the AMSR‐E SWE algorithm should be based on reliable in situ data as the current AMSR‐E SWE algorithm cannot reflect the spatio‐temporal variability of snow density values. Additionally, we derived better results considering saturation effect of AMSR‐E SWE. Despite the demise of AMSR‐E, this study's analysis is significant for providing a baseline for the new sensor and suggests parameters important for obtaining more reliable SWE. Copyright © 2013 John Wiley & Sons, Ltd.     

Changes to flood peaks of a mountain river: implications for analysis of the 2013 flood in the Upper Bow River,Canada

The mountain headwater Bow River at Banff, Alberta, Canada, was subject to a large flood in June 2013, over which considerable debate has ensued regarding its probability of occurrence. It is therefore instructive to consider what information long‐term streamflow discharge records provide about environmental change in the Upper Bow River basin above Banff. Though protected as part of Banff National Park, since 1885, the basin has experienced considerable climate and land cover changes, each of which has the potential to impact observations, and hence the interpretations of flood probability. The Bow River at Banff hydrometric station is one of Canada's longest‐operating reference hydrological basin network stations and so has great value for assessing changes in flow regime over time. Furthermore, the station measures a river that provides an extremely important water supply for Calgary and irrigation district downstream and so is of great interest for assessing regional water security. These records were examined for changes in several flood attributes and to determine whether flow changes may have been related to landscape change within the basin as caused by forest fires, conversion from grasslands to forest with fire suppression, and regional climate variations and/or trends. Floods in the Upper Bow River are generated by both snowmelt and rain‐on‐snow (ROS) events, the latter type which include flood events generated by spatially and temporally large storms such as occurred in 2013. The two types of floods also have different frequency characteristics. Snowmelt and ROS flood attributes were not correlated significantly with any climate index or with burned area except that snowmelt event duration correlated negatively to the Pacific Decadal Oscillation. While there is a significant negative trend in all floods over the past 100 years, when separated based on generating process, neither snowmelt floods nor large ROS floods associated with mesoscale storms show any trends over time. Despite extensive changes to the landscape of the basin and in within the climate system, the flood regime remains unchanged, something identified at smaller scales in the region but never at larger scales. Copyright © 2016 John Wiley & Sons, Ltd.     

Influence of melt‐freeze‐cycles on the radionuclide transport in homogeneous laboratory snowpack

Radionuclides released to the environment and deposited with or onto snow can be stored over long time periods if ambient temperature stays low, particularly in glaciated areas or high alpine sites. The radionuclides will be accumulated in the snowpack during the winter unless meltwater runoff at the snow base occurs. They will be released to surface waters within short time during snowmelt in spring. In two experiments under controlled melting conditions of snow in the laboratory, radionuclide migration and runoff during melt‐freeze‐cycles were examined. The distribution of Cs‐134 and Sr‐85 tracers in homogeneous snow columns and their fractionation and potential preferential elution in the first meltwater portions were determined. Transport was associated with the percolation of meltwater at ambient temperatures above 0 °C after the snowpack became ripe. Mean migration velocities in the pack were examined for both nuclides to about 0.5 cm hr^?1 after one diurnal melt‐freeze‐cycle at ambient temperatures of ?2 to 4 °C. Meltwater fluxes were calculated with a median of 1.68 cm hr^?1. Highly contaminated portions of meltwater with concentration factors between 5 and 10 against initial bulk concentrations in the snowpack were released as ionic pulse with the first meltwater. Neither for caesium nor strontium preferential elution was observed. After recurrent simulated day‐night‐cycles (?2 to 4 °C), 80% of both radionuclides was released with the first 20% of snowmelt within 4 days. 50% of Cs‐134 and Sr‐85 were already set free after 24 hr. Snowmelt contained highest specific activities when the melt rate was lowest during the freeze‐cycles due to concentration processes in remaining liquids, enhanced by the melt‐freeze‐cycling. This implies for natural snowpack after significant radionuclide releases, that long‐time accumulation of radionuclides in the snow during frost periods, followed by an onset of steady meltwater runoff at low melt rates, will cause the most pronounced removal of the contaminants from the snow cover. This scenario represents the worst case of impact on water quality and radiation exposure in aquatic environments.     

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.     

Coupling the WRF model with a temperature index model based on remote sensing for snowmelt simulations in a river basin in the Altay Mountains,north‐west China

Snowmelt water is an important freshwater resource in the Altay Mountains in north‐west China; however, warming climate and rapid spring snowmelt can cause floods that endanger both public and personal property and safety. This study simulates snowmelt in the Kayiertesi River catchment using a temperature index model based on remote sensing coupled with high‐resolution meteorological data obtained from National Centers for Environmental Prediction (NCEP) reanalysis fields that were downscaled using the Weather Research Forecasting model and then bias corrected using a statistical downscaled model. Validation of the forcing data revealed that the high‐resolution meteorological fields derived from the downscaled NCEP reanalysis were reliable for driving the snowmelt model. Parameters of the temperature index model based on remote sensing were calibrated for spring 2014, and model performance was validated using Moderate Resolution Imaging Spectroradiometer snow cover and snow observations from spring 2012. The results show that the temperature index model based on remote sensing performed well, with a simulation mean relative error of 6.7% and a Nash–Sutcliffe efficiency of 0.98 in spring 2012 in the river of Altay Mountains. Based on the reliable distributed snow water equivalent simulation, daily snowmelt run‐off was calculated for spring 2012 in the basin. In the study catchment, spring snowmelt run‐off accounts for 72% of spring run‐off and 21% of annual run‐off. Snowmelt is the main source of run‐off for the catchment and should be managed and utilized effectively. The results provide a basis for snowmelt run‐off predictions, so as to prevent snowmelt‐induced floods, and also provide a generalizable approach that can be applied to other remote locations where high‐density, long‐term observational data are lacking. Copyright © 2016 John Wiley & Sons, Ltd.     

Surface moisture area during rainfall–run‐off events to understand the hydrological dynamics of a basin in a plain region

The understanding of the hydrology of plain basins may be improved by the combined analysis of rainfall–run‐off records and remote sensed surface moisture data. Our work evaluates the surface moisture area (SMA) produced during rainfall–run‐off events in a plain watershed of the Argentine Pampas Region, and studies which hydrological variables are related to the generated SMA. The study area is located in the upper and middle basins of the Del Azul stream, characterized by the presence of small gently hilly areas surrounded by flat landscapes. Data from 9 rainfall–run‐off events were analysed. MODIS surface reflectance data were processed to calculate SMA subsequent to the peak discharge (post‐SMA), and previous to the rainfall events (prev‐SMA), to consider the antecedent wetness. Rainfall–run‐off data included total precipitation depth (P), maximum intensity of rainfall over 6 hr (I6max), surface run‐off registered between the beginning of the event and the day previous to the analysed MODIS scene (R), peak flow (Qp), and flood intensity (IF). In contrast with other works, post‐SMA showed a negative relationship with the R. Three groups of cases were identified: (a) Events of low I6max, high prev‐SMA, and low R were associated with slow and weakly channelized flow over plain areas, leading to saturated overland flow (SOF), with large SMA; (b) events of high I6max, low prev‐SMA, and medium to high R were rapidly transported along the gentle slopes of the basin, related to Hortonian overland flow (HOF) and low post‐SMA; and (c) events of medium to high I6max and prev‐SMA with medium R were related to heterogeneous input‐antecedent‐run‐off conditions combined: Local spatial conditions may have produced HOF or SOF, leading to an averaged response with medium SMA. The interactions between the geomorphology of the basin, the characteristics of the events, and the antecedent conditions may explain the obtained results. This analysis is relevant for the general knowledge of the hydrology of large plains, whose functioning studies are still in their early stages.     

Impact of climate change on runoff from a mid‐latitude mountainous catchment in central Japan

Hydrologic balance in high‐altitude, mid‐latitude mountain areas is important in terms of the water resources available to associated lowlands. This study examined how current and historical shifts in precipitation (P) patterns and concurrent increases in temperature (T) affected runoff (Q) and other hydrologic components in a mid‐latitude mountain catchment of central Japan, using a combination of long‐term data and a simplified hydrologic model, along with their stochastic treatment. The availability of intensive meteorological and hydrological data from the period 1997–2001 allowed the derivation of key relationships for the current climate that tie the forcing term to the parameters or state variables. By using the data recorded in the period 1965–2001, the force for driving the historical simulation was generated. Based on this model and historical shifts in P and T, the probability density functions of Q (pdf(Q)) was computed. A main novelty in this study is that such a stochastic representation, which is useful for considering the influence of projected shifts in environmental factors on the hydrologic budget, was provided. Despite the large increase in the rate of T in winter and spring, pdf(Q) in spring and summer varied appreciably during the time studied mainly because of an increase in snowmelt. An interannual change in whole‐year Q was robust to shifts in T because while Q in spring increased, in summer it decreased, implying a crucial effect of global warming on mountain hydrologic regimes is change in the timing of Q. Copyright © 2009 John Wiley & Sons, Ltd.     

Effects of frozen soil and snow cover on cold‐season soil water dynamics in Tokachi,Japan

Despite the potential impact of winter soil water movements in cold regions, relatively few field studies have investigated cold‐season hydrological processes that occur before spring‐onset of snowmelt infiltration. The contribution of soil water fluxes in winter to the annual water balance was evaluated over 5 years of field observations at an agricultural field in Tokachi, Hokkaido, Japan. In two of the winters, soil frost reached a maximum depth of 0·2 m (‘frozen’ winters), whereas soil frost was mostly absent during the remaining three winters (‘unfrozen’ winters). Significant infiltration of winter snowmelt water, to a depth exceeding 1·0 m, occurred during both frozen and unfrozen winters. Such infiltration ranged between 126 and 255 mm, representing 28–51% of total annual soil water fluxes. During frozen winters, a substantial quantity of water (ca 40 mm) was drawn from deeper layers into the 0–0·2 m topsoil layer when this froze. Under such conditions, the progression and regression of the freezing front, regulated by the thickness of snow cover, controlled the quantity of soil water flux below the frozen layer. During unfrozen winters, 13–62 mm of water infiltrated to a depth of 0·2 m, before the spring snowmelt. These results indicate the importance of correctly evaluating winter soil water movement in cold regions. Copyright © 2010 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.     

Estimating the distribution of snow water equivalent and snow extent beneath cloud cover in the Salt–Verde River basin,Arizona

The temporal and spatial continuity of spatially distributed estimates of snow‐covered area (SCA) are limited by the availability of cloud‐free satellite imagery; this also affects spatial estimates of snow water equivalent (SWE), as SCA can be used to define the extent of snow telemetry (SNOTEL) point SWE interpolation. In order to extend the continuity of these estimates in time and space to areas beneath the cloud cover, gridded temperature data were used to define the spatial domain of SWE interpolation in the Salt–Verde watershed of Arizona. Gridded positive accumulated degree‐days (ADD) and binary SCA (derived from the Advanced Very High Resolution Radiometer (AVHRR)) were used to define a threshold ADD to define the area of snow cover. The optimized threshold ADD increased during snow accumulation periods, reaching a peak at maximum snow extent. The threshold then decreased dramatically during the first time period after peak snow extent owing to the low amount of energy required to melt the thin snow cover at lower elevations. The area having snow cover at this later time was then used to define the area for which SWE interpolation was done. The area simulated to have snow was compared with observed SCA from AVHRR to assess the simulated snow map accuracy. During periods without precipitation, the average commission and omission errors of the optimal technique were 7% and 11% respectively, with a map accuracy of 82%. Average map accuracy decreased to 75% during storm periods, with commission and omission errors equal to 11% and 12% respectively. The analysis shows that temperature data can be used to help estimate the snow extent beneath clouds and therefore improve the spatial and temporal continuity of SCA and SWE products. Copyright © 2004 John Wiley & Sons, Ltd.     

Long‐term investigations of the snow cover in a subalpine semi‐forested catchment

To improve spring runoff forecasts from subalpine catchments, detailed spatial simulations of the snow cover in this landscape is obligatory. For more than 30 years, the Swiss Federal Research Institute WSL has been conducting extensive snow cover observations in the subalpine watershed Alptal (central Switzerland). This paper summarizes the conclusions from past snow studies in the Alptal valley and presents an analysis of 14 snow courses located at different exposures and altitudes, partly in open areas and partly in forest. The long‐term performance of a physically based numerical snow–vegetation–atmosphere model (COUP) was tested with these snow‐course measurements. One single parameter set with meteorological input variables corrected to the prevailing local conditions resulted in a convincing snow water equivalent (SWE) simulation at most sites and for various winters with a wide range of snow conditions. The snow interception approach used in this study was able to explain the forest effect on the SWE as observed on paired snow courses. Finally, we demonstrated for a meadow and a forest site that a successful simulation of the snowpack yields appropriate melt rates. Copyright © 2006 John Wiley & Sons, Ltd.