The response of evapotranspiration (ET) to warming is of critical importance to the water and carbon cycle of the boreal biome, a mosaic of land cover types dominated by forests and peatlands. The effect of warming-induced vapour pressure deficit (VPD) increases on boreal ET remains poorly understood because peatlands are not specifically represented as plant functional types in Earth system models. Here we show that peatland ET increases more than forest ET with increasing VPD using observations from 95 eddy covariance tower sites. At high VPD of more than 2 kPa, peatland ET exceeds forest ET by up to 30%. Future (2091–2100) mid-growing season peatland ET is estimated to exceed forest ET by over 20% in about one-third of the boreal biome for RCP4.5 and about two-thirds for RCP8.5. Peatland-specific ET responses to VPD should therefore be included in Earth system models to avoid biases in water and carbon cycle projections.

Humid boreal forests are unique environments characterized by a cold climate, abundant precipitation, and high evapotranspiration. Transpiration ( $E_T$ ), as a component of evapotranspiration (E), behaves differently under wet and dry canopy conditions, yet very few studies have focused on the dynamics of transpiration to evapotranspiration ratio ( $E_T/E$ ) under transient canopy wetness states. This study presents field measurements of $E_T/E$ at the Montmorency Forest, Québec, Canada: a balsam fir boreal forest that receives $\sim 1600$ mm of precipitation annually (continental subarctic climate; Köppen classification subtype Dfc). Half-hourly observations of E and $E_T$ were obtained over two growing seasons using eddy-covariance and sap flow (Granier’s constant thermal dissipation) methods, respectively, under wet and dry canopy conditions. A series of calibration experiments were performed for sap flow, resulting in species-specific calibration coefficients that increased estimates of sap flux density by $34\%\pm 8\%$ , compared to Granier’s original coefficients. The uncertainties associated with the scaling of sap flow measurements to stand $E_T$ , especially circumferential and spatial variations, were also quantified. From 30 wetting–drying events recorded during the measurement period in summer 2018, variations in $E_T/E$ were analyzed under different stages of canopy wetness. A combination of low evaporative demand and the presence of water on the canopy from the rainfall led to small $E_T/E$ . During two growing seasons, the average $E_T/E$ ranged from $35\%\pm 2\%$ to $47\%\pm 3\%$ . The change in total precipitation was not the main driver of seasonal $E_T/E$ variation, therefore it is important to analyze the impact of rainfall at half-hourly intervals.

Rain-on-snow events can cause severe flooding in snow-dominated regions. These are expected to become more frequent in the future as climate change shifts the precipitation from snowfall to rainfall. However, little is known about how winter rainfall interacts with an evergreen canopy and affects the underlying snowpack. In this study, we document 5 years of rain-on-snow events and snowpack observations at two boreal forested sites of eastern Canada. Our observations show that rain-on-snow events over a boreal canopy lead to the formation of melt–freeze layers as rainwater refreezes at the surface of the sub-canopy snowpack. They also generate frozen percolation channels, suggesting that preferential flow is favoured in the sub-canopy snowpack during rain-on-snow events. We then used the multi-layer snow model SNOWPACK to simulate the sub-canopy snowpack at both sites. Although SNOWPACK performs reasonably well in reproducing snow height (RMSE = 17.3 cm), snow surface temperature (RMSE = 1.0 °C), and density profiles (agreement score = 0.79), its performance declines when it comes to simulating snowpack stratigraphy, as it fails to reproduce many of the observed melt–freeze layers. To correct for this, we implemented a densification function of the intercepted snow in the canopy module of SNOWPACK. This new feature allows the model to reproduce 33 % more of the observed melt–freeze layers that are induced by rain-on-snow events. This new model development also delays and reduces the snowpack runoff. In fact, it triggers the unloading of dense snow layers with small rounded grains, which in turn produces fine-over-coarse transitions that limit percolation and favour refreezing. Our results suggest that the boreal vegetation modulates the sub-canopy snowpack structure and runoff from rain-on-snow events. Overall, this study highlights the need for canopy snow property measurements to improve hydrological models in forested snow-covered regions.