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Detailed assessment of small‐scale heterogeneity in local surface water balance is essential to accurate estimation of evapotranspiration in semiarid climates. However, meteorological approaches are often impractical to implement in sites with sparse and diverse vegetation composition, especially with seasonally variable leaf canopy features. Ground‐based infrared thermometry (TIR) provides spatially and temporally continuous resolution of surface skin temperature that can be directly related to the land surface energy balance. We made repeated measurements with a portable TIR camera to capture seasonal replicates for patch scale heat images for four sagebrush communities. The heat images near peak foliage and near the end of the growing season were compared by computation of surface energy fluxes from TIR sensing to surface energy balance (SEB) and Bowen ratio (BR). Estimates of sensible (H) and latent heat flux (LE) were evaluated with eddy covariance measurements to disaggregate the expression of seasonal phenology of sagebrush species across wetness and elevation. Estimations showed reasonable agreement with ground‐basedLEobservations for most cases (r² = 0.59–0.76 for SEB and 0.22–0.72 for BR; root mean squared error = 73.4–106.4 W m⁻²for SEB and 109.9–204.0 W m⁻²for BR). Predictability declined as the fraction of senescent foliage increased in dry conditions. The field trials suggest the methods have the potential for monitoring land surface energy fluxes and plant health at a very fine spatial scale. The ability to partition heat fluxes from various plant communities over a range of moisture availability will provide valuable information associated with the consumptive water use and phenological processes in the semiarid West.

Soil moisture and evapotranspiration (ET) are important components of boreal forest hydrology that affect ecological processes and land‐atmosphere feedbacks. Future trends in soil moisture in particular are uncertain. Therefore, accurate modeling of these dynamics and understanding of concomitant sources of uncertainty are critical. Here, we conduct a global sensitivity analysis, Monte Carlo parameterization, and analysis of parameter uncertainty and its contribution to future soil moisture and ET uncertainty using a physically based ecohydrologic model in multiple boreal forest types. Soil and plant hydraulic parameters and LAI have the largest effects on simulated summer soil moisture at two contrasting sites. In future scenario simulations, the selection of parameters and global climate model (GCM) choice between two GCMs influence projected changes in soil moisture and ET about as much as the projected effects of climate change in the less sensitive GCM with a late‐century, high‐emissions scenario, though the relative effects of parameters, GCM, and climate vary among hydrologic variables and study sites. Saturated volumetric water content and sensitivity of stomatal conductance to vapor pressure deficit have the most statistically significant effects on change in ET and soil moisture, though there is considerable variability between sites and GCMs. The results of this study provide estimates of: (a) parameter importance and statistical significance for soil moisture modeling, (b) parameter values for physically based soil‐vegetation‐atmosphere transfer models in multiple boreal forest types, and (c) the contributions of uncertainty in these parameters to soil moisture and ET uncertainty in future climates.

Soil moisture is an important driver of growth in boreal Alaska, but estimating soil hydraulic parameters can be challenging in this data‐sparse region. Parameter estimation is further complicated in regions with rapidly warming climate, where there is a need to minimize model error dependence on interannual climate variations. To better identify soil hydraulic parameters and quantify energy and water balance and soil moisture dynamics, we applied the physically based, one‐dimensional ecohydrological Simultaneous Heat and Water (SHAW) model, loosely coupled with the Geophysical Institute of Permafrost Laboratory (GIPL) model, to an upland deciduous forest stand in interior Alaska over a 13‐year period. Using a Generalized Likelihood Uncertainty Estimation parameterisation, SHAW reproduced interannual and vertical spatial variability of soil moisture during a five‐year validation period quite well, with root mean squared error (RMSE) of volumetric water content at 0.5 m as low as 0.020 cm³/cm³. Many parameter sets reproduced reasonable soil moisture dynamics, suggesting considerable equifinality. Model performance generally declined in the eight‐year validation period, indicating some overfitting and demonstrating the importance of interannual variability in model evaluation. We compared the performance of parameter sets selected based on traditional performance measures such as the RMSE that minimize error in soil moisture simulation, with one that is designed to minimize the dependence of model error on interannual climate variability using a new diagnostic approach we call CSMP, which stands for Climate Sensitivity of Model Performance. Use of the CSMP approach moderately decreases traditional model performance but may be more suitable for climate change applications, for which it is important that model error is independent from climate variability. These findings illustrate (1) that the SHAW model, coupled with GIPL, can adequately simulate soil moisture dynamics in this boreal deciduous region, (2) the importance of interannual variability in model parameterisation, and (3) a novel objective function for parameter selection to improve applicability in non‐stationary climates.

The projected shifts in winter weather and snowpack conditions are expected to impact carbon storage in western U.S. rangelands. Sagebrush shrublands comprise much of the western United States, yet contribution of winter CO₂efflux to the overall carbon budget of these ecosystems remains uncertain. We explored factors controlling winter CO₂efflux measured using eddy covariance at five sagebrush‐dominated sites along an elevation/climate transect extending from 1,425 to 2,111 m. Results showed that winter CO₂efflux was modest but had important impacts on annual carbon budgets, and its impact increased in high‐elevation, snow‐dominated ecosystems compared to low, rain‐dominated ones. Observed cumulative winter CO₂efflux accounted for 8–30% of annual gross ecosystem production (GEP) and roughly approximated annual net carbon uptake. Omission of winter periods would have increased net uptake by 1.5 to 2.2 times. Within‐site variability in observed 30‐min winter CO₂efflux was related to soil temperature and moisture. Between‐site variability was attributed to available carbon stocks, including soil organic carbon and the previous year's GEP. At low elevations, lack of snow cover to insulate soil from freezing, coupled with lower carbon stocks, limited CO₂efflux. Conversely, large carbon stocks and deep snowpack that prevented soil freezing at high elevation led to increased CO₂efflux. These results show how climate and biota exert strong controls on winter ecosystem respiration and extend our understanding of how state factors influence winter CO₂efflux. Collectively, our findings suggest that an upward climatic shift in the rain‐to‐snow transition elevation may alter the carbon budget of sagebrush shrublands.

In the western USA, shifts from snow to rain precipitation regimes and increases in western juniper cover in shrub‐dominated landscapes can alter surface water input via changes in snowmelt and throughfall. To better understand how shifts in both precipitation and semi‐arid vegetation cover alter above‐ground hydrological processes, we assessed how rain interception differs between snow and rain surface water input; how western juniper alters snowpack dynamics; and how these above‐ground processes differ across western juniper, mountain big sagebrush and low sagebrush plant communities. We collected continuous surface water input with four large lysimeters, interspace and below‐canopy snow depth data and conducted periodic snow surveys for two consecutive water years (2013 and 2014). The ratio of interspace to below‐canopy surface water input was greater for snow relative to rain events, averaging 79.4% and 54.8%, respectively. The greater surface water input ratio for snow is in part due to increased deposition of redistributed snow under the canopy. We simulated above‐ground energy and water fluxes in western juniper, low sagebrush and mountain big sagebrush for two 8‐year periods under current and projected mid‐21st century warmer temperatures with the Simultaneous Heat and Water (SHAW) model. Juniper compared with low and mountain sagebrush reduced surface water input by an average of 138 mm or 24% of the total site water budget. Conversely, warming temperatures reduced surface water input by only an average of 14 mm across the three vegetation types. The future (warmer) simulations resulted in earlier snow disappearance and surface water input by 51 and 45 days, respectively, across juniper, low sagebrush and mountain sagebrush. Information from this study can help land managers in the sagebrush steppe understand how both shifts in climate and semi‐arid vegetation will alter fundamental hydrological processes. Copyright © 2016 John Wiley & Sons, Ltd.