| 1. |
- Granlund, Nils, et al.
(författare)
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Laboratory study of the influence of salinity on the relationship between electrical conductivity and wetness of snow
- 2010
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Ingår i: Hydrological Processes. - : John Wiley & Sons. - 0885-6087 .- 1099-1085. ; 24:14, s. 1981-1984
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Tidskriftsartikel (refereegranskat)abstract
- Snow water equivalent of a snowpack can be estimated using ground-penetrating radar from the radar wave two-way travel time. However, such estimates often have low accuracy when the snowpack contains liquid water. If snow wetness is known, it is possible to take it into account in the estimates; it is therefore desirable to be able to determine snow wetness from already available radar data. Our approach is based on using radar wave attenuation, and it requires that the relationship between electrical conductivity and wetness of snow should be known. This relationship has been tentatively established in previous laboratory experiments, but only for a specific liquid water salinity and radar frequency. This article presents the results of new laboratory experiments conducted to investigate if and how this relationship is influenced by salinity. In each experiment, a certain amount of snow was melted and a known amount of salt (different for different experiments) was added to the water. Water salinity was measured, and the water was added step-wise to a one-meter thick snowpack, with radar measurements taken between additions of water. Our experiments have confirmed the earlier established linear relationship between electrical conductivity and wetness of snow, and they allow us to suggest that the influence of liquid water salinity on electrical conductivity is negligible when compared to the influence of liquid water content in snow.
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| 2. |
- Lundberg, Angela, et al.
(författare)
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Estimating winter evaporation in boreal forests with operational snow course data
- 2003
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Ingår i: Hydrological Processes. - : Wiley. - 0885-6087 .- 1099-1085. ; 17:8, s. 1479-1493
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Tidskriftsartikel (refereegranskat)abstract
- Snow course measurements from 11 sites located in eastern and northern Finland were used to estimate the total interception evaporation of a winter season for different forest categories. We categorized the sites based on forest density and tree species. Results showed that interception loss from gross precipitation increased with forest density and approached 30% for a forest with the highest density class. Interception loss for the most common forest density class was 11%. Interception losses were slightly larger in spruce forests than in pine, deciduous, or mixed forests. We provide suggestions as to how to design snow surveys to estimate wintertime interception evaporation better. Rough terrain and transition zones between forest and open areas should be avoided. Since evaporation fraction was strongly dependent on tree crown characteristics, snow course data should include direct estimates of canopy closure. Qualitative observations made by different observers should be given a reference frame to ensure comparability of records from different sites.
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| 3. |
- Lundberg, Angela, et al.
(författare)
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Snow accumulation in forests from ground and remote sensing data
- 2004
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Ingår i: Hydrological Processes. - : Wiley. - 0885-6087 .- 1099-1085. ; 18:10, s. 1941-1955
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Tidskriftsartikel (refereegranskat)abstract
- Winter-forest processes affect global and local climates. The interception-sublimation fraction (F) of snowfall in forests is a substantial part of the winter water budget (up to 40%). Climate, weather-forecast and hydrological modellers incorporate increasingly realistic surface schemes into their models, and algorithms describing snow accumulation and snow-interception sublimation are now finding their way into these schemes. Spatially variable data for calibration and verification of wintertime dynamics therefore are needed for such modelling schemes. The value of F was determined from snow courses in open and forested areas in Hokkaido, Japan. The value of F was related to species and canopy-structure measures such as closure, sky-view fraction (SVF) and leaf-area index (LAI). Forest structure was deduced from fish-eye photographs. The value of F showed a strong linear correlation to structure: F = 0·44 - 0·6 × SVF for SVF < 0·72 and F = 0 for SVF > 0·72, and F = 0·11 LAI. These relationships seemed valid for evergreen conifers, larch trees, alder, birch and mixed deciduous stands. Forest snow accumulation (SF) could be estimated from snowfall in open fields (So) and to LAI according to SF = So (1 - 0·11 LAI) as well as from SVF according to SF = So (0·56 + 0·6 SVF) for SVF < 0·72. The value of SF was equal to So for SVF values above 0·72. The value of sky-view fraction was correlated to the normalized difference snow index (NDSI) using a Landsat-TM image for observation plots exceeding 1 ha. Variables F and SF were related to NDSI for these plots according to: F = -0·37NDSI + 0·29 and SF = So (0·81 + 0·37NDSI). These relationships are somewhat hypothetical because plot-size limitation only allowed one sparse-forest observation of NDSI to be used. There is, therefore, a need to confirm these relationships with further studies.
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| 4. |
- Lundberg, Angela, et al.
(författare)
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Snow and frost : implications for spatiotemporal infiltration patterns - a review
- 2016
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Ingår i: Hydrological Processes. - : Wiley. - 0885-6087 .- 1099-1085. ; 30:8, s. 1230-1250
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Tidskriftsartikel (refereegranskat)abstract
- Vast regions of the northern hemisphere are exposed to snowfall and seasonal frost. This has large effects on spatiotemporal distribution of infiltration and groundwater recharge processes as well as on the fate of pollutants. Therefore, snow and frost need to be central inherent elements of risk assessment and management schemes. However, snow and frost are often neglected or treated summarily or in a simplistic way by groundwater modellers. Snow deposition is uneven, and the snow is likely to sublimate, be redistributed and partly melt during the winter influencing the mass and spatial distribution of snow storage available for infiltration, the presence of ice layers within and under the snowpack and, therefore, also the spatial distribution of depths and permeability of the soil frost. In steep terrain, snowmelt may travel downhill tens of metres in hours along snow layers. The permeability of frozen soil is mainly influenced by soil type, its water and organic matter content, and the timing of the first snow in relation to the timing of sub-zero temperatures. The aim with this paper is to review the literature on snow and frost processes, modelling approaches with the purpose to visualize and emphasize the need to include these processes when modelling, managing and predicting groundwater recharge for areas exposed to seasonal snow and frost
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| 5. |
- Lundberg, Angela, et al.
(författare)
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Snow density variations : consequences for ground-penetrating radar
- 2006
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Ingår i: Hydrological Processes. - : Wiley. - 0885-6087 .- 1099-1085. ; 20:7, s. 1483-1495
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Tidskriftsartikel (refereegranskat)abstract
- Reliable hydrological forecasts of snowmelt runoff are of major importance for many areas. Ground-penetrating radar (GPR) measurements are used to assess snowpack water equivalent for planning of hydropower production in northern Sweden. The travel time of the radar pulse through the snow cover is recorded and converted to snow water equivalent (SWE) using a constant snowpack mean density from the drainage basin studied. In this paper we improve the method to estimate SWE by introducing a depth-dependent snowpack density. We used 6 years measurements of peak snow depth and snowpack mean density at 11 locations in the Swedish mountains. The original method systematically overestimates the SWE at shallow depths (+25% for 0·5 m) and underestimates the SWE at large depths (-35% for 2·0 m). A large improvement was obtained by introducing a depth-density relation based on average conditions for several years, whereas refining this by using separate relations for individual years yielded a smaller improvement. The SWE estimates were substantially improved for thick snow covers, reducing the average error from 162 ± 23 mm to 53 ± 10 mm for depth range 1·2-2·0 m. Consequently, the introduction of a depth-dependent snow density yields substantial improvements of the accuracy in SWE values calculated from GPR data.
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| 6. |
- Lundberg, Angela, et al.
(författare)
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Towards automated 'Ground truth' snow measurements : a review of operational and new measurement methods for Sweden, Norway, and Finland
- 2010
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Ingår i: Hydrological Processes. - : Wiley. - 0885-6087 .- 1099-1085. ; 24:14, s. 1955-1970
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Tidskriftsartikel (refereegranskat)abstract
- Manual snow measurements are becoming increasingly expensive and climate-change-imposed snow alterations are affecting run-off and frost patterns; snow observations are included in run-off modelling, making reliable snow observations of utmost importance. Multiple new and modified ground-based techniques for monitoring snow depth, density, snow water equivalent (SWE), wetness, and layering have been tested over the last decade, justifying a review of such methods. Techniques based on snow mass, electrical properties, attenuation of radioactivity, and other miscellaneous properties are reviewed. The following sensors seem suitable for registration of temporal variations: ultrasonic (depth) and terrestrial laser scanning (depth), several snow pillows at the same location (SWE), Cold Regions Research and Engineering Laboratory/Natural Resources Conservation Service weighing sensor (SWE), Snowpower (depth, density, SWE, and wetness), active and passive (cosmic) gamma-ray attenuation (SWE), and adjusted time domain reflectometry probes (density and wetness). Ground-penetrating radar (GPR) is, depending on the design and operation modes, suitable for different purposes; when arrays of antennas are pulled by a snowmobile, the technique is suitable for monitoring of spatial variations in depth, density, and SWE for dry snow. Techniques are under development, which will hopefully improve the accuracy for wet snow measurements. Frequency-modulated continuous wave GPRs seem fit for measurement of snow layering. Some suggested techniques are not operational yet. Copyright (C) 2010 John Wiley & Sons, Ltd.
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