Cold Regions Hydrological Model
– background and modelled
mountain hydrological change in
North America
John Pomeroy, Logan Fang, Kabir Rasouli, Tom Brown
University of Saskatchewan
Mountain Observation Sites
Dempster
Highway
Transect
Bologna
Glacier
Rio Roca Station
35 Meteorological
& Snow Stations
Wolf Creek
12 Streamflow
gauges
Wolf Creek
Columbia
Icefield
Helen Creek &
Peyto Glacier
Fortress Ridge
Marmot Creek
Fortress
Mountain &
Burstal Creek
Reynolds Creek
Mountain Hydrological Modelling Strategy

Model Development





Model Applications



Model structural complexity needs to be appropriate for
governing processes, parameter & meteorological data.
Detailed parameter information is know in research basins
and must be transferred with care
Basin discretization using hydrological response length
Structure, parameters and scale are informed by the
results of process studies and distributed modelling at a
network of research basins.
Creating driving meteorological and parameter data is
critical
Models can be used to examine sensitivity and system
response to changing climate and land cover
Model Transfer

Algorithm recasting for larger scale and operational
models
Cold Regions Hydrological Model
Platform (CRHM)




Started in late 1990s as
Env Canada land use
hydrology model.
Attempted to write
Canadian modules for
USGS MMS
1999 Tom Brown
developed CRHM platform
in Windows environment –
central coding ensures
reliable model performance
Development of modules
from MAGS, PAMF, NERC,
Quinton-CFCAS, IP3, DRI,
CCRN and other research
Multiple contributors:
Brown, Gray, Granger,
Hedstrom, Pomeroy,
Shook, Ellis, MacDonald,
Dornes, Fang, Quinton,
Pradhananga, Harder,
Marsh, Essery, Marks, Link
The Cold Regions Hydrological Model Platform 2003
C:\Program Files\CRHM\Examples\badlakeflow 7475.prj










































220
210
200
190
180
170
160
150
140
130
(m3/s)

120
110
100
90
80
70
60
50
40
30
20
10
0
28/10/1974
27/11/1974
27/12/1974
26/01/1975
25/02/1975
27/03/1975
26/04/1975
26/05/1975
basinf low (1)
outflow (1)
outflow (2)
outflow (3)
SWE(1)
SWE(2)
SWE(3)
Cold Regions Hydrological Model
Platform: CRHM



Modular – purpose built from C++ modules
Parameters set by knowledge rather than optimization
Hydrological Response Unit (HRU) basis










landscape unit with characteristic hydrological processes/response
single parameter set
horizontal interaction along flow cascade matrix
Model tracks state variables and flows for HRU
Coupled energy and mass balance, physically based algorithms
applied to HRUs via module selection
HRUs connected aerodynamically for blowing snow and via dynamic
drainage networks for streamflow
Flexible - can be configured for prairie, mountain, boreal, arctic basins
Sub-basins connected via Muskingum routing
Visualisation tools, GIS interface
Model failure is embraced and instructive
Pomeroy et al., 2007 Hydrol. Proc.
Tom Brown, CRHM Modeller
Hydrological Response Units (HRU)

A HRU is a spatial unit in the
basin described by a single set
of parameters, defined by
 biophysical structure - soils,
vegetation, drainage, slope,
elevation, area (determine
from GIS, maps)
 hydrological state – snow
water equivalent, internal
energy, soil moisture,
depressional storage, lake
storage, water table (track
using model)
 hydrological flux - snow
transport, sublimation,
evaporation, melt discharge,
infiltration, drainage, runoff.
Fluxes are determined using
fluxes from adjacent HRU
and so depend on location
in a flow sequence.
Alpine Hydrological Response Units
Sublimation
Elevation ~2310 mASL
Wind Direction
Solar Radiation
Snow Deposition
South Face (bottom)
South Face
(top)
Ridge
Top
Snow Transport
North Face
Forest
Sink
Source
Forest gaps on slopes: radiation
‘Hot’ radiation
gaps
‘Cold’ radiation
gaps
Shortwave
Longwave
Simulations: Adaptation of CRHM for forest gaps
Vgap
L`γ
L`
h
θ
d
Forest gap
radiation outputs
Shortwave
Longwave
CRHM
Mountain Hydrology in CRHM Precipitation
Evapotranspiration
Sublimation
Snowfall
Rainfall
Interception
Surface runoff
Subsurface
discharge
Surface runoff
(infiltration-excess or
saturation-excess
overland flow)
Stream
Rainfall
infiltration
Snowmelt
infiltration
Subsurface
discharge
m a cro p o re s
Evaporation
Recharge via
percolation
Recharge
Groundwater
discharge
Groundwater
discharge
Recharge
layer
Lower
layer
Soil
layers
Groundwater
layer
CRHM Mountain Structure
HRU Delineation





Driving meteorology:
temperature,
humidity, wind speed,
snowfall, rainfall,
radiation
Blowing snow,
intercepted snow
Snowmelt and
evapotranspiration
Infiltration &
groundwater
Stream network
Marmot Model Structure
Physically based hydrological modules
RB 1: Cabin Creek Sub-basin
HRUs:
•South-facing Alpine Rock
•North-facing Alpine Rock
•North-facing Alpine Larch/Spruce
•South-facing Alpine Larch/Spruce
•North-facing Spruce/Fir/Lodgepole Pine
•South-facing Spruce/Fir/Lodgepole Pine
•Level Spruce/Fir/Lodgepole Pine
•Forest Clearings
•Level Lodgepole Pine
•South-facing Lodgepole Pine
•North-facing Lodgepole Pine
RB 4: Marmot Confluence
Sub-basin
HRU:
•Valley
Bottom
Cabin Creek
RB 2: Middle Creek Sub-basin
HRUs:
•North-facing Alpine Rock
•South-facing Alpine Rock
•South-facing Alpine Larch/Spruce
•North-facing Alpine Larch/Spruce
•North-facing Spruce/Fir/Lodgepole Pine
•South-facing Spruce/Fir/Lodgepole Pine
HRU:
•Valley Bottom
HRU:
•Valley
Bottom
Middle Creek
Marmot Creek
Marmot Creek Basin Outlet
RB 3: Twin Creek Sub-basin
HRUs:
•North-facing Alpine Rock
•South-facing Alpine Rock
•South-facing Alpine Larch/Spruce
•North-facing Alpine Larch/Spruce
•North-facing Spruce/Fir/Lodgepole Pine
•South-facing Spruce/Fir/Lodgepole Pine
•North-facing circular clearings
•South-facing circular clearings
HRUs:
•Forest Clearings
•North-facing Lodgepole Pine/Aspen
•South-facing Lodgepole Pine/Aspen
•Level Lodgepole Pine/Aspen
•South-facing Lodgepole Pine
•Level Lodgepole Pine
•North-facing Lodgepole Pine
HRU:
•Valley
Bottom
Twin Creek
Forest Snow Dynamics Simulations
Forest
Clearing
North
Face
Ridgetop
Alpine
Snow
Dynamics
Simulations
Upper
South Face
Snow redistribution from
north face and ridgetop
to south face and larch forest
Lower
South Face
Larch
Forest
uncalibrated
Observed and Modelled Streamflow
Marmot Creek
2006
2007
2008
2009
2010
2011
2012
All seasons
NSE
0.63
0.77
0.63
0.61
0.50
0.77
0.75
0.71
RMSD
0.117
0.141
0.134
0.093
0.131
0.136
0.164
0.133
NRMSD
0.60
0.47
0.50
0.47
0.64
0.48
0.52
0.52
MB
-0.39
-0.09
0.11
-0.01
0.22
-0.02
-0.08
-0.03
Precipitation Phase Uncertainty
Testing new psychrometric energy balance algorithm in CRHM
Rocky Mountain
Subarctic
Mountain
Subarctic
Tundra
Prairie
Harder and Pomeroy, 2014
Rain-on-Snow Modelling - CRHM
South-facing Snowdrift
Pomeroy et al, submitted
Rain-on-Snow Modelling - CRHM
Pomeroy et al, submitted
Flood Modelling - CRHM
Fang and Pomeroy, in review
Flood Antecedent Condition Analysis
Fang and Pomeroy, in review
Flood Land Use Scenarios
Fang and Pomeroy, in review
Snow Regime Sensitivity to
Climate Change - CRHM
5
5
4
annual peak SWE (mm)
70
80
90
o
20000
1
300 1
2
Temperature increase ( C)
Temperature
increase ( oC)
5
10
43
400
3
1
500
20
5
80
1
4
03
80
52
1
4
0
5 0
4
3
4
23
2
1
1
00
80
80
5
annual peak SWE (mm)
90
100
50
9090
60
100
100
20
1
0
13
3
3
2
1
2
change of annual peak SWE (%)
−4
0
0
−3
−−7250
0
−1
−60
Sheltered
0
Wolf Creek Yukon
Reynolds Creek, Idaho10
−45
−30
20
−15
0
5
0
0
−50
4
00
0
0
7
1
−
3
2
−
1
4
−2015
0
4
1
−10
0 3
80
90
100
110
120
110
120
0
160
5 2
−75
Exposed
0
100
10
1
18
4
−60
0
150
5
0
3
−45
0
−5
0
0
4
−4
70 200
3
−
−−320
0
0
2 3
250 8
−1
−15
0
2
300 90
0
1
10
1
350 00
5
1
1
20
0 0
110110
120120
80 80
90 90
100 100
110 110
120 120
Precipitation (%)
Precipitation (%)
600
100
4
4
change of annual peak SWE (%)
Rasouli et al., 2015
Hydrological Process Sensitivity
to Climate Change - CRHM
actual evapotranspiration
snow transport
sublimation
200
Variable (mm/year)
Wolf Creek, Yukon
150
100
50
0
0
2
4
Temperature increase (°C)
Rasouli et al., 2014
Streamflow Sensitivity to
Climate Change - CRHM
100
annual runoff (mm)
120 140 160 180
200
change of annual runoff (%)
−40 −30 −20 −10
0
10 20
220
5
5
Wolf Creek, Yukon
3
2
2
30
1
1
0
80
20
10
0
−10
220
3
−20
4
−30
200
180
160
140
120
4
−40
100
Temperature increase ( oC)
30
90
100
110
0
120 80
Precipitation (%)
90
100
110
120
Climate Change in the Rockies (2060s-1990s)
Comparison: WCRB and RME
Reynolds Mountain East
Wolf Creek Research Basin
Reynolds Mountain East
^
Sites
203
0
Elevation (m)
20
40
Sage 1
Sage 2
2050
Basin
Sage 3
2060
Sage 4
Drift Sage
Low Sage
^ Sheltered
20
80
Grass
2070
Aspen
20
90
Drift Aspen
Fir
^ Exposed
Riparian Willow
2090
2100
2110
Area: 179 km2
Newman et al.(2014)
1
2
Area: 0.4 km2
2120
2130
Transient changes in mountain vegetation under
climate change
Mountains are expected
to warm more than others
by 2100 :
o 3 °C in temperate
areas
o 5 °C in northern
latitudes
Changing
productivity
under climate change
may
also
change
vegetation:
-growing season length
-climatic time averages
(P, Ta, sunshine hours)
-Nutrients + CO2
Rasouli et al., in preparation
Sensitivity of Snow Regimes at Wolf Creek
Research Basin & Reynolds Mountain East
−3
15
control(1993-2011)
(1993−2011)
Control
ΔVeg
only
∆Veg
only
ΔClim
only(All
(Mean−AllRCMs)
∆Clim
only
RCMs)
∆Clim
+ ∆Veg
ΔClim
+ ΔVeg
10
5
0
probability density function
probability density function
15
−3
x 10
x 10
control
(1983−2008)
Control
(1983-2008)
ΔVeg
onlyonly
∆Veg
ΔClim
onlyonly
(Mean−AllRCMs)
∆Clim
(All RCMs)
∆Clim
+ ∆Veg
ΔClim
+ ΔVeg
10
5
0
0
50
100
150
200
WCRB SWE (mm)
250
300
0
100
200
300
400
500
600
700
RME SWE (mm)
Rasouli et al, in preparation
5
15
10
5
density
15
function
−3
10
5
0
x 10
10
−3
15
probability density function
−3
probability density function
6
4
10
control (1983−2008)
ΔVeg only
6
400
50
100
150
200
250
300
350
5
−3
10
5
0
0
6
5
Runof (m )
100
150
200
4
2
0
200
−3
400
600
200
400
600
800
0
0
400
6
4
4
2
2
0
0
600
800
0
Basin SWE (mm)
50
100
150
600
800
0.5
1
1.5
2
2.5
Runoff (mm)
200
250
300
350
350
−3
15
x 10
10
5
0
0
0.05
−3
0.1
x 10
10Runoff
0.15
0.2
(mm)
RME
8
6
2
6
400
Intercepted SWE (mm)
0
200
4
8
200
5
0
Sheltered SWE (mm)
2
8
0
−3
x 10
10
0
4
10
20
2
6
Source SWE (mm)
x 10
800
4
8
800
600
6
0
0
10
−3
250 x 10300
10
Low Elevation SWE (mm)
control (1983−2008)
ΔVeg only
ΔClim only (Mean−AllRCMs)
ΔClim + ΔVeg
8
10
50
0
400
Sink SWE (mm)
Medium Elevation SWE (mm)
x 10
15
2
200
15
0
0
4
0
−3
x 10
8
2
0
6
4
800
10
4
0
600
Source SWE (mm)
x 10
8
0
200
−3
x 10
8
−3
10
6
2
0
10
x 10
8
only (Mean−AllRCMs)
10ΔClim
ΔClim + ΔVeg
2
0
Control
∆Veg only
∆Clim only (All RCMs)
∆Clim + ∆Veg
−3
8
5
x 10
0
0 50 10 150 20 250 30 350 0 0. 5 0.1 0.15 0.2
Low Elevation SWE (m )
−3
Medium Elevation SWE (m )
probability
probability
density
function
High Elevation SWE (m )
x 10
x 10
10
WCRB
−3
15
High Elevation SWE (mm)
0
0 50 10 150 20 250 30 350 0 50 10 150 20 250 30 350
x 10
10
−3
probability density function
0
control (1993−2011)
ΔVeg only
ΔClim only (Mean−AllRCMs)
ΔClim + ΔVeg
probability density function
10
−3
x 10
15
x 10
probability density function
control (19 3−201 )
ΔVeg only
ΔClim only (Mean−AlRCMs)
ΔClim +ΔVeg
function
15
density
−3
x 10
probability
probability
density
function
probability density function
Sensitivity of Streamflow Regimes at Wolf Creek
Research Basin & Reynolds Mountain East
0
0
−3
x 10
200
400
600
800
Sink SWE (mm)
20
0
−3
x 10
200
400
600
800
Intercepted SWE (mm)
15
10
0
200
400
600
Sheltered SWE (mm)
800
5
30
0
0
200
400
600
Basin SWE (mm)
800
0
0.5
1
1.5
Runoff (mm)
2
2.5
Sensitivity to Climate and Transient Vegetation Changes 2060s vs 1990s
Basin
Variable
Wolf Creek Research Basin
SWE
runoff
Reynolds Mn East
SWE
runoff
Control
∆Veg
∆Clim
∆Veg+∆Clim
Peak [mm]
144
137
134
128 (11%)
Peak date
Season Length
(day)
Apr 2
Apr 1
Mar 28
Mar 27
278
277
266
266(~2 wk)
Annual [mm]
201
178
224
199 (1%)
Peak [cms]
5
4
5
4
Peak date
Jun 21
Jun 18
Jun 17
Jun 13
Peak [mm]
376
283
329
184 (51%)
Peak date
Season Length
(day)
Mar 9
Feb 28
Feb 27
Feb 7
206
183
179
135(~2.5 mo)
Annual [mm]
384
284
401
302 (22%)
Peak [cms]
0.08
0.06
0.07
0.06
Peak date
May 17
May 8
Apr 17
Apr 12
31
Conclusions
Uncertainty to parameterisations
 Diagnostic modelling of extreme events
 Snow sensitivity to changes in vegetation
and climate
 Alpine hydrological sensitivity to soils,
vegetation, climate


Comparisons could be expanded