The IP3 Research Network:
Enhancing Understanding of Water Resources
in Canada’s Cold Regions
John Pomeroy & the IP3 Network
www.usask.ca/ip3
IP3...
...is devoted to understanding water
supply and weather systems in cold
Regions at high altitudes and high
latitudes (Rockies and western Arctic)
...will contribute to better prediction
of regional and local weather, climate,
and water resources in cold regions, including ungauged basin
streamflow, changes in snow and water supplies, and calculation of
freshwater inputs to the Arctic Ocean
...is composed over about 40 investigators and collaborators from
Canada, USA, UK, France, Germany, Italy
…runs from 2006-2010
Why IP3?
Need to forecast changing flow regime
of streams and rivers in the Western
Cordillera and North
Increasing consumptive use of Rocky
Mountain water in Prairie Provinces
Uncertainty in design for resource (oil & gas, diamond, etc)
development and restoration activities in small to medium size,
headwater ‘ungauged’ basins
Opportunity to improve cold regions snow, ice, frost, soil and water
processes in models to reduce predictive uncertainty in:
Atmospheric impacts on snow, ice and water resources
Simulation of land-cryosphere-atmosphere interaction
Cycling and storage of water, snow and ice
Prediction of future climate change
IP3 Network Investigators
Sean Carey, Carleton University
Richard Essery, Edinburgh University
Raoul Granger, Environment Canada
Masaki Hayashi, University of Calgary
Rick Janowicz, Yukon Environment
Philip Marsh, University of Saskatchewan
Scott Munro, University of Toronto
Alain Pietroniro, University of Saskatchewan
John Pomeroy (PI), University of Saskatchewan
William Quinton, Wilfrid Laurier University
Ken Snelgrove, Memorial University of Newfoundland
Ric Soulis, University of Waterloo
Chris Spence, University of Saskatchewan
Diana Verseghy, Environment Canada
(people in bold are on Scientific Committee)
IP3 Science Focus
Snow – redistribution,
accumulation, sublimation,
radiative transfer and melt
Forests – effect on radiative
and turbulent transfer to snow and frozen ground
Glaciers - interactions with the atmosphere
Frozen ground – freezing, thaw, water transmission
and storage
Lakes/Ponds – advection, atmospheric fluxes, heat
storage, flow in drainage systems
IP3 – Goals and Theme Structure
Theme 1 Processes: Advance our understanding
of cold regions hydrometeorological processes
Theme 2 Parameterisation Develop mathematical
parameterisation of cold regions processes for small
to medium scales
Theme 3 Prediction Evaluate and demonstrate
improved hydrological and atmospheric prediction
at regional and smaller scales in the cold regions of
Canada
Ultimately – contribute to multiscale assessment of
coupled climate system, weather and water
resources in cold regions
IP3 Research Basins
Havikpak Creek,
NT
taiga woodland
Wolf Creek, YT
subarctic tundra
cordillera
Trail Valley Creek,
NT
arctic tundra
Polar Bear Pass,
NU
arctic wetlands
Baker Creek, NT
subarctic shield
lakes
Peyto Glacier,
AB
glacierized alpine
Scotty Creek, NT
permafrost
wetlands
Lake O'Hara,
BC
wet alpine
Reynolds Creek, Idaho
mountain rangeland
Marmot Creek,
AB
subalpine forest
New IP3 Initiatives
Advanced data management system
Courses on CRHM and MESH given in Ontario,
Manitoba, Alberta (Calgary, Edmonton, Red
Deer), NWT
Outreach meetings
Science monograph
Policy implications book
Network Completion
HESS Special Issue on Cold Regions
Hydrology
No cost extension of IP3 to end of March 2011
−
Science Spending to cease by ~ August 2010
−
Special Prediction Effort to cease by Feb 2011
Secretariat, Outreach and Information
Management funded to end of March 2011
IP3 Legacy
Canada a leader in the understanding of cold regions
hydrology (snow, permafrost, ice, rivers)
Development of network of research basins from
Cordillera to Arctic
Trained cold regions hydrologists and climatologists
Cold regions hydrological models
Mechanism for transfer of knowledge to users
Coupled atmospheric-hydrological prediction models
for Government of Canada and other users
Informed public policy on mountain and northern water
resources
IP3 Final Outputs
Improved understanding of cold regions
hydrological processes at multiple scales
Unique observational archive of research
basin data
More effective incorporation of cold regions processes and
parameterisations into hydrological and meteorological models at
regional and smaller scales – CRHM, MESH
Improved environmental predictive capability in cold regions in
response to greater water resource demands:
Enhanced hydrological and atmospheric model performance at
multiple spatial scales and at scales requested by users
Improved streamflow prediction in ungauged basins with less
calibration of model parameters from gauged flows
Improved weather and climate prediction due to rigorous model
development and testing
Policy Implications from IP3
Loss of hydrological “stationarity” due to climate and
land use change means traditional risk management
analyses are inadequate for water resources
management.
Information for water policy, allocation, conservation
and development is required that cannot be provided
by analysis of observations alone.
Improved information can be obtained from the results
of coordinated observation and prediction systems that
incorporate aspects of data assimilation, enhanced
observations, improved model development and
continuing process research to deal with evolving
unknowns
Snow Regimes
Forest Snow
–
Open Snow
Shrub Growth?
1993
2008
2001
Shrub Growth!
2008
Snow Accumulation Variability
Blowing Snow in Complex Terrain
Inter-basin water
transfer
Transport of snow
to drifts
Supports glaciers,
late lying snowfields,
hydrological
contributing areas
Blowing Snow Entering Basin
Shrub Tundra Accumulation Becoming Higher
than Sparse Tundra
250
225
200
SWE (mm)
175
Shrub Tundra
Alpine
150
125
100
75
50
25
0
1994
1995
1996
1998
1999
2000
2001
Shrub Tundra
87
111
134
139
179
216
168
Alpine
65
77
35
74
83
Note that shrub tundra at this site is 50 cm taller now than in 1994
Pomeroy et al., 2006 Hydr Proc
29
dSWE
= Χ S − ∇ ⋅ T − ES
dt
SF
d
Win
LiDAR used to develop
topography and vegetation DEM
n
ctio
e
r
i
D
NF
Granger Basin,
Wolf Creek,
Yukon Territory
Essery and Pomeroy, in preparation
Computer simulation of wind flow over mountains
Windspeed
Direction
3000
3000
2500
2500
2000
2000
1500
1500
1000
1000
500
500
0
0
0
500
1000
1500
2000
2500
3000
0
500
3 km
Granger Basin, Wolf Creek, Yukon
1000
1500
2000
2500
3000
Simulation of Hillslope Snowdrift
3 km
Intercepted Snow
Snow intercepted for weeks to
months in cold regions forests
Low albedo, high net
radiation, high turbulent
transfer result in enhanced
sublimation loss
Accumulation =
Snowfall – Interception
+ Unloading + Drip
or
Accumulation =
Snowfall - Sublimation
Snow in Forest / Snow in Clearing
Effect of Forest Removal on Snow
Accumulation
1
0.9
Deforestation Effect
0.8
0.7
Sparsely Wooded
0.6
0.5
Medium Density, Young
0.4
0.3
Dense Mature Canopy
Measured
0.2
Parametric Model
0.1
0
0
1
2
3
Leaf Area Index
4
5
Pomeroy et al., 2002 Hydr Proc
Snowmelt
Incoming solar
and thermal
radiation
Warm air masses
Energy storage
Terrain and
vegetation effects
Snow Energetics
Incoming Longwave in Arctic Mountains
30
Percent increase in
longwave irradiance due
to terrain emission due to
sky view factor (Vf) and
surface temperature (Ts).
25
Ts (°C)
20
Air temperature is 0°C
and the clear sky
emissivity is 0.65
15
10
5
0
0.5
0.6
0.7
0.8
0.9
1
Sky View Factor Vf
Thermal IR Image
Sicart et al. 2006 Hyd Proc
Wolf Creek shrubs
Marmot Creek level forest
Solar radiation to snow beneath shrubs and trees
1000
400
SW (W/m )
300
2
2
SW (W/m )
800
600
400
200
0
123
200
100
0
124
125
74
Day (2003)
Pomeroy et al., J Hydrometeorol, 2008
75
Day (2005)
76
Hot Trees
Longwave Exitance Pine Stand
350
330
Exitance W/m²
310
290
270
250
Needles
230
Trunk
210
190
Sky
170
Air
150
74
74.5
75
75.5
Pomeroy et al., J Hydromet. 2009
76
Julian Day
76.5
77
77.5
78
Slope and Forest Density Effect on Net
Radiation for Snowmelt
Ellis et al,
submitted
Clearing
Mature Forest
Net radiation = solar + thermal radiation
Landscape Heterogeneity
Modelling Approach
Aggregated vs. Distributed
Dornes et al., 2008 Hydrol Proc.
Snowmelt and Streamflow
2003
250
180
160
Obs SWE
Aggregated
Distributed
200
SWE [mm]
120
100
80
150
100
60
50
40
20
0
0
4/17/02 4/24/02
5/1/02
5/8/02
5/15/02 5/22/02 5/29/02
4/17/03
6/5/02
Time [days]
0.5
1.0
Obs
Aggregated
Distributed
0.4
Q [m3/s]
0.8
Q [m3/s]
SWE [mm]
140
Obs SWE
Aggregated
Distributed
0.6
0.4
4/26/03
5/05/03
5/14/03
5/23/03
6/01/03
Time [days]
Obs
Aggregated
Distributed
0.3
0.2
0.2
0.1
0.0
5/01/02 5/09/02 5/17/02 5/25/02 6/02/02 6/10/02
0.0
4/17/03 4/26/03 5/05/03 5/14/03 5/23/03 6/01/03
Time [days]
Time [days]
Concluding Remarks
Relationships between snow and vegetation are strongly influenced by
atmospheric energy and mass inputs which in turn are controlled by weather
and topography
−
Less forests => more snow (except if windblown)
−
More shrubs => more snow (if windblown)
−
Less forests => more rapid snowmelt on south facing, slower melt on north
facing slopes
Increasing shrub height and coverage and decreasing forest coverage in
cold regions mountains with both tend to increase snow accumulation in
some locations and will both tend to increase melt rate except on north
facing slopes.
Further questions
−
What snow regime is optimal for sustaining current vegetation communities?
−
What are stable snow-vegetation regimes for various climates and how do these
respond to and modulate climate change impacts?
−
Can we develop integrated snow ecology – hydrology models to show how
climate change, terrestrial ecosystem shifts and hydrology interact as a system?