Runoff Processes and Thermal
Modelling in Subarctic Catchments
Sean K. Carey, Yinsuo Zhang, Celina Ziegler,
Michael Treberg, Jessica Boucher
Dept. Geography & Environmental Studies
Carleton University, Ottawa
IP3 Workshop #2
Overview
ƒ HRU runoff sources and pathways
ƒ Evaluate existing numerical descriptions for frozen
and organic soils
ƒ HRU Classification
ƒ Future Program
The Wolf Creek Research Basin
Location:
60o31 N, 135o 31’ W
Area:
Approx. 200 km2
Elevation Range:
800 to 2250 m a.s.l.
(3 ecozones)
Mean Annual Precipitation:
300 to 400 mm (40% snow)
Mean Annual Temperature:
-3 oC
HRU Runoff Processes (conceptual model)
Figure Source: Encyclopedia of Hydrological Sciences, John Wiley & Sons, Ltd.
Granger Basin
ƒ Intra-basin variability:
ƒ Vegetation, soils, frozen ground, climate
Granger Sub-basins
2.9 km2
1.5 km2
1.1 km2
2.1 km2
Techniques
ƒ High-frequency Sampling
ƒ Synoptic Sampling
ƒ Hydrometric
ƒ Hydrochemical
Data - Streamflow
100
400
80
60
200
40
Stage
Dilution
SpC
A+C
100
0
May 1
June 1
June 16
July 1
July 16
2500
2000
1500
1000
ƒ Areas with limited
permafrost extent are
important sources of
baseflow.
0
Aug 1
300
Runoff (accumulated)
2006 Post-Freshet Discharge
5
250
4
Discharge (L/s)
Runoff (mm/d)
3000
500
0
May 16
6
3
2
1
0
June 10
20
Specific Conductance (ms cm-1)
Discharge (L s-1)
3500
300
ƒ Each HRU contributes
approximately equal
amounts of flow per
unit-area.
4000
Major Anion + Cation Flux (mg s-1)
500
GB_01
GB_02
GB_03
GB_04
200
150
100
50
June 20
June 30
July 9
July 19
July 29
0
June 10
June 20
June 30
July 9
July 19
July 29
Data – Simple Hydrochemistry
3000
60
Major Anions + Cations (post-freshet)
2000
1500
1000
40
30
20
10
500
0
June 10
50
SpC (μs cm-1)
GB_01
GB_02
GB_03
GB_04
-1
Major Ions (mg s )
2500
July
July
July
July
8
14
19
25
0
June 20
June 30
July 9
July 19
July 29
GB1 A GB2 B
C
D GB3 E
F GB4 H
I
Sampling Location
Major Anions + Cations
normalized for sub-basin area
500
-1
-2
Major Ions (mg s km )
600
400
300
200
100
0
June 10
June 20
June 30
July 9
July 19
July 29
ƒ Each HRU has a (mostly) unique
hydrochemistry.
ƒ Areas underlain with permafrost
have dilute supra-permafrost
signatures compared with more
ionic deep (sub permafrost)
groundwater
Stable Isotopes
-156
ƒ Results ongoing. Data
from 2006 being
supplemented with 2007
and historical data.
-158
-160
δ2H(%0)
-162
-130
3.
-166
1.
-168
GB_01
Snowmelt
GB_02
GB_03
GB_04
GB_01a
-140
-150
δ2H(%0)
Early Melt
Peak Melt
Late Melt
-164
-170
-172
2.
-174
-176
-178
-23.0
-22.5
-22.0
-21.5
-21.0
δ18O(%0)
M
-160
W
ƒ δ18O/ δ2H show unique
water signatures.
L
-170
-180
-190
-26
-24
-22
δ18O(%0)
-20
-18
Runoff summary
ƒ
All HRUs contribute water to the stream in
approximately equal volume.
ƒ
Much greater deep groundwater flow
than previously reported or anticipated.
ƒ
Work ongoing to assess seasonal
dominance of HRUs (logistics).
ƒ
Will extended to entire Wolf Creek,
although problems in methodology arise.
Ground thermal modelling (organic soils)
ƒ Ground thaw/freeze processes have a large influence
on the land surface energy balance and hydrology in
permafrost regions.
ƒ Large diversity exists in current simulation algorithms
and parameterisation methods.
ƒ Objectives:
– Evaluate the performance of commonly used
simulation algorithms in permafrost regions
– Evaluate commonly used soil parameterisation
schemes for both mineral and organic soil
– Provide guidelines for the implementation of
appropriate ground thermal models
Ground Thermal Modelling
Site name
Coordinates
Vegetation
Organic
layer depth
Permafrost
table
Scotty Creek
61o18’N
121o18’W
Black
Spruce
3m
>0.7m
Granger
Creek
60o32’N
135o18’W
Willow
Shrub
0.35m
>0.4m
Wolf Creek
NFS
61o31’N
135o31’W
BlackSpruce
0.23m
>1.4m
Wolf Creek
SFS
61o31’N
135o31’W
Aspen
Forest
No
No
Simulation Algorithms
Semiempirical
Accumulated Temperature
Index Algorithm (ATIA)
Z = β F 0.5
Two Directional Stefan
Algorithm (TDSA)
Analytical
Hayashi’s Modification to
Stefan Algorithm (HMSA)
Finite Difference Thermal Conduction
Method with DECP (FD_DECP)
Numerical
Finite Difference Thermal Conduction
Method with AHCP (FD_AHCP)
Finite Element Thermal Conduction
Method with AHCP (FE_TONE)
Latent Heat
Parameterisation
DECP: Decoupled Energy
Conservation
Parameterisation
AHCP: Apparent Heat
Capacity
Parameterisation
Parameter tests
Tests of soil thermal conductivity parameterisation
ƒ
--Johansen’formulation
ƒ
--De Vries’s formulation
Test of unfrozen water parameterisation
ƒ
--Segmented linear functions
ƒ
--Power function
ƒ
--Water potential-freezing point depression formulation
Tests of simulation algorithms (best parameterisation)
ƒ
--Run1: All the available inputs (Ttop, Tbot, θw, θice,Ts,ini)
ƒ
--Run2: Without Tbot, lower boundary conditions and
θw, θice,Ts,ini have to be assumed.
ƒ
--Run3: Only Ttop was supplied. Soil water assumed to
be saturated at all times.
Model Results
D epth(m )
0.0
(a)
-0.2
(b)
-0.4
-0.6
SC
SC
-0.8
0.0
0
20
40
60
0
50
100
150
D epth(m )
(c)
200
(d)
-0.1
-0.2
-0.3
GC
GC
D epth(m )
D epth(m )
-0.4
0.0
-0.2
-0.4
-0.6
-0.8
-1.0
-1.2
-1.4
0.0
-0.2
-0.4
-0.6
-0.8
-1.0
-1.2
-1.4
0
20
40
60
20
40
60
(f)
WC_NFS
WC_NFS
0
20
40
60
80
0
50
100
150
(g)
20
200
(h)
WC_SFS
0
WC_SFS
40
60
80
Days after observed thawing-start
Tests of different soil thermal conductivity parameterisation
methods, i.e. Complete Johansen’s equations (dark solid
lines), Commonly used Johansen’s equations (grey solid
lines), and a simplified de Vries’s method (dashed lines).
Open circles are observations.
0
(e)
0
50
100
150
200
Days after observed freezing-start
Test of unfrozen water parameterisation methods, i.e.
segmented linear function (dark solid lines), power function
( grey solid lines) and water potential-freezing point
depression
Model Results
Comparisons of observed (symbols) and simulated (lines)
thawing (dark circles for observation) and freezing (grey
circles for observation) depths at Scotty Greek with six
algorithms and three sets of model runs, i.e., Run1 (dark
solid lines), Run2 (dark dashed lines) and Run3 (grey solid
lines).
Comparisons of observed (symbols) and simulated (lines)
thawing (dark circles for observation) and freezing (grey
circles for observation) depths at Granger Greek with six
algorithms and three sets of model runs, i.e., Run1 (dark
solid lines), Run2 (dark dashed lines) and Run3 (grey solid
lines).
Some Key Findings
ƒ
A simplified de Vries’s formulation generated reasonable GTFD simulations at
all the four tested sites, while a commonly used Johansen’s formulation only
achieved good results at the three organic covered permafrost sites. The
formulations originally designed by Johansen for peat did not work at the
organic soils of the tested sites.
ƒ
The analytical algorithms are less sensitive to resolution of soil layers than the
numerical models. A six-layer resolution worked well for both HMSA and TDSA,
while at least nine soil layers were needed in the 5-m soil column for the three
numerical models, in order to simulate the GTFD with acceptable accuracy.
ƒ
The semi-empirical algorithm ATIA worked well at all the four tested sites
when site-calibrated coefficients (β) were used. However, due to the large
variations of the β values from thawing to freezing, from site to site and from
year to year, it is not recommended to apply this method to dynamic
analyses of GTFD.
ƒ
All three numerical algorithms (FD_DECP, FD_AHCP and TONE) traced GTFD
evolutions more precisely than other algorithms at all sites, particularly when
observed and best estimated soil moisture was supplied .
Landscape Classification
LB
SF
UB
TS3
SS2
SS1
TS2
TS1
SS1
Gauge
500 m
Ongoing Work
ƒ Infiltration into frozen soils
– New Field Experiments
– New Instrumentation (MFHPP)
– New Modelling
ƒ Modify Hydrus 1-D
– Simplify and C++ coding
– Incorporate frozen ground parameterizations
– Test at a variety of sites
Ongoing Work
ƒ Role of Channel Snow and Ice
– What is the role of icing and channel ice?
– GPR to establish volume, overlay on DEM
– Measure decay through time,
geochemical signature, establish
contribution to flow
Ongoing Work
ƒ Snowmelt processes
– Test SNAP and existing snow
melt/percolation routines in
CRHM.
– Isotopic evolution of snowpack,
snowmelt, and its relation to soil
water and runoff