Snow Depth Distribution Research Articles

Towards a snow-depth distribution model in a heterogeneous subalpine forest using a Landsat TM image and an aerial photograph

AbstractFor landscapes with a complex topography and a heterogeneous forest mosaic it is not feasible to map the snow depth directly from optical satellite images. In this paper, an indirect method to predict the snow-depth distribution is presented and applied to a 0.7 km2 subalpine catchment in central Switzerland. The method consists of (a) a parsimonious linear regression model which includes the attributes of topography and vegetation indices (derived from a Landsat Thematic Mapper (TM) image) as explanatory variables, and (b) geostatistical interpolationtechniques. A previous analysis of the forest mosaic revealed two main scales showing up in the Landsat TM image and an aerial photograph. This discrepancy in scale was assumed to be the major reason why the vegetation indices derived from the Landsat TM image were only weak explanators of the snow-depth variation measured at 100–200 locations within the catchment. Surprisingly, the geostatistical interpolation (universal kriging) was not able to improve the prediction of the snow-depth distribution significantly. The residuals of the regression model showed hardly any spatial dependence for single snow-measurement dates.

Development of an algorithm for estimating snow hydrological parameters in wet snow areas using satellite-based SAR images

The objective of this study is to develop an algorithm for quantitatively estimating snow hydrological parameters using a Synthetic Aperture Radar (SAR) mounted on a satellite and a numerical scattering model. Simultaneous RADARSAT SAR observations were carried out during the winter seasons of 1996 to 1998. The study area is located in the Hokuriku District, Niigata Prefecture, Japan, that is well known for having wet snow with a complicated layer structure from the beginning of the winter season. In previous studies, we sought to estimate the distributions of snow depth and surface roughness using these multi-temporal RADARSAT images. However, snow depths over 20cm were underestimated because the extinction effects at C-band microwave were too large. In this study, we develop an algorithm to estimate distributions of snow density and roughness using observation datasets with some parameterization techniques and assumptions. Furthermore, we show the possibility of inferring snow depths from combined parameters estimated with a L-band SAR image at test sites.

Effect of forest on surface failure caused by snowmelt

We estimated the effect of forest by simulating on surface failure caused by snowmelt at the slopes of forested and unforested areas in the Kobira River basin. The simulation model consisted of a snow model and a surface failure model . The snow model estimates snow depth distribution and snowmelt, using the heat balance method. The surface failure model estimates the ground water level and slope stability, using analyses of saturated-unsaturated infiltration and infinite slope stability model.Generally, landslides are thought more likely on unforested slopes, because of increased snowmelt. In the Kobira River basin, however, forest prolonged snowmelt causing surface failures when heavy rainfall in early April coincided with the peak of snowmelt. The model verified that the presence of forest changed the landslide potential . This will make it possible to predict surface failures and debris flows during the snowmelt period . These results provide fundamental information for planning warning and evacuation systems to prevent sediment disasters.

OBSERVATION OF SNOWFALL BY RADAR RAFNGAUGE

To utilize data of Radar rain gauge in prediction for snowfall disttibution a model was proposed In this model, a calculation of wind field on arbitrary terrain is included. The accuracy of the prediction model are examined by comparisons with field data of hourly measurements of snow fall at seven sites, maximum snow depth distribution in dam depth basin and dam inflow.

Initial results from a distributed, physically based model of glacier hydrology

This paper describes the development and testing of a distributed, physically based model of glacier hydrology. The model is used to investigate the behaviour of the hydrological system of Haut Glacier d'Arolla, Valais, Switzerland. The model has an hourly time-step and three main components: a surface energy balance submodel, a surface flow routing submodel and a subglacial hydrology submodel. The energy balance submodel is used to calculate meltwater production over the entire glacier surface. The surface routing submodel routes meltwater over the glacier surface from where it is produced to where it either enters the subglacial hydrological system via moulins or runs off the glacier surface. The subglacial hydrology submodel calculates water flow in a network of conduits, which can evolve over the course of a melt season simulation in response to changing meltwater inputs. The main model inputs are a digital elevation model of the glacier surface and its surrounding topography, start-of-season snow depth distribution data and meteorological data. Model performance is evaluated by comparing predictions with field measurements of proglacial stream discharge, subglacial water pressure (measured in a borehole drilled to the glacier bed) and water velocities inferred from dye tracer tests. The model performs best in comparison with the measured proglacial stream discharges, but some of the substantial features of the other two records are also reproduced. In particular, the model results show the high amplitude water pressure cycles observed in the borehole in the mid-melt season and the complex velocity/discharge hysteresis cycles observed in dye tracer tests. The results show that to model outflow hydrographs from glacierized catchments effectively, it is necessary to simulate spatial and temporal variations in surface melt rates, the delaying effect of the surface snowpack and the configuration of the subglacial drainage system itself. The model's ability to predict detailed spatial and temporal patterns of subglacial water pressures and velocities should make it a valuable tool for aiding the understanding of glacier dynamics and hydrochemistry. © 1998 John Wiley & Sons, Ltd.

A snow-transport model for complex terrain

AbstractAs part of the winter environment in middle- and high-latitude regions, the interactions between wind, vegetation, topography and snowfall produce snow covers of non-uniform depth and snow water-equivalent distribution. A physically based numerical snow-transport model (SnowTran-3D) is developed and used to simulate this three-dimensional snow-depth evolution over topographically variable terrain. The mass-transport model includes processes related to vegetation snow-holding capacity, topographic modification of wind speeds, snow-cover shear strength, wind-induced surface-shear stress, snow transport resulting from saltation and suspension, snow accumulation and erosion, and sublimation of the blowing and drifting snow. The model simulates the cold-season evolution of snow-depth distribution when forced with inputs of vegetation type and topography, and atmospheric foreings of air temperature, humidity, wind speed and direction, and precipitation. Model outputs include the spatial and temporal evolution of snow depth resulting from variations in precipitation, saltation and suspension transport, and sublimation. Using 4 years of snow-depth distribution observations from the foothills north of the Brooks Range in Arctic Alaska, the model is found to simulate closely the observed snow-depth distribution patterns and the interannual variability.

A snow-transport model for complex terrain

AbstractAs part of the winter environment in middle- and high-latitude regions, the interactions between wind, vegetation, topography and snowfall produce snow covers of non-uniform depth and snow water-equivalent distribution. A physically based numerical snow-transport model (SnowTran-3D) is developed and used to simulate this three-dimensional snow-depth evolution over topographically variable terrain. The mass-transport model includes processes related to vegetation snow-holding capacity, topographic modification of wind speeds, snow-cover shear strength, wind-induced surface-shear stress, snow transport resulting from saltation and suspension, snow accumulation and erosion, and sublimation of the blowing and drifting snow. The model simulates the cold-season evolution of snow-depth distribution when forced with inputs of vegetation type and topography, and atmospheric foreings of air temperature, humidity, wind speed and direction, and precipitation. Model outputs include the spatial and temporal evolution of snow depth resulting from variations in precipitation, saltation and suspension transport, and sublimation. Using 4 years of snow-depth distribution observations from the foothills north of the Brooks Range in Arctic Alaska, the model is found to simulate closely the observed snow-depth distribution patterns and the interannual variability.

The features of sea-ice cover, snow distribution and its densification in the central arctic ocean

Based on the observation of sea-ice cover and measurement of snow depths and stratigraphy during China’s First North Pole Scientific Expedition, three types of surface topography of sea ice and correspondingly three categories of snow distribution in the central Arctic are classified. It is considered that the classification will help to determine the sites for snow depth measurement, stratigraphy observation and snowpits sampling. The snow cover is slowly accumulated during the long Arctic winter, approximately from September to early May next year, while its ablation shows abrupt from south to north. By the end of August, the snow cover is almost totally removed. The spatial distribution of snow depth is characterized by a northwardly decreasing trend, which is proposed to result from the remote vapour sources, i.e., the major vapour over the Arctic regions is transported from mid-latitudes. The stratigraphy of the snowpits are characterized by the extensively existed depth hoar at the deeper part of the pits, which is probably a signal of the beginning of the long Arctic winter. The present of infiltration-congelation ice adhering to sea ice surface at the end of the ablation season indicates that the annual accumulation is approximately equals to the annual ablation near north pole.

SMALL-SCALE SPATIAL STRUCTURE OF SHALLOW SNOWCOVERS

The results of a field study of the small-scale spatial structure of the depth of shallow seasonal snowcovers in prairie and arctic environments are presented. It is shown that the spatial distribution of snow depth is fractal at small scales, becoming random at scales beyond some limiting length. This is due to the autocorrelation of depth at small sampling distances. The transition of fractal to random behaviour is indexed by a 'cutoff length', which is defined by the intersection of the 'fractal' slope and horizontal tangent of a logarithmic plot of the standard deviation of depth versus sampling distance. The magnitude of the cutoff length is related to the degree of macroscopic variability of the underlying topography. An increase in length due to the effects of macroscopic topographic variability on snowcover accumulation is confirmed by de-trending field measurements. The de-trended data shown a cutoff length for wheat stubble and fallow surfaces of approximately 30 m, which is consistent with the distance determined from measurements on 'flat' fields. The implications of the transition of snow depth from fractal to random structure on the scales of snow sampling and modelling are presented. The cutoff length may provide a statistic for stratifying shallow snowcovers, by linking snowcover properties to the underlying topography.

On water balance in a basin with heavy snow area

Annual water balance is investigated in the Taki dam basin, which area is about 2, 000km2 and has heavy snow area. A method of snowfall correction on precipitation, the Thornthwaite method on evapotranspiration and a simple balance model on ground water are applied to evaluate each components in hydrological cycle and the total balance is discussed. Snowmelt volume is calculated from both the tank model and water balance equation and the runoff delay of meltwater is discussed. Conclusions are; 1. snowdepth distribution depends on the total snowfall volume 2. actual evapotranspiration can be estimated by the Thornthwaite method and 3. daily snowmelt runoff is almost constant.

On the estimation of snow volume in Tohoku district

Snow volume in Tohoku district is evaluated by using measured snow covered area and snow depth distribution model. Snow covered area is detected from NOAA/AVHRRda ta by authors shceme. In order to obtain snow distribution of whole Tohoku district, a new method is used to composit three different images. The snow depth distribution is studied empirically. The dependency of snow depth on height, latitude and longitude is comfirmed by referring AMeDASda ta. Combining above methods, snow volume in Tohoku district at the first ten days of Feburary is estimated.

Snowdepth model during snowmelt season in the Taki dam basin

An evaluation method of total precipitation (snow and rain) volume in the Taki dam basin from a few meteorological points is discussed. This method is based on comparison of snow depth data at observation points with the snow survey conducted once a year. 1) Evapotranspiration and groundwater balance are evaluated by Thornthwaite method and by simple model respectively. 2) Water balance in the basin is studied in snowmelt season. 3) Taking account of the relationship between snow moisture volume and snow area from NOAA-AVHRR data, snow depth distributions is estimated.

Strategies of Survival in Plants of the Fenoscandian Tundra

Many arctic species originated outside the Arctic and some of their physiological responses are similar to those in temperate latitudes. Unique adaptations to the Arctic have rarely been found. The recent influx of other species has, however, broken down reproductive barriers and gene flow has been stimulated. In extreme arctic environments, selection forces driving evolution are mainly of the physical environment and plant interactions are positive. Elsewhere, biotic factors, such as herbivory, are important and plant interactions become negative through competition. Physical selective forces operate in winter and summer. Low winter temperatures rarely affect arctic plants, but snow depth and duration influence species distributions. Deep and persistent snow deforms plants and limits the period of resource acquisition. Cryptogams are common in such snow beds. Little or no snow cover exposes plants to abrasion by wind-blown particles and desiccation. In such fell-field sites, deciduous species and xerophytes, such as evergreen cushion plants, are common. Arctic summers are short and developmental processes are extended beyond one growing season, with perennials predominating. Cushion plants efficiently increase their temperatures above ambient, while evergreen and deciduous ericaceous dwarf shrubs coexist and have complementary strategies for intercepting radiation in a low canopy. Tundra soils are generally infertile and may be disturbed by freeze/thaw cycles. Nutrients are conserved by cycling within shoots and between ramets within clones. Vegetative proliferation enhances the survival of young ramets, while physiological integration between ramets enables young ramets to forage across patchy environments. Negative plant-animal relationships are particularly important in the Subarctic. Periodic infestation of moth caterpillars defoliate large areas of mountain birch and stimulate increases in populations of their predators. Periodic population peaks of small rodents graze or kill much vegetation and they may moderate the dynamic structure of plant communities, as the plant species have different abilities to regenerate.Key words: arctic plants, tundra, winter, snow, frost

Monte Carlo Simulation of Snow Depth in a Forest

Snow depth in a forest is highly variable and to reduce the cost of extensive field sampling for obtaining mean depths, a simulation model was developed. First, the location of individual trees in a representative portion of the forest is either surveyed in the field or simulated based on the statistical characteristics pertaining to the distribution of trees. In this forest, a large number of randomly located sample points is generated by Monte Carlo technique. The azimuth and distance from each point to the nearest tree is determined, and a snow depth simulated based on the observed snow depth distribution around individual trees. The model was applied successfully to a northern spruce forest in subarctic Ontario, showing that this simulation provides a useful approach to determine mean snow depth.

The mountain snowfall in Chugoku district, west Japan

Characteristics of snowfall in the mountain region of the Chugoku district, west Japan are reviewed and compared with the results of an areal snow survey. The regional dependency of the snow depth distribution is marked compared to the altitude effect. The non-existence of terrain obstacles to the winter monsoon is favorable for heavy snowfall. Orographic development of cumulus clouds is suggested through the decreasing rate of chemical content in the snow. The regional difference of cumulus development is also revealed by snow crystal observations. The oxygen isotope composition of the snow particles suggests a different mechanism of snowfall on the west side of the mountains.

On the Use of Telephone Poles for the Observation of Areal Snow-Depth Distribution

For the observation of areal snow-depth distribution over a wide area, such as the Ishikari Plain in Hokkaido, Japan, existing telephone poles were used in place of the snow scales. Telephone pole number plates (telephone poles in Japan have number plates) were photographed by a 35 mm camera with zoom lens ranging from 80 mm to 200 mm through the window of the observation vehicle. The snow depth was calculated by the ratios of the length of the number plates to the distance between the lower edge of the number plates and the snow surface. Since measurements by direct sounding using a rod as compared with the values by the above method showed a good coincidence with an accuracy of ± 10 cm, it was considered satisfactory for snow depth observation over a wide area.

On the Use of Telephone Poles for the Observation of Areal Snow-Depth Distribution

For the observation of areal snow-depth distribution over a wide area, such as the Ishikari Plain in Hokkaido, Japan, existing telephone poles were used in place of the snow scales. Telephone pole number plates (telephone poles in Japan have number plates) were photographed by a 35 mm camera with zoom lens ranging from 80 mm to 200 mm through the window of the observation vehicle. The snow depth was calculated by the ratios of the length of the number plates to the distance between the lower edge of the number plates and the snow surface. Since measurements by direct sounding using a rod as compared with the values by the above method showed a good coincidence with an accuracy of ± 10 cm, it was considered satisfactory for snow depth observation over a wide area.

Snow Surveys by aerial photographs

On the occasion of the heavy snow fall in January, 1963 in Hokuriku district the Geographical Survey Institute started its snow surveys by aerial photographs on a scale of 1 : 20, 000. Snow depth was measured at snow fissures on the slopes or exposed snow sections near the water on the photographs, using Stereotope, the third order instrument. At the same time the data on snow depth were collected at the observatories in the area. On the basis of these materials and stereoscopic photointerpretation the snow depth map 1 : 200, 000 was compiled, on which the isodepth lines of snow cover were illustrated at one meter interval. Distribution of snow avalanches as well as the prevailing wind direction on the ground were also analyzed by stereoscopic photointerpretation.After this, maps of the same kind, but more improved, were compiled for many areas. In this paper, referring the snow surveys along the planning routes of Tokai-Hokuriku, Chugoku-Odan and Tohoku-Odan Expressways, the method of show depth measurement, classification of mountain slopes for predicting the occurrence of snow avalanches and the method for estimating the force of snow avalanches are explained. To measure the snow depth on aerial photographs, the so-called relative height method is mainly used, that is to measure the relative height of snow surface from the ground using facilities such as airphoto signals for snow season. At the same time as indirect method the comparison of exposure of roads, railways as well as houseroofs in the snow and non snow seasons were also introduced. The deepest snow depth in the past was estimated from the photographing date by correlation analysis.The main results obtained are the classification of mountain slopes based on the occurrence ratio of snow avalanches and results of field surveys (Table 5), the map of snow depth and snow avalanches distribution (Fig. 11), and of the danger-degree distribution of snow avalanches (Fig. 12).

Distribution of Snow Depth on the Western Slope of Mt. Jizô

On the western slope of Mt. Jizo, the northernmost peak of Zao Mountains, the maximum snow depth was seen at the height of about 1500 m above sea level on 19th March 1969, and the depth was lees both on the lower and higher slope (Fig. 1). The snow density decreased according to the altitude making a concave curve as Fig. 2. The distribution pattern of snow depth on 3rd April, about two weeks later, resembles that on 19th March (Fig. 1), but the snow depth was less in the lower slope and more in the upper.

Effect of wind speed and microtopography on the distribution of snow depth

Effect of wind speed and microtopography on the distribution of snow depth