Challenges and Capabilities in Estimating Snow Mass Intercepted in Conifer Canopies With Tree Sway Monitoring. Issue 3 (9th March 2022)

• Record Type: Journal Article
• Authors: Raleigh, Mark S.; Gutmann, Ethan D.; Van Stan, John T.; Burns, Sean P.; Blanken, Peter D.; Small, Eric E.
• Is Part Of: Water resources research. Volume 58:Issue 3(2022)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2022-03-09
• Subjects: snow interception -- tree sway -- coniferous forests -- accelerometers -- time‐lapse imagery; Hydrology -- Periodicals; 333.91
• DOI: 10.1029/2021WR030972
• Languages: English
• ISSNs: 0043-1397

Abstract

Abstract: Snowpack accumulation in forested watersheds depends on the amount of snow intercepted in the canopy and its partitioning into sublimation, unloading, and melt. A lack of canopy snow measurements limits our ability to evaluate models that simulate canopy processes and predict snowpack. We tested whether monitoring changes in wind‐induced tree sway is a viable technique for detecting snow interception and quantifying canopy snow water equivalent (SWE). Over a 6 year period in Colorado, we monitored hourly sway of two conifers, each instrumented with an accelerometer sampling at 12 Hz. We developed an approach to distinguish changes in sway frequency due to thermal effects on tree rigidity versus intercepted snow mass. Over 60% of days with canopy snow had a sway signal that could not be distinguished from thermal effects. However, larger changes in tree sway could not generally be attributed to thermal effects, and canopy snow was present 93%–95% of the time, as confirmed with classified PhenoCam imagery. Using sway tests, we converted changes in sway to canopy SWE, which were correlated with total snowstorm amounts from a nearby SNOTEL site (Spearman r = 0.72 to 0.80, p < 0.001). Greater canopy SWE was associated with storm temperatures between −7°C and 0°C and wind speeds less than 4 m s −1 . Lower canopy SWE prevailed in storms with lower temperatures and higher wind speeds. Monitoring tree sway is a viable approach for quantifying canopy SWE, but challenges remain in converting changes in sway to mass and distinguishing thermal and snow mass effects on tree sway. Key Points: Six years of tree sway data from accelerometers on two conifers revealed changes in sway frequency at sub‐daily to seasonal scales After accounting for thaw‐freeze cycles, changes in tree sway due to snow interception were detected and checked with time‐lapse images Sway data yielded canopy snow mass estimates consistent with snowfall data and storm conditions