Fassnacht, S.R., K.A. Dressler, D.M. Hultstrand, R.C. Bales, and G. Patterson, 2012. Temporal Inconsistencies in Coarse-scale Snow Water Equivalent Patterns: Colorado River Basin Snow Telemetry-Topography Regressions. Pirineos, 167, 167-186 [doi: 10.3989/Pirineos .2011.166008].
The relation between snow water equivalent (SWE) and 28 variables (27 topographically-based topographic variables and canopy density) for the Colorado River Basin, USA was explored through a multi-variate regression. These variables include location, slope and aspect at different scales, derived variables to indicate the distance to sources of moisture
and proximity to and characteristics of obstacles between these moisture sourcesand areas of snow accumulation, and canopy density. A weekly time step of snow telemetry (SNOTEL) SWE data from 1990 through 1999 was used. The most important variables were elevation and regional scale (81 km2) slope. Since the seasonal and inter-annual variability is high,
a regression relationship should be formulated for each time step. The inter-annual variation in the relation between SWE and topographic variables partially corresponded with the amount of snow accumulated over the season and the El Nino Southern Oscillation cycle.
Keywords: Colorado River, SNOTEL, snow water equivalent, surface topography
Venable, N.B.H., S.R. Fassnacht, G. Adyabadam, Tumenjargal S., M. Fernández-Giménez, and B. Batbuyan, 2012. Does the Length of Station Record Influence the Warming Trend That is Perceived by Mongolian Herders near the Khangai Mountains? Pirineos, 167, 71-88 [doi: 10.3989/Pirineos.2012.167004].
Temperatures changes can be difficult to infer from changes in vegetation patterns or other ecological changes, yet warming can be inferred through changes in the habits of people who live in close connection with their natural environment. Herders near the Khangai Mountains of central Mongolia have perceived a warming trend in recent years. Since it is difficult to determine the exact time
period over which perceived warming has occurred, we examined the statistical difference in changes based on the length of data and the specific period of record used in the analysis. We used temperature data from five meteorological stations for up to 50 years (1961-2010). We examined varying lengths of record from 15 to 50 years with varying start periods (1961 through 1986),
based on the length of record. We found that the most statistically significant changes occurred for the longest time periods and for the annual average minimum temperatures. We also found that one very cold winter, in particular 2009-2010 decreased the warming trend and for shorter periods of record reduced the statistical significance.
Keywords: Climate change, warming, Mongolia, statistical significance, herder perceptions
López-Moreno, J.I., S.R. Fassnacht, S. Beguería, and J.B.P. Latron, 2011. Variability of snow depth at the plot scale: implications for mean depth estimation and sampling strategies. The Cryosphere, 5, 617-629, [doi:10.5194/tc-5-617-2011].
Snow depth variability over small distances can affect the representativeness of depth samples taken at the local scale, which are often used to assess the spatial distribution of snow at regional and basin scales. To assess spatial
variability at the plot scale, intensive snow depth sampling was conducted during January and April 2009 in 15 plots in the Rio Ésera Valley, central Spanish Pyrenees Mountains. Each plot (10x10 m; 100m 2) was subdivided into a grid of
1m2 squares; sampling at the corners of each square yielded a set of 121 data points that provided an accurate measure of snow depth in the plot (considered as ground truth). The spatial variability of snow depth was then assessed using sampling
locations randomly selected within each plot. The plots were highly variable, with coefficients of variation up to 0.25. This indicates that to improve the representativeness of snow depth sampling in a given plot the snow depth measurements
should be increased in number and averaged when spatial heterogeneity is substantial.
Snow depth distributions were simulated at the same plot scale under varying levels of standard deviation and spatial autocorrelation, to enable the effect of each factor on snowpack representativeness to be established. The results
showed that the snow depth estimation error increased markedly as the standard deviation increased. The results indicated that in general at least five snow depth measurements should be taken in each plot to ensure that the estimation
error is <10 %; this applied even under highly heterogeneous conditions. In terms of the spatial configuration of the measurements, the sampling strategy did not impact on the snow depth estimate under lack of spatial autocorrelation.
However, with a high spatial autocorrelation a smaller error was obtained when the distance between measurements was greater.
Fassnacht, S.R., M. Toro Velasco, P.J. Meiman, and Z.C. Whitt, 2010. A Local Aeolian Influence in the Surface Roughness of Melting Snow, Byers Peninsula, Antarctica. Hydrological Processes, 24(14), 2007-2013 [doi, 10.1002/hyp.7661].
The surface of the snowpack is the bottom boundary layer for air movement, and its roughness influences aerodynamics. The
presence of aeolian deposits on a snowpack decreases its albedo and is shown to decrease the roughness of the surface. During
snowmelt in the Lake Limnopolar basin on Byers Peninsula of Livingston Island of the South Shetland Islands, Antarctica,
wind moved coarse soil grains (1-4 mm particles) from a bare, dry and snow-free area to an adjacent snowpack. This addition
of large soil particles rapidly changed the snowpack surface characteristics. Within several days, the sun-cups, initially present
on the melting snow surface, had been smoothed out in areas where soil was deposited on the snow surface. The differences
in the snowpack surface were assessed using digital imagery of a roughness board inserted into the snow, both parallel and
perpendicular to the dominant wind direction. The random roughness was twice as variable for the clean snow compared to
the snow with soil; it was 27% more and 26% less perpendicular versus parallel to the wind for the clean snow and snow
with soil, respectively. Variogram analysis showed that the clean snow had up to four different scales of roughness over the
55 x 55 cm area of analysis, with fractal dimensions varying from 1.33 to 1.83. The snow with soil did not vary substantially
from 0.1 to 55 cm with fractal dimensions of 1.65 in parallel and perpendicular to the wind.
Keywords: wind transport, surface roughness, snowmelt, Antarctica
López-Moreno, J.I., B. Alvera, J. Latron, and S.R. Fassnacht, 2010. Instalación y Uso de un Colchón de Nieve para la Monitorización del Manto de Nieve, Cuenca Experimental de Izas (Pirineo Central). Cuadernos de Investigación Geográfica (Journal of Geographical Research), 36(1), 73-85.
Keywords: snow, SNOTEL
Fassnacht, S.R., 2010. Temporal changes in small scale snowpack surface roughness length for sublimation estimates in hydrological modeling. Cuadernos de Investigación Geográfica (Journal of Geographical Research), 36(1), 43-57.
Snowpack aerodynamic surface roughness length (zo) is a critical
variable in estimating heat transfers to and from a snow surface and thus
sublimation rates. This variable has been shown to be site specific. To illustrate a
temporal variation in zo, laboratory experiments were performed using a small
evaporation pan sitting on a load cell with a constant wind flow over the snow
surface. Comparing multi-layer meteorological data above the pan to sublimation
measured from mass change showed a decrease in the snowpack surface roughness
length as the snow metamorphosed. The sensitivity of snowpack zo changes over
time in modeling of sublimation was examined using hourly meteorological data
for the winter of 2000-2001 at Syracuse, New York and Leadville Colorado for
several scenarios, including increasing or decreasing zo after a snowfall event,
considering directionality of zo as a function of the wind direction, and a ratio of
latent heat to momentum roughness lengths. The base case used a constant zo of
0.01 metres. The modeled differences were a function of the values of zo, which
varied with the frequency of occurrence of fresh snow and the distribution of wind
from various directions. The temporal and spatial variability in surface roughness
is crucial in computing the energy and mass balance of a snowpack.
Keywords: roughness length, snow, sublimation
Fassnacht, S.R., C.M. Heun, J.I. López-Moreno, and J.B.P. Latron, 2010. Variability of Snow Density Measurements in the Rio Esera Valley, Pyrenees Mountains, Spain. Cuadernos de Investigación Geográfica (Journal of Geographical Research), 36(1), 59-72.
An accurate assessment of snow depth and snow density is
essential to determine that amount of water stored in the snowpack, i.e., snow
water equivalent (SWE). The measurement of snow density is much more difficult
and time consuming than snow depth. The variability in snow density is evaluated
for a 5.4-km stretch of the Rio Esera headwaters in the Spanish Pyrenees
Mountains. The traditional snow tube method is compared to the more labour intensive
but accurate snow pit method. The former method measures snow depth
and extracts a snow core that is weighed. The latter method uses a wedge cutter
to extract a 1-L snow sample to estimate density at 10-cm intervals through the
snowpack. The variability in snowpack density is not systematic and can only be
explained at lower elevation when the snowpack is known to be melting, as
identify by an isothermal snowpack at zero degrees Celsius. This occurred during
a mid-January survey. A late-April survey showed that these lower elevation sites
were still more dense.
Keywords: snow density, snow water equivalent, Ésera Valley, Pyrenees Mountains
Fassnacht, S.R., and J.E. Derry, 2010. Defining similar regions of snow in the Colorado River Basin using self-organizing maps. Water Resources Research, 46, W04507 [doi:10.1029/2009WR007835].
We used self-organizing maps (SOMs) to define regions of homogeneity in the Colorado River Basin using snow telemetry (SNOTEL)
snow water equivalent (SWE) data. SOMs are a specific application of artificial neural networks. Daily data for 216 stations using 15 years (1991-2005)
of data from 1 October through 30 June were used. To identify areas of similar snow accumulation, persistence, and ablation patterns,
data were transformed by dividing by the 15 year average peak SWE. Three experiments were performed to determine how the regions of homogeneous
snowpack characteristics changed. The number of groups was increased from 4 to 6 to 9 to 16. By increasing this resolution, more subtle variations
were defined. The temporal resolution of the data was decreased from daily to weekly to monthly to yearly. The accumulation and ablation of the snowpack
over time represents a plot called a niveograph, which was summarized for yearly data by three variables. These were peak SWE, length of season,
and date of peak SWE. Very similar results were produced using daily, weekly, and monthly time steps. However, using peak SWE produced only 50%
of the same groupings, while using the other annual summary variables, even together, produced less than 25% of the same groupings.
Using 18 physiographic variables to represent the SNOTEL stations yielded groups that were similar to those from using peak SWE
but more evenly distributed in space. Using Ward's method of cluster analysis could only be performed with the individual annual summary variables.
It produced groupings similar to the comparable SOM application but slightly less representative of the daily data groupings.
Keywords: snow, SNOTEL
Fassnacht, S.R., M.W. Williams, and M.V. Corrao, 2009. Changes in the surface roughness of snow from millimetre to metre scales. Ecological Complexity, 6(3), 221-229 [doi:10.1016/j.ecocom.2009.05.003].
The roughness of snow influences the movement of air across the snow surface and resulting transfers of
energy. Here we focus on the roughness of the snowpack surface to determine its range of variability for
different snow conditions (e.g., time since last snowfall), across spatial scales that ranged from 0.01 cm
(card) to more than 1000 cm (transect) or more than 5-orders of magnitude, and due to the deposition of
aeolian constituents. Digital photogrammetry of snow surfaces was used to compute two roughness
metrics at two mountain sites in north-central Colorado. These metrics are the random roughness (RR)
that disregards the spatial structure and the fractal dimension (D) computed from variogram analysis.
At the crystal scale, D is between 1.67 (card) and 1.60 (board), which increases to 1.77 between 0.1
and 1.0 cm. At longer scales, D is 1.53 (board) to 1.56 (transect). There was no significant change in
surface roughness during the accumulation season, with RR values at about 0.002. During the melt
season the surface roughness doubled, with the RR values increasing from about 0.002 to 0.004. Snow
was more rough parallel to the wind when dunes were present, and roughness varied spatially. The
average RR value computed for the white snow surface of 0.014 is substantially greater than the value
computed for the red dust surface of 0.0032. Due to undulations of smaller amplitude and as a result of
the dust itself, the red dust surface is more random(D is 2.62 versus 2.23 for the white snow). Our results
show that there is consistency in roughness over different scales, yet large scale processes (e.g., wind and
radiation activity) influence the magnitude of roughness metrics much more than small scale processes
(e.g., crystal form and metamorphism).
Keywords: Snow, Surface roughness, Roughness index, Fractal dimension, Aeolian dust
Fassnacht, S.R., J.D. Stednick, J.S. Deems, and M.V. Corrao, 2009. Metrics for assessing snow surface roughness from digital imagery. Water Resources Research, 45, W00D31, [doi:10.1029/2008WR006986].
Digital image profiles of snowpack surfaces were acquired concurrently with 1-cm
resolution manual measurements. The manual measurements confirmed that unaltered
digital images accurately represented a two-dimensional roughness profile of the
snowpack surface. Roughness indices, such as random roughness, that have been used to
represent soil surfaces were computed, and their utility for quantifying snowpack
surface roughness is illustrated. Variogram analysis was used to determine the fractal
dimension and scale break. Surface characteristics were a function of the scale, with a rough
snow surface and graupel yielding similar results. A relatively smooth snow surface showed
no crystal-scale features and had a fractal dimension approaching that of a random surface.
Deems, J.S., S.R. Fassnacht, and K.J. Elder. Interannual consistency in fractal snow depth patterns at two Colorado mountain sites. Journal of Hydrometeorology, 9(5): 977-988.
Fractal dimensions derived from log-log variograms are useful for characterizing spatial structure and
scaling behavior in snow depth distributions. This study examines the temporal consistency of snow depth
scaling features at two sites using snow depth distributions derived from lidar datasets collected in 2003 and
2005. The temporal snow accumulation patterns in these two years were substantially different, but both
years represent nearly average 1 April accumulation depths for these sites, with consistent statistical
distributions. Two distinct fractal regions are observed in each log-log variogram, separated by a scale
break, which indicates a length scale at which a substantial change in the driving processes exists. The lag
distance of the scale break is 15 m at the Walton Creek site and 40 m at the Alpine site. The datasets show
consistent fractal dimensions and scale break distances between the two years, suggesting that the scaling
features observed in spatial snow depth distributions are largely determined by physiography and vegetation
characteristics and are relatively insensitive to annual variations in snowfall. Directional variograms
also show consistent patterns between years, with smaller fractal dimensions aligned with the dominant
wind direction at each site.
Ryan, W.A., N.J. Doesken, and S.R. Fassnacht, 2008. Preliminary results of ultrasonic snow depth sensor testing for National Weather Service (NWS) snow measurements in the US. Hydrological Processses, 22(15): 2748-2757 [doi:10.1002/hyp.7065].
During the 2006-2007 winter season, 17 sites across the US including Alaska tested an automated snow measurement system.
This article aims to describe successes and failures of this system and provide insight into data collected this season. The
system was designed in collaboration with both Environment Canada and Snow Sensor Study participants during the summer
of 2006. This system included three Campbell Scientific SR-50 sensors oriented 120 o from one another and a temperature
probe centred in the plot. Data collection efforts were successful with minimal amounts of data missing because of system or
sensor failures. The system integrated automated retrieval of data from dataloggers, as well as automated file transfer protocol
(FTP) to the study website for data archival and graphical display.
Overall, the sensors and installation worked well with only a few problems noted. The sensors compared well with both
manual observations taken adjacent to each sensor as well as traditional total snow depth (TSD) on ground measurements.
The comparison to depths, taken adjacent to the sensors, allows for investigation of frost heave and indicates periods where
the sensors were not functioning properly. The comparison to TSD on ground reveal problems with siting at some locations
that are recommended to be remedied by re-installation or re-location of those sites prior to the 2007-2008 snow season.
These results are preliminary and research will be ongoing for signal processing, snowfall algorithm development and optimal
installation in preparation for the 2007-2008 snow season. This research has potential to return important snow observations
to national weather service(NWS) observing networks that were discontinued when automation began as well as provide
continuous snowpack monitoring to data users.
Ryan, W.A., N.J. Doesken, and S.R. Fassnacht, 2008. Evaluation of ultrasonic snow depth sensors for U.S. snow measurements. Journal of Atmospheric and Oceanic Technology, 25(5): 667-684.
Ultrasonic snow depth sensors are examined as a low cost, automated method to perform traditional snow
measurements. In collaboration with the National Weather Service, nine sites across the United States were
equipped with two manufacturers of ultrasonic depth sensors: the Campbell Scientific SR-50 and the Judd
Communications sensor. Following standard observing protocol, manual measurements of 6-h snowfall and
total snow depth on ground were also gathered. Results show that the sensors report the depth of snow
directly beneath on average within +/-1 cm of manual observations. However, the sensors tended to underestimate
the traditional total depth of snow-on-ground measurement by approximately 2 cm. This is mainly
attributed to spatial variability of the snow cover caused by factors such as wind scour and wind drift.
After assessing how well the sensors represented the depth of snow on the ground, two algorithms were
created to estimate the traditional measurement of 6-h snowfall from the continuous snow depth reported
by the sensors. A 5-min snowfall algorithm (5MSA) and a 60-min snowfall algorithm (60MSA) were
created. These simple algorithms essentially sum changes in snow depth using 5- and 60-min intervals of
change and sum positive changes over the traditional 6-h observation periods after compaction routines are
applied. The algorithm results were compared to manual observations of snowfall. The results indicated that
the 5MSA worked best with the Campbell Scientific sensor. The Campbell sensor appears to estimate
snowfall more accurately than the Judd sensor due to the difference in sensor resolution. The Judd sensor
results did improve with the 60-min snowfall algorithm. This technology does appear to have potential for
collecting useful and timely information on snow accumulation, but determination of snowfall to the current
requirement of 0.1 in. (0.25 cm) is a difficult task.
Bales, R.C., K.A. Dressler, B. Imam, S.R. Fassnacht, and D. Lampkin, 2008.
Fractional snow cover in the Colorado and Rio Grande basins, 1995-2002. Water Resources Research, 44: W01425
[doi:10.1029/2006WR005377].
A cloud-masked fractional snow-covered area (SCA) product gridded at 1 km was
developed from the advanced very high resolution radiometer for the Colorado River and
upper Rio Grande basins for 1995-2002. Cloud cover limited SCA retrievals on any
given 1-km2 pixel to on average once per week. There were sufficient cloud-free scenes to
map SCA over at least part of the basins up to 21 days per month, with 3 months having
only two scenes sufficiently cloud free to process. In the upper Colorado and upper
Grande, SCA peaked in February-March. Maxima were 1-2 months earlier in the lower
Colorado. Averaged over a month, as much as 32% of the upper Colorado and 5.5% of
the lower Colorado were snow covered. Snow cover persisted longest at higher
elevations for both wet and dry years. Interannual variability in snow cover persistence
reflected wet-dry year differences. Compared with an operational (binary) SCA product
produced by the National Operational Hydrologic Remote Sensing Center, the current
products classify a lower fraction of pixels as having detectable snow and being cloud
covered (5.5% for SCA and 6% for cloud), with greatest differences in January and June
in complex, forested terrain. This satellite-derived subpixel determination of snow cover
provides the potential for enhanced hydrologic forecast abilities in areas of complex,
snow-dominated terrain. As an example, we merged the SCA product with interpolated
ground-based snow water equivalent (SWE) to develop a SWE time series. This
interpolated, masked SWE peaked in April, after SCA peaked and after some of the lower elevation
snow cover had melted.
Fassnacht, S.R., 2007. Data time step to estimate snowpack accumulation at select United States meteorological stations. Hydrological Processes, 21(12): 1608-1615.
When estimating the water balance for a cold region watershed, that is one that receive a substantial portion of its annual
precipitation as snow, accumulation and other winter hydrological processes must be considered. For many of theses watersheds,
all but the most fundamental meteorological data (temperature and precipitation), are either not measured or not measured at
a reasonable time step. Of particular importance are wind data, as wind influences underestimates of precipitation due to wind
undercatch and losses of snow from the snowpack, specifically, snowpack sublimation, and the occurrence and magnitude
of blowing snow. Estimating snow accumulation to yield snowmelt amounts requires summing of gauged precipitation and
gauge undercatch, and subtracting minus snowpack sublimation and blowing snow transport. The first two components are
computed on a daily time step, while the latter two are computed on an hourly time step. From five National Weather Service
meteorological stations (Pullman WA, Rawlins WY, Leadville CO, Rhinelander WI, Syracuse NY), the variations in computed
snowpack mass losses minus undercatch using data at different time intervals show that at most sites it is difficult to use
monthly time steps for computations derived using hourly or daily data. At the relative dry and cold Leadville, Colorado site
the computations were transferable between time steps.
Keywords: solid precipitation, meteorological data, undercatch, sublimation, blowing snow
Dressler, K.A., S.R. Fassnacht, and R.C. Bales, 2006. A comparison of snow telemetry (SNOTEL) and snowcourse measurements in the Colorado River Basin. Journal of Hydrometeorology, 7(4): 705-712.
Temporal and spatial differences in snow-water equivalent (SWE) at 240 snow telemetry (SNOTEL) and
at 500 snow course sites and a subset of 93 collocated sites were evaluated by examining the correlation of
site values over the snow season, interpolating point measurements to basin volumes using hypsometry and
a maximum snow extent mask, and variogram analysis. The lowest correlation at a point (r = 0.79) and
largest interpolated volume differences (as much as 150 mm of SWE over the Gunnison basin) occurred
during wet years (e.g., 1993). Interpolation SWE values based on SNOTEL versus snow course sites were
not consistently higher or lower relative to each other. Interpolation rmse was comparable for both datasets,
increasing later in the snow season. Snow courses correlate over larger distances and have less short-scale
variability than SNOTEL sites, making them more regionally representative. Using both datasets in hydrologic
models will provide a range of predicted streamflow, which is potentially useful for water resources
management.
Fassnacht, S.R., 2006. Upper versus Lower Colorado River sub-basin streamflow: characteristics, runoff estimation and model simulation. Hydrological Processes, 20: 2187-2205 [doi: 10.1002/hyp.6202].
Streamflow in the upper Colorado River in the western USA is always snowmelt dominated, whereas the lower river's
perennial streamflows are snowmelt dominated only 50% of the time. The magnitude and timing of peak flows is
important for water resources management. In the upper basin the annual maximum daily discharge usually occurs
in May or June, and in the lower basin this peak is observed to occur in any month except May or June. The
timing of one-half of the specific runoff is used as a second measure of the variability in timing and magnitude of
streamflows. For the upper basin, nine watersheds are used to illustrate streamflow trends, with the Yampa River
used as a sample sub-basin. For the lower basin, five watersheds are used, of which Salt River is used as sample
sub-basin. The differences in monthly flow variation over 20-year time periods (1920-1939, 1940-1959, 1960-1979,
and 1980-1999) are substantial for the Salt River but not for the Yampa River.
Three model types were used to estimate streamflow characteristics. An autocorrelation model was used to generate
winter specific runoffs, which were more reasonable for the Yampa River than the Salt River. A regression between
snow water equivalent (SWE) and winter specific runoff showed a good correlation for the two sub-basins. A weaker
relationship exists between SWE and non-winter flows for the sample lower basin watershed. Streamflow was simulated
relatively well using the Precipitation Runoff Modeling System hydrological model.
Keywords: peak flow, specific runoff, Colorado River, snow course, statistical modelling, hydrological modelling
Fassnacht, S.R., Z.-L. Yang, K.R. Snelgrove, E.D. Soulis, and N. Kouwen, 2006. Effects of averaging and separating soil moisture and temperature in the presence of snow cover in a SVAT and hydrological model. Journal of Hydrometeorology, 7(2): 298-304.
The energy and water balances at the earth's surface are dramatically influenced by the presence of snow
cover. Therefore, soil temperature and moisture for snow-covered and snow-free areas can be very different.
In computing these soil state variables, many land surface schemes in climate models do not explicitly
distinguish between snow-covered and snow-free areas. Even if they do, some schemes average these state
variables to calculate grid-mean energy fluxes and these averaged state variables are then used at the
beginning of the next time step. This latter approach introduces a numerical error in that heat is redistributed
from snow-free areas to snow-covered areas, resulting in a more rapid snowmelt. This study focuses on
the latter approach and examines the sensitivity of soil moisture and streamflow to the treatment of the soil
state variables in the presence of snow cover by using WATCLASS, a land surface scheme linked with a
hydrologic model. The model was tested for the 1993 snowmelt period on the Upper Grand River in
Southern Ontario, Canada. The results show that a more realistic simulation of streamflow can be obtained
by keeping track of the soil states in snow-covered and snow-free areas.
Deems, J.S., S.R. Fassnacht, and K.J. Elder, 2006. Fractal distribution of snow depth from LiDAR data. Journal of Hydrometeorology, 7(2): 285-297.
Snowpack properties vary dramatically over a wide range of spatial scales, from crystal microstructure to
regional snow climates. The driving forces of wind, energy balance, and precipitation interact with topography
and vegetation to dominate snow depth variability at horizontal scales from 1 to 1000 m. This study
uses land surface elevation, vegetation surface elevation, and snow depth data measured using airborne
lidar at three sites in north-central Colorado. Fractal dimensions are estimated from the slope of a logtransformed
variogram and demonstrate scale-invariant, fractal behavior in the elevation, vegetation, and
snow depth datasets. Snow depth and vegetation topography each show two distinct fractal distributions
over different scale ranges (multifractal behavior), with short-range fractal dimensions near 2.5 and longrange
fractal dimensions around 2.9 at all locations. These fractal ranges are separated by a scale break at
15-40 m, depending on the site, which indicates a process change at that scale. Terrain has a fractal
distribution over nearly the entire range of scales available in the data. Directional differences in the fractal
dimensions for each parameter are also present at multiple scales, and are related to the wind direction
frequency distributions at each site. The results indicate that different sampling resolutions may yield
different results and allow rescaling in specific scale ranges. Resolutions of 10 m and finer are consistently
self-similar, as are resolutions greater than 30 m, though the coarser resolutions show nearly random
distributions.
Fassnacht, S.R., and J.S. Deems, 2006. Measurement sampling and scaling for deep montane snow depth data. Hydrological Processes 20: 829-838 [doi: 10.1002/hyp.6119].
The resolution of snow depth measurements was scaled from a nominal horizontal resolution of approximately 1.5 m
to 3, 5, 10, 20, and 30 m using averaging (AVG) and resampling with a uniform random stratified sampling (RSS)
scheme. The raw snow depth values were computed from airborne light detection and ranging data by differencing
summer elevation measurements from winter snow surface elevations. Three montane study sites from the NASA
Cold Lands Processes Experiment, each covering an 1100 m by 1100 m area, were used.
To examine scaling, log-log semi-variograms with 50 log-width bins were created for both of the different subsetting
methods, i.e. RSS and AVG. From the raw data, a scale break, going from a structured to a nearly spatially random
system, was observed in each of the log-log variograms. For each site, the scale break was still detectable at slightly
greater than the resampling resolution for the RSS scheme, but at approximately twice the subsetting resolution for
the AVG scheme. The resolution required to identify the scale break was still from 5 to 10 m, depending upon the
location and sampling method.
Keywords: snow depth, sampling, scaling, variograms, LiDAR
Dressler, K.A., G.H. Leavesley, R.C. Bales, and S.R. Fassnacht, 2006. Evaluation of gridded snow water equivalent and satellite snow cover products for mountain basins in a hydrologic model. Hydrological Processes, 20: 673-688 [doi: 10.1002/hyp.6130].
The USGS precipitation-runoff modelling system (PRMS) hydrologic model was used to evaluate experimental,
gridded, 1 km2 snow-covered area (SCA) and snow water equivalent (SWE) products for two headwater basins
within the Rio Grande (i.e. upper Rio Grande River basin) and Salt River (i.e. Black River basin) drainages in
the southwestern USA. The SCA product was the fraction of each 1 km2 pixel covered by snow and was derived
from NOAA advanced very high-resolution radiometer imagery. The SWE product was developed by multiplying
the SCA product by SWE estimates interpolated from National Resources Conservation Service snow telemetry point
measurements for a 6 year period (1995-2000). Measured SCA and SWE estimates were consistently lower than values
estimated from temperature and precipitation within PRMS. The greatest differences occurred in the relatively complex
terrain of the Rio Grande basin, as opposed to the relatively homogeneous terrain of the Black River basin, where
differences were small. Differences between modelled and measured snow were different for the accumulation period
versus the ablation period and had an elevational trend. Assimilating the measured snowfields into a version of PRMS
calibrated to achieve water balance without assimilation led to reduced performance in estimating streamflow for the
Rio Grande and increased performance in estimating streamflow for the Black River basin. Correcting the measured
SCA and SWE for canopy effects improved simulations by adding snow mostly in the mid-to-high elevations, where
satellite estimates of SCA are lower than model estimates.
Keywords: assimilation, snow water equivalent, snow-covered area, hydrologic modelling, PRMS
Fassnacht, S.R., 2004. Estimating alter-shielded gauge snowfall undercatch, snowpack sublimation, and blowing snow transport at six sites in the coterminous United States. Hydrological Processes, 18(18): 3481-3492 (doi:10.1002/hyp.5806).
Computing the monthly and winter water balance for cold regions can be difficult due to data scarcity. Historically, the spatial and temporal resolution, and the number of variables measured have been limited. Currently these data are once again becoming limited. To estimate the net snowpack accumulation, measured precipitation must be adjusted to consider precipitation underestimation
due to gauge undercatch, the snow lost to sublimation, and blowing snow transport. Using existing formulations, hourly meteorological data were used to estimate snowpack sublimation and blowing snow transport losses for three winters at six National Weather Service (NWS) Automated Surface Observation Stations across the coterminous United States. Wind-induced undercatch was estimated
from daily data for the colocated NWS Alter-shielded gauges. For the average wind speed sites (the average wind speed was from 2.4 to 4.3 m/s), 70% of the snow that fell was caught, while at the low wind site (1.3 m/s), 90% was caught and only 46% was caught at the high wind site (5.6 m/s). Average snowpack sublimation ranged from 7 mm per month at either low wind or low precipitation sites
to over 20 mm per month at average wind sites with either average precipitation and low humidity or high precipitation and moderate humidity. Blowing snow transport was only important at higher wind sites (>4 m/s). A distinct relationship was not obvious for average monthly meteorology for undercatch versus snowpack sublimation plus blowing snow losses. Seasonally, they are approximately equal
for more snowy and wet environments.
Keywords: snowfall undercatch, snow sublimation, blowing snow transport, water balance, meteorological stations
Molotch, N.P., S.R. Fassnacht, R.C. Bales, and S.R. Helfrich, 2004. Estimating the distribution of snow water equivalent and snow extent beneath cloud cover in the Salt-Verde River basin, Arizona. Hydrological Processes, 18(9): 1595-1611 (doi:10.1002/hyp.1408).
The temporal and spatial continuity of spatially distributed estimates of snow water equivalent (SWE) and snow-covered area (SCA) is limited by the availability of cloud-free satellite imagery, as SCA is required 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. An accuracy optimization function of gridded positive accumulated degree-days (ADD) and binary SCA (derived from the Advanced Very High Resolution Radiometer (AVHRR)) was used to define a threshold
temperature to define the area capable of having snow cover. The optimized threshold temperature increased during snow accumulation periods, reaching a peak at maximum snow extent. The thresholds then decrease during the first time period after peak snow extent due to the low amount of energy required to melt the "intermittent" snow cover at lower
elevations. The area defined as being capable of having snow cover was then used to define the extent of the SWE interpolation. The simulated snow capable area was compared to observed SCA from AVHRR to assess the simulated snow map accuracy. During periods without precipitation, the average commission and omission errors were 12.2% and 8.0% respectively.
Commission and omission errors increased to 12.9% and 18.7% during periods of precipitation. The analysis shows that temperature data can be useful in defining the snow extent beneath clouds and therefore improve the spatial and temporal continuity of SCA and SWE products.
Keywords: snow water equivalent, snow cover, time series, temperature, hydrological data
Fassnacht, S.R., F. Yusuf, and N. Kouwen, 2004. Paralysing January 1999 snowstorms produced minimal streamflow for Southern Ontario. Canadian Water Resources Journal, 29(1): 1-12.
On January 2, 1999, the city of Toronto and surrounding regions of southern Ontario, Canada were brought to a standstill by a large storm event that resulted in near-record snowfalls. Several smaller winter storms followed and by January 15 approximately 100 cm of snow had fallen across the area,
creating a flooding concern for water resources managers. A statistical analysis of the 1999 snowpack depth and snow water equivalent (SWE) for the Grand River Basin showed that the snow depths were the largest on record with two-week snow depth increases at several sites having return periods from 50
to 200 years. However, the amount of water in the snowpack was small, with the return period for SWE being between two and 21 years. Above freezing temperatures occurred in mid-January partially melting the pack and producing some streamflow. No flooding occurred, and the spring peak streamflows were amongst the lowest on record.
Fassnacht, S.R., K.A. Dressler, and R.C. Bales, 2003. Snow water equivalent interpolation for the Colorado River Basin from snow telemetry (SNOTEL) data. Water Resources Research, 39(8): 1208 (doi:10.1029/2002WR001512).
Inverse weighted distance and regression non-exact techniques were evaluated for interpolating methods snow water equivalent (SWE) across the entire Colorado River Basin of the western United States. A 1-km spacing was used for the gridding of snow telemetry (SNOTEL) measurements, for the years 1993, 1998, and 1999, which on average represented a higher than average,
average and lower than average snow years. Due to the terrain effects, the regression techniques (hypsometric elevation and multi-variate physiographic parameter) were found to be superior to the weighted distance approaches (inverse distance weighting squared, and optimal power inverse distance weighting).
A regression detrended inverse weighted distance method was developed for the hypsometric and multi-variate techniques, in order to preserve the point SNOTEL data. Based on root mean square error analysis and estimates of SWE volumes in different elevation zones for the entire basin and for sub-basins, the elevation detrended method with a point-by point regression
was found to be the most appropriate technique. Various search radii and anisotropies of the search ellipse were tested with the hypsometric method, producing only small difference in the root mean square error and SWE volumes.
Keywords: snow water equivalent, SNOTEL, spatial interpolation, Colorado River
Fassnacht, S.R., and E.D. Soulis, 2002. Implications during transitional periods of improvements to the snow processes in the Land Surface Scheme - Hydrological Model WATCLASS. Atmosphere-Ocean, 40(4): 389-403.
The representation of snow processes is crucial in both hydrological models and land surface schemes. The importance of detailed physical representation for four snow processes into the WATCLASS hydrological-land surface scheme model is examined. The snow processes
are the occurrence of mixed precipitation, the density of fresh snow, the maximum snowpack density and canopy snowfall interception. It is shown that the inclusion of the non-static processes does not significantly improve the simulated streamflow. The changes in the
simulation of state variables, in particular, the snowpack depth, snow water water equivalent, soil temperature and soil moisture content are small, but may become important during transitional periods, such as the initial accumulation and depletion of snow-covered area
during snowmelt. This substantially alters the surface heat fluxes during these periods.
Fassnacht, S.R., N. Kouwen, and E.D. Soulis, 2001. Surface temperature adjustments to improve weather radar representation of multi-temporal winter precipitation accumulations. Journal of Hydrology, 253(1-4): 148-168.
Hydrologists and water resources managers who work in areas that receive a significant portion of the annual precipitation in the form of snowfall rely on good approximates of snow accumulation in order to assess snowpack volumes for snowmelt streamflow estimation.
Weather radar rainfall estimation has been used for hydrological modelling and radar has been used for the estimation of snowfall from individual events, yet radar has rarely been used to measure snowfall accumulation over time periods longer. Snowfall estimates for
weekly, monthly, and seasonal accumulation periods have been compared to measured Nipher-shielded Belfort precipitation gauge quantities. A local scaling issue that caused overestimates is discussed. To enhance the accumulation estimates, the conventional scan radar
images were adjusted using the near surface air temperatures. The adjustment for mixed precipitation improved the accumulation estimates, while the subsequent particle shape adjustment for snow crystal shape did not further enhance the radar estimates.
Keywords: snowfall, snow accumulation, weather radar, mixed precipitation, snow particles
Fassnacht, S.R., 2000. Flow modelling to establish a suspended sediment sampling schedule in two Canadian Deltas. Hydrology and Earth System Sciences, 4(3): 425-438.
The approximate travel times for suspended sediment transport through two multi-channel network is estimated using flow modelling. The focus is on the movement of high sediment concentrations that travel rapidly downstream. Since
suspended sediment transport through river confluences and bifurcation movement is poorly understood, it is assumed that the sediment moves at approximately the average channel velocity during periods of high sediment load movement.
Calibration of the flow model is discussed, with an emphasis on the incorporation of cross-section data, that are not referenced to a datum, using a continuous water surface profile. Various flow regimes are examined for the Mackenzie
and the Slave River Deltas in the Northwest Territories, Canada, and a significant variation in travel times is illustrated. One set of continuous daily sediment measurements throughout the Mackenzie Delta are used to demonstrate
that the travel time estimates are reasonable.
Keywords: suspended sediment, multi-channel river systems, flow modelling, sediment transport
Fassnacht, S.R., and F.M. Conly, 2000. The persistence of a scour hole on the East Channel of the Mackenzie Delta, NWT. Canadian Journal of Civil Engineering, 27(4): 798-804.
Anomalies in the bathymetry of river channels are of great practical concern for designing sub-bed pipeline crossings. Of particular interest is the long-term stability of deep holes. Bathymetric evidence indicates that one unusually deep hole in the
East Channel of the Mackenzie River, referred to as a scour hole, has existed as early as 1956. Detailed hydraulic and morphologic data were first collected in 1985, and again in 1992 in order to assess the spatial and temporal stability of the feature.
Even with a record flood on the Mackenzie River in 1988, the hole, with a maximum depth approaching 30 metres, was vertically stable over the seven year period. However, lateral erosion and sedimentation have resulted in a shift in the horizontal position
of the scour hole, with a maximum horizontal erosion of approximately 2 metres per year. The average rates of lateral outward movement were observed to be 0.8 metres per year.
Keywords: Mackenzie Delta, rivers, fluvial sediment, channel stability, scour, scour hole
Fassnacht, S.R., E.D. Soulis, and N. Kouwen, 1999. Algorithm application to improve weather radar snowfall estimates for winter hydrologic modelling. Hydrological Processes, 13(18): 3017-3039.
Algorithms were applied to weather radar data to improve the precipitation estimation for winter hydrologic modelling. The radar data were adjusted to consider the occurrence of mixed precipitation at above freezing air temperatures, the shape of snow particles,
and a site specific scaling phenomena. Radar data, uncorrected and corrected gridded gauge precipitation data were used as input to the linked WATFLOOD/CLASS hydrologic model for simulation of streamflow. WATFLOOD performed the horizontal water routing and CLASS
performed the vertical energy and water budgetting. Modelling of the Grand River watershed that is within the coverage of the Atmospheric Environment Service C-band radar in King City, Ontario, Canada for the five winters from 1993 to 1997 illustrated that on
average the adjusted radar images produced +/- 15% of the observed runoff volumes whereas the corrected gauge precipitation yielded 35% less runoff than observed. Substantial seasonal variation was observed. Radar provided more realistic winter precipitation
quantities for streamflow modelling than the corrected gauge data. Application of the algorithms improved upon the raw radar estimates.
Keywords: hydrologic modelling, weather radar, precipitation gauges, winter hydrology, snow
Fassnacht, S.R., J. Innes, N. Kouwen, and E.D. Soulis, 1999. The specific surface area of fresh dendritic snow crystals. Hydrological Processes, 13(18): 2945-2962.
The surface area to mass ratio or specific surface area (SSA) is an often neglected characteristic of the snowpack that varies substantially with time, and with the shape of the individual snow crystal for fresh snow.
The SSA for the dendritic shape of snow crystals was computed using a series of images presented in Bentley and Humphries (1931). The specific images were dendritic crystals (P1d, P1e, P1f) and crystals that take a partial
dendritic form and have ends or extensions (P2a, P2b, P2d, P2e, P2f, P2g) according to the Magono and Lee (1966) snow crystal classification. Image analysis using known geometric relationships between length and width and
particle size distributions examined the spatial properties of 50 sample snow crystals. Probability distribution functions were derived for SSA and these compared well with measured and other computed estimates of fresh
snow SSA. For the non-rimed condition, the average SSA was 0.182 m2/g with a range from 0.09 to 0.33 m2/g. The presence of rime is discussed. Depending on the shape of the rime particles and the degree of surface coverage,
the SSA can be doubled (20% coverage for needle or plate rime). Fractal analysis was performed to determine various geometric relationships that characterize the dendritic form of snow crystal.
Keywords: snow crystals, specific surface area, dendrites, Bentley images, fractal analysis
Fassnacht, S.R., 1997. A multi-channel suspended sediment transport model for the Mackenzie Delta, NWT. Journal of Hydrology, 197(1-4): 128-145.
To model the suspended sediment transport through the Mackenzie River Delta, Northwest Territories, Canada, a one-dimensional multi-channel suspended sediment model (FOSH-MC) has been developed. The
model links an established network flow model that has been successfully applied to the Mackenzie Delta with an existing suspended sediment model. Sediment travel times along channels, that are useful
to establish suspended sediment sampling schedules, are estimated as a model output product. The sediment output also includes total loads at each network node and reach suspended sediment concentrations.
The model can route both cohesive and non-cohesive suspended sediment.
This research is a first attempt to dynamically model sediment transport through the Mackenzie Delta. All previous efforts have examined long-term fluxes. The FOSH-MC model has the potential to trace
the pathways of contaminants through the Mackenzie Delta. The model also has the potential to be applied to other multi-channel networks that primarily carry suspended sediment.
Keywords: sediment, sediment transport, suspended sediment, multi-channel network, travel time, modelling, Mackenzie Delta
Fassnacht, S.R., T. Sukh, M. Fernández-Giménez, B. Batbuyan, N.B.H. Venable, M. Laituri and G. Adyabadam, 2011. Local understanding of hydro-climatic changes in Mongolia. Cold Region Hydrology in a Changing Climate (Proceedings of symposium H02 held during IUGG2011 in Melbourne, Australia, July 2011), IAHS, 346, 120-129.
Air temperatures in semi-arid regions have increased more over the past few decades than those in many other parts of the world. Mongolia has an arid/semi-arid climate where large portions of the population
are herders whose livelihood depends upon limited water resources. This paper combines local knowledge and understanding of recent changes in water availability in streams, springs, and wells with an analysis of
climatic and hydrological change from meteorological station data to illustrate the degree of change among Mongolian water resources. We find that herders' perceptions of hydro-climatic change are very similar to
the results of the station-based analysis. Additionally, since station data are spatially limited, local knowledge can emphasize smaller-scale variability in changes to climate and hydrology. For this paper, we
focus on a site in the Khangai Mountains and another in the Gobi desert-steppe, both in Central Mongolia.
Fassnacht, S.R., E.D. Soulis, and N. Kouwen, 2003. Radar precipitation for winter hydrological modelling. Information from Weather Radar and Hydrological Modelling (Proceedings IUGG 2003 Symposium HS02, Sapporo Japan, July 2003), IAHS, 281: 8 pages.
Interpolated precipitation gauge measurements and weather radar snowfall estimates were used as input to a physically based hydrological model (WATCLASS). The gauge measurements were corrected for wind undercatch according to WMO standards.
Post-processing of the radar data was undertaken to consider underestimation due to the use of winter radar coefficients for liquid precipitation. Streamflow was simulated for the Upper Grand River Basin in central southwestern Ontario, Canada
for the five winters from 1993 - 1997. For each year, except 1995, the radar data provided precipitation estimates that were better, in terms of simulated runoff volumes, than those provided by the gauge data.
Along with runoff volumes, peak streamflows were more closely estimated from radar precipitation than gauge precipitation. Gauge estimates consistently yielded lower than observed peak streamflows.
Keywords: snow hydrologic modelling, weather radar, precipitation gauges, winter hydrology
Fassnacht, S.R., K.R. Snelgrove, and E.D. Soulis, 2001. Daytime incoming longwave radiation approximation for physical hydrological modelling. Soil-Vegetation-Atmosphere Transfer Schemes and Large-Scale Hydrological Models (Proceedings Sixth IAHS Scientific Assembly Symposium S5, Maastricht, July 2001), IAHS, 270: 279-286.
Since incoming long-wave radiation is not routinely measured in Canada, when it is required as a meteorological parameter, such as input to a physically-based hydrological model, the data must be derived. These data have been successfully computed as a function of near surface air temperature and cloud cover. However, cloud cover data are also not routinely measured. A method is described to compute
the cloud cover fraction, for use to estimate the long-wave radiation, from a comparison of measured to theoretical short-wave radiation at three sites in central southwestern Ontario. The daytime cloud cover fraction is on average slightly more than 0.50. The impact of different long-wave radiation estimates from varying cloud cover fraction assumptions is illustrated in terms of simulated streamflow
resulting from snowmelt.
Keywords: incoming long-wave radiation, short-wave radiation, snowmelt modelling, cloud cover
Fassnacht, S.R., E.D. Soulis, and N. Kouwen, 2001. Enhancing weather radar winter precipitation accumulation estimates. Remote Sensing in Hydrology 2000 (Proceedings IAHS Remote Sensing and Hydrology Conference 2000, Santa Fe, April 2000), IAHS, 267: 46-49.
Snowfall estimates for weekly, monthly, and seasonal accumulation periods have been compared to measured Nipher-shielded Belfort precipitation gauge quantities. A local scaling issue that caused overestimates is discussed. To enhance the accumulation estimates, the conventional scan radar images were adjusted using the near surface air
temperatures. The adjustment for mixed precipitation improved the accumulation estimates, while the subsequent particle shape adjustment for snow crystal shape did not further enhance the radar estimates.
Keywords: snowfall, mixed precipitation, rainfall, precipitation measurement, radar
Fassnacht, S.R., E.D. Soulis, and N. Kouwen, 1999. Shape characteristics of freshly fallen snowflakes and their short-term changes. Interactions between the Cryosphere, Climate and Greenhouse Gases (Proceedings IUGG 99 Symposium HS2, Birmingham, July 1999), IAHS, 256: 111-122.
The shape of newly formed snowflakes is an important qualitative parameter as input to the development of a snowpack, and for potential atmospheric scavenging, while changes in the shape of freshly fallen crystals influence the metamorphosis and transport of snow and contaminants. This paper uses known spatial properties to simulate the needle-shaped
crystal structures that can occur in the range of -4 to -6 degrees C. Probability distribution functions (pdfs) are derived for the surface area to mass ratio, ranging from 0.10 to 0.30 m2.g-1. Observations of freshly fallen flakes are compared to predicted pdfs. The modification in the snow crystal shape, immediately after accumulation, is estimated from
laboratory experiments that measured sublimation rates directly from the pack. For fresh flakes, there is a rapid decrease in the effective surface area up to 50% over only 2-3 days.