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 regimeof streams and rivers in the WesternCordillera 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 waterprocesses 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 understandingof 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 predictionat 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

Marmot Creek, AB

subalpine forest

Lake O'Hara, BC

wet alpine

Peyto Glacier, AB

glacierized alpine

Baker Creek, NTsubarctic shield

lakes

Wolf Creek, YTsubarctic tundra

cordillera

Trail Valley Creek, NT

arctic tundra

Havikpak Creek, NT

taiga woodland

Reynolds Creek, Idahomountain rangeland

Polar Bear Pass, NU

arctic wetlands

Scotty Creek, NTpermafrost wetlands

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 regionshydrological processes at multiple scales

Unique observational archive of researchbasin data

More effective incorporation of cold regions processes andparameterisations 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

Shrub Growth!2001 2008

Snow Accumulation Variability

Blowing Snow in Complex Terrain

Inter-basin water

transfer

Transport of snowto drifts

Supports glaciers,

late lying snowfields,

hydrologicalcontributing areas

Blowing Snow Entering Basin

Shrub Tundra Accumulation Becoming Higher

than Sparse Tundra

0

25

50

75

100

125

150

175

200

225

250

SW

E (

mm

)

Shrub Tundra

Alpine

Shrub Tundra 87 111 134 139 179 216 168

Alpine 65 77 35 74 83 29

1994 1995 1996 1998 1999 2000 2001

Note that shrub tundra at this site is 50 cm taller now than in 1994Pomeroy et al., 2006 Hydr Proc

Granger Basin,

Wolf Creek,

Yukon Territory

NF

SF

LiDAR used to develop

topography and vegetation DEM

Wind D

irection

SS ETdt

dSWE−⋅∇−Χ=

Essery and Pomeroy, in preparation

0 500 1000 1500 2000 2500 3000

0

500

1000

1500

2000

2500

3000

0 500 1000 1500 2000 2500 3000

0

500

1000

1500

2000

2500

3000

Computer simulation of wind flow over mountains

Windspeed Direction

3 km

Granger Basin, Wolf Creek, Yukon

3 km

Simulation of Hillslope Snowdrift

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

Effect of Forest Removal on Snow

Accumulation

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

0 1 2 3 4 5

Leaf Area Index

Sn

ow

in

Fo

rest

/ S

no

w i

n C

leari

ng

Measured

Parametric Model

Sparsely Wooded

Medium Density, Young

Dense Mature Canopy

Deforestation Effect

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

0.5 0.6 0.7 0.8 0.9 1

Vf

0

5

10

15

20

25

30

Ts (°C

)

Percent increase in longwave irradiance due to terrain emission due to sky view factor (Vf) and surface temperature (Ts).

Air temperature is 0°C and the clear sky emissivity is 0.65

Sicart et al. 2006 Hyd Proc

Thermal IR Image

Sky View Factor

0

100

200

300

400

74 75 76

Day (2005)

SW

(W

/m2)

0

200

400

600

800

1000

123 124 125

Day (2003)

SW

(W

/m2)

Solar radiation to snow beneath shrubs and trees

Wolf C

reek s

hru

bs

Marm

ot C

reek level fo

rest

Pomeroy et al., J Hydrometeorol, 2008

Hot Trees

Longwave Exitance Pine Stand

150

170

190

210

230

250

270

290

310

330

350

74 74.5 75 75.5 76 76.5 77 77.5 78Julian Day

Exit

an

ce W

/m²

Needles

Trunk

Sky

Air

Pomeroy et al., J Hydromet. 2009

Slope and Forest Density Effect on Net

Radiation for Snowmelt

Clearing Mature Forest

Net radiation = solar + thermal radiation

Ellis et al, submitted

Landscape Heterogeneity

Modelling Approach

Aggregated vs. Distributed

Dornes et al., 2008 Hydrol Proc.

Time [days]

5/01/02 5/09/02 5/17/02 5/25/02 6/02/02 6/10/02

Q [

m3/s

]

0.0

0.2

0.4

0.6

0.8

1.0

Obs

Aggregated

Distributed

Time [days]

4/17/02 4/24/02 5/1/02 5/8/02 5/15/02 5/22/02 5/29/02 6/5/02

SW

E [

mm

]

0

20

40

60

80

100

120

140

160

180

Obs SWE

Aggregated

Distributed

2003

Time [days]

4/17/03 4/26/03 5/05/03 5/14/03 5/23/03 6/01/03

SW

E [

mm

]

0

50

100

150

200

250

Obs SWE

Aggregated

Distributed

Time [days]

4/17/03 4/26/03 5/05/03 5/14/03 5/23/03 6/01/03

Q [

m3/s

]

0.0

0.1

0.2

0.3

0.4

0.5

Obs

Aggregated

Distributed

Snowmelt and Streamflow

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?