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Modelling the Potential Impacts of
Climate Change on Snowpack in the
St. Mary River Watershed, Montana
Ryan MacDonald
November, 2008
Thesis Objectives
Develop spatial surfaces of
hydrometeorological variables over
mountainous terrain in the St. Mary
River watershed
Assess potential impacts of climate
change on mountain snowpack in the
St. Mary watershed for a range of GCM
derived scenarios using the GENESYS
model.
Study Area
Study Area
Developing Spatial Surfaces of
Hydrometeorological Variables
Spatial Characteristics

Slope

Aspect

Elevation

Land cover
Meteorology

Temps

Radiation

Humidity

Precipitation
Hydrology

Snowpack

Soil water

ET, ETP, Sublimation

Interception

Runoff
180
Precipitation (mm)
Many Glacier SnoTel
140
120
100
80
60
40
20
0
JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC
Month
180
Precipitation (mm)
Difference in
seasonal
distribution of
precipitation
between
eastern slopes
and western
mountain
regions
160
160
St. Mary Climate Station
140
120
100
80
60
40
20
0
JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC
Month
Seasonally varying precipitation
elevation lines
Mean monthly precipitation (mm)
summer
fall
winter
spring
180
170
160
150
140
130
120
110
100
90
80
70
60
50
40
1400
1600
1800
2000
2200
Elevation (m)
2400
2600
2800
Applying differences in seasonality
to daily data
Ratio
2800m
1400m
2000m
5
4.5
4
3.5
3
2.5
2
1.5
1
0.5
0
JAN
FEB
MAR
APR
MAY
JUN
Month
JUL
AUG
SEP
OCT
NOV
DEC
Predicted annual runoff
volume
Simulated flow volume (m3)
1,600,000,000
Y = 1.110x
r2 = 0.957
1,400,000,000
1,200,000,000
1,000,000,000
800,000,000
600,000,000
400,000,000
200,000,000
0
0
200,000,000
400,000,000
600,000,000
800,000,000
1,000,000,000 1,200,000,000 1,400,000,000 1,600,000,000
Observed flow volume (m3)
10 year daily SWE Simulation at
Many Glacier SnoTel
700
600
SWE (mm)
500
400
300
200
100
0
Observed
Simulated
Assessing the Potential Impacts of
Climate Change on snowpack
Verified
hydromet model
General Circulation
Model (GCM)
derived climate
change scenarios
Predictions of
future snowpack
-Precipitation
phase
-Spatial change
in annual mean
SWE
-Change in
annual maximum
SWE
-Change in timing
of the onset of
melt
12
CGCM2 A21
CGCM2 A22
11
CGCM2 A23
10
CGCM2 B21
9
CGCM2 B22
CGCM2 B23
8
CGCM2 B2x
7
GFDLR30 A21
6
GFDLR30 B21
Precipitation Change (%)
ECHAM4 A21
5
ECHAM4 B21
4
CSIROMk2b
A11
CSIROMk2b
B11
CSIROMk2b
A21
CSIROMk2b
B21
CCSRNIES A1FI
3
2
1
CCSRNIES A1T
0
0
0.5
1
1.5
-1
2
2.5
CCSRNIES A11
CCSRNIES B11
CCSRNIES A21
-2
CCSRNIES B21
-3
HadCM3 A21
-4
HadCM3 A22
HadCM3 A23
-5
HadCM3 A2x
-6
HadCM3 B21
HadCM3 B22
Temperature Change (oC)
HadCM3 B11
Climate change scenarios
Table X. GCMs used in this study (Adapted from Barrow and Xu, 2005)
Scenario
GCM
Emissions Scenario
Resolution (°)
ECHAM
ECHAM4
A2 (1)
2.8 x 2.8
CSIRO
CSIRO-Mk2
A1 (1)
5.6 x 3.2
CGCM
CGCM2
A2 (3)
3.75 x 3.75
CCSR
CCSR/NIES
A1T
5.62 x 5.62
NCAR
NCAR-PCM
B2 (1)
2.8 x 2.8
Table X. Annual temperature and precipitation changes predicted by each GCM
Time
period
2020s
2050s
2080s
ECHAM
Temp Precip
(°c)
(%)
1.4
-4
2.6
-1
3.8
-2
CSIRO
Temp Precip
(°c)
(%)
1.7
3
3.3
4
4.8
10
CGCM
Temp Precip
(°c)
(%)
1.4
1
2.7
-1
4.6
3
CCSR
Temp Precip
(°c)
(%)
1.0
-3
4.3
3
6.3
8
NCAR
Temp Precip
(°c)
(%)
1.2
5
1.5
7
2.0
14
100
80
30
35
36
37
70
65
64
63
Historical
2020s
2050s
2080s
60
40
20
0
Snow
Rain
Proportion of total precip
Proportion of total precip
Precipitation phase change
100
80
30
33
37
60
60
40
70
67
63
20
40
0
Historical
2020s
Snow
2050s
Rain
2080s
Spatial change in mean annual SWE
under climate change
BASE
2020
2050
2080
Depth of Maximum SWE
Historical
CCSR
1800
Maximum SWE (mm)
Significant
decreasing
trend in the
CCSR
scenario at
the 99%
confidence
level, no
significant
trend in
NCAR
scenario
NCAR
1600
1400
1200
1000
800
600
400
200
0
1961 1971 1981 1991 2001 2011 2021 2031 2041 2051 2061 2071 2081 2091
Year
Julian Date of Maximum SWE
Historical
CGCM
140
120
Julian Date (Days)
Significant
decreasing
trends at the
90% and
99%
confidence
levels for the
NCAR and
CGCM
scenarios
respectively
NCAR
100
80
60
40
20
0
1961 1971 1981 1991 2001 2011 2021 2031 2041 2051 2061 2071 2081 2091
Year
Conclusions
• Physically based spatial models provide useful
tools for estimating climate change impacts in
mountainous regions
• Climate change projections are highly
dependent on scenario selection
• Not necessarily an annual runoff volume issue
• Hydrological timing may shift
• Late season water shortages
Questions ?