CHARACTERISTICS OF SNOWMELT FROM NRCS SNOTEL (SNOwTELemetry) SITES by Keith R. Cooley and Peter Palmer
Hydro-fuels-, Maintenance-, and Pricing Risk Management --Changing Times in Snow Zone Water Management by Gary J. Freeman
SPATIALLY-DISTRIBUTED MODELING OF SNOW IN THE BOREAL FOREST: A SIMPLE APPROACH by Robert E. Davis, C. Woodcock, J.P. Hardy, W. Ni, R. Jordan and J.C. McKenzie
ESTIMATING THE SPATIAL DISTRIBUTION OF SNOW WATER EQUIVALENCE IN A MONTANE WATERSHED by Kelly Elder, Walter Rosenthal, Bert Davis
SNOW ACCUMULATION UNDER VARIOUS FOREST STAND DENSITIES AT TENDERFOOT CREEK EXPERIMENTAL FOREST, MONTANA, USA by Chadwick A. Moore and Ward W. McCaughey
HISTORIC ROLE OF FIRE IN DETERMINING ANNUAL WATER YIELD FROM TENDERFOOT CREEK EXPERIMENTAL FOREST, MONTANA, USA by Ward W. McCaughey, Phillip E. Farnes, and Katherine J. Hansen
FIELD MEASUREMENTS OF SNOWDRIFT DEVELOPMENT RATE by R.B. Haehnel, J.H. Lever and R.D. Tabler
ATLANTIC OCEAN-ATMOSPHERE INTERACTIONS AND SNOWFALL IN SOUTHERN NEW ENGLAND by Suzanne Hartley
THE EFFECTS OF LIGHT INTENSITY AND BLUE, GREEN AND RED WAVELENGTHS ON MATING STRATEGIES IN THE SNOW ALGA, CHLOROMONAS SP.-D, FROM THE TUGHILL PLATEAU, NEW YORK STATE by Ronald W. Hoham, Jennifer Y. Kang, Andrew J. Hasselwander, Alissa F. Behrstock, Ian R. Blackburn, Rurik C. Johnson and Erin M. Schlag
THE IMPACT OF GLACIER RECESSION UPON THE DISCHARGE OF THE BOW RIVER ABOVE BANFF, ALBERTA, 1951-1993 by Chris Hopkinson and Gordon Young
SNOWPACK CHEMISTRY AS AN INDICATOR OF POLLUTANT EMISSION LEVELS FROM MOTORIZED WINTER VEHICLES IN YELLOWSTONE NATIONAL PARK by George Ingersoll, John Turk, Craig McClure, Sean Lawlor, Dave Clow, and Alisa Mast
SNOW ABLATION MODELING IN CONIFER AND DECIDUOUS STANDS OF THE BOREAL FOREST by Hardy, J.P., R. E. Davis, R. Jordan, W. Ni and C. Woodcock
VERY WARM STORMS AND SIERRA NEVADA SNOWPACKS by Richard Kattelmann
ACCUMULATION OF INTERCEPTED SNOW IN THE BOREAL FOREST: MEASUREMENTS AND MODELLING by N. R. Hedstrom and J. W. Pomeroy
APPLICATION OF SLURP HYDROLOGICAL MODEL TO A SUB-ARCTIC BASIN by B. Li, G. Kite and U. Haberlandt
AN OPERATIONAL DISTRIBUTED SNOW DYNAMICS MODEL FOR THE SAVA RIVER, BOSNIA by Melloh, R., S. Daly, R. Davis, R. Jordan and G. Koenig
SPATIALLY-DISTRIBUTED SNOWMELT RATES IN A BOREAL FOREST BASIN by Metcalfe, R.A., and Buttle, J.M.
LOCAL ADVECTION OF SENSIBLE HEAT DURING SNOWMELT by Natasha Neumann and Philip Marsh
DEVELOPMENT OF THE PRAIRIE BLOWING SNOW MODEL FOR APPLICATION IN CLIMATOLOGICAL AND HYDROLOGICAL MODELS by J. W. Pomeroy and L. Li
THE INTERACTIVE MULTISENSOR SNOW AND ICE MAPPING SYSTEM by Bruce H. Ramsay
AN EXPERIMENT IN USE OF SEASONAL LONG-RANGE WEATHER FORECASTS FOR WATER SUPPLY FORECASTS IN NORTHERN CALIFORNIA by Maurice Roos and Charles Ross
EFFECTS OF CLIMATE CHANGE ON WATER RESOURCES AND RUNOFF IN AN ALPINE BASIN by Klaus Seidel, Cornel Ehrler and Jaroslav Martinec
LEARNING SCIENTIFIC WRITING THROUGH SNOWPACK STUDY by Richard M. Chisholm
STEPWISE MULTIPLE REGRESSION SNOW MODELS: GIS APPLICATIONS IN THE MARMOT CREEK BASIN, (KANANASKIS COUNTRY, ALBERTA) CANADA AND THE NATIONAL PARK BERCHTESGADEN, (BAYERN) GERMANY by K. Wayne Forsythe
SPATIAL AND TEMPORAL VARIABILITY OF CANADIAN MONTHLY SNOW DEPTHS, 1946- 1995 by Ross D. Brown and Robert O. Braaten
IMPACT OF CLIMATIC WARMING TO THE DROUGHTS OF CANADIAN PRAIRIES by Thian Yew Gan, Purushottam R. Singh and Michael Seneka
THE NET VOLUMETRIC LOSS OF GLACIER COVER WITHIN THE BOW VALLEY ABOVE BANFF, 1951-1993. by Chris Hopkinson
COAL LAKE OUTLET FREEZE-UP, CONTAINMENT OF WINTER INFLOWS AND ESTIMATES OF RELATED OUTBURST FLOOD ON WOLF CREEK, YUKON TERRITORY by M. Jasek and G. Ford
A DETECTOR FOR DETERMINING SNOW WATER CONTENT BASED ON ATTENUATION OF COSMIC RADIATION by Frank Gehrke
COMPARISON OF AVERAGE ANNUAL PRECIPITATION DISTRIBUTED BY DIFFERENT GIS MODELS FOR THE BITTERROOT WATERSHED, MONTANA by Robert G. Hammer, Phillip E. Farnes, and Robert A. McLeod
RIVER BASIN VARIATIONS IN SIERRA NEVADA SNOWPACK ACCUMULATION TRENDS by Tammy Johnson, Jeff Dozier, Joel Michaelsen and Pete Fohl
SCALE EFFECTS IN A DISTRIBUTED SWE AND SNOWMELT MODEL FOR MOUNTAIN BASINS by Don Cline, Kelly Elder, Roger Bales
DETERMINATION OF SNOW COVERED AREA USING RADARSAT IMAGERY ON TWO SMALL TEST SITES IN SOUTHERN ONTARIO by F. Seglenieks, E.D. Soulis, and N. Kouwen
MEASUREMENT OF DIFFERENCES IN SNOW ACCUMULATION, MELT, AND MICROMETEOROLOGY BETWEEN CLEARCUT AND MATURE FOREST STANDS by Pascal Storck, Travis Kern, Susan Bolton
SPATIALLY DISTRIBUTED SNOWMELT INPUTS TO A SEMI-ARID MOUNTAIN WATERSHED by Charles H. Luce, David G. Tarboton, Keith R. Cooley
OVERCOLLECTION OF SOLID PRECIPITATION BY A STANDARD PRECIPITATION GAGE, NIWOT RIDGE, COLORADO by Tim Bardsley and Mark W. Williams
SNOWPACK CHARACTERISTICS OF AN ALPINE SITE IN THE SIERRA NEVADA by Richard Kattelmann
AN INVESTIGATION OF THE THERMAL PROPERTIES OF TRADITIONAL SNOW SHELTERS by Derek Mueller
Snowmelt is affected by a number of factors including elevation, slope, aspect, exposure, snowpack depth, surface reflectance and climatic or meteorologic variables such as solar radiation, temperature, wind speed, vapor pressure, and precipitation. Snowmelt models attempt to account for these factors in various degrees from simple empirical relationships based on air temperature to detailed energy balance procedures. While detailed energy balance models should be superior in estimating snowmelt, there are rarely, if ever, adequate data sets available in practice to use these methods without making simplifying assumptions. Unfortunately, these simplifications usually reduce the models’ ability to account for the various meteorologic factors that cause snowmelt to occur. Thus the models can produce estimates of snowmelt based on the input data available and the assumptions required, but these estimates may not relate to actual snowmelt in timing or rate. Since actual snowmelt data is very limited, it is seldom possible to compare model simulated melt rates with actual values. This paper is significant because it presents an analysis of snowmelt data under a variety of conditions encountered at representative SNOTEL sites selected from nearly 600 locations in the western United States. It thus provides a range of snowmelt information including average and maximum daily melt rates, time of onset and cessation of melt, and average day of maximum snowmelt that can be used to compare with snowmelt model simulations and other uses.
In August 1996, the California Legislature passed legislation (AB 1890) that established new policies and restructured California’s electric Industry. The Bill established an Independent System Operator (ISO), a Power Exchange (PX), a rate-reduction financing program, a public benefits program, and called for increased system reliability. With the deregulation of California’s electric utility industry taking place, the water management team at Pacific Gas and Electric Company (PG&E), an investor owned utility, is facing a new challenge. Future pricing uncertainty will likely become as important to snow zone reservoir management as seasonal remaining weather uncertainty has traditionally been for forecasting snowmelt runoff and maximizing hydro generation in the past. While PG&E has been utilizing probabilistic extended streamflow predictions for some time in making hydroelectric scheduling decisions, it has only recently begun to look at how weather uncertainty will be handled by energy traders that are selling electricity into the California Power Exchange and eventually into a futures market. Electricity futures market pricing (one to three months ahead) is beginning to have a significant effect on how much risk an operator may be willing to take with regard to storing water in anticipation of a better price at some future date. In a sense, water is perishable with regard to use for hydro generation. If stored, there is risk that the weather could turn wet and that water may be spilled past fully loaded powerhouses.
Simulations using physics-based, coupled canopy-snow models provided the basis for developing simple regression models of net energy transfer to snow cover in the boreal forest. The simple models were driven by incoming solar radiation to the top of forest canopies, forest species, tree height and canopy density. Maps of the forest characteristics provided the basis for spatially distributing snow predictions over two test areas in the boreal forest. Over both test areas, variation of incoming solar radiation explained much of the variance in net energy transfer to snow cover. We found the strongest correlations for the relatively open, discontinuous canopies of the northern boreal forest.
We describe an approach to model distributed snow water equivalence (SWE) that merges field measurements of depth and density with remotely sensed snow-covered area (SCA). In 1993 two teams conducted an intensive snow survey in the 92.8 km2 Blackcap Basin of the Kings River. We measured snow depth at 709 points and density in five snow pits and along five transects using a Federal Sampler. Sample locations were chosen to be representative of the range of elevations, slopes and aspects of the basin. Regression tree models showed that net radiation, elevation, and slope angle account for 60-70% of the variance in the depth measurements. Density was distributed over the basin on a 30 m grid with a multiple linear regression model that explained 70% of the observed variance as a function of the same three variables. The gridded depth estimates combined with modeled density produced spatially distributed estimates of SWE. An unsupervised spectral unmixing algorithm estimated snow cover fractions from Landsat-5 Thematic Mapper data acquired at the time of the snow survey. This method provides a snow cover fraction estimate for every pixel. We used this subpixel map as our best estimate for SCA and combining it with the SWE map allowed us to compute SWE volume. We compared the estimated volume using the subpixel SCA map with several SCA maps produced with simulations of binary SCA mapping techniques. Thresholds of 40%, 50% and 60% fractional cover were used to map binary cases of full snow cover or no snow cover. The difference in basin SWE volume was up to 13% depending on the threshold used to classify snow-covered versus snow-free areas. The percent differences in volumes roughly corresponded to the percent differences in SCA between the methods.
Snow accumulation in forested watersheds is controlled by climate, elevation, topographic factors and vegetation structure. Conifers affect snow accumulation principally by intercepting snow with the canopy which may later be sublimated. Various tree, stand, species and canopy densities of a subalpine fir habitat (ALBA/VASC) in central Montana were studied to determine if there was a response of snow accumulation to vegetation. Tree canopy cover, basal area, age since stand initiation, and species composition were measured at several sites with minimal topographic differences. Peak snow water equivalent was measured at 270 sample points within 8 stands divided between 3 study areas and at three corresponding open meadows. The study took place during the winter of 1995-1996 on the Tenderfoot Creek Experimental Forest in the Little Belt Mountains near Great Falls, Montana. It is administered by the USDA Rocky Mountain Research Station.
Variation in peak accumulation (SWE) on the forest floor was impacted the greatest by the percent of canopy cover measured by the 30o view angle of a photocanopyometer. Half of the variation in snow accumulation can be attributed to variation in canopy cover. A 6.4 percent decrease in peak snow water equivalent was observed per 10 percent increase in canopy density. Snow samples under subalpine fir and Engelmann spruce canopies showed a closer correlation between canopy and peak snow water equivalent than did lodgepole pine canopies. Basal area was found to be a poor predictor of snow accumulation.
Water production from mountain watersheds depends on total precipitation input, the type and distribution of precipitation, the amount intercepted in tree canopies, and losses to evaporation, transpiration and groundwater. A systematic process was developed to estimate historic average annual runoff based on fire patterns, habitat cover types and precipitation patterns on the Tenderfoot Creek Experimental Forest.
A fire history study in the Little Belt Mountains of central Montana indicates much of the experimental forest watershed burned in the 1700’s and 1800’s. Fire scars and existing timber stands on the 3,709 ha experimental forest show that two fires occurred in the 1700’s and six in the 1800’s covering more than 1,660 ha (45 percent) and 2,415 ha (65 percent), respectively. One small 32 ha stand on the experimental forest has not burned since 1580. The last major fire (206 ha) occurred in 1902 and three other small fires (covering only 19 ha) have been observed since the implementation of active fire suppression in the early 1900’s. There has been no logging on this 3,709 ha forest of which 9 percent of the total area is composed of non-timbered meadows or rock outcrops.
Annual water yield was estimated for Tenderfoot Creek Experimental Forest for the past 400+ years utilizing fire history, habitat cover types, current average annual precipitation and water yield/precipitation/cover type relationships. The maximum average annual runoff was estimated at 12,480 cubic dekameters (dams3) in the late 1500’s based on 30 years of average annual precipitation (1961-1991). The 1581 to 1997 average water yield was estimated to be 11,680 dams3. The maximum water yield estimated for Tenderfoot Creek Experimental Forest, if all timber were removed, would be around 13,240 dams3. The minimum runoff if the entire forest was composed of mature lodgepole pine would be 11,230 dams3. The present yield of 11,360 dams3 is near the lowest yield of 11,250 dams3 estimated for 1873 and near the minimum possible for this experimental forest. During a wet year with all of the timber removed, runoff could be as high as 21,190, or in a dry year with most of the watershed covered with a mature forest as low as 5,620 dams3. On TCEF, fire suppression and succession appear to be creating conditions for a major fire event unless portions of the forest are removed by management actions that mimic historic vegetation patterns.
For successful snow drift modeling, similitude of drift geometry and development rate must be preserved between model and prototype. Earlier work revealed that field data documenting drift development are scarce, yet such data are necessary to validate proposed modeling methods. This requires measurement of the evolving drift topography and concurrent measurement of the incident mass transport and flow field throughout the drifting event. The authors established a field program to measure drift development on a two-dimensional solid fence during the winters of 1996 and 1997 at two field sites located in Wyoming. The developing drift topography was measured using graduated snow stakes placed around the objects. The incident mass transport was measured using a Wyoming snow fence as a snow trap. The incident flow field was also documented. Here we compare prototype drift geometries and development rates with corresponding preliminary model data obtained in a snow drifting wind tunnel. The field data revealed some inaccuracies in the model drift geometry and development rate which might result from distortion in snow transport concentration and particle trajectory lengths. Further work is required to minimize the effects of model distortions. The field data obtained in this work will serve as benchmark data for evaluating modeling methodologies.
This paper examines in further detail a previously identified inverse association between seasonal snowfall totals in southern New England and sea surface temperature anomalies (SSTAs) in the adjacent Atlantic Ocean. Variations of western Atlantic SSTAs and of the mid-tropospheric circulation over North America and the adjacent Atlantic Ocean during the cold-season months of October-March are each examined by principal component analysis. Canonical correlation analysis identifies the dominant modes of joint variability (contemporaneous and lagged) between Atlantic SSTAs and the atmospheric circulation. Comparisons are made between HIGH-SNOW and LOW-SNOW winters. Results suggest that the mid-tropospheric circulation of December has a disproportionate influence on seasonal snowfall. Persistence of Atlantic SSTAs established partly through atmosphere-ocean coupling in the late fall/early winter is proposed as a possible linkage. The extent to which the SSTAs then influence precipitation form is still currently under investigation, but there are indications that SSTAs might influence the Atlantic Coast storm track, as well as air temperatures in southern and coastal New England.
In this study, four strains of the snow alga, Chloromonas sp.-D, were isolated from the Tughill Plateau, Whetstone Gulf State Park, NY, to study mating strategies under different light conditions. Experiments were conducted in white acrylic test tube holders that were placed in growth chambers with controlled light, temperature and photoperiod. Two light sources were used, Wide-Spectrum (WS) and Cool-White (CW), and the effects of blue, green and red light were tested by covering the holders with corresponding cellophanes. Cells were fixed with OsO4 and observed and tabulated using Zeiss phase-contrast microscopes. Using similar light intensities, blue light regimes produced more matings than green light regimes in four of four trials (two were significantly different, P<0.05), and blue light regimes produced more matings than red light regimes in seven of eight trials (three were significantly different, P<0.05). There were no trends in mating when green and red light regimes were compared in three trials. A photon light intensity of 200 mmol m -2 s -1 produced the most mating under both WS and CW regimes, but more mating occurred under CW in all intensities tested. When red light regimes of higher photon intensity (180 mmol m -2 s-1) were compared to those of blue light regimes of lower intensity (60 mmol m-2 s-1 ), more mating occurred under red light in four of four trials, but none were significantly different. Mating pairs of three types were observed: oblong-oblong (o-o), oblong-sphere (o-s) and sphere-sphere (s-s). Cell packs that produced mating types and o-o mating pairs diminished with time. However, o-s and s-s mating pairs and quadriflagellate zygotes produced from the mating pairs increased with time.
Three methods were used to determine the net volumetric loss (wastage) of glacier cover within the Bow Valley above Banff, Alberta between 1951 and 1993 (see Hopkinson, 1997). It was estimated that between 1100 and 1650 m3 x 106 of ice volume was lost during this time period. The median value of 1375 m3 x 106 was converted to a water equivalence value of approximately 1170 m3 x 106 by assuming a glacier ice (including firn and voids)/water ratio of approximately 85%.
The bulk glacier wastage estimate was divided into proportions using the Peyto Glacier mass balance record. Unfortunately, the record began in 1966 and a back-cast to 1952 was necessary. Banff maximum summer temperature and Lake Louise snow course data were used as surrogates for summer and winter glacier mass balance, respectively. Seasonal wastage contributions to river flow were estimated for 1967 to 1974 using modelled values of glacial melt (ice and firn only) generated for Peyto Creek by Young (1982).
An estimate of the temporal variation of glacier recession inputs to the Bow River hydrograph at Banff was facilitated by comparing known basin yields with the modelled wastage values. For 1952 to 1993, the average annual wastage/basin yield ratio is found to be around 2.3%. For the extremely low flow year of 1970 this ratio increases to 12.5%. The proportion of flow derived from glacier recession in August of this year is estimated to be around 53%. It is thought that the mass balance back-cast may slightly under-estimate wastage values in the early part of the time series, therefore, leading to an over-estimation later on.
Wintertime visitors to Yellowstone National Park, Wyoming, consider scenery, wildlife, and clean air as three important qualities of their experience in the Park. Because the majority of winter visitors tour Yellowstone by motorized winter vehicles, and winter visitation has increased nearly tenfold since 1968, the effects of vehicle use are a growing concern for resource managers. The extent of effects on air quality and ecosystem health from increasing vehicular emissions throughout the Park is not fully understood.
Snowpack chemistry provides a composite record of atmospheric deposition of airborne pollutants throughout winter. Pollutant levels from vehicular emissions inside the Park were characterized by snowmelt- chemical data from three sites at a variety of high- and low-traffic locations. At each site snow samples representing most of the annual snowpack were collected at an off-road site 20 m to 100 m from motorized- traffic routes, and at a site directly in snow-packed roadways used by over-snow vehicles. Snowmelt chemistries were compared between these three pairs of samples collected in-road and off-road to determine whether concentrations decreased with distance from the source.
Concentrations of ammonium, nitrate, and sulfate in snowmelt positively correlated with vehicle usage. Ammonium and sulfate levels were consistently higher for the in-road snow compared to off-road snow for each pair of sites, but nitrate concentrations did not decrease within a distance of 100 m from the emission source.
This method demonstrates that snowpack chemistry can be used as a quantifiable indicator of airborne pollutants from vehicular traffic. A correlation was shown between pollutant levels and vehicle traffic. Additional results indicate the nitrate ion may be used to distinguish between local and regional emissions sources.
Both coniferous and deciduous forests alter the energy exchange and the accumulation and ablation of snow on the ground. Snow ablation modeling at the stand scale presents challenges to account for the variability in snow cover and the large variations of solar and thermal radiation incident to the forest floor. Previous work by the authors coupled a one-dimensional snow process model (SNTHERM), modified for forested conditions, with a model of radiation interactions with forest canopies to successfully predict snow ablation in a mature jack pine stand. Now, we use the same approach and model snow ablation in black spruce and aspen stands and verify the modeling effort by comparison with field data. A new routine is added to SNTHERM to account for forest litter on the snow surface, thereby affecting the albedo. We conducted field work during March 1996 in central Saskatchewan. We measured snow pack physical properties, meteorological parameters within the forest canopy, and incoming solar and thermal irradiance beneath the forest canopy. At peak accumulation snow depths in black spruce tree wells were approximately 65 % of that measured in forest gaps. Snow in the aspen stand ablated 26 days before snow in the black spruce stand and both results compare favorably with available measured data.
Winter storms in the Sierra Nevada typically have rain/snow levels between 1200 and 2000 m. Warm storms with higher rain/snow levels of up to 2500 m occur a couple of times in most winters and generate rain- on-snow floods. However, in the past two years, very warm storms with rain/snow levels up to 3500 m have generated serious flooding. These very warm storms provided an opportunity to examine snowpack response to rainfall at high elevations where such warm temperatures during storms have rarely been observed. At our snow- research station at 2930 m on Mammoth Mountain in the eastern Sierra Nevada, air temperatures exceeded 4oC during both storms. Rainfall was about 140 mm in the 1996 event and 220 mm in 1997 at this site. The snowpack had just begun to melt and produce outflow a few days before the warm storm in May 1996. The event in 1997 occurred in mid-winter on cold and dry snow cover. The spring snowpack delivered water to the soil within two hours of the onset of rain, but the winter snowpack delayed release of water by 9 to 23 hours. The winter snowpack developed a highly variable and complex stratigraphy with dozens of alternating wet and dry layers.
A new snowfall interception model is introduced. The model incorporates physically-based processes to scale from the branch to canopy. Previous models of snow interception have neglected the persistence of intercepted snow load and the effects of temperature on maximum intercepted load and hence have only been applicable to climates where snow is regularly and quickly lost from the canopy. To investigate snow interception at the forest stand scale, measurements of above and subcanopy snowfall, accumulation of snow on the ground and the load of snow intercepted by a suspended, full-size conifer were collected from boreal forest spruce and pine stands. These data show that interception increases with increasing snowfall, to a point when the intercepted load overcomes the strength of branches to support it. Hence, the interception efficiency decreases with snow load and amount of fresh snowfall. Leaf area index, tree species and initial snow load determine the maximum canopy snow storage. The maximum storage, canopy coverage and snowfall are used to calculate snow interception for a canopy, presuming exponential decay in incremental interception as the amount of snowfall increases. The sensitivity of the model to temperature, wind speed and other factors is examined. This method can be used to calculate snow interception over an entire winter period using relatively standard meteorological and forest inventory variables.
The SLURP model developed at NHRI, is a distributed conceptual model which simulates the behaviour of a watershed by carrying out vertical water balances for each element of a matrix of land covers and subareas of a watershed and then routing the resulting runoff between subareas. The model is able to simulate snowpack accumulation and depletion, groundwater response of watersheds, and rainfall and snowmelt generated streamflow. This study describes an approach of applying the SLURP hydrological model to a mountainous sub- arctic streamflow of Wolf Creek Basin. In this sub-arctic region, annual peak flow is generally dominated by snowmelt. As a research basin, the Wolf Creek basin has been equipped with instruments to measure the snow depth and density. A procedure to convert snow data time series into winter precipitation required by SLURP is developed. The generated winter precipitation data, together with other related climate data from three meteorological stations within the basin were used for both model calibration and model verification. Two years of streamflow data were tested with good results obtained for the calibration period 1994-1995 and somewhat lesser for the verification period 1995-1996.
A method of estimating and forecasting snow pack dynamics for a large remote basin in Bosnia was developed and consists of a highly automated, spatially distributed model for operational simulation and forecasting of snow pack depth, snow water equivalent, soil freeze-thaw state, and flux of snow melt and rain infiltration to the base of the pack. The model, applied to hydrologic forecasts in Bosnia during the winter of 1996-1997, has potential use in domestic flood and water supply forecasting. SNTHERM, a complex one- dimensional energy balance model that takes into account most physical processes within the snow cover, was used for snow pack computations. The model was distributed across the landscape by 1-km pixels, using a categorical classification of the basin into 216 slope, aspect and meteorology types. The model system was highly automated. Runoff ratios (runoff/rainfall) for the winter of 1996-1997 compared well to long term average runoff coefficients, indicating precipitation data used to drive the model were reasonable. Supporting research issues are discussed.
Spatial variation in snowmelt rates in the boreal forest can be explained by differences in canopy density. Canopy density, represented as gap fractions (GF), controls both the amount of shortwave radiation reaching the snowpack surface and wind speed over the snow surface, which in turn regulates sensible and latent heat fluxes. These reductions outweigh any increased contributions from longwave radiation as a result of increased biomass. Differences in the total energy available for melt do not translate to equally proportional changes in melt rates under different canopy densities. As available energy increases, the melt rate increases with decreasing canopy density and the form of the relationship can vary depending on climatic conditions. A good relationship between ground-based GF measurements and a canopy closure index derived from Landsat TM, provides the spatial fabric for the physically-based distribution of snowmelt rates that shows comparable patterns of snow ablation during years of very different climatological conditions. This physically-meaningful method of determining the
Heterogeneous land surface characteristics during the spring melt of an Arctic snowpack produce a horizontal transfer of energy at a small scale, a process termed local advection. Techniques were developed and applied to determine the importance of this local scale advection to both the magnitude of snowmelt and the average flux from a composite snow and snow-free surface. A tile-model approach was evaluated in estimating the spatial sensible heat flux over a patchy snow cover by comparison to eddy correlation measurements. These model results (Liston, 1995), was used to determine the effect of advection on local snowmelt patterns. These calculations resulted in different patterns of influence, probably due to differences between the ideal modelled and natural surface conditions.
The Prairie Blowing Snow Model (PBSM) is a single column, physically-based, mass and energy balance that calculates blowing snow transport and sublimation rates. New features of the model include a correction for snowfall undermeasurement, mid-winter snowmelt, snow density estimates and estimation of the effect of exposed vegetation on aerodynamic roughness height during blowing snow. Importantly, the model now includes algorithms to estimate the threshold wind speed for snow transport and to estimate the probability of blowing snow occurrence. The probability of blowing snow occurrence is used to scale the blowing snow fluxes horizontally so that estimates from a 1 x 1 km surface area control volume may be extrapolated to larger scales, varying fetches and vegetation types. As a demonstration, the model is operated using standard meteorological data from meteorological stations in the Canadian Prairies and compared to snow accumulation measurements at these stations. The model is also used to estimate snow accumulation for comparison to extensive field snow surveys from the Bad Lake experimental basin in west-central Saskatchewan. It is shown that the new version of PBSM can provide estimates of snow accumulation, melt, transport and sublimation from hourly to seasonal time periods for varying land surfaces.
The Interactive Multisensor Snow and Ice Mapping System (IMS) was developed to give snow and ice analysts the tools, on one platform, to visually inspect imagery and mapped data from various sensor sources to determine the presence of snow and ice and to depict snow and ice covered areas on a map on a daily basis, in one hour or less. Snow and ice analysts in the National Environmental Satellite, Data, and Information Service have been creating weekly maps showing the extent of snow cover for the Northern Hemisphere since 1966 using visible imagery from polar-orbiting and geostationary satellites and surface observations as data sources. The current process is mostly manual and time consuming, taking up to 10 hours to produce a map during the snow season. Where cloud cover precludes an unobstructed view of an area during the entire week, the analysis from the previous week is carried forward. Each week the analyst draws a new map by hand, then digitizes the extent of snow and ice cover using an 89x89 line grid overlaid on a stereographic map of the Northern Hemisphere. The hand drawn map is photocopied and distributed and the digitized map is saved to a file for use in National Weather Service numerical models and for archival storage. IMS was designed and built to replace and improve this process by producing a more accurate, timely product.
From 1978 through 1992 Scripps Institution of Oceanography made quarterly long-range weather forecasts of precipitation in the Sierra Nevada. The 15 year experiment showed some skill in the winter and spring season. In the 1980s an attempt was made to apply the skills that existed to an early season December 1 forecast of water year runoff on selected rivers. The methodology of adjusting the conventional runoff forecast and the conventional expected range of runoff (which are based on climatology for future weather) for the demonstrated weather forecasting skill will be described in the paper. Some test results are shown. Unfortunately, the weather forecasting skills declined during the period of hydrological testing to below the threshold of usefulness and the forecasting experiment was put aside for a later time. But we believe there is merit to documenting the methodology and results of this experiment for other professionals.
The combined influence of increased temperatures and changed precipitation on the seasonal snow cover and runoff is evaluated for the upper Rhine basin at Felsberg (3250 km2, 560-3614 m a.s.l.). The runoff regime reflects the snow accumulation in the winter half year and snowmelt in the summer half year. The method of predicting future runoff regimes is based on high resolution periodical snow cover mapping by satellites in order to evaluate the climate-effected snow cover and runoff by the SRM-ETH model. Conditions of the present climate are represented by a normalised year. Snow conditions and yearly hydrographs are evaluated for the years 2030 and 2100 according to the given climate scenarios for this region. Quantitative results indicate the decrease of the snow accumulation on 1 April as well as the seasonal redistribution and changes of runoff.
It is a pity that most people think a scientist is a specialized person in a special situation, like a lawyer or a diplomat. To practice law, you must be admitted to the bar. To practice diplomacy, you must be admitted to the Department of State. To practice science, you need only curiosity, patience, thoughtfulness, and time. Alan Holden and Phylis Morrison Preface to Crystals and Crystal Growing
Science is a fundamentally social activity, which implies that it depends on good communication. Hermann Bondi
The goal of scientific research is publication. ... Thus the scientist must not only “do” science but must “write” science. Robert A. Day
In my course in Technical Writing at Plymouth State College, students learn how to do scientific writing through snowpack study. In previous presentations in various publications, I have described the scope and nature of the course. This presentation describes how students learn to do scientific writing through both traditional and innovative activities. The aims of the course are as follows:
Geographic Information Systems (GIS) and satellite remote sensing are now used extensively in analyses of natural environments. This research examined the usefulness of a GIS and remote sensing based approach for integrating many different and widely varying data sources. The multisource data sets were used in stepwise, multiple linear regression models that analyzed the variation in snow depth and snow-water equivalent (SWE) depth.
Models were developed in the Marmot Creek Basin using Landsat Thematic Mapper (TM) satellite data, Digital Elevation Model (DEM) data and various mapped data layers in combination with historical snow depth and SWE measurements. The best model for snow depth produced a coefficient of determination or adjusted R2 of 0.6370. The independent variables of elevation, incidence, tree height and principal component four of the TM data could explain approximately 64% of the variation in snow depth. The best model for SWE depth had an adjusted R2 of 0.5814. The independent variables that explained the variation in SWE depth were elevation, incidence, and TM band seven.
The National Park Berchtesgaden models build upon the approach used in the Marmot Creek Basin. Landsat TM data and a DEM provided the basis for the regression independent variables. Additional analyses of these data were performed within the GIS to calculate variables such as across and down slope curvature and a Normalized Difference Vegetation Index (NDVI). The best model for snow depth produced an adjusted R2 of and principal component four of the TM data.
In 1995 the Canadian Atmospheric Environment Service (AES) made a major effort to digitize paper records of daily and weekly snow depth which were not in the Canadian Digital Archive of Climate Data. This resulted in the extension of the snow depth record at many stations back to the late 1940s, and the filling of missing data from a number of stations, particularly in the Arctic. This paper describes the database and the methods used to quality control and reconstruct missing data, and presents an analysis of the spatial and temporal characteristics of the data over the 1946-1995 period. Principal component analysis of monthly snow depths revealed that snow depths varied coherently over relatively large regions of Canada with dominant centres of action located over the West Coast, Prairie, Yukon-Mackenzie, southern Ontario, Northern Québec and Maritime regions. In many cases, nodes of coherent snow depth variations were associated with corresponding nodes of coherent snow cover duration fluctuations, with the two times series exhibiting significant positive correlations. Winter and early spring snow depths were observed to have decreased significantly over much of Canada in the 1946-1995 period, with the greatest decreases occurring in February and March. The snow depth changes were characterized by a rather abrupt transition to lower snow depths in the mid-1970s which coincided with a well-documented shift in atmospheric circulation in the Pacific-North America sector of the Northern Hemisphere.
Results from applying Kendall’s test to 37 stations of temperature and precipitation data, 50 stations of natural streamflow data and 13 stations of evapotranspiration data show that the Prairies have become warmer and somewhat drier in the last four to five decades. The earlier onset of spring snowmelt runoff detected by Burn (1994) further supports this finding. Results on Kendall’s test on precipitation, natural streamflow and areal ET indicate that the Prairie may have become drier but the trends detected are less extensive when compared to warming trends. The correlation-distances reveal that temperature data are generally more correlated to each other than precipitation data. The bivariate precipitation versus maximum temperature test failed to detect any link between precipitation and temperature and Kendall’s test on the drought duration, severity and magnitude prepared by Bauer and Welsh (1988) for two sites in Saskatchewan also shows no significant trend in the Prairie drought.
Three methods have been used to explore the volumetric change of glaciers in the Bow Basin above Banff for the years 1951 to 1993. Using aerial photography, the extent of glacier covers for the two years were mapped at a scale of 1:50,000. The first volumetric calculation of glacier loss was based on inventory criteria (Stanley, 1970); the second a hypsographic curve method based on Young’s investigations in Mistaya Basin (1991) and the third: stereo air photogrammetry and DEM comparisons using the computer software package Surfer®. These methods were applied to the highly glacierized Hector Lake catchment within the Bow Valley and then extrapolated up to the whole basin above Banff. Reasonable agreement was achieved between the methods and the magnitude of net glacier loss from 1951 to 1993 is estimated to be 1100 to 1650 m3 x 106. The true value for volumetric change is considered to be towards the upper end of the range given, due to the likelihood for systematic underestimation during the extrapolation up to the basin above Banff.
Spring snowmelt is generally the dominant annual peak flow generating mechanism in subarctic regions, though smaller basins may occasionally experience peak flow events due to summer rain storms. An unusual lake outburst flood event was observed at Wolf Creek, a small tributary of the Yukon River. The event was focused at the outlet of Coal Lake the only major storage element in the basin.
During the unusually cold January of 1996 ice growth at the outlet of Coal Lake created an ice dam which progressively grew through aufies formation as the lake levels increased. The ice dam failed in late April approximately 9 days after the onset of mean daily positive temperatures sending a significant flood wave downstream. This event was in excess of 1996 freshet flows which occurred more than one month later. There are three hydrometric stations on Wolf Creek however these were not activated until the recession of the outburst event. A water balance was carried out to reconstruct this flood event using observed lake levels for the containment period, the recorded recession limbs of hydrographs at the Coal Lake hydrometric station and a downstream hydrometric station, winter recession flows at an upstream hydrometric station and personal observation.
The analyses indicated that the outburst event was greater in magnitude than the subsequent freshet event. In addition to facilitating the reconstruction of the annual hydrograph, the analyses provides valuable information on a little known streamflow generation mechanism in small subarctic basins with lake storage.
Water content of the snow pack is measured at approximately 100 sites within the State of California by snow sensors. The sensors detect the water content as a weight exerted on either stainless steel or rubber bladders filled with fluid. The tanks are connected to either a stilling well with a shaft encoder or a pressure transducer. The resulting signal is proportional to the weight of the water in the snow.
These sensor suffer from a variety of problems. They require a large footprint, at least 7.5 square meters to avoid edge effects, with consequent environmental disruption. The tanks and associated plumbing are prone to puncture from both human and animal disturbance. Transport of the bladders poses significant difficulties in wilderness areas where mechanical transport is prohibited. Loss of the sensors for an entire season is not uncommon due to water intrusion into the transducer or leaks in the tanks.
Adding insult to injury, the sensors do not accurately measure the water content under certain conditions. Extensive ice layers in the snow can support part of the pack’s weight so that the registered water content is less than actual. Later, after these layers lose some of their structure, or additional snow accumulates to collapse the bridging structure, the sensor readings will reflect actual snow water content.
This paper will describe the development of a detector which measures cosmic radiation and determines the snow water equivalent based on the attenuation of the radiation. The detector has had two seasons of field verification tests at the Central Sierra Snow Laboratory with very promising results.
No abstract. This is a poster paper.
Mountainous areas, particularly in the western United States, provide a large fraction of the fresh water supply. This reserve, which supplies most of California’s growing water needs, is vulnerable to changes in climate. Regional precipitation patterns, especially snow, which is a sensitive indicator of change, are predicted to vary according to future climate models. This study uses a statistical model which links snow water equivalent (SWE) measurements over a 60-year time series to analyze the snow accumulation trends in the Sierra Nevada. We utilized snow course measurements with data difficulties including inconsistent monthly sampling, added and removed stations and possibly a few moved or otherwise altered snow courses. To determine the effects of a monthly and irregular sampling schedule we analyzed daily snow sensor data spanning 25 years. Furthermore, we employed a statistical test to check for possibly discontinuous snow course stations. We found that the overall maximum amount of seasonal SWE is not changing. However, below 2700 meters, snowmelt timing has recently been occurring earlier, whereas elevations above 2900 meters are melting later. The eastern draining river basins consist of steeper, drier slopes that have mostly increasing SWE trends. The Owens River basin, in the southeastern tip of the range, has gained the most SWE while the neighboring, westside Kern has received less snow.
We present results of an investigation into the effect of increasing spatial and temporal resolutions on modeled distributions of SWE and snowmelt in the Emerald Lake Watershed of the Sierra Nevada of California, U.S.A. We used a coupled remote sensing/distributed energy balance snowmelt model (SNODIS), and used previously validated results from a high spatial (30-m) and temporal (hourly) resolution model run in ELW as a control. We selected spatial resolutions that are commensurate with standard product DEMs or with existing or planned satellite remote sensing data, and temporal resolutions that are factors of typical operational intervals for meteorological data. We degraded the spatial resolution of the DEM from 30 m to 90, 250, and 500 m prior to computing the distributed micrometeorological data. We degraded the classified remote sensing data to the same spatial resolutions prior to computing the duration of the snowcover. Similarly, we degraded the temporal resolution of the micrometeorological data from 1 hour to 3 and 6 hours prior to computing the distributed energy balance and snowmelt. We compared mean basin SWE, basin snowpack water volume, and the spatial patterns of SWE from each test to our previous, high-resolution results. We found no significant differences between the mean basin-wide SWE computed from the 250-m and 500-m spatial resolutions and that of our high-resolution control, regardless of temporal resolution. At each temporal resolution mean basin SWE was over-estimated at the 90-m resolution by 14-17%. Coarsening of the spatial resolution did result in a loss of explicit information regarding the location of SWE in the basin, as expected. We discuss these results in terms of their implications for applying the SNODIS model to larger regions.
This study was performed in order to determine if the areal extent of a wet discontinuous snowcover could be effectively mapped using a RADARSAT image. The sites chosen for the experiment were two agricultural areas located in southern Ontario. On March 27, 1997 oblique aerial photography was acquired and used to create a ground reference map for two sites, showing the location of bare ground and snowcovered ground in selected fields. On March 26, 1997 a RADARSAT C-HH SAR image was acquired, which was classified into bare ground and snowcovered ground and then compared to the ground reference map. The classification accuracies were 62.3% and 67.3% for the sites, however the percent snowcovered area was calculated to be within 5% of the ground reference map estimate after accounting for the melt that occurred in the day between the acquisition of the two images.
To quantify the hydrologic response of forest harvesting, measurements of snow accumulation, melt, and micro-meteorological were taken in mature and harvested units of the Gifford Pinchot (GP) and Umpqua National Forests. Data were collected as part of the Demonstration of Ecosystem Management Options (DEMO) project. The study areas are located in the transient snow zone of the western Cascades of southwestern Washington and central Oregon, respectively. The GP site contains six units at approximately 900 meters in elevation (five mature secondary growth, 1 clear-cut). The Umpqua site contains five units at approximately 900 meters in elevation (four mature, one shelterwood), and three units at 1200 meters elevation, (two mature, one shelterwood). Data have been collected during the past three snow seasons. In the summer of 1997, each site’s mature stands (excluding one control) will be harvested with varying retentions and additional seasons of data will be collected. Measurements of incoming and reflected shortwave radiation, incoming longwave radiation, windspeed, relative humidity, air temperature, and precipitation (or through fall) were taken in the units. Snow accumulation and melt at the unit scale (10ha) was measured weekly throughout the winter and spring with snow courses taken on a twenty point grid. Point observations of snow pack outflow consisted of two non-weighing snow lysimeters (2.6 sq. m. each) in each unit. Comparison of lysimeter observations between shelterwood and mature units during the 95/96 season show a 56% increase in 3 day production of runoff and a greater than 150% increase in 3 day snowmelt (outflow-throughfall). The shelterwood also shows nearly a 50% increase in snowmelt during radiation-dominated spring events. Snow course data taken at the GP before and 10 days after the rain-on-snow event of February 1996 show a decrease in the average snow water equivalent of the clearcut unit from 26 to 16 cm and a decrease in an adjacent mature stand’s SWE from 21 to 18 cm.
Spatial variability in snow accumulation and melt due to topographic effects on solar radiation, drifting, air temperature, and precipitation is important in determining the timing of snowmelt releases. Precipitation and temperature effects related to topography tend to affect snowpack variability at large scales and are generally included in models of hydrology in mountainous terrain. The effects of spatial variability in drifting and solar input are generally only included in distributed models at small scale. Previous research has demonstrated that snowpack patterns are not well reproduced when topography and drifting are ignored. These observations imply that larger scale representations that ignore drifting could be greatly in error. Detailed measurements of the spatial distribution of snow water equivalence within a small, intensively studied, 26-ha watershed were used to validate a spatially distributed snowmelt model. This model was then compared to basin-averaged snowmelt rates for a fully distributed model, a single point representation of the basin, a two point representation that captures some of the variability in drifting and aspect, and a model with distributed terrain and uniform drift. The model comparisons demonstrate that the lumped, single point representation and distributed terrain with uniform drift both yielded very poor simulations of the basin-averaged surface water input rate. The two-point representation was an improvement but the late season melt required for the observed streamflow was still not simulated because the deepest drifts were not represented. These results imply that representing the effects of subgrid variability of snow drifting is equally or more important than representing subgrid variability in solar radiation.
A snow research site has been operated on Mammoth Mountain in the eastern Sierra Nevada of California since 1978. Records from this timberline study plot illustrate some of the characteristics of snowpack development and ablation in the high Sierra Nevada. In most years, a snowpack of at least 50 cm depth has been in place by the first of December. Mid-winter storms have deposited a few centimeters to a few meters of snowfall. Wind redistributes snow around the site and is a critical influence throughout the accumulation season. Snow depth usually reaches a maximum sometime in April. Over the period of record, peak depths have ranged from 2 to 8 m with water equivalence of 0.7 to 2.5 m. Sustained spring snowmelt usually begins in late April or early May after storms have become infrequent. Daily melt amounts in May tend to average about 20 mm per day. Snow cover usually disappears during June but has persisted until August.
Traditional snow shelters have been constructed and used by Indigenous groups for centuries. Modern science has done little to quantify and compare the thermal properties of these structures. In February 1995, three snow shelters (an igloo, snow cave and quinzee) were built near the Montmorency Forest Research Station in the Laurentides, Quebec. Eight copper-constantan thermocouples were placed at intervals throughout the wall, outside and inside each snow shelter (on the floor, in the cold air trap and near the roof). During the night, temperatures were recorded using a Campbell Scientific 21X datalogger in the occupied structure. Thermal conductivities of the snow walls were calculated for each shelter. The wall of the igloo had the lowest thermal conductivity (k = 0.27 Wm-1K-1), followed by the snow cave wall (k = 0.36 Wm-1K-1). The quinzee wall had the highest thermal conductivity (k = 0.56 Wm-1K-1). The results indicate that the igloo wall was the best insulator out of the three snow shelter types.