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 and water supply. Here, we tested whether monitoring changes in wind-induced tree sway can enable snow interception detection and estimation of canopy snow water equivalent (SWE). We monitored hourly tree sway across six years based on 12 Hz accelerometer observations on two subalpine conifer trees in Colorado. 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 in the range of possible thermal effects. However, when tree sway decreased outside the range of thermal effects, canopy snow was present 93-95% of the time, as confirmed with classifications of PhenoCam imagery. Using sway tests, we converted significant changes in sway to canopy SWE, which was 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. Lower canopy SWE prevailed in storms with lower temperatures and higher wind speeds. We conclude that monitoring tree sway is a viable approach for quantifying canopy SWE, but challenges remain in converting changes in sway to mass and further distinguishing thermal and mass effects on tree sway.

From inside the stemflow research community, the past decade’s progress might look great: 1) the number of papers published on stemflow per year has doubled; 2) citations of stemflow publications have more than doubled; and 3) the number of research sites monitoring stemflow is on the rise. However, from a broader perspective, a brief Web of Science bibliometric analysis of the past decade reveals issues with these trends: 1) annual publication numbers have increased year-to-year for most topics in natural science, but stemflow publication trends are lower than related and broader disciplines; 2) self-citation is significantly higher for stemflow research than other disciplines (e.g., 26% compared to 2% for all hydrology); and, most importantly, 3) we may have more stemflow data, but we still lack a clear understanding of stemflow’s mechanistic importance. This creates ambiguities as to whether and how stemflow processes can be incorporated into hydrological models and concepts. In this presentation, I argue that we should progress from using metrics that are exclusively used by those who work on stemflow (e.g., unitless metrics such as funneling and enrichment ratios) towards using scaled flux-per-unit-area metrics that may support better integration into hydrological and ecological models (e.g., water or chemical yield per unit canopy area). While the magnitudes of funneling and enrichment ratios from individual plants have effectively conveyed to broader audiences the possibility for stemflow to play important roles in ecosystem functioning, I argue that we need to now move onto mechanistic investigations of stemflow’s impact on specific processes at ecohydrologically relevant scales. Dimensionless (often individual plant-scale) funneling-type metrics may not be useful in this regard, as they tell us nothing about where stemflow goes or what roles stemflow may play in the ecosystem. They also rely on an estimate of infiltration area, which has rarely been observed to date. Their use is further limited to falling liquid-phase rain, which prevents comparison of stemflow observations/processes under occult precipitation (fog, condensation) or mixed and solid-phase precipitation (snow, rime, etc). Please view the “Make Stemflow Unit-ed Again” companion video on YouTube: https://youtu.be/4vPk9m45V0c