Snowmelt energy balance in a burned forest stand, Crowsnest Pass, Alberta, CanadaKatie Burles and Sarah Boon, Dept. of Geography, University of Lethbridge, katie.burles@uleth.ca

BACKGROUND

Removal of the forest canopy by wildfire

reduces the interception capacity of

forests, increasing snow accumulation in

burned stands3. Reduced forest canopy

increases short-wave radiation reaching

the snow surface, increases wind speeds,

increases vapour pressure and

temperature gradients between the snow

surface and the atmosphere, decreases

long-wave radiation emissions towards the

snow surface, and subsequently

enhances the energy available for snow

melt.

STUDY SITE

Two north-facing 2500 m2 stands at the northern

edge of the 2003 Lost Creek wildfire boundary in

the Crowsnest Pass(Figure 2), were selected for

study. The healthy (control) stand is located at

~1680 m and is representative of the mature

forest of the region and the burned stand is

located at ~1775 m, ~1km away is representative

of the most severely burned forest in the Lost

Creek fire. The dominant tree species is

subalpine fir with small portions of white spruce

and lodgepole pine.

Figure 2. Study area region (inset) and location of forest stands.

10 m meteorological towers were installed in

each site to measure air pressure (P), air

temperature (Ta), snow surface temperature (Tss),

sonic air temperature (θ), relative humidity (RH),

wind speed (μ), ground heat flux (GHF), soil

temperature (Ts), soil volumetric water content (VWC), incoming short-wave (K↓)and long-wave

radiation (L↓), snow surface albedo (α), and

snow depth (Figure 3).

Figure 3. Meteorological stations in the burned (left) and healthy (right) forest

stands.

1-D ENERGY BALANCE SIMULATION

Energy balance components (Figure 4)

were simulated hourly for each stand

during the snow melt period (Apr 1- May

25) using the above equation. Advective

energy (energy supplied to the snow pack

by rainfall) was not considered as it was

not observed during the 2009 snow melt

period. Additionally, internal snow pack

processes are not physically represented

however, cold content was calculated and

incorporated empirically into the

simulation to account for energy required

to warm the snow pack to the melting

point (0ºC).

in MJ m-2 h-1

Table 1. Comparison of simulated vs. measured SWE (Apr 1-

May 25, 2009).

RESULTS & DISCUSSION

ACKNOWLEDGEMENTS & REFERENCESFunding was provided by the Natural Sciences and Engineering Research Council of Canada (NSERC) - Alexander Graham

Bell Canadian Graduate Scholarship (CGS-M), University of Lethbridge – Startup Funds granted to Dr. Sarah Boon, and Alberta

(AB) Sustainable Resource Development (SRD) Forest Management Branch.

Thank you to the University of Alberta – Forest Hydrology, and the University of Lethbridge – Mountain Hydrology Research

Group for invaluable field assistance.

University of Lethbridge Mountain Hydrology Research Group

Southwestern Alberta (AB) has seen a mean annual temperature increase of 2ºC in the last

century1. Predicted shifts in climate may increase the susceptibility of forest environments

to natural disturbances such as insect infestation and wildfire, and associated

anthropogenic disturbances such as salvage harvesting. Wildfire frequency and area

burned in Canada have been increasing since the early 20th century2. Forest disturbance

ultimately opens the forest canopy; however, specific structural impacts vary between

disturbance types, with difference effects on snow processes. Burned forest stands are a

unique disturbance type, where needles and small branches are completely removed and

all that remains are dead standing trunks and branches (Figure 1).

No research has been conducted to quantify the effects of forest cover change following

wildfire on snow processes. The purpose of this research is to quantify the effects of

wildfire on snow melt energy balance and seasonal timing of melt in a burned versus

healthy mature forest stand in the Crowsnest Pass, AB.

Figure 1. Burned forest stand in the Crowsnest Pass, AB.

Peak snow accumulation and snow pack

depletion were monitored by measuring

snow water equivalence. Snow density

was measured at 36 snow survey sites

on a 50 m x 50 m grid. Snow depth (n =

121) was measured at 5 m intervals in

the same grid. Snow surveys took place

in mid February, early March, and

weekly throughout the melt period. All

measurements were made in 2009, 5-

years post-fire.

SIMULATION VALIDATION AND PERFORMANCE

0

5

10

15

20

25

30

35

1-Apr-09 11-Apr-09 21-Apr-09 1-May-09 11-May-09 21-May-09 31-May-09

Sno

w w

ate

r e

qu

ival

ent

(SW

E) (

cm)

Time (Hours)

B_Observed B_Simulated H_Observed H_Simulated

Burned Healthy

n (hours) 1271 1439

r2 0.94 0.96

Slope 1.09 1.10

Intercept -0.33 -2.65

E 0.81 0.94

RMSE (cm) 2.48 1.01

Date of snow pack removal

Measured 143 151

Simulated 141 151

Figure 6. Simulated and observed snow water equivalent (Apr 1-May 31, 2009).

Simulation performance was assessed by comparing the rate and timing of continuous records of

observed versus simulated melt (Figure 6). Observed SWE was derived from the continuous

snow depth record and averaged snow survey density measurements. Goodness-of-fit between

observed and simulated SWE was determined using three quantitative measures of performance:

coefficient of determination (r2), coefficient of efficiency (E), and root mean square error (RMSE)6

(Table 1).

Burned Healthy

Tss (oC)

Ta (oC)

μ (m s-1)τc

τL

α

-3.5

1.5

1.2

0.82

0.82

0.62

-1.5

1.8

0.4

0.085

0.18

0.35

Ts (oC) 1.1 0.1

VWC(%) 13 30

Figure 7. Cumulative (Apr 1 – May 25, 2009) energy balance components: burned and healthy forest stand.

Table 2. Average meteorological conditions (Apr 1- May 25, 2009)

and forest structure parameters at both sites.

Figure 5. Hemispherical photographs taken in the burned

(top) and healthy (bottom).

Maximum observed SWE was greater in

the burned site than in the healthy site

(Figure 8). In 2009 and 2010, SWE peaked

in both stands just before April 1st . The

snow pack in the burned stand melted more

rapidly; complete snow pack removal

occurred seven days sooner than in the

healthy site. More snow water equivalent

was observed in 2009 relative to 2010

(Figure 8).

Differences in micrometeorological variables and forest structure parameters between

stands (Table 2) resulted in larger energy balance fluxes in the burned than the healthy

stand (Figure 7). 83% more energy was available for melt in the burned stand. Snow

melt was largely driven by K* and SHF in the burned stand, and a combination of K*,

L* and SHF in the healthy stand.

Net

Radiation

(K*+L*)

Sensible

Energy

(SHF)

Latent

Energy

(LHF)

Advective

Energy

(Qr)

Snow

Ground

Change in Internal Energy (Qθ)

Θrm Q+Q+GHF+SHF+LHF+*L+*K=Q

Ground Heat

(GHF)

Figure 4. Schematic of the vertical energy fluxes during snow melt in a forested

environment.

Canopy density parameters were calculated using

hemispherical photos taken in close proximity to the

meteorological stations. Hemi-photos (Figure 5) were

processed using SideLook edge-detection software 4,

and Gap Light Analyzer (GLA)5 to determine the sky

view factor (τL :fraction of hemisphere visible from

beneath the canopy). Ability of the canopy to transmit

radiation (canopy transmissivity: τc) (K↓) in the burned

site was assumed to equal τL because there are no

needles or branches to restrict transmissivity of K↓. τc

was calculated in the healthy stand using a 60-day

average ratio of 20-minute measurements of K↓ in the

burned stand to K↓ measured beneath the healthy

forest canopy.

References: 1 Schindler, D.W., and Donahue, W.F. 2006. ‘An impending water crisis in Canada’s western prairie provinces’, P. Natl. Acad. Sci. USA. 103, 7210–

7216; 2 Podur, J., Martell, D. L.,and Knight, K. 2002. ‘Statistical quality control analysis of forest fire activity in Canada’, Can. J. Forest Res. 32, 195–205; 3

Farnes, P.E., and Hartmann, R.K. 1989. ‘Estimating the effects of wildfire on water supplies in the Northern Rocky Mountains’. Proc 57th Western Snow Conf.,

CO, Apr 18-20, 90-99; 4 Nobis, M., and Hunkizer, U. 2005. ‘Automatic thresholding for hemispherical canopy-photographsbased on edge detection’, Agric. For.

Meteor. 128, 243-250; 5 Frazer, G.W., Canham, C.D., and Lertzman, K.P. 1999. ‘Gap light analyzer (GLA), Version 2D0: Users manual and program

documentation’, Burnaby: Simon Fraser University and Millbrook: Institute of Ecosystem Studies; 6 Confalonieri, R., Bregaglio, S., and Acutis, M. 2010. ‘A

proposal of an indicator for quantifying model robustness based on the relationship between variability of errors and of explored conditions’, Ecol. Model. 21,

960-964.

-1.0

-0.5

0.0

0.5

1.0

1.5

2.0

2.5

En

erg

y (

MJ

m-2

d-1

)

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-0.5

0.0

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En

erg

y (

MJ

m-2

d-1

)

Components of the snowmelt energy balance

LHF

LHF

SHF

SHF

GHF

GHF

K*

K*

L*

L* Qm

Qm

Burned

Healthy (Reference)

0

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10

15

20

25

30

35

40

16-Feb-09 7-Apr-09 27-May-09

Sn

ow

wate

r eq

uiv

ale

nt

(SW

E)

(cm

)

Time (Days)

Burned Healthy (Reference)

2009

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16-Feb-10 7-Apr-10 27-May-10

Sn

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nt

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E)

(cm

)

Time (Days)

Burned Healthy (Reference)

0

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10

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25

30

35

40

16-Feb 7-Apr 27-May

Sn

ow

wate

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uiv

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nt

(SW

E)

(cm

)

Time (Days)

2009 20100

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40

16-Feb 7-Apr 27-May

Sn

ow

wate

r eq

uiv

ale

nt

(SW

E)

(cm

)

Time (Days)

2009 2010

Figure 8. Snow survey results. 2009 (top left) and 2010 (top right) snow water equivalent (SWE) in the burned and healthy stand. SWE between

years in the burned (bottom left) and healthy (bottom right).

2010

Burned Healthy (Reference)

How does snow water equivalent (SWE) in 2009 compare to 2010?