Poster C33C-1283
Modeling Climate Change Impacts on Snow Water Equivalent
(SWE) in Alpine Headwaters, Glacier National Park, MT
University of Lethbridge,
Lethbridge, Alberta, Canada
R. Larson, J. Byrne, S. Kienzle, M. Letts, and D. Johnson
The predicted continuing trend of increasing rainto-snow ratios (McCabe and Wolock, 1999) will
likely
have
the
following
hydrological
consequences in the area:
• More winter runoff;
• Less snow accumulation;
• Decline in spring and summer water supply.
(Lapp et al., 2005, Leith and Whitfield, 1998)
Colder temperatures and modest precipitation in the
Alberta-Montana Rockies cause larger and more
persistent snowpacks than in most regions of the
western USA (Selkowitz et al., 2002). The headwaters
of the transboundary St. Mary River system provides
water to approximately 200,000 ha of irrigation in
Alberta and 56,600 ha in Montana (AAFRD, 2000).
Therefore, climate change effects on snowpack in the
upper St. Mary River are key to determining the
basin’s future downstream water supply needs.
Detailed assessments are needed to predict
whether increased winter precipitation will
compensate for increasing temperatures in spring
SWE. The two main objectives of this study are:
• Develop an alpine hydrometeorology model for
predicting daily SWE over the upper St. Mary
watershed;
• Apply the model for the historical period, for
validation purposes, with the objective of
applying to future climate change scenarios.
2. Temperature Routine Validation
SIMGRID-simulated TMAX and TMIN were compared with
observed values from Lakeview Ridge, for the 2005-2006
winter period.
Lakeview Ridge (Figure 2) is located
approximately 50 km from the upper St. Mary watershed
(Figure 1), and exhibits near-perfect NW, SW, SE, and NE
aspects, with microclimate measurements on each. Sensors
are at 1900 m elevation. 1m-height TMAX comparisons on
opposing aspects are reasonable (Figure 3).
Site simulations are based on Park Gate base climate
station. Overall, the temperature simulations are well
correlated with observed values (Table 2). Due to the
site’s proximity to the study watershed, the temperature
routine is considered valid for our model. Also, this
model was developed and validated for sites in
Montana (see Hungerford et al., 1989).
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Preliminary Results
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Observed (Site)
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Simulated (Site)
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Park Gate (Base)
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Observed (Site)
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Simulated (Site)
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-Feb-0
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ar- 06
Park Gate (Base)
Figure 3. Temperature Comparisons of two sites at Lakeview Ridge
The model was run for several years within the historical
period (1981-2003). SWE fields were produced for
random years for display purposes.
SWE (mm)
The maps below illustrate April 1st watershed SWE fields
and total snowpack depth. As expected, higher snow
accumulations occur at higher elevations.
April 1st, 1991
April 1st, 2003
April 1st, 1986
Figure 2. Microclimate stations are located on all
aspects of Lakeview Ridge (in the background). The
flat prairies are visible beyond the peak.
Total April 1st
Snowpack
Methods
Table 1. Watershed Site Classifications
Figure 5. The Preston snow survey spans from 1300 m
to 2300 m, an elevation area comprising 81.6% of the
upper Saint Mary watershed area (see Table 1).
The linear regression used to derive C1 in Equation (1)
was determined by having the difference between
∆SWE and StMP on the y-axis, and the adjusted
elevation on the x-axis (Figure 6). C1 was 0.261, and
the forced origin r2 value was 0.56.
6.19 X 108 m3
Summary and Directions
Figure 4. Snow surveying in the upper St. Mary watershed
Figure 6. (∆SWEE-StMP) vs. Elevation. The wider, outer
band is the 95% confidence interval (CI) for an individual
case. The narrow inner band is the long-term 95% CI.
We are thankful to the United States
Geological Survey (USGS) for providing the
SWE database, as well as continued support
with the project. Research funding from the
Alberta Ingenuity Centre for Water Research
(AICWR) is greatly appreciated.
∆SWE (m m )
600
600
7-Feb-95
500
7-Mar-95
500
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400
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100
0
0
0
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600
400
600
800
0
200
600
20-Jan-00
500
∆SWE (m m )
400
600
800
600
800
25-Feb-03
500
400
400
300
300
200
200
100
100
0
0
0
600
200
400
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800
0
500
200
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600
27-Mar-03
)
Box 1. Preston Proxy Precipitation Derivation
1. Further work is required to calibrate the model. A second
base climate station may be added, and the effect of
dominant westerly air flow patterns will be investigated.
Calibration will proceed using the Many Glacier SNOTEL
station.
2. Large-scale natural variability governing hydroclimate will
be investigated. Although there is a consistent upward
∆SWE-Elevation relationship in the watershed, monthly
variability has been observed (Figure 7).
3. Monthly and annual precipitation and temperatures are
influenced by seasonal synoptic patterns, as well as
interannual and interdecadal large-scale climate indices,
such as the Southern Oscillation Index (SOI) and Pacific
Decadal Oscillation (PDO) (Fagre et al., 2003; McCabe
and Dettinger, 2002; Regonda, 2005). If relationships
between such indices and hydroclimate are found, indices
may be used to better characterize variability over the
watershed.
4. Climate change scenarios will be applied to the
watershed, using appropriate Global Climate Models
(GCMs), Regional Climate Models (RCMs), and possibly
large-scale variability indices.
Acknowledgements:
1. Terrain Classification
5.19 X 108 m3
28-Feb-06
500
400
400
(
Figure 1. Study area maps. The SWE modeling is conducted over the upper St. Mary
Figure
1. Waterton-Glacier
the Canada-US
watershed
(using the St. Park
Marystraddles
base climate
station). The nearby Lakeview Ridge climate
border
in the
west,
in station)
the left map.
Study
area
stations
(and
Parkappearing
Gate base
are used
to validate
the model’s temperature routine.
details are in the right map.
6.15 X 108 m3
∆SWE (m m )
Snow course data was used to derive a precipitation
formulation for the watershed. Approximately monthly
snow surveys were conducted during the 1994-2006
period (Figures 4 and 5). SWE from one survey to the
next was determined for each location (elevations
adjusted to metres above St. Mary climate station, 1390
masl), see Box 1.
The watershed area’s terrain characteristics were
classified into 869 categories (sites), shown in Table 1.
In a GIS, a 10 m Digital Elevation Model (DEM) was
used to create the categories, which were then
reclassed to 100 m pixels.
The SIMGRID code was
updated
to
incorporate
monthly base precipitation,
and the new precipitationelevation relationship (Box 2).
-5
3. Precipitation Routine Formulation
The distributed hydrometeorology model SIMGRIDSNOPAC was adopted. Based upon the MTCLIM
microclimate model, SIMGRID extrapolates base station
climate information to sites distributed within the
watershed, according to aspect, slope, and elevation.
Subroutines derive daily solar radiation, relative
humidity, and of greatest importance to this study,
maximum and minimum temperature and precipitation
for each site. SNOPAC then uses the daily site
temperatures and precipitation to calculate snow
accumulation. Four steps were taken to begin applying
SIMGRID-SNOPAC to the study watershed, explained
in the following two columns.
Box 2. SIMGRID-SNOPAC Inputs and Outputs
5
5
Study Area
The upper St. Mary watershed is located on the
Rocky
Mountain
eastern
slopes.
Predominantly alpine regions lie to the west of
this region, while the flat prairies lie to the east
(Figure 1). The headwaters study area is 722
km2 and lies almost entirely within WatertonGlacier International Peace Park, MontanaAlberta.
4. Model Modification
SE Aspect Site - 1m Tmax Comparison
NW Aspect Site - 1m Tmax Comparison
Table 2. Lakeview Ridge site characteristics
and temperature simulated-observed statistics.
Tmax (°C)
Snowpack contributes between 70-90% of annual
runoff in mountain watersheds of western North
America (Stewart et al., 2005, Palmer 1988), and
accounts for more than 60% of the annual variability in
streamflow over the same area (Doesken et al., 1989).
Monitoring changes in snow water equivalent (SWE),
the depth of water stored in snowpack, is important for
water supply forecasting.
robert.larson@uleth.ca
Tmax (°C)
Introduction and Objectives
300
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200
100
0
100
0
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400
600
800
Local Elevation (metres above St. Mary, 1390m)
0
200
400
600
800
Local Elevation (metres above St. Mary, 1390m)
Figure 7. Monthly ∆SWE-Elevation graphs are plotted. The lines
plotted exhibited high r-square values, and were chosen to depict
the monthly variability observed in the watershed
References:
Alberta Agriculture, Food & Rural Development (AAFRD). Irrigation in Alberta, Part 2. Lethbridge, Alberta.
2000.
Doesken, N.J., D. Changnon, and T.B. McKee, Interannual variations in snowpack in the Rocky Mountain
region, in Proceedings of the Western Snow Conference, pp. 21-30, 1989.
Fagre, D.B., D.L. Peterson, and A.E. Hessl, Taking the Pulse of Mountains: Ecosystem Responses to
Climatic Variability, Climatic Change, 59 (1-2), 263-282, 2003.
Lapp, S., J.M. Byrne, S.W. Kienzle, and I. Townshend, Climate warming impacts on snowpack
accumulation in an alpine watershed: A GIS based modeling approach, International Journal of
Climatology, 25 (4), 521-526, 2005.
Leith, R.M., and P.H. Whitfield, Evidence of Climate Change effects on the hydrology of stream in SouthCentral B.C., Canadian Water Resources Journal, 23, 219-230, 1998.
Hungerford, R.D., R.R. Nemani, S.W. Running, and J.C. Coughlan, MTCLIM: Mountain Microclimate
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Intermountain Research Station, Ogden, UT, 1989.
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directions, in 56th Western Snow Conference, pp. 43-51, Kalispell, 1988.
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Selkowitz, D.J., D.B. Fagre, and B.A. Reardon, Interannual variations in snowpack in the Crown of the
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Stewart, I.T., D.R. Cayan, and M.D. Dettinger, Changes toward Earlier Streamflow Timing across Western
North America, Journal of Climate, 18, 1136-1115, 2005