Challenges and Capabilities in Estimating Snow Mass Intercepted in Conifer Canopies With Tree Sway Monitoring

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.

Three Fundamental Challenges to the Advancement of Stemflow Research and Its Integration into Natural Science

“…While this peculiar phenomenon has been serendipitously observed (and appreciated) by internet naturalists (https://imgur.com/hgemi5E (accessed on 22 December 2023); also available in the Supplemental Materials), it has not been formally studied to the best of our knowledge. An improved accounting of this (potentially) ~10% of intercepted snow (which can represent dozens of mm in snow-water equivalents [64]) may refine our understanding of forest hydrology during winter months.…”

Comparison of snowpack structure in gaps and under the canopy in a humid boreal forest

“…Modelling the physical properties of seasonal snow cover and how it is affected by the forest structure is key to many applications, notably hydrological, meteorological and climate modelling, as well as hydropower reservoir inflow forecasting or forest management (Dickerson-Lange et al, 2021;Musselman et al, 2012;Rutter et al, 2009). Fortunately, the effect of canopy structure on snow hydrology is being progressively addressed in recent model developments (Broxton et al, 2015;Mazzotti et al, 2019;Sun et al, 2018), but major challenges remain (Lundquist et al, 2021;Raleigh et al, 2022).…”

Snowtography quantifies effects of forest cover on net water input to soil at sites with ephemeral or stable seasonal snowpack in Arizona, USA

“…While hydrologic partitioning has been well‐studied in watersheds with stable seasonal snowpack, that is, a continuous winter‐long snowpack, less is known about the growing number of watersheds with ephemeral snowpack. Characterization of snowpack dynamics and resulting impacts for soil moisture and streamflow are particularly challenging in forested environments with an ephemeral snowpack, where many processes affect snow partitioning (e.g., air temperature, humidity, hydrometeor size and temperature and fall rate; see also Harder and Pomeroy (2013); Harpold et al (2017)) and the net water input to soils (e.g., canopy interception, sublimation, unloading and melt drip of the incepted snowfall; Bonner et al (2022); Dickerson‐Lange et al (2015); Raleigh et al (2022)). Furthermore, drought‐related disturbances and/or management practices are altering vegetation cover in many forests, with unknown consequences for water balance.…”