Snowmelt energy balance in a burned forest stand, Crowsnest Pass, Alberta, Canada Katie Burles and Sarah Boon, Dept. of Geography, University of Lethbridge, [email protected] BACKGROUND Removal of the forest canopy by wildfire reduces the interception capacity of forests, increasing snow accumulation in burned stands 3 . 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 m 2 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 (T a ), snow surface temperature ( T ss ), sonic air temperature (θ), relative humidity (RH), wind speed (μ), ground heat flux (GHF), soil temperature (T s ), 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 (0 º C). in MJ m -2 h -1 Table 1. Comparison of simulated vs. measured SWE (Apr 1- May 25, 2009). RESULTS & DISCUSSION ACKNOWLEDGEMENTS & REFERENCES Funding 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 2 º C in the last century 1 . 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 20 th century 2 . 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 Snow water equivalent (SWE) (cm) Time (Hours) B_Observed B_Simulated H_Observed H_Simulated Burned Healthy n (hours) 1271 1439 r 2 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 (r 2 ), coefficient of efficiency (E), and root mean square error (RMSE) 6 (Table 1). Burned Healthy T ss ( o C) T a ( o C) μ (m s -1 ) τ c τ L 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 T s ( o C) 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 1 st . 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) Θ r m 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 (τ L :fraction of hemisphere visible from beneath the canopy). Ability of the canopy to transmit radiation (canopy transmissivity: τ c ) (K↓) in the burned site was assumed to equal τ L because there are no needles or branches to restrict transmissivity of K↓. τ c 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. Sc i. 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 57 th 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 Energy (MJ m-2 d-1) -1.0 -0.5 0.0 0.5 1.0 1.5 2.0 2.5 Energy (MJ m-2 d-1) Components of the snowmelt energy balance LHF LHF SHF SHF GHF GHF K* K* L* L* Q m Q m Burned Healthy (Reference) 0 5 10 15 20 25 30 35 40 16-Feb-09 7-Apr-09 27-May-09 Snow water equivalent (SWE) (cm) Time (Days) Burned Healthy (Reference) 2009 0 5 10 15 20 25 30 35 40 16-Feb-10 7-Apr-10 27-May-10 Snow water equivalent (SWE) (cm) Time (Days) Burned Healthy (Reference) 0 5 10 15 20 25 30 35 40 16-Feb 7-Apr 27-May Snow water equivalent (SWE) (cm) Time (Days) 2009 2010 0 5 10 15 20 25 30 35 40 16-Feb 7-Apr 27-May Snow water equivalent (SWE) (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?